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					BEHAVIORAL BIASES OF
INVESTMENT ADVISORS - The Effect
of Overconfidence and Hindsight
Bias




                                                      Finance
                                               Master's thesis
                                                Antti Seppälä
                                                        2009




        Department of Accounting and Finance
         HELSINGIN KAUPPAKORKEAKOULU
         HELSINKI SCHOOL OF ECONOMICS
Helsinki School of Economics                                                          Abstract
Master’s Thesis                                                                       August 31, 2009
Antti Seppälä

BEHAVIORAL BIASES OF INVESTMENT ADVISORS:
    THE EFFECT OF OVERCONFIDENCE AND HINDSIGHT BIAS

PURPOSE OF THE STUDY
The objective of this thesis is to examine the effects of three behavioral biases on investment
advisors. These biases are hindsight bias, overconfidence and self-attribution bias. A survey study is
carried out to find out how the studied biases affect the investment advisors. The same survey study is
also carried out for two control groups for comparative purposes. In addition, the effects of individual
thinking style and cognitive abilities on the exposure to behavioral biases are studied.


DATA
The data in this study is collected in controlled field surveys. The surveys are carried for three
separate groups of people; financial professionals, university students and employees of an
engineering company The participants of the surveys answer a q   uestionnaire that contains financial
market related estimation tasks.

The main insight of the survey study is the two-pronged structure of the surveys. The ability to
recollect answers and repeat the surveys enables the examination of the biases at issue. The biases
are studied by comparing observations from different phases of the surveys to each other. Hindsight
bias is observed by differences between initial answers and the recollections. Overconfidence is
                                        ed
studied using initial answers and realiz results. Analyses of self-attribution bias use initial answers
from first and second round.


RESULTS
The main finding of this study is that people in general are exposed to the studied behavioral biases
but the degree and impact are affected by experience and other characteristics. Investment advisors
are generally less exposed to hindsight bias than other people. Moreover, professionals generally
outperform other people with lower level of confidence, which indicates lower overconfidence.
However, professionals are most exposed to self-attribution bias. The results indicate that in
addition to expertise, individual thinking style explains behavioral biases. People with high faith
in intuition are more exposed to behavioral biases. Overall, the results of this thesis provide
valuable new information on behavioral biases and investment advisors.


KEYW ORDS
Behavioral Finance, Investment advisors, overconfidence, hindsight bias, self-attribution bias
Table of Contents


1.      INTRODUCTION ...................................................................................................................................................... 3

     1.2.        BACKGROUND AND MOTIVATION ......................................................................................................................3
     1.3.        RESEARCH QUESTIONS .......................................................................................................................................4
     1.4.        CONTRIBUTION ...................................................................................................................................................6
     1.5.        RESULTS SUMMARY ............................................................................................................................................6
     1.6.        STRUCTURE OF THE STUDY ................................................................................................................................7

2.      PSYCHOLOGICAL FACTORS IN DECISION MAKING...............................................................................8

     2.1.        HINDSIGHT BIAS .................................................................................................................................................. 9
     2.2.        OVERCONFIDENCE ............................................................................................................................................11
     2.3.        SELF-ATTRIBUTION BIAS...................................................................................................................................11
     2.4.        FACTORS AFFECTING EXPOSURE TO BEHAVIORAL BIASES ..............................................................................12

3.      DATA AND METHODS .........................................................................................................................................16

     3.1.        DATA .................................................................................................................................................................16
     3.2.        METHODS ..........................................................................................................................................................25

4.      RESULTS ..................................................................................................................................................................32

     4.1.        HINDSIGHT BIAS ................................................................................................................................................32
     4.2.        OVERCONFIDENCE ............................................................................................................................................54
     4.3.        SELF-ATTRIBUTION BIAS...................................................................................................................................67
     4.4.        COGNITIVE -EXPERIENTIAL SELF-THEORY ........................................................................................................70

5.      CONCLUSIONS ......................................................................................................................................................73

6.      REFERENCES .........................................................................................................................................................76

7.      EXHIBITS .................................................................................................................................................................81

     7.1.        DISTRIBUTIONS OF THINKING STYLE SCORES ..................................................................................................81
     7.2.        REGRESSION STATISTICS...................................................................................................................................82
     7.3.        QUESTIONNAIRE SHEETS...................................................................................................................................86
                                                                                      2

LIST OF TABLES


Table 1 –Survey dates and return estimate periods...........................................................................................................17
Table 2 –Distribution of age ...............................................................................................................................................18
Table 3 –Return statistics....................................................................................................................................................23
                                                 3
Table 4 –Hindsight bias, asset selection effect 1/ ...........................................................................................................34
                                                3
Table 5–Hindsight bias, asset selection effect 2/ ...........................................................................................................37
                                                3
Table 6–Hindsight bias –asset selection effect 3/ .........................................................................................................39
                                               2
Table 7–Hindsight bias, sign of return effect 1/.............................................................................................................43
                                               2
Table 8–Hindsight bias, sign of return effect 2/.............................................................................................................46
Table 9 –Hindsight bias, drift of return effect ...................................................................................................................50
Table 10 –Hindsight bias, strength of view effect ............................................................................................................53
                                                 2....................................................................................................5
Table 11 –Overconfidence, confidence boundaries 1/                                                                                                     4
                                                 2....................................................................................................5
Table 12 –Overconfidence, confidence boundaries 1/                                                                                                     5
Table 13 –Overconfidence, volatility estimation ..............................................................................................................56
                                                  3
Table 14 –Overconfidence, confidence-performance 1/ ................................................................................................60
                                                 3
Table 15–Overconfidence, confidence-performance 2/ ................................................................................................62
                                                 3
Table 16–Overconfidence, confidence-performance 3/ ................................................................................................64
Table 17–overconfidence, confidence ..............................................................................................................................66
Table 18–Self-attribution bias, individual answers test ...................................................................................................67
Table 19 –Self-attribution bias, person level test ..............................................................................................................69
Table 20 –Individual thinking ............................................................................................................................................71




LIST OF FIGURES


Figure 1 –Distribution of experience .................................................................................................................................19
Figure 2 –Personal investment experience ........................................................................................................................21
Figure 3 –Return development timeline ............................................................................................................................24
Figure 4 –Hindsight bias, asset selection effect ................................................................................................................41
Figure 5–Hindsight bias, sign of return effect..................................................................................................................48
Figure 6–Hindsight bias, drift of return effect .................................................................................................................51
Figure 7–Overconfidence, volatility estimation ...............................................................................................................59
                                                 2
Figure 8–overconfidence, confidence-performance 1/ ..................................................................................................61
                                                  2
Figure 9 –overconfidence, confidence-performance 2/ ..................................................................................................62
Figure 10 –Self-attribution bias, person level test ............................................................................................................69
Figure 11 –Individual thinking ...........................................................................................................................................72
                                                 3


     to u to
1. In r d cin

Investment advisors are professionals who assist their clients in financial decision making issues
such as investing, insurance, borrowing, taxation and retirement planning. Thus investment
advisors have a great impact on their clients’ decisions. The advices and recommendations
investment advisors give to their clients are naturally affected by the beliefs and conceptions they
possess. Biases in these beliefs and conceptions can strongly affect the decision making of the
clients and thus it is important to study investment advisors’ behavioral biases.



1.2. Background and Motivation

    Previous literature shows that psychological factors have a substantial effect on people’s
                                          4)
decision making. Tversky and Kahneman (197 present that people rely on a limited number of
                                           uite
heuristic principles which in general are q useful, but sometimes lead to severe and systematic
biases. This study focuses to examine three such biases;hindsight bias, overconfidence and self-
attribution bias.

    Hindsight bias refers to a tendency to perceive own performance better than it actually is,
after learning the realiz                             )
                         ation. Biais and W eber (2008 find that for hindsight biased agents the ex-
post recollection of the initial belief will be closer to the realization than the true ex-ante
                                                 8
expectation. According to Buksar and Conolly (198 ) hindsight bias hinders learning from past
                                                    )
experience. In a similar vein Biais and W eber (2008 present that hindsight biased agents also fail
to remember how ignorant they were before observing outcomes and answers This leads agents
to underestimate volatility, which again results in inefficient portfolio choice and poor risk
management. One explanation of hindsight bias is the availability heuristic: the event that did
                            s
occur is more salient in one'mind than the possible outcomes that did not.

    Overconfidence refers to the habit of overestimating own ability to perform in given tasks.
People tend to be overconfident about own capabilities and level of knowledge. Overconfidence
                           better than average’, ‘
has several forms, such as ‘                                        setting too narrow
                                                 optimism bias’ and ‘
confidence limits’. According to Barber and Odean (2000) overconfidence causes excess trading
which can be risky to financial well being.
                                                 4


    Self-attribution bias refers to a tendency to overestimate the degree to which people are
                                                                       0)      W
responsible for their own success. Hastorf, Schneider, and Polifka (197 write, " e are prone to
                                                                         .
attribute success to our own dispositions and failure to external forces” In a similar vein, Gervais
and Odean (2001) find that success of traders leads to increased overconfidence. W hen a trader is
successful, he attributes too much of his success to his own ability and revises his beliefs about
his ability upward too much, which increases overconfidence.

    However, the exposure to behavioral biases is not homogenous. Certain factors are reported
                                                                     7
to explain the level of exposure. Lewellen, Lease and Schlarbaum (197 ) find that men have
stronger tendency to overconfident behavior than woman have. Korniotis and Kumar (2007)
                                                                              )
show that overconfidence decreases with age. Kaustia, Alho, and Puttonen (2008 find that
                                                               )
expertise reduces the degree of anchoring bias. Frederick (2005 presents that people with higher
cognitive abilities make more optimal decisions. This study uses a rational-experiential test by
                   )              e
Epstein et al (1996 to characteriz individual cognitive ability and thinking style. The effect of
these psychological information processing styles in behavioral biases is studied.



   . se
1.3 Re archQuestions

    The fact that investment advisers are commonly used when it comes to saving and investing
raises the question if their behavior is less exposed to behavioral biases than the behavior of their
potential customers’. Investment advisors have a great impact on the decisions of their customers
and if their judgment is biased, it will affect the way their customers act on financial markets (see
                           ).
e.g. Bluethgen et al., 2007 Irrational decision making can lead to e.g. suboptimal asset
allocation and thus poor investment results.

    To find out how these biases affect financial decision making, a field survey is conducted.
The survey is designed to enable studying the three biases. The main insight is the two-phased
structure of the survey. The biases are studied by comparing observations from different phases
of the surveys to each other. Hindsight bias is observed by differences between initial answers
                                                                                 ed
and the recollections. Overconfidence is studied using initial answers and realiz results.
Analyses of self-attribution bias use initial answers from first and second round. The empirical
study uses the data from the surveys and answers to the following questions:
                                                  5


   1. How does the hindsight bias affect the ex-post conception of the ex-ante expectation?
           x   Do investment advisors suffer from hindsight bias?
           x   Does expertise reduce the hindsight bias?
           x   W hat characteristics affect the severity of hindsight bias?


   2. How does the overconfidence affect the setting of confidence limits?
           x   Do investment advisors set too narrow confidence limits?
           x   Does expertise reduce overconfidence?
           x   W hat characteristics affect the severity of overconfidence?


   3. How does the self-attribution bias affect confidence in repeated tasks?
           x   Do investment advisors adjust their confidence based on the results?
           x   Does expertise reduce the self-attribution bias?
           x   W hat characteristics affect the severity of self-attribution bias?


    The empirical research is conducted using Finnish investment advisors who can be classified
   professionals’ as the participants have passed a General Securities Examination organiz by
as ‘                                                                                      ed
the Finnish Association of Securities Dealers (FASD). In addition to the professionals, the survey
is also carried out for two control groups, university students and employees of an engineering
company (laypeople).

    In relation to the research questions, there are several hypotheses according to which the
behavior of the respondents is expected to occur. The hypotheses make the manners that the
behavioral biases suggest concrete. There are also hypothesis for the impacts of certain
characteristics. The hypotheses of this study are:

x Hindsight biased people overestimate their initial ability to perform after learning the outcome
x Overconfident people overestimate their initial ability to perform before a task
x People suffering from self-attribution bias become more confident after a success
x Expertise and experience reduce behavioral biases
       o Professionals are least exposed to behavioral biases
       o Students are less exposed to behavioral biases than laypeople
x High cognitive ability decreases the exposure to behavioral biases
                                                 6


   .
1.4 Contribution

    In this thesis I study three behavioral biases of financial industry professionals using a field
survey. Majority of behavioral finance articles focus on one bias only (e.g. Barber and Odean
2001). In addition, the use of experimental or survey method is still relatively infrequent in
financial research. Typical experimental or survey studies on behavioral biases use samples that
                                             8                                     ).
include only students (Buksar and Conolly 198 ) or only professionals (Montier 2006 Studies
comparing financial market professionals and other people are rare and typically concentrate on
differences between two types of respondents (Kaustia et al 2008and Törngren and Montgomery
2004). This thesis uses a sample consisting of three separate groups of people; financial
professionals, university students and employees of an engineering company. In addition to the
diversity, the data of this thesis is also rare due timing. The surveys of this thesis are conducted
during the period of historically high uncertainty in financial markets, at the end of year 2008.

    Some of the methods used in this thesis have not been used before. To demonstrate hindsight
                     asset selection’ and ‘
bias I developed the ‘                    sign of return’ methods. The main insight in the new
                                                                                   ).
methods is in the two-phased structure, which is rarely used (Biais and W eber 2008 The ability
to recollect answers and repeat the surveys allows studying hindsight bias and self-attribution
                                                                )
bias in this thesis. Both hindsight bias (Biais and W eber, 2008 and self-attribution bias (Gervais
and Odean, 2001) are relatively infrequently studied in financial context. Overall, the results of
this thesis provide valuable new information on behavioral biases and investment advisors.



   . sul
1.5 Re ts summary

    This section presents a brief summary on the results of this study. The results of this study
are in line with following statements:

   x   People are exposed to hindsight bias
   x   Investment advisors are generally less exposed to hindsight bias than other people
   x   Investment advisors have a tendency to exaggerate their initial ability to predict asset
       returns, after learning the realization. The exaggeration reinforces with experience.
                                                  7


   x   People are overconfident
   x   Professionals generally outperform other people with lower level of confidence, which
       indicates lower overconfidence


   x   People suffer from self-attribution bias
   x   Investment advisors suffer more from self-attribution bias than other people


   x   Experience and expertise generally reduce exposure to behavioral biases
   x   Analytical thinking does not explain exposure to behavioral biases
   x   Faith in intuition explains exposure to behavioral biases


   x   Female professionals rank high in faith in intuition and bottom in analytical thinking
   x   Male professionals rank bottom in faith in intuition and top on analytical thinking


   . tructureof eS
1.6 S          th tudy

    The structure of the thesis is the following: Section 2 discusses the theoretical background.
Section 3 describes the data and methods used in the empirical test. Section 4 presents the results.
                          es
Finally, section 5summariz the thesis and concludes the results.
                                                   8


    y h lgc l a t r n e iin k n
2. Ps c oo ia f co si d cso ma ig

    The purpose of this chapter is to provide background information for the empirical tests that
are carried out. In this chapter I also describe the studied biases and discus the ways how
psychological factors affect financial decision making. I also go through the existing literature
about the issues that are related to this study.

    Previous empirical evidence shows that psychological factors have a substantial effect on
people’s decision making in several fields, including finance. In their classic study, Tversky and
             4)
Kahneman (197 present that people rely on a limited number of heuristic principles in complex
tasks involving uncertainty. In general, these heuristics are quite useful, but sometimes they lead
                                                                4)
to severe and systematic biases. Since Tversky and Kahneman (197 academic research has
reported numerous different biases. This study focuses on biases affecting individual conception
of person’s own ability to perform in given tasks. People have a tendency to be optimistic about
the future and their own ability to make forecasts, which indicates overconfidence.
Overconfidence leads people to i.e. take too much risk, which has severe consequences in
financial decision making.

    People also tend to overestimate their own performance to make forecasts after learning the
outcome. Indeed, people remember their initial estimates to been better than those actually were,
if asked afterwards. This is called hindsight bias. Hindsight bias and overconfidence are actually
very close each other;both demonstrate such individual thinking where an agent sees himself
better than he actually is. The existence of hindsight bias hinders the individual’s composition of
realistic assumptions about own capabilities and thus strengthens overconfidence. People fail to
        e
recogniz their true capability if the conception of success is based on their own memory.

    People have a tendency to attribute themselves about success but blame external issues for
failure. This bias, also related to conception about own capabilities is known as self-attribution
                                                          e
bias. Due to self-attribution bias people fail to recogniz their true capability even if they learn
their success from an unbiased source. Even though people are told about their failure, they keep
overestimating their own capabilities as they do not attribute the failure for themselves. As a
result of hindsight and self-attribution bias, it is difficult for people to learn to avoid
overconfidence.
                                                 9


    However, some previous studies show that with expertise and experience an individual is
                                                                                         )
able to learn to avoid biases. W ithin financial decision making e.g. Kaustia et al (2008 and
                            )
Alevy, Haigh, and List (2007 find that financial market professionals are less exposed to
behavioral biases than students. However, contradicting results also exists;Haigh and List (2005)
find that the behavior of traders is more biased than the behavior of students.



             t ias
2.1. Hindsigh b

    Hindsight bias refers to a tendency to perceive own performance better than it actually is,
after learning the realiz                                                              5
                         ation. The first studies of hindsight bias were Fischhoff (197 ) and
                        5                 5
Fischhoff and Beyth (197 ). Fischhoff (197 ) finds that receipt of outcome knowledge affects
subjects’ judgments in the direction predicted by the tendency to perceive reported outcomes as
                                                               creeping determinism’ but is
having been relatively inevitable. This tendency was called as ‘
                                                       5
nowadays better known as hindsight bias. Fischhoff (197 ) concludes that unperceived creeping
determinism can seriously impair our ability to judge the past or learn from it. In a more recent
                            )
study Biais and W eber (2008 present that for hindsight biased agents the ex-post recollection of
the initial belief will be closer to the realization than the true ex-ante expectation. Such agents
also fail to remember how ignorant they were before observing outcomes and answers.

    The effect of hindsight bias on learning has substantial consequences as hindered learning
                                                     9)
leads to increased overconfidence. Camerer et al (198 suggest that hindsight bias narrows the
gap between what occurred and what predictions are recalled, reducing valuable feedback and
                                                                             8
inhibiting learning. This in line with the results of Buksar and Conolly (198 ), who present also
that hindsight bias hinders learning from past experience. According to Biais and W eber (2008)
hindsight bias hinders learning and lead agents to underestimate volatility, which again results in
inefficient portfolio choice, loss making trades and poor risk management. In their study Biais
                )
and W eber (2008 arrange a two phase experiment to demonstrate hindsight bias. Their results
show that people have a tendency to adjust their 2nd phase answers (i.e. the recollection of the
initial estimates) based on the realization.

    Hindsight bias is not affecting only in unconscious way, like in ex-post evaluation of ex-ante
                                                                             8
decision, but also when subject is aware of the bias. Buksar and Conolly (198 ) find that student
                                                  10


subjects working on a strategic choice case, both alone and in groups, were unable to ignore what
they had been told about the actual results of a choice. As a result, they distorted their evaluations
of the original decision and the factors influencing it.

                                                      ed
    Behavior caused by Hindsight bias is also recogniz in studies observing other biases.
                  9),
Camerer et al (198 who study judgmental errors in economic settings, find that asymmetric
information is not always beneficial for the better-informed agent, which violates the common
assumption of economic analyses. This effect is known as curse of knowledge. According to
                  9),
Camerer et al (198 the curse of knowledge may also influence individual decision making
under uncertainty. Exaggerating the predictability of events intensifies the regret people feel
when choices yield outcomes worse than those that would have resulted from forgone options.
                                                                              I
This is in line with hindsight bias as people thinking behind this goes like “ knew this would
                                   .                                        8
happen, why I didn’t act correctly” In a similar vein Baron and Hershey (198 ) present that the
curse of knowledge suggests that outcome information will be overused;principals will tend to
think that ex ante optimal decisions with unfavorable outcomes were nonoptimal and that
                                                                             9)
nonoptimal decisions with favorable outcomes were optimal. Camerer et al (198 continue that
                                  ed
agents will be excessively penaliz for negative outcomes and insufficiently rewarded for
                                          8                                                   s
favorable results. Buksar and Conolly (198 ) present that when outcomes are poor, then, people'
                                                                                  I
evaluations of earlier decisions tend to be biased in an unflattering direction. " should have
                                 z
known it all along”they feel, puz led at their poor decision making.

    Traditional way to justify market rationality is to state that even though some investors are
irrational, markets in total are rational as the individual irrationalities are random and thus on
                                                 9)
average cancel each other out. Camerer et al (198 found that hindsight bias in markets was half
as large as bias in individual judgments. Their data suggest that the error-correcting power of
markets derives not from the feedback they provide, but from the disproportionate activity of
more rational traders.

    Hindsight bias is also affecting performance evaluation in principal agent relation.
                             )                 )
Mangelsdorff and W eber (1998 and Madarasz(2008 show that, in a principal agent relation, the
hindsight bias will prevent the principal from correctly evaluating the performance of the agent.
                                   ),
According to Biais and W eber (2008 biased principals fail to remember what was known when
the agent’s decision was taken.
                                                11


2.2. Ove    ide
        rconf nce

    People have a tendency to be overly confident about own capabilities and level of
knowledge. Psychological research has discovered many ways how overconfidence affects
human behavior in several fields. The effects of overconfidence are strongly present in difficult
decisions that include uncertainty. Thus financial decision making is very likely affected by
                                                                 better than average’,
overconfidence. Overconfidence appears in several forms, such as ‘
optimism bias’ and ‘
‘                  setting too narrow confidence limits’.

    Studies of overconfidence have typically examined people’s confidence in their ability to
answer general knowledge questions, but similar results have also been found in financial
settings. Results imply that people suffer from overconfidence also in financial decision making.
The effects of overconfidence on financial decisions are serious and can be risky to financial well
                                       7
being. According to Lewellen et al (197 ) overconfident investors trade more, believe returns to
be highly predictable and expect higher returns than what less confident people do. In similar
                )
vein Odean (1998 finds that overconfident investors will overestimate the value of their private
information, causing them to trade actively. However, active trading does not lead to better
performance. Indeed, Barber and Odean (2000), who study trading behavior of households, find
that households that trade freq                                   ed
                               uently earn much lower net annualiz geometric mean return than
those that trade infrequently. Thus overconfidence can be hazardous to individual’s wealth.

    Overconfidence is not affecting only individual investors;also the professionals suffer from
                 )            4%
it. Montier (2006 finds that 7 of fund managers perceive themselves as above average at their
jobs while only a small minority believes that they are below the average. Törngren and
Montgomery (2004) find that professionals overestimate their probability to choose the better
                                                               )
performing stock from two alternatives by over 20%. Olsen (1997 finds that professional
investment managers tend to overestimate probabilities of outcomes that are positive to the
respondent and to underestimate undesired outcomes.



   . ef-
2.3 S l attribution bias

    Self-attribution bias refers to a tendency to overestimate the degree to which people are
                                                                                    0)
responsible for their own success. According to Hastorf, Schneider, and Polifka (197 people are
                                                 12


prone to attribute success to our own dispositions and failure to external forces. In a similar vein
Gervais and Odean (2001) explain that people assess their own abilities not so much through
introspection as by observing our successes and failures. Most people tend to take too much
credit for our own successes.

    Self-attribution bias affects the conception about own capabilities as it hinders the evaluation
of past performance. This leads to overconfidence. Indeed, Gervais and Odean (2001), who
studied the effects of past results in traders’ behavior, find that success leads to increased
overconfidence. W hen a trader is successful, he attributes too much of his success to his own
ability and revises his beliefs about his ability upward too much, which increases overconfidence.
Gervais and Odean (2001) also find that both volume and volatility increase with the degree of a
      s
trader' learning bias. As a result overconfident traders behave suboptimally, thereby lowering
their expected profits

    Deaves, Lüders, and Schrö         )
                             der (2005 study overconfidence in making stock market
expectations among German financial professionals. They find that the professionals are not just
overconfident but their level of overconfidence increases after a successful forecast measured by
90% confidence interval. In addition, the adjustment to wider confidence interval after failure is
smaller than the adjustment to narrower interval after success. This results from psychological
phenomenon of cognitive dissonance, which suggests that people prefer to forget their failures
and rather remember their successes. Cognitive dissonance is closely related to self-attribution
bias and also somewhat related to hindsight bias. Even though self-attribution bias aggravates
overconfidence Gervais and Odean (2001) present that average levels of overconfidence are
greatest in those who have been trading for a short time. W ith more experience, people develop
better self-assessments.



   .         fe
2.4 Factors af cting e           e avioral iase
                      xposureto b h       b s

    The exposure to behavioral biases is individual;however it is affected by demographic and
socioeconomic factors. In this chapter I discuss how different characteristics have been found to
affect behavioral biases. The two characteristics, experience and thinking style, that are in the
focus of this study are discussed in separate sections 2.4.1 and 2.4.2.
                                                 13


    The two most studied and natural demographic factors, gender and age, affect both to the
degree of exposure to behavioral biases. Psychological research has established that men are
more prone to overconfidence than women, particularly so in male-dominated realms such as
                                   7
finance. Indeed Lewellen et al (197 ) find that men have stronger tendency to overconfident
behavior than woman have. These findings are supported by Barber and Odean (2001), who find
that men are more active traders, which serves as a proxy for overconfidence. Using the same
                                                              )
database as Barber and Odean (2001), Korniotis and Kumar (2007 find that older investors have
better knowledge about investing and hold less risky and more diversified portfolio. This implies
                                                                 )
that overconfidence decreases with age. Korniotis and Kumar (2007 also find that the negative
age effect is less apparent in the group of individuals with higher education and higher income.



   .1.
2.4 Expertise

    In the economics literature it is commonly believed that more sophisticated subjects behave
fundamentally differently, as they learn from experience to avoid biases and their behavior is also
influenced by higher incentives. However, there is no fully coherent evidence in previous
literature about the effects of expertise on behavioral biases.

    Studies comparing the decision making of financial market professionals to other people find
that whether or not professionals are less biased depends on the context. According to Bradley
    1),
(198 people with high degree of perceived expertise in the area of a general knowledge
question are likely to have unrealistically high expectations of the probability of answering
correctly. In a similar vein Törngren and Montgomery (2004), who study overconfidence of stock
market professionals and laypeople, find that both laypeople and professionals were
overconfident, but the professionals overestimated their ability by a greater margin. Their results
suggest that the information-based predictions of the professionals do not outperform the simple
heuristics used by laypeople, although the professionals expect that to happen. Haigh and List
     )
(2005 find that the floor traders at the Chicago Board of Trade (CBOT) demonstrate a greater
                                                                          )
degree of myopic loss aversion than students. Alevy, Haigh, and List (2007 find that students
more closely follow Bayes’ rule, whereas CBOT professionals are better at assessing the quality
                                                                        )
of public information, and thus earn higher profits. Kaustia et al (2008 study anchoring effect
and find that the effect obtained with students is several times higher than the effect obtained
                                                            14


with professionals. Thus their results imply that expertise significantly attenuates behavioral
                                            ing
biases. A series of field experiments utiliz the market for sports memorabilia reported in List
                      )
(2003;2004a;2004b;2006 supports the notion that experience attenuates behavioral biases in
                                                                                       )
general. However, it seems that a limit to sophistication exists as Kaustia et al (2008 do not find
difference among the professionals regardless of the level of experience.

       The evidence among students implies that expertise reduces behavioral biases. Kaustia et al
     )
(2008 find less sophisticated students to anchor their return estimates more than the group of
                                                                       )
more sophisticated students. In the framing study of Glaser et al (2006 a further comparison
between students who study finance and those who do not study finance shows that financial
education decreases the effect of framing.



   .2.         il                th         l
2.4 Cognitiveab ityand individual inking stye

       Similarly to expertise, individual’s cognitive ability is found to reduce behavioral biases.
                            )
Lubinski and Humphreys (1997 explain that general intelligence or various more specific
                                                                                         ),
cognitive abilities are important causal determinants of decision making. Frederick (2005 who
studied how the score of the cognitive reflection test (CRT)1 explains individual’s decision
making, found that CRT scores are predictive of the types of choices that feature prominently in
tests of decision-making theories, like expected utility theory and prospect theory.

                                                      )
       In his tests of time preference Frederick (2005 found that people who scored higher on the
CRT were generally more “        ;
                         patient” their decisions implied lower discount rates. For short-term
choices between monetary rewards, the high CRT group was much more inclined to choose the
later larger reward. It appears that greater cognitive reflection fosters the recognition or
appreciation of considerations favoring the later larger reward. In the test of risk preference
               )
Frederick (2005 found that in the domain of gains, the high CRT group was more willing to
gamble, particularly when the gamble had higher expected value. For items involving losses, the


1
    The cognitive reflection test (CRT) refers to a test which is designed to measure individual’s cognitive ability using
                                         offers’ wrong answer but which can be solved by systematic thinking. An
simple tasks for which intuition usually ‘
                             bat
example of such task is the “ and ball”problem (see Nagin and Pogarsky, 2003). High CRT score refers to a
tendency to think (rational system) whereas low CRT score refer to impulsive decision making (experiential system)
                                                      15


high CRT group was less risk seeking;they were more willing accept a sure loss to avoid playing
a gamble with lower (more negative) expected value. Although discount rates and perceived
utilities are individual, Frederick’s (2005 findings are so strong2 that they indicate that people
                                           )
with higher cognitive abilities are more capable in making optimal decisions.

       In psychological literature it is commonly accepted that people process information by two
parallel, interactive systems: a rational system and an experiential system (see i.e. Tversky and
             3
Kahneman, 198 and W einberger and McClelland, 1991). Based on cognitive-experiential self-
                                                                  )
theory (CEST, Epstein 1990, 1991, 1993, 1994), Epstein et al (1996 present a test for cognitive
ability, called rational-experiential inventory (REI). The REI-test contains two dimensions, one
measuring analytic-rational processing, and the other measuring intuitive-experiential processing.

       The analytic-rational processing is measured using the need for cognition (NFC) scale of
                       2).                                 )
Cacioppo and Petty (198 According to Cacioppo et al., (1996 people with higher NFC are
found to do better on arithmetic problems, anagrams, trivia tests and college coursework, to be
more knowledgeable, more influenced by the quality of an argument, to recall more of the
information to which they are exposed, to generate more “task relevant thoughts”and to engage
in greater “information-processing activity.”Thus people with high NFC scores can be expected
to be less exposed to behavioral biases.

       The intuitive-experiential processing is measured using a scale called faith in intuition (FI).
                                )
According to Epstein et al (1996 strong experientiality (high FI score) may interfere with logical
thinking;that is, people who are strongly experiential tend to accept their heuristic thinking as
rational. However, the use of heuristics does not necessarily lead to rational behavior (Tversky
                 4).
and Kahneman, 197 Thus people with high FI scores are expected to be more exposed to
behavioral biases.




2
                               )                                              %
    For example Frederick (2005 found that only 31% of low CRT sample chose 15 change of $1.000.000 (expected
       15                    5
value $ 0.000) over certain $ 00. The respective proportion of high CRT sample was 60%.
                                                16


     t n     to s
3. Da aa d meh d

    In order to find answers to the research questions an empirical study is conducted. In this
section I present the data and methods used in the study. In section 3.1 I describe the
characteristics of the data and the process of data collection. Section 3.1 also includes a short
                       ue
description of the uniq period during the surveys. In section 3.2 I discuss the tests that are
carried to measure the studied biases.



 .1.
3 Data

    The data section is divided into two subsections. The first subsection describes the process of
how the data is collected. The first subsection also discusses the characteristics of the sample
groups. The second subsection describes the events of the 2008 finance crisis, which was at its
peak during the surveys of this study.



3        le        th
 .1.1. Col ction of edata

    Data for the empirical study is collected in several controlled field surveys. In these surveys
the participants are asked to fill a questionnaire. The setting includes two phases for each group.
Time between the phases is approximately three weeks, depending on group (see table 1). The
first phase questionnaire contains questions for background information, a rational-experimental
inventory and three return estimation tasks. The background information questions include sex,
age and financial experience related questions. The rational-experimental inventory includes ten
statements about individual thinking style. Based on the answers the thinking style of the
respondent is charted. The answers for these statements are collected on a one to five scale. The
complete list of statements can be found on section 3.2.4. In the return estimation tasks the
respondents are shown a graph that contains the development of two assets’ total return indices in
last 12 months. The respondents are then asked to choose the better performing asset from the
pair during an approximately three week period and classify the strength of their view (i.e. the
certainty that their selection wins) on a one to five scale. In addition they are asked to give an
estimate for the return of the better performing asset and set a 90% confidence interval limits for
                                                         17


this return. The asset pairs used are Russian vs. Brazilian shares, EUR-GBP vs. EUR-SEK, and
oil vs. gold3. The complete phase one questionnaires can be found from the appendix 7.3.

       In the second phase questionnaire the participants were asked to summon up their initial
answers and estimates from the first phase. These answers and estimates were then recollected.
The respondents were told that it is very important that they answer now even though they could
not remember their initial answers very well. The respondents were also asked to classify how
well they remember their initial answers. In addition to the recollection, the second phase
questionnaire also included the same return estimation tasks than the first phase questionnaire,
naturally with updated return periods. The complete phase two questionnaires can be found from
              .3.
the appendix 7 The timing of the survey dates and the lengths of the return estimation periods
are shown in table 1. Phase 1 return estimation periods start on the survey date and end on the
phase 2 survey date. Phase 2 return estimation periods start on the survey date and end at
31.12.2008.



        be      r e a e n eu n si t e id
      Ta l 1 –Su v yd tsa dr t r e tma ep ro s
                                               ae
                                           Ph s 1                 ae
                                                              Ph s 2             nt
                                                                               Le g h1             nt
                                                                                                 Le g h2
       Group 1 (professionals)              25 .9.08          20.10.08           25                72
       Group 2 (professionals)              29.9.08           30.10.08           31                62
       Group 3 (professionals)              2.10.08            4.12.08           63                27
       Group 4 (students)                  17 .10.08          14.11.08           28                47
       Group 5(laypeople)                  30.10.08           27 .11.08          28                34




3.1.2. S   e aracte
        ampl ch    ristics

       The sample of the study includes five separate groups of controlled field survey participants.
Three of the groups consist of investment advisors working in a Finnish bank, one of students at
Helsinki School of Economics and one of people working at a large industrial engineering
company. The three investment advisor groups are merged to a single group for analysis
purposes. The groups are named as investment advisors, students and laypeople. Respectively the

3
                                              il
    The indices of the assets are: FTSE W Braz Euro total return index, FTSE W Russia Euro total return index, UK £
to Euro (W MR&DS) exchange rate, Swedish Krona to Euro (W MR) exchange rate, MLCX Crude Oil (W TI) total
return index (OFCL), and MLCX Gold total return index (OFCL). The indices are downloaded from Datastream.
                                                18


   es                   6                      9               5
siz of the groups are: 5 investment advisors, 8 students, and 5 laypeople. Thus the total
          e
sample siz is 200.

                                                                                      her
    The overall sample includes 104 men, 95 women and 1 who did not want to reveal his/
                                                                  1)                     1
sex. The respective distributions within the groups are 20 + 35 (+ investment advisers, 6 + 28
                                                                          5
students and 23 + 32 laypeople. Ages of respondents range between 18 and 6 years. Due to the
fact that majority of students are 18 to 24 years the overall age distribution is relatively skewed.
Table 2 presents the age distributions by groups.



           be     srb to f g
         Ta l 2 –Diti u ino a e
                Age            v d.
                             In . a v         St de t
                                                u n            y ol
                                                             La pe p e           All
               18-24           0%               4
                                               8 %              4%              39 %
               25-29           27%             11 %            22 %             19 %
               30-34           14 %            0%              15%              8%
               35-39           14 %            1%              16%              9%
               40-44           16%             2%              20 %             11 %
               45-49           21 %            1%               7%              9%
                0-5
               5 4             7%              0%               5%              4%
                5 9
               5 -5            0%              0%               9%              3%
                0-6
               6 5             0%              0%               2%              1%



    On average the investment advisors have over ten years of industry experience, the median
experience is eight years. The distribution of experience is skewed. The majority of investment
advisors in this study have experience less than ten years but on the other hand many have a long,
over 20 years experience. Figure 1 shows the distribution of expertise. To demonstrate the
proportion of inexperienced investment advisors a separate column is drawn for experience of 0
                                                                                   ed
to 2 years. The investment advisors have passed the first level examination organiz by FASD
and were studying for the second level examination at the time of the data collection.
                                                19


          gr      srb to f x e in e
         Fiu e1 –Diti u ino e p re c

                                         s rbuton  x re e
                                        Di ti i ofe pe i nc

           0
          4 %

           5
          3 %

           0
          3 %

           5
          2 %

           0
          2 %

           5
          1 %

           0
          1 %

          5%

          0%
                 0 -2    -
                        05           61
                                      -0              11
                                                     1 -5            62
                                                                    1 -0              0
                                                                                     2-
                                                 s      perenc
                                              Year of ex i e




    The surveys for the professionals’ sample are held in context of FASD examination training
sessions. The participants arrive to the first phase sessions without knowing in advance about the
survey. At the beginning of the training session the participants are asked to voluntarily take part
in a research.

    The student sample consists of undergraduate students at Helsinki School of Economics. The
survey is carried out in a corporate finance exercise session that these students attend. The course
in mandatory for students majoring in finance or accounting, and it typically is their second
course in finance. All students attend an elementary finance course and have thus been exposed
to the basics of financial markets, including return and volatility. The students are at the
beginning of their specialization in university business studies, and have limited work experience
                                                                                     )
in financial markets. This student sample is very similar to what Kaustia et al (2008 had in their
study.

    The laypeople sample consists of employees of a large multinational engineering company.
The participants are professionals on their own occupation but have limited knowledge on
finance. The educational background of the participants is relatively typical: 23% of the
                                              %
respondents have a university level degree, 38 have college level degree and 39% have 2nd
level or lower education. Majority of the respondents have either technical or commercial
                                                            20


                                            %                          %
education: 39% have commercial education, 36 have technical and only 25 have some other
education. The sample includes participants from numerous organizational positions (e.g. senior
vice president, customer service employee and product responsible engineer).

       The collection of the student and laypeople samples differ a little from the collection of
professional sample. Similarly to professional sample the participants arrive to the exercise
session /monthly briefing without prior information about the survey. For practical reasons the
questionnaires are dealt at the beginning of the session even though the actual time reserved for
the survey is at the end of the session. At the beginning the participants are briefly told the
purpose of the questionnaire and that there is time reserved for filling at the end of the session.
The survey is conducted after the normal agenda. The participants are instructed for the
questionnaire and told about the second phase. However the participants are not specifically
asked to remember their answers for the second phase. The participants are also told that all are
given a small reward for participating4. The setting for second phase is similar to the first phase,
with the exception that the participants know about the coming survey.

       The students and laypeople were asked if they have made stock market transactions
                       %
themselves. In total 48 of non-professionals had made personal stock market transactions.
There is no difference between students and laypeople. However, men have more personal
                                       5%
experience in stock market investments; 6 of men have made transactions whereas only 35%
                                                                            7
of women have. Also the major (students) and education (laypeople) affects;5 % of students
with finance major have personal experience but only 41% students with other major have.
W ithin the laypeople sample 60% of respondents with technical education has personal
investment experience. The respective proportion for respondents with commercial education is
  %.
45 This rather surprising observation partly results from the fact that only 23% of commercial
                                           %
employees have university degree whereas 35 of technical employees have university degree.
People with university degree generally are in higher positions in work organizations and thus
have more funds to invest. Accordingly, 69% of respondents with university degree have
personal investment experience. The respective proportion of people with lower level of
education is 42%. Figure 2 presents the results in graphical form.


4
    All participants receive a stock market related card game at the second phase session.
                                                     21



            gr       ro a i v sme t x e in e
           Fiu e2 –Pe s n ln e t n e p re c

                                   Personal investment experience by group

                      M en
                   W om an

                   Students
              nance m aj
             Fi         or
                  her or
               O t m aj

                Laypeopl  e
                 Techni cal
               Com m ercial
                U ni     t
                    versiy
               Low erlevel

                              0%            20 %          40 %           60 %       80 %

                                              Personal investment experience




 .1.3               20 8
3 . Financecrisis of 0

    The surveys for the data gathering were held between 25.9.2008and 27        .
                                                                        .11.2008 This period
included elusively violent events and exceptionally strong volatility on the financial markets. For
example the wide-ranking bankruptcy of Lehman Brother took place only a few days prior to the
first survey. This most likely affects the thinking of the survey participants, especially the
professionals. As the reasons that caused the finance crisis of 2008 are wide and complex and
thus out of the scope of this study, I discuss these issues only very briefly and in a simplifying
manner.

    The 2008 finance crisis stems from the problems with subprime mortgages that started to
            uly   .
build up in J 2007 Between 2000 and 2003, the Federal Reserve lowered the federal funds
                  .5
rate target from 6 % to 1.0%. The reason behind this was an attempt to soften the effects of the
collapse of the dot-com bubble and of the September 2001 terrorist attacks. These actions
lowered the cost of capital in the market and made the lending to customers with lower than
normal refund ability profitable for banks. This resulted a high demand in houses as people who
had not been able to buy own houses before were now able to do that. The high demand
transmitted to house prices that increased strongly, eventually causing a bubble.
                                                22


                                                                   ed
    The mortgages granted to subprime debtors were mainly securitiz and diversified to a wide
range of financial market participants. These financial agreements known as mortgage-backed
securities (MBS), which derive their value from mortgage payments and housing prices, became
more and more common. The market for the MBS’s worked properly as long the housing prices
increased, however problems started to build up as prices started to decline and repayment
failures increased. The values of MBS’s started to deteriorate sharply and the holders had to
report losses. The fact that MBS’s are difficult to value and have low transparency caused a
situation where the holders of MBS’s were not able to explicitly report the value of their
                                                           e
holdings. This caused a market wide lack of thrust and froz the interbank debt market. This
resulted in a liquidity crisis.

    Insufficient liquidity was the single most important reason behind the bankruptcies of e.g.
                        ),                                      ).
Bear Stearns (March 2008 Lehman Brothers and AIG (September 2008 Even though financial
institutions faced significant losses from subprime mortgages the lack of thrust and thus
negligible liquidity was the reason that made those to collapse. The market wide shortage of
liquidity increased the cost of capital dramatically and thus diminished the investments and
activities of other than financial sector too. This made the international stock markets to plummet
rapidly. The return and volatility for each combination of asset and respondent group in this study
are shown in table 3. Table 3 is divided into two panels;panel A for phase 1 statistics and panel
B for phase 2 statistics. Figure 3 shows the survey dates on a timeline with return development of
each asset.
                                           23


  be      t r t tsis
Ta l 3 –Reu nsa itc
 Pa nelA:phase 1       ofessi
                      Pr     onal 1    ofessi
                                      Pr     onal 2   Pr
                                                       ofessional 3   Student    Engi "
                                                                                 "    neer
           Return         3
                         - 3%             3
                                         - 4%            - 2%
                                                          2            1
                                                                       - 5%         1
                                                                                   - 7%
   azl
 Br i
                li
           Volatity       43
                         1 %              45
                                         1 %             1 %
                                                          15            12
                                                                      1 %            9
                                                                                   8 %
           Return         4
                         - 5%            - 5%
                                          4               3
                                                         - 0%           6%          1
                                                                                   - 2%
 Russia
                li
           Volatity       27
                         1 %              45
                                         1 %             1 %
                                                          16            24
                                                                      1 %           07
                                                                                   1 %
           Return          7
                         1, %            1,
                                         - 5%            - 9%
                                                         5,            6,
                                                                      - 7%         7,
                                                                                   - 6%
 GBP
                li
           Volatity        2
                         1 %               4
                                         1 %             1 %
                                                           6            6
                                                                       1 %           7
                                                                                   1 %
           Return        3,
                         - 0%            2,
                                         - 4%            - 4%
                                                         5,            1,
                                                                      - 6%         3,
                                                                                   - 7%
 SEK
                li
           Volatity        0
                         1 %               1
                                         1 %             1 %
                                                           3            0
                                                                       1 %           4
                                                                                   1 %
           Return         3
                         - 4%             3
                                         - 7%            - 1%
                                                          4            2
                                                                       - 4%         2
                                                                                   - 5%
  l
 Oi
                li
           Volatity        4
                         7 %               4
                                         7 %             7 %
                                                           7            9
                                                                       7 %           4
                                                                                   8 %
           Return         9
                          -%              1
                                         - 6%             -%
                                                          2             9
                                                                       -%            4
                                                                                   1 %
 Gold
                li
           Volatity        6
                         3 %               8
                                         3 %             4 %
                                                           0            0
                                                                       4 %           0
                                                                                   4 %


       B:
 Panel phase 2         ofessi
                      Pr     onal 1    ofessi
                                      Pr     onal 2   Pr
                                                       ofessional 3   Stud ent   Engi "
                                                                                 "    neer
          Return          1
                          - 3%            - 6%
                                          1                6%           4
                                                                       -%           7
                                                                                    -%
   azl
 Br i
               li
          Volatity         8
                          8 %              8
                                          7 %             6 %
                                                           2             5
                                                                       7 %           8
                                                                                   6 %
          Return          2
                          - 3%            3
                                          - 3%            - 7%
                                                          1             1
                                                                       - 6%         2
                                                                                   - 3%
 Russia
               li
          Volatity         8
                          8 %              2
                                          8 %             5 %
                                                           4             3
                                                                       6 %           3
                                                                                   5 %
          Return         1 6
                         - 9, %          1 8
                                         - 8, %          - 0, %
                                                         1 0           1 7
                                                                      - 2, %       1 5
                                                                                  - 4, %
 GBP
               li
          Volatity         7
                          1 %              7
                                          1 %             2 %
                                                           1             7
                                                                       1 %           8
                                                                                   1 %
          Return          8,
                         - 9%            1 1
                                         - 0, %          - 0%
                                                          3,           8,
                                                                      - 4%         6,
                                                                                   - 5%
 SEK
               li
          Volatity         7
                          1 %              7
                                          1 %             1 %
                                                           9             9
                                                                       1 %           0
                                                                                   2 %
          Return          3
                          - 7%            - 3%
                                          3                3%           1
                                                                       - 8%         1
                                                                                   - 7%
 Oil
               li
          Volatity         6
                          8 %              8
                                          8 %             7 %
                                                           5             0
                                                                       9 %           2
                                                                                   9 %
          Return           5
                          1 %             2 %
                                           3               6
                                                          1 %            9
                                                                       1 %          8%
 Gold
               li
          Volatity         7
                          3 %              6
                                          3 %             3 %
                                                           1             5
                                                                       3 %           2
                                                                                   3 %
                               24

 gr       t r e eo me t i ln
Fiu e3 –Reu nd v lp n tmei e
                                                 25


 .2. th
3 Me ods

    In this chapter I discuss the methods used in the empirical study. The data gathered in the
controlled field surveys enables a wide range of analyses to be carried out. The structure of the
survey makes it possible to study the three biases in question. The main insight in formulating the
tests described in this section is to compare the observations from different phases of the surveys
to each other. Hindsight bias is observed by differences between initial answers and the
                                                                         ed
recollections. Overconfidence is studied using initial answers and realiz results. Analyses of
self-attribution bias use initial answers from first and second round.



3              t ias
 .2.1. Hindsigh b

    In this study the effects of hindsight bias are examined in four aspects of behavior. The tests
                                  e
are designed to versatilely utiliz the data collected in the survey. The underlying logic for all of
the four tests is the main attribute of hindsight bias;people tend to percept their own initial
behavior as more optimal than it actually is after learning the future.



3            t lction efct
 .2.1.1. Asse see      fe

    The first aspect is to study if remembering own selection in a winner selection task is
                         asset selection effect’. Asset selection effect refers to an attribute of
unbiased. This is called ‘
hindsight bias where people tend to remember their initial selection incorrectly in a task where
they are asked to select a winner from two alternatives. After learning the outcome hindsight
biased agents remember that they chose the winning asset even though it may not be true.

    The logic behind the asset selection test of this study is based to the effect where hindsight
                              e
biased agents fail to recogniz a failure in a winner selection task, like the one in this study. The
tendency of overestimating own success is measured by comparing the actual proportion of
correct answers and the respective remembered proportion. Thus this analysis uses the initial
                                                                      ed
selections, the recollections of the initial selections and the realiz results from the
questionnaire. Naturally some proportion of the recollections is incorrect simply because the
                            her
respondent has forgotten his/ initial selection. However, these falsely remembered answers
                                                       26


should distribute randomly and irrespective of the outcome and thus should not affect the results
related to hindsight bias.

    The statistical significance of the difference between true and remembered proportions of
successful answers is tested using a difference in proportions z-test. The z-score is calculated
using equation 1. In the equation p1 refers to the true proportion of successful answers, p2 refers
to the proportion of respondents who believe they answered correctly, n1 and n 2 refer to the sizes
of the samples.

                                                     p1  p 2
                                              z
                                                      s p1  p 2                                 (1)
W here,


                                                  p (1  p )   p (1  p )
                             s p1  p 2                      
                                                      n1           n2                            (2)


W here,

                                                  n1 p 1  n 2 p 2
                                          p
                                                     n1  n 2                                    (3)




3         ign re    fe
 .2.1.2. S of turn efct

    The second aspect is to study if remembering the sign of own return estimate in return
                                            sign of return effect’. The logic of this analysis is an
estimation task is unbiased. This is called ‘
attribute of hindsight bias where people tend to remember the sign of their initial return estimate
                                      ed
incorrectly. After learning the realiz return hindsight biased agents remember that they
estimated the sign of return correctly even though it may not be true. The method and logic in
this test are similar to the assets selection test. The only difference is that hindsight bias is
measured from the sign of a return estimate instead of asset selection. The tendency of
overestimating own success is measured by comparing the actual proportion of correctly
estimated sign of return and the respective remembered proportion. The statistical significance of
                                                     27


the difference between true and remembered proportions of correct sign of return is tested using
the exact same difference in proportions z-test as in asset selection test.



3      .   t re      fe
 .2.1.3 Drifof turn efct

    The third aspect is to study a tendency of remembering own initial estimates to be closer to
          ed
the realiz figures than they actually are (i.e. moving closer to realized). This is done by
comparing the actual return estimates, the recollections of the actual estimates, and the realized
returns. In this design the subjects are first asked to report their ex-ante expectations at the first
phase of the survey. Then, they learn the realization of the return at the second phase. Finally
they are asked to report their ex-post recollection of their ex-ante expectations.

    The difference between the initial return estimate and the recollection is calculated for each
respondent. To demonstrate hindsight bias the sample is divided into two groups based on the
initial answer –realization relationship. Such answers in which the initial estimate is higher than
          ed
the realiz result form the first group. Answers in which the initial estimate is lower than the
      ed
realiz result form the other group. The logic in this structure is to separate the answers based on
                    drift’ is likely to affect.
which direction the ‘

    To test the statistical significance of the differences between initial answers and the
recollections a paired t-test is used. The t-stat is calculated using equation 4. In the equation x1
refers to the initial return estimate, x2 to the recollected version, sD refers to the standard
deviation in the group of x 2-x1, and N is the sample size.



                                            x   2    x1                                           (4)
                                t
                                        s   D         N


3      . tre    vie fe
 .2.1.4 S ngthof w efct

    The fourth aspect studied is the change of confidence, which in this study is represented by
the strength of the view score. This aspect is studied by comparing the initial strengths of the
                                     ed
view, their recollections, and realiz returns. The main interest is in the alteration between the
                                                     28


initial strength of view and the recollection, not in the actual level of confidence. To demonstrate
hindsight bias the sample is divided into two groups based on success of the asset selection task.
The other group is the ones with believed correct answer and the other is the ones with believed
incorrect answer. The logic behind this is an attribute of hindsight bias according to which people
that believe they answered correctly may overestimate their initial certainty and people that
believe they answered incorrectly may underestimate it. The difference between the initial
strength of view and the recollection is tested and the statistical significance is determined using
the same paired t-test method as in drift of return test.



3.2.2. Ove    ide
          rconf nce

                                                                                        setting too
    Overconfidence is studied in two sets of tests. The first set of tests observes the ‘
narrow limits’ –effect by examining how the respondents estimate volatility. The second set of
tests observes the relation between perceived confidence and actual ability to success in asset
selection task.

                                        setting too narrow limits’ effect, is studied by collecting
    The first aspect of overconfidence, ‘
90% confidence boundaries for return in the return estimation tasks. In the simplest analysis
overconfidence is measured as the difference between the actual hit rate and 90%. This simple hit
rate comparison test is however vulnerable to extraordinary market conditions (see section 3.1.3)
and thus overconfidence is also measured by observing the estimated volatilities. The 90 %
confidence boundaries are converted to volatility estimates using the following equation 5:


                                                 s
                                                 2
                                             N  ,9
                                                0         
                                    V                                                            (5)
                                              T
                                                25 0
W here,
          s = width of the spread (upper limit –lower limit)
                                                              ed
          N = Probability as standard deviations in standardiz normal distribution (z)
          T = duration of the estimation period (days)
                                                           29


    The fact that the surveys were held on different dates and the estimation periods were
uneq                                                                                     es
    ually lengthy makes accurate volatilities difficult to calculate. Also the sample siz for
separate asset – return period combinations would be very small. For these reasons a simplified
analysis is carried out. In this analysis the three investment advisor groups are pooled together
and the volatilities for each asset class are calculated by averaging the individual volatilities of an
asset-time combination. Student and laypeople samples are issued separately but the volatilities
for each asset class are also calculated with the same method. These converted and averaged
                                           ed
volatility estimates are compared to realiz and previous volatilities.

    The second set of overconfidence analyses uses a logit-regression to forecast success in
picking the better performing asset. Logit-regression is a convenient way to demonstrate the
effects of certain variables on a probability to succeed in a binary task. For the purpose of this
study logit-regression is appropriate method to study which factors contribute to the probability
that a respondent chooses the better performing asset from the two alternatives. The regression
uses the binary variable of success as the response (dependent) variable. The used explanatory
(independent) variables for the regression are determined based on the collected background
information. In addition to background information the strength of view score is used in the
regression. The main interest in the regression analysis is to study the effect of confidence
(strength of view score) on performance. A negative impact on the probability to succeed would
be a strong sign of overconfidence. Also the independency of success from strength of view is
interpreted as overconfidence.

    The statistical significance of the regression coefficients is tested using a W ald test. The
W ald score is calculated using eq        .
                                  uation 6 The score is compared against a chi-square
distribution.


                                                ( Tˆ  T 0 ) 2
                                         w                                                          (6)
                                                  Var ( Tˆ )

W here,
          ^
                  = the maximum likelihood estimate of an variable
              0   = Proposed value of the variable ( 0 )
                                                  30


    As the relation of confidence and success is studied and existence of overconfidence is
determined based on this relation, it is important to study factors affecting confidence. For this
reason an ordinary least square regression is carried. The purpose of this regression is to discover
factors affecting confidence. An increase in confidence for some variable while the same variable
lowers performance, indicate overconfidence. Thus the results of this OLS-regression are
compared to results of the logit-regression. The regression uses the strength of view score as the
response (dependent) variable for confidence. The used explanatory (independent) variables are
gender, profession and the thinking style scores NFC and FI. The significance of the results is
demonstrated using standard t-test.



 .2.3 efattrib
3 . S l-      ution bias

    The effects self-attribution bias of are studied in two tests. Both tests measure self-attribution
bias by the change in perceived certainty of success between first and second rounds. The
difference is in the determination of success. First test uses individual answers whereas second
test uses pooled answers for a single person.

    In the first test a respondent’s recollected certainty (strength of view score) of an individual
task at phase 1 is compared to the given certainty to the repetition of the same task. Self-
attribution bias is determined by the difference between these scores. The analysis uses
recollection instead of initial strength of view score to eliminate effects of hindsight bias to this
analysis. To demonstrate self-attribution bias the sample is divided into two, based on the
perceived correctness of the initial answer. The logic in this is an attribute of self-attribution bias
according to which people that believe to be successful attribute themselves on the success and
thus increase their confidence on a repetition of the task. On the contrary people who believe to
be unsuccessful may decrease their confidence on a repetition of the task. The statistical
significance of these differences is calculated using a similar paired t-test as with hindsight bias
analyses.

    The second test is similar to the first test with exception that the respondents are categorized
into four groups based on how many correct answers they believe they had on the first round. The
change of confidence in each group is observed using the same method of calculating the
                                                    31


difference in the strength of view score between phase 1 (recollection) and phase 2. Also
similarly to other tests in this study, the significance of the differences is calculated using a paired
t-test.



 .2.4      -xpe ntial ntory
3 . Rationale rie    inve

     This section presents the rational-experiential inventory and the calculation of Need for
Cognition (NFC) and Faith in Intuition (FI) scores. The calculation of the scores is based on the
inventory consisting of ten statements. The answers for these statements are collected on a one to
five scale. The following list shows the statements. The score to which the statement is related is
                                                                                    ed.
reported in parenthesis after the statement. The order of the statements is randomiz The
marking of (R) after the statement refers to the reverse nature of the statement.

    1. Thinking hard and for a long time about something gives me little satisfaction (NFC) (R)
    2. I trust my initial feelings about people (FI)
    3. I prefer to do something that challenges my thinking abilities rather than something that
          requires little thought (NFC)
    4. I believe in trusting my hunches (FI)
     .
    5 I prefer complex to simple problems (NFC)
     .
    6 I try to avoid situations that require thinking in depth about something (NFC) (R)
     .                                                            gut
    7 W hen it comes to trusting people, I can usually rely on my " feelings"(FI)
     .
    8 My initial impressions of people are almost always right (FI)
            t
    9. I don'like to have to do a lot of thinking (NFR) (R)
                                                                        t
    10. I can usually feel when a person is right or wrong even if I can'explain how I know (FI)

     The scores are calculated using the equations 7 and 8 (subscript number refers to the
question). Reversed questions naturally have negative impact on the total score. To transform the
                               2,
answers on a scale from -2 to + three is deducted from all the actual scores. The reason for this
is to create a scale distributed evenly around zero.

   NFC = -(score1 - 3) + (score 3 - 3) + (score5- 3) - (score 6- 3) - (score 9 - 3)               (7)

   FI = (score2 -3 ) +(score 4 - 3) + (score7- 3) + (score8-3 ) + (score10 -3 )                   (8)
                                                 32


     sls
4. Re ut

    The results section presents the results from the tests described in section 3.2. In addition to
the plain presentation of the result I discuss the possible reasons behind the results and the
consequences. The interconnection between the biases and possibly explanatory characteristics is
also discussed. The first three subsections discuss the actual behavioral biases observed in this
study. These sections are considered as the main contribution of this study. In addition the results
from the psychological test are presented in the last subsection.

    As investment advisors are the most important sample of this study and stock market
estimates are most usual for investment advisors, separate analyses on investment advisors’ stock
market estimates are carried. For several of the tests, there are such extra analyses after the actual
results discussion. These analyses use the same methods as the actual tests but focus on the
impacts of professionals’ biases on their occupation.



 .1.      t ias
4 Hindsigh b

    The effects of hindsight bias are studied in four different tests. The results of the first two
       asset selection’ and ‘
tests, ‘                    sign of return’, are considered as main contribution of the hindsight
bias section of this study. However results from the latter two tests, drift of return and strength of
                                                             ues
view also support the analysis of hindsight bias. The techniq used are discussed in more detail
in section 3.2.1.



4          t lction efct
 .1.1. Asse see      fe

    Asset selection effect refers to an attribute of hindsight bias where people remember their
initial selection incorrectly in a task where they are asked to select a winner from two
alternatives. Hindsight biased agents remember that they chose the winning asset even though it
may not be true. In this study asset selection effect is tested by comparing the true and
remembered proportions of correct answers in the asset selection tasks. Table 4 shows the results
from the test. The purpose of table 4 is to show the initial selections in relation to recollected
versions of the selections. Thus both true and remembered proportions of successful answers in
                                                33


the asset selection tasks are shown, as well as the difference. To discover the statistical
significance of the results a difference on proportions z                      True’ sample consists
                                                         -test is carried out. ‘
                                                            remembered’ sample consists of all
of all answers that included the selection of asset and the ‘
                                                                                            es
answers that included the selection of asset and the recollection. Thus the total sample siz are
 8       7         es
5 8and 36 . The siz of the subsamples may vary depending on the number of rejected answers
sheets.
                                                        34


  be     n sg t is a s t ee to fe t 3
Ta l 4 –Hid ih b a , se s lcinefc 1/
Table 4 reports both True and Remembered proportions of successful answers in the asset selection tasks. True
refers to the actual percentage of correct answers whereas Remembered refers to the percentage of answers
perceived correct in the recollection. Diff. indicates the difference between the two proportions, Remembered less
True. The score of a difference on proportions z      -test is reported in parentheses. The table is divided in four
panels, A, B, C, and D, in which the results of partitioned sample are shown.

  ne A: mp e riin d sd n oeso
Pa l Sa l Pa tto e Ba e o Pr fsin
                                 Success %
                         True                                      Remembered                        Diff.
Professionals             3
                         6 %                                           7
                                                                      6 %                            4%
                              6
                       (N = 16 )                                          8
                                                                    (N =15 )                        (0,72)
Students                                44 %                           9
                                                                      5 %                          15%* **
                                             8
                                      (N = 25 )                     (N =107)                        (2,62)
  y e pe
La p o l                                 5
                                        4 %                           55 %                          10%*
                                      (N = 164)                     (N =10 2)                       (1,65)

Panel B: Sample Partitioned Based on Need for Cognition Score
                                                u c ss
                                               S ce %
                                      u
                                    Tr e                      me ee
                                                           Re mb rd                                    f.
                                                                                                     Dif
  C
NF <2 (lw)o                        52 %                        65 %                                14%**
                                 (N = 190)                   (N =10 6)                              (2,25)
     C
2 <NF <6                                51 %                          59 %                           8%
                                      (N =231)                      (N =165)                        (1,60)
  C     ih
NF >6 (hg )                              5
                                        4 %                           61 %                         17 %***
                                      (N = 161)                      (N =96)                        (2,60)

                                              ntu
Panel C: Sample Partitioned Based on Faithin I ition Score
                                                u c ss
                                               S ce %
                                      u
                                    Tr e                    me ee
                                                          Re mb rd                                     f.
                                                                                                     Dif
 I     o
F < 1 (lw)                         53 %                      56 %                                    3%
                                 (N = 160)                 (N =111)                                   ,54
                                                                                                    (0 )
    I
1 <F <5                                  8
                                        4 %                           60%                          12 %**
                                      (N =229)                      (N =148)                        (2,22)
 I      ih
F > 5 (hg )                              8
                                        4 %                           69 %                         21 %***
                                      (N = 193)                     (N =10 8)                       (3,49)

Panel D: Sample Partitioned Based on Gender
                                                      u c ss
                                                     S ce %
                                          u
                                        Tr e                         me ee
                                                                   Re mb rd                            f.
                                                                                                     Dif
 e l
F mae                                   50%                           65 %                         16 %***
                                      (N = 273)                     (N =188)                        (3,32)
   l
M ae                                     9
                                        4 %                           57 %                          8 %*
                                      (N = 312)                     (N =176)                        (1,70)

 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%
                                    35


    l at in f h mpe o
         t                     o t e fe t n h n e ewe n e mb rd n re
                                  i
   Al p ri o s o tesa l sh w ap si v efc i c a g b t e rme ee a d tu
ae f c e        we e, o me at in h ifrn e s o stt c l g iia t a e
                              t                     st y
rt o su c ss. Ho v r f rso p ri o s tedfee c i n t ai ial sinfc n. P n l
    o   h e l o a h e o d n ru .
              s                         e r fssin l mpe o       ny
A sh ws te rsut f re c rsp n e tg o p Th p o e o as sa l sh ws o l a 4 %
 ifrn e ih s o ai c ly g i c n v n t
                   st      i              ec n g i c n e e e
                                                  i
dfee c whc i n tstt ial sinf a te e a 10 p re tsinf a c lv l(z= 0.72).
 td ns mpe o             ec n ifrn e h t s ihy g ii n
                                                   c                   .0
S u e t sa l sh ws a 15 p re tdfee c ta i hg l sinf a t(z = 2.62, p < 0 1).
  y e pe mpe o            ec n ifrn e h t s g iia t t    ec n g iia c
La p o l sa l sh ws a 10 p re tdfee c ta i sinfc n a 10 p re tsinfc n e
e e (z          se n h se e l r fssin l e o e h e st x o d n u e th
                             s
lv l = 1.65). Ba do te rsut p o e o as se m t b tela e p se a dstd n te
  st x o d ru , a p o l a n ewe n e a t h t r fssin l r e st x o d o
mo e p se go p ly e pely i b t e . Th fc ta p o e o as ae la e p se t
 sse lci fe t p o t h y oh si h t x et e u e e a irl ise
        o                                 se                        we e,
a tsee t n efc su p rs teh p te s ta e p ri rd c s b h vo a ba s. Ho v r
h    p o t s ny a s u e t o         r g r x o r h n a p o l, l u h h
                                     o                         h
te su p r i o l we k a std ns sh w st n e e p su e ta ly e pe ato g te
 y oh si h t u e t o ss    r x et h n
                                  se      al a p o l s o a r n n .
                                            e
h p te s ta std ns p sse mo ee p ri ta soc l dly e pei n t sto go e

     e fe t f n iiu l hn ig ye n sse lci fe t s o n mbg o s.
                                       o
   Th efc o idvd a tikn stl o a tsee t n efc i n tu a iu u The
  e o     g io
             i     C) o e h t e rse t n lt l hn ig o s o x li sse
                                          c
Ne d f rCo nt n (NF sc r, ta rp e ns a ayia tikn , d e n te pan a t
  lci fe t i al. a e
     o       n             rse t h t oh ih n o
see t n efc l e ry P n lB p e ns ta b t hg a d lw NF    o e at o s o
                                                              t
                                                    C-sc r p riin sh w
 ai c l g iia t ifrn e ewe n r e n e mb rd c e ae u o o h
   st y
stt ial sinfc n dfee c b t e tu a d rme ee su c ss rts b tn tf rte
 d l at in
        t       e o     ec n    C mpe o           ec n ifrn e h t s
mide p ri o . Th lw 30 p re t NF sa l sh ws a 14 p re t dfee c ta i
 g iia t t ec n g iia c e e                 e d l 0 ec n mpe o       n
sinfc n a 5 p re tsinfc n elv l(z= 2.25). Th mide4 p re tsa l sh ws a 8
 ec n ifrn e         ). e ih    ec n mpe o           ec n dfee c h t s
p re tdfee c (z= 1.60 Th hg 30 p re tsa l sh ws a17 p re t ifrn eta i
 ihy g i a c
         i              ,     .0     e e l o o p o t h y oh si h t
                                            s
hg l sinfc n e (z = 2.60 p < 0 1). Th se rsut d n tsu p r te h p te s ta
 n lt lhn ig e u e e a irl ise
     c
a ayia tikn rd c s b h vo a ba s.

     lk n lt l hn ig at n nut n o
            c           h     i           rihf r r eai shp ewe n
                                                        o
   Unie a ayia tikn , fi i iti o sh ws a stag to wad rlt n i b t e
 sse lci fe t n n iiu l hn ig ye at n nut n I o e e o x li
        o                              h      i
a tsee t n efc a d idvd a tikn stl. F i i I tio (F ) sc r se ms t e pan
 sse lci fe t i al. a e
        o       n              o h e l r m e s n mpe at in d a d
                                        s                  t
a tsee t n efc l e ry P n lC sh ws tersut fo tst o sa l p ri o e b se
 n -sc r. e o      ec n I mpe o       ny     ec n ifrn e ewe n r e n
o FI o e Th lw 30 p re tF sa l sh ws o l a3 p re tdfee c b t e tu a d
e mb rd c e ae        e ifrn e s o sinfc n e e t     ec n sinfc n e e e
rme ee su c ss rts. Th dfee c i n t g iia t v n a 10p re t g iia c lv l
     .54   e d l 0 ec n mpe o           ec n ifrn e h t s g i a t t
                                                             i
(z= 0 ). Th mide4 p re tsa l sh ws a12 p re tdfee c ta i sinfc n a 5
 ec n e e             n l h ih
                         y         ec n mpe o       po     ec n ifrn e
p re tlv l(z= 2.22). Fial tehg 30 p re tsa l sh ws u t 21 p re td fee c
h t s ihy g ii n
              c          9,    .0     e e l n a e C mpy h t h r s
                                           s                      rn
ta i hg l sinf a t(z= 3.4 p < 0 1). Th rsut i p n l i l ta teei asto g
eai shp ewe n at n nut n n e a irl ise
   o            h     i
rlt n i b t e fi i itio a db h vo a ba s.
                                   36


    so e d r fe t e o xst a e            o h e l at o e y e d r e
                                                   s    t
   Al a g n e-efc se ms t e i . P n lD sh ws te rsut p riin d b g n e. Th
e l mpe o            ec n ifrn e ewe n re n e mb rd c e ae
fmae sa l sh ws a16 p re tdfee c b t e tu a d rme ee su c ss rts. The
 ifrn e s ih y g i c n (z
                  i                .0     e e e t ifrn e o
                                                 v            n s ec n
dfee c i hg l sinf a t = 3.32, p< 0 1). Th rsp cied fee c frme i 8 p re t
  ih s g i c n a 10 ec n sinfc n e e e (z
          i
whc i sinf a t t p re t g iia c lv l = 1.70).

     eal h e l n a l n iae h t e pe id h msev s c e dn
              s                                         r f hy
                                                            e
   Ov rltersut i tbe4idc t ta p o l fn te le su c e igmo eo tnte
 cu ly o i p o t h vd n e h t e pe fe r m id g t is. i h t hsn
a tal d . Ths su p rs te e ie c ta p o l su frfo hn sih ba If d ta ti
 fe t e rse t r g o m f id g t is. t e urs
               o                            r     n w t l ln ’ id f
efc rp e ns ast n f r o hn sih ba I rq ie mo e ‘Ik e i alao g kn o
hn ig o l n ’s iay h ie f lci h n mpy du a i a st e o e h
         e                     o                n     ma
tikn t atro e bn r c oc o see t nta si l a jst l e re i t t me tte
e l t . e h se sse s l
   z o                     r o cee n h s a e o e mb r h n eu n
raiain Th c o n a ti aso mo e c n rt a d tu e sirt rme e ta a rtr
 st e n u e o ma. n iay lci a h be t a ny k ih o wr n
   ma                             o
e i t i an mb rf r t I abn r see t ntsktesu jc c no l ma earg t r o g
 h ie
c oc .

     oh r ssu h t a e e r m a l     s h ef r n e f a h r u .
   An te i e ta c n b se n fo tbe 4 i te p ro ma c o e c g o p The
 ef r n e s   a rd s h ec na e f oa o rc n r o e e dn           eh r t s
p ro ma c i me su e a tep re tg o ttlc re ta swes n td p n ig wh te i i
 o rcl e mb rd
      y           e r fssin l r o rc n         f a s, u e t 4   n
c re t rme ee . Th p o e o as ae c re ti 63 % o tsk std ns 4 % a d
apo l 5         mpe on o s o rc 50 f i s, h ny r u up ro mig u e
ly e pe4 %. As si l c i tss i c re t % o tme teo l g o po tef r n p r
a d mn ss s h rfssin l r u .
rn o e i tep o e o as g o p

     e e l n ae
          s          fal      p o t h y oh si h t x et e u e e a irl
                                                       se
   Th rsut i p n lA o tbe 4 su p r te h p te s ta e p ri rd c s b h vo a
 ise    we e h a t h t u e t h t r y oh sie o o s       r x et h n
                                                                se
ba s. Ho v rte fc ta std ns, ta ae h p te z d t p sse mo e e p ri ta
a p o l, e o e h     st x o d ru ase    u sto n h b r fssin ifrn e
ly e pe se m t b temo e p se go pri s aq e ino tesu -p o e o dfee c s
 n x etse     n r hs u st o  u te n lsi n x ein e s l are u. be
o e p ri . Toa swe ti q e inaf rh ra ay s o e p re c i asoc rido tTa l 5
e o t h me ifrn e ewe n r n e mb rd c e ae s a l , t h
                           u                                   h
rp rs te sa dfe e c b t e t e a d rme ee su c ss rts a tbe 4 wi te
 x e t h t a h f h r fssin mpe r u te at in d a d n x et eae
      o                                     t                 se
e c pin ta e c o tep o e o sa ls aef rh rp ri o e b se o e p ri rltd
 aibe
v ra ls.
                                          37


   le          t ias,                     /
Tab 5– Hindsigh b asset selection effect 23
  be e o t oh u n          me ee r p ri s f c e u n r n h sse lci a s. u
                                         o                                  o
Ta l 5 rp rs b t Tr ea d Re mb rd p o o t n o su c ssf la swes i te a tsee t n tsk Tr e
 ees o h cu l ec na e f o rc n r           ee s me ee ees o h ec na e f n r
rfr t te a ta p re tg o c re ta swes wh ra Re mb rd rfr t te p re tg o a swes
 ec ie o rc i h e ol t . f. n iae h ifrn e ewe n h wo r p ri s, me ee e
                       e o                                            o
p rev dc re tnterc l cin Dif idc ts tedfee c b t e tet p o o t n Re mb rdlss
  u . e o e f ifrn e n r p ri s -tsts e o td n ae te s.
                                o
Tr e Th sc r o adfee c o p o o t n z e i rp re i p rnh se

                                         u c ss
                                        S ce %
                               u
                              Tr e                  me ee
                                                  Re mb rd                  f.
                                                                           Dif
 r fssin l
P oe o as
     p re c    er
  Ex ein e< 5 y as           65 %                   68 %                   3%
                            (N =63)                (N =57)                (0,39)
     p re c     er
   Ex ein e> 5 y as           62 %                   66 %                  4%
                            (N = 103)              (N =10 1)              (0,63)

    ann
   Triig                     69 %                   69 %                   -1 %
                            (N =39)                (N =35)                   ,0
                                                                          (-0 6)
      ann
   NoTriig                    61 %                   67 %                  5%
                            (N = 127)              (N =123)               (0,86)
 td ns
Su e t
   ia c    jr
  Fn n eM ao                  50%                   57 %                   7%
                            (N = 105)              (N =51)                (0,86)
            p re c
       OwnEx ein e           50%                    57 %                   7%
                            (N =60)                (N =30)                  ,60
                                                                          (0 )
              p
       NoOwnEx .              9
                             4 %                    57 %                   8%
                            (N =45)                (N =21)                (0,62)

    h r jr
   Ote M ao                    0
                              4 %                   61 %                 21 %***
                            (N = 153)              (N =56)                (2,68)
            p re c
       OwnEx ein e            9
                             4 %                    62 %                  12 %
                            (N =65)                (N =26)                (1,06)
              p
       NoOwnEx .             33 %                   60%                   27%***
                            (N =88)                (N =30)                 (2,61)

        p re c
   OwnEx ein e                50%                   59 %                   9%
                            (N =125)               (N =56)                (1,16)
          p re c
   NoOwnEx ein e              38 %                  59 %                  20%**
                            (N = 133)              (N =51)                 (2,50)
  y e pe
La p o l
         p re c
  OwnEx ein e                 3
                             4 %                     9
                                                    4 %                    6%
                            (N =81)                (N =59)                  ,70
                                                                          (0 )
          p re c
   NoOwnEx ein e              6
                             4 %                    63 %                  17 %*
                            (N =83)                (N =43)                (1,81)

 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%
                                     38


     e b r fssin e l f h r fssin l mpe r me a q a t a h te
                     s                                      h
   Th su -p o e o rsut o te p o e o a sa l ae so wh te u lwi e c oh r
 n n i n   t h oa r fssin l mpe e l
            h                         s.  e ifrn e ewe n r e n
a d i l e wi te ttl p o e o a sa l rsut Th dfee c b t e tu a d
e mb rd c e ae o n f h o r b r u s s o stt c ly g i c n e e t
                                                  st       i
rme ee su c ss rts f ra yo tef u su -g o p i n t ai ial sinf a t v na 10
 ec n g ii n e e e.
          c            n r ifrn e s n riig aibe o r fssin l o
p re tsinf a c lv l A mio dfee c i i tann v ra l. Th se p o e o as wh
 a e at p td n e a irl ia c mia ro o h r e ssin o
       c                                                          rci l
                                                                      c y
h v p riiae i ab h vo a fn n ese n r(p irt tesu v yse o ), sh w ap a t al
   ec n ifrn e ewe n r e n e mb rd c e ae             .0     we e, h
0 p re tdfee c b t e tu a d rme ee su c ss rts (z = -0 6). Ho v r te
e et v ifrn e o rfssin l o a e o at p td n c mia s
                                          c                      ec n
rsp cie dfee c f rp o e o as wh h v n tp riiae i su h se n ri 5 p re t
  ih s o g i a t
             i
whc i n tsinfc n (z = 0        e h u h h b r ai so      a , t p ot h
                       .86). Ev n to g te o sev t n i we k i su p rs te
 y oh si h t x et e u e e a irl ise
                 se
h p te s ta e p ri rd c s b h vo a ba s.

     e b r fssin e l f h u e t n a p o l mpe e o e ah r oai o
                     s                                            e
   Th su -p o e o rsut o testd n a dly e pesa ls se m t b rte v ltl f r
  ge ai a d n x et
       o              se n h u e t mpe jr f h e o d n n eso a
se rg t n b se o e p ri . I te std n sa l mao o te rsp n e ta d p r n l
n e me t x ein e e o x li h x o r o sse lci fe t l td ns
                                                    o        .
iv st n e p re c se m t e pan te e p su e t a tsee t n efc wel Su e t
 u yn i n e s h i jr a e
       n                     ec n dfee c ewe n r e n e mb rd c e
std igf a c a termao h v a7 p re t ifrn eb t e tu a drme ee su c ss
ae     ih s o g i c n
                 i
rts, whc i n tsinf a t(z= 0         h o tay u e t t te h n ia c
                                                     h               jr
                           .86). On tec nrr std ns wi oh rta fn n emao
  o       ec n dfee c ,  ih s ihy g ii n
                                      c                  .0 n     mi en
                                                                    a
sh w a21 p re t ifrn e whc i hg l sinf a t(z= 2.68, p < 0 1). I asi lrv i
 u e t h t a e eso a n e me t x ein e o         ec n ifrn e     ih s o
std ns ta h v p r n liv st n e p re c sh w a 9 p re tdfee c , whc i n t
 g ic n
    i                td ns    o o o a e eso a n e me t x ein e o
sinf a t(z = 1.16). S u e t wh d n th v p r n liv st n e p re c sh w a 20
 ec n ifrn e ih s g iia t t ec n g iia c e e                ). e e l s
p re tdfee c , whc i sinfc n a 5 p re tsinfc n elv l(z= 2.50 Th sersut
  p o th y oh si h t x et n x ein e e u e e a irl ise
                          se
su p r teh p te s ta e p ri a de p re c rd c b h vo a ba s.

    i l l o h u e t mpe h
       a                         b rfssin e l f h a p o l mpe r
                                              s
   S mi ry t te std n sa l, te su -p o e o rsut o te ly e pe sa l ae
 fe td y eso a n e me t x ein e     sp n e t h t a e eso a n e me t
afce b p r n l iv st n e p re c . Re o d ns ta h v p r n l iv st n
 x ein e o ny         ec n ifrn e ewe n r e n e mb rd c e ae         i
e p re c sh w o l a6 p re tdfee c b t e tu a d rme ee su c ss rts. Ths
 ifrn e s o g ii n v n t e ec n g iia c e e
                c                                      .70    h o tay
dfee c i n tsinf a te e a tn p re tsinfc n e lv l(z = 0 ). On te c nrr
e o d ns h t o o h v eso a iv st n e p re c o          ec n dfee c , ih
rsp n e t ta d n t a ep r n ln e me t x ein esh w a17 p re t ifrn e whc
s g ic n t
     i         ec n sinf a c e e =
                        i                    so h se e l p o t h y oh si
                                                        s
i sinf a ta 10p re t g i c n elv l(z 1.81). Al te rsut su p r teh p te s
h t x ein e e u e e a irl ise
ta e p re c rd c s b h vo a ba s.

     eal h e l n a l
              s          p o t h y oh si h t x et e u e e a irl ise
                                                 se
   Ov rl tersut i tbe5 su p r teh p te s ta e p ri rd c s b h vo a ba s.
  we e, f x et r y e u e e a irl ise h y oh si h t u e t o s
              se u                                                     r
Ho v r i e p ri t l rd c s b h vo a ba s, teh p te s ta std ns p sse mo e
 x et h t al a p o l a n t e c e td e se e e l n a l
     se        e                                   s          o h th r
e p ri ta soc l dly e pec n o b a c pe p r . Th rsut i tbe5 sh w ta tee
 r g i a t ifrn e n d u e t n a p o l mpe
       i                                          i g e s h t o sieig
ae sinfc n dfee c s isiestd n a d ly e pesa ls. Ths su g st ta c n d rn
                                               39


 x o r o e a irl ise t s      a igu f eso r l s a l   a t i n il o tx
                                                          h n
e p su et b h vo a ba s i i me nn f li ap r n tuyi fmiirwi f a ca c ne t
h o g eso a n e me t x ein e r d c t . o    e ru      eso s tewi
tr u h p r n l iv st n e p re c o e u ain Th g o p a p r n i oh r se
 ae o ie o s o mp ra t      t n x ein e a p o l n      u e t o eso a
c tg rz d t i n t i o tn. Boh ie p re c d ly e pe a d std ns (n p r n l
n e me t x ein e r ia c    jr r    st x o d o sse see t fe t u e t en
                                                       o
iv st n e p re c o fn n emao ) aemo e p se t a t lcinefc, std ns b ig
 v n r x o d h n a p o l.   u te n lz hs b r ai h u e t n a p o l
                                                  o
e e mo ee p se ta ly e pe Tof rh ra ay eti o sev t ntestd n a dly e pe
  mpe r o ld o eh r n h n iie a d n eso a x ein e be              rse t
sa ls ae p oe tg te a d te dvd d b se o p r n le p re c . Ta l 6 p e ns
h se e l
te rsut s.



   le          t ias                        /
Tab 6– Hindsigh b – asset selection effect 33
  be e o t oh u n          me ee r p ri s f c e u n r n h sse lci a s. u
                                         o                                  o
Ta l 6 rp rs b t Tr ea d Re mb rd p o o t n o su c ssf la swes i te a tsee t n tsk Tr e
 ees o h cu l ec na e f o rc n r           ee s me ee ees o h ec na e f n r
rfr t te a ta p re tg o c re ta swes wh ra Re mb rd rfr t te p re tg o a swes
 ec ie o rc i h e ol t . f. n iae h ifrn e ewe n h wo rp ri s, me ee e
                       e o                                            o
p rev dc re tnterc l cin Dif idc ts tedfee c b t e tet p o o t n Re mb rdlss
  u . e o e f ifrn e n r p ri s -tst s e o td n ae te s. e a l s iie n wo a es,
Tr e Th sc r o adfee c o p o o t n z e i rp re i p rnh se Th tbei dvd di t p n l
                                o
   n    n ih h e l f at in d mpe r o .
                      s      t                        e n rt h fe t f x et n r
A a d B i whc tersut o p rio e sa l aesh wn To d mo staeteefcs o e p ri i mo e se
 eal r fssin l r x ld d r m h mpe n oh a es. n n e u e t r x ld d n a e B.
     ,
d ti p oe o as aee cu e fo tesa l i b t p n l Fia c std ns aee cu e i p n l

Panel A: Students and Laypeople
                                               u c ss
                                              S ce %
                                     u
                                    Tr e                  me ee
                                                        Re mb rd            f.
                                                                           Dif

        p re c
   OwnEx ein e                       7
                                    4 %                   54%              7%
                                  (N = 206)             (N =115)          (1,17)
          p re c
   NoOwnEx ein e                     1
                                    4 %                   61 %           19 %***
                                  (N = 216)              (N =94)          (3,15)

Panel B: Stu                     ors
            dents less finance maj and Laypeople
                                              u c ss
                                             S ce %
                                      u
                                     Tr e                 me ee
                                                        Re mb rd            f.
                                                                           Dif

        p re c
   OwnEx ein e                       6
                                    4 %                   53 %             7%
                                  (N = 146)              (N =85)          (1,03)
          p re c
   NoOwnEx ein e                    39 %                  62 %           22 %***
                                  (N =171)               (N =73)          (3,22)

 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%




     e e l f h o ld mpe f u e t n a p o l a e
          s                                              rse t u te
   Th rsut o te p oe sa l o std ns a d ly e pe (P n lA) p e n frh r
 x ln to n h mp c f x ein e n e a irl ise e pe t eso a n e me t
                                                       h
e pa ain o te i a to e p re c o b h vo a ba s. P o l wi p r n liv st n
 x ein e o         ec n ifrn e ewe n r e n e mb rd c e ae
e p re c sh w a 7 p re t dfee c b t e tu a d rme ee su c ss rts. The
                                    40


 ifrn e o sinfc n a 10 ec n sinf a c e e (z
                               i                     e e e t ifrn e o
                                                            v
dfee c n t g iia t t p re t g i c n elv l = 1.17). Th rsp ciedfee c f r
 e pe t u p r n ln e me t x ein e s
        h                                 ec n whc s ihy g i a t
                                                             i
p o l wi o t eso a iv st n e p re c i 19 p re t ihi hg l sinfc n (z= 3.15,
    .0     e vd n e n x ein e is e u ig e d n y s r g e e l n a e B,
                                                      o          s
p< 0 1). Th e ie c o e p re c ’s b a rd cn tn e c i st n . Th rsut i P n l
  ih x ld s n r f ia c      jr u e t rse t v n r n e if n e f x ein e
                                                          u
whc e cu e a swes o fn n emao std ns, p e n e e sto g r n le c o e p re c .
 e pe t eso a n e me t x ein e o l
        h                                     ec n ifrn e ewe n r e n
P o l wi p r n liv st n e p re c sh w aso a7 p re tdfee c b t e tu a d
e mb rd c e ae        e ifrn e o g iia t t     ec n g iia c e e
rme ee su c ss rts. Th dfee c n tsinfc n a 10 p re tsinfc n e lv l(z =
   3). we e, e pe t u eso a n e me t x ein e o
                   h                                     ec n ifrn e
1.0 Ho v r p o l wi o tp r n liv st n e p re c sh w a22 p re tdfee c .
  e ifrn e s ihy g iia t                 .0     i rn te s h vd n e h t
Th dfee c i hg l sinfc n (z = 3.22, p < 0 1). Th s ste gh n te e ie c ta
 x ein e e u e e a irl ise
e p re c rd c s b h vo a ba s.

     oh r y o b r e sse lci fe t s o o ae h e l d n e ol td
                            o                      z          e
   An te wa t o sev a tsee t n efc i t c mp r te raie a d rc l ce
 i rb t s f h oa u e f o rc n r f n n iiu l e o i s h t id g t
       o
dstiuin o tettln mb ro c re ta swes o a idvd a. Th lgci ta hn sih
 is y fe th ec ie u e o c re t n r n h s h e ol td i rb t
                                                    e        o
ba ma afc tep rev dn mb r f o rc a swes a dtu terc l ce dstiuinmay
 e it r m h e l d c r ig o h id g t is y oh si h i rb t
               z                                        o ol e
d vaefo teraie . Ac o dn t tehn sih b a h p te s tedstiuin sh ud b
  r i e o r s ih u e f o rc n r
      t                                    e o h eai l o u e f
                                                    v
mo e tl d twad hg n mb r o c re ta swes. Du t te rlt ey lw n mb r o
e o d ns n p rt r u s, hs n lsi s o e o o ld mpe n ldn l rsp n e t
rsp n e t i se aaeg o p ti a ay s i d n t ap oe sa l, icu igal e o d ns
 t l h e nt l n r n h i e ol t s.
  h        i                     e o     ai d ees o h r p ri
                                           z                    o f
wi altre ii a a swes a d ter rc l cin ‘Re l e ’ rfr t te p o o t n o
e o d ns    o a h e et   v u e f o rc n r             c l td ees o h
                                                         e
rsp n e t wh h d te rsp cie n mb r o c re ta swes. ‘Re olce ’ rfr t te
 r p ri f e o d ns
       o                o ec ie o a e h e e t  v u e f o rc n r
p o o t n o rsp n e t wh p rev d t h v te rsp cie n mb ro c re ta swes.
  f.’ n iae h ifrn e ewe n ai d n
                                z           c l td c l td e
                                               e       e         ai d
                                                                   z
‘Dif idc ts tedfee c b t e ‘Re l e ’ a d ‘Re olce (Re olce lss Re l e ).
    e n rt ai c l g i c n e
                st     i        ifrn e n rp rin -tst o e s ac ltd
To d mo stae stt ia sinf a c a dfee c i p o o to s z e sc r i c luae .
 iu e    o h e l f hs e .
                  s
F g r 4sh ws tersut o ti tst
                                           41


       re          t ias,
   Figu 4– Hindsigh b asset selection effect


                             Distribution of correct answers
        50 %

        45 %

        40 %

        35 %

        30 %

        25 %

        20 %

        15 %

        10 %

            5%

            0%
                    ore t
                 0 c rc                ore t
                                    1 c rc                  ore t
                                                         2 c rc       ore t
                                                                    3c rc
       aize
     Re l d        8,6 %             42,2 %               35,3 %    13,8 %
       c l td
          e
     Re ol ce      3,4 %             31,0 %               47,4 %    18,1 %
      ff
     Di .         -5,2 %             -11,2 %              12,1 %     4,3 %
     z-s a
        tt         -1,65 *            -1,77 *              1,87 *    0,90




       a e e r m iu e e pe e d o e o t ih r u e o o rc a swes n h
   As c nb se nfo fg r 4p o l tn t rp r ahg e n mb r fc re t n r i te
e ol t h n h y cu l o ih.
    e o            y           i s ni
rc l cin ta te a tal g trg t Ths i i l e wi te h p te s a d aso wi te
                                      n    h
                                          t h y oh si n l         h
                                                                 t h
e l i u d b v . ee e o e eg f o d n a e l b t e n n wo
    s
rsu t dsc sse a o e Th r se ms t b av r eo g o a db d rsut ewe no ea d t
 o rc a swes. e pe r eu tn t e o nz h a t h t h y a e ny eo r n o rc
c re t n r P o l aerlca t orc g ietefc t a te h v o l z r o o ec re t
 n r n ah r ei e h t h y a e wo r h e o rc n r
                 e                                  fee c ewe n r e
a swe a d rte b l v ta te h v t o trec re ta swes. Difrn eb t e tu
 n ei e r p ri s o eo o rc n r s
       e           o                                 ih s g ii n t e ec n
                                                             c
a d b l v d p o o t n f rz r c re ta swes i -5.2%, whc i sinf a ta tn p re t
 g iia c e e               e e etv ifrn e o n o rc n r s                 ih
sinfc n elv l(z= -1.65). Th rsp ciedfe e c f ro ec re ta swe i -11.2%, whc
s l    g iia t t e ec n g i c n e e e
                            i                       o wo o rc n r h
i aso sinfc n a tn p re tsinf a c lv l(z = -1.77). F rt c re ta swes te
 ifrn e s o t ,
             v           e ifrn e s g ii n t e ec n e e
                                       c                               o
dfee c i p siie 12.1%. Th dfee c i sinf a ta tn p re tlv l(z = 1.87). F r
h e o rc a swes h ifrn e s .3%, whc h we e i n t g i c n (z= 0 ).
trec re t n r tedfee c i 4                          i
                                  ih o v r s o sinf a t       .90
                                   42


4.1.2. Sign of return effect

     in f eu n fe t ees o n trb t f id g t is ee e pe e mb r h g
    S g o rtr efc rfr t a atiueo hn sih ba wh r p o l rme e tesin
 f h i ii l eu n st e n o rcl n a
         i         ma               ee h y r sk d o rdc te eu n f n
o ter nta rtr e i t ic re tyi atskwh r te aea e t p e ith rtr o a
 sse. n sih ise g ns e mb r h t h y r be o rdc h g f h eu n
a t Hid g tba d a e t rme e ta te wee a l t p e itte sin o te rtr
 o rcl v n h u h t y o e r e in f eu n fe t s e e y o ai h r e
                                                             n
c re ty e e to g i ma n tb tu . S g o rtr efc i tstd b c mp r g te tu
 r p ri f o rcl st e g s f eu n
       o          y ma                 u ’) n e mb rd rp ri f o rc
                                                             o
p o o t n o c re t e i td sin o rtr (‘Tr e a d rme ee p o o t n o c re t
 g f eu n    me ee ’) n eu n st i a . be
                               ma o            o h e l rm h e .
                                                        s
sino rtr (‘Re mb rd i rtr e i t n tsk Ta l 7 sh ws tersut fo tetst
  e u p se f a l s o e n rt h ifrn e ewe n u ’ n           me ee ’
Th p ro o tbe 7 i t d mo stae te dfee c b t e ‘Tr e a d ‘Re mb rd
 r p ri s f o rcl st e g s f eu n
       o              ma                   i o e h ai c l g i a c f h
                                                      st      i
p o o t n o c re ty e i td sin o rtr . To dsc v rtestt ia sinfc n eo te
 ifrn e     ifrn e n r p ri s -tst s are u.
                           o                    e p r a h o hs n lsi s
dfee c s a dfee c o p o o t n z e i c rid o t Th a p o c t ti a ay s i
 mi t h sse see t n lsi n ci .1.1.
   a             o            o
si lr otea t lcina ay s i se t n4

      e o dt n o n r o e n ld d n g f eu n mpe r: isty t o tis h
            i
    Th c n i o s f ra swes t b icu e i sino rtr sa l ae fr l i c nan te
  lci f sse a d h e ol t ; c n l t o tis h eu n st e n e ol t n
     o               e o                          ma         e o
see t no a t n terc l cin se o d yi c nan tertr e i t a drc l cini
 o rc o ma; n hr l h e ol t
                          e o f sse lci s q a o h nt l lci . e
                                         o               i       o
c re tf r t a d tidyterc l cin o a tsee t n i e u lt teii a see t n Th
e so s o ist n   c n o dt n r b iu h e so o h hr o dt n s n
                           i                                       i
ra n fr fr a d se o d c n i o s ae o vo s, te ra n f r te tid c n io i i
 l ai h sse see t fe t u h mpe z n h ist h se s 28 n
  mi n           o                                         nh
ei n t gtea t lcinefc. Th s tesa l siei tefr p a i 4 a d264i te
  c n h se e mpe o si s f n r y 5 e o d ns.
se o dp a . Th sa l c n st o a swes b 14 rsp n e t
                                                43


   le          t ias,         rn       /
Tab 7– Hindsigh b sign of retu effect 12
  be e o t oh u ’ n           me ee ’ rp ri s f o rc g s n h eu n st i a s. u
                                            o                        ma o
Ta l 7 rp rs b t ‘Tr e a d ‘Re mb rd p o o t n o c re tsin i tertr e i t n tsk Tr e
 ees o h cu l ec na e f o rc sin f eu n ee s me ee ees o h ec na e f g s f
rfr t tea ta p re tg o c re t g s o rtr wh ra Re mb rdrfr t tep re tg o sin o
 eu n ec ie o rc n h e ol t .   e o    f. n iae h ifrn e ewe n h wo rp ri s,
rtr p rev d c re t i te rc l cin Dif idc ts te d fee c b t e te t p o ot n     o
  me ee e       u . e o e f ifrn e n rp ri s -tst s e o td n ae te s. e a l s
                                                o
Re mb rd lss Tr e Th sc r o adfee c o p o o t n z e i rp re i p rnh se Th tbei
 iie n o r a es,          n    n ih h e l f at in d mpe r o .
                                            s     t
dvd di fu p n l A, B, C, a dD, i whc tersut o p rio e sa l aesh wn

Panel A: Sample Partitioned Based on Profession
                                             e itd o rcl
                                          Prdce c re ty%
                                      u
                                    Tr e                  me ee
                                                        Re mb rd            f.
                                                                          Dif
 r fssin l
P oe o as                          11 %                    23 %         12 %***
                                 (N = 166)               (N =121)        (2,64)
 td ns
Su e t                            19 %                     26 %           7%
                                (N = 145)                 (N =65)        (1,12)
  y e pe
La p o l                          24%                      23 %          -1 %
                                (N = 117)                 (N =78)          ,14
                                                                        (-0 )

Panel B: Sample Partitioned Based on Need for Cognition Score
                                            e itd o rcl
                                          Prdce c re ty%
                                      u
                                    Tr e                       me ee
                                                           Re mb rd         f.
                                                                          Dif
  C
NF <2 (lw)o                        16 %                         24%       8%
                                 (N = 128)                    (N =72)        0
                                                                         (1,4 )
     C
2 <NF <6                          18 %                      22 %          4%
                                (N =183)                  (N =129)       (0,97)
  C     ih
NF >6 (hg )                       19 %                     27 %           8%
                                (N = 113)                 (N =63)        (1,30)

                                              ntu
Panel C: Sample Partitioned Based on Faithin I ition Score
                                            e itd o rcl
                                          Prdce c re ty%
                                      u
                                    Tr e                    me ee
                                                          Re mb rd          f.
                                                                          Dif
 I     o
F < 1 (lw)                         16 %                      17 %         1%
                                 (N = 126)                 (N =87)       (0,26)
    I
1 <F <5                           19 %                     27 %           8%
                                (N =162)                  (N =97)            4
                                                                         (1,4 )
 I      ih
F > 5 (hg )                       17 %                     28 %         11 %*
                                (N = 136)                 (N =80)       (1,85)

Panel D: Sample Partitioned Based on Gender
                                            e itd o rcl
                                          Prdce c re ty%
                                      u
                                    Tr e                 me ee
                                                       Re mb rd             f.
                                                                          Dif
 e l
F mae                              17 %                   25 %           8 %*
                                 (N = 214)              (N =14 1)        (1,84)
   l
M ae                              18 %                      23 %          4%
                                (N = 211)                 (N =123)         ,94
                                                                         (0 )

 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%
                                    44


    l at in f h mpe x ldn a p o l, o
         t                                      o t fe t n h n e ewe n
                                                   v
   Al p ri o s o tesa l, e cu ig ly e pe sh w ap siieefc i c a g b t e
e mb rd n r e ae f c e n st i h g f eu n we e, h ifrn e r
                              ma n
rme ee a dtu rt o su c ss i e i t gtesino rtr . Ho v r tedfee c s ae
 ai c ly g ii n ny o h e b mpe a e
   st       c                                o h e l o ah e o d n
                                                      s
stt ial sinf a to l f rtresu sa ls. P n lA sh ws tersut fre c rsp n e t
 r u . nee i l r fssin l o h rae ifrn e ewe n r e n e mb rd
            n
g o p I trst gy p o e o as sh w te ge tstdfee c b t e tu a d rme ee
  c e ae       e r fssin l mpe o              ifrn e ih s ai i ly ihy
                                                               c
su c ss rts. Th p o e o as sa l sh ws a 12 % dfee c whc i sttst al hg l
 g ic n
    i            ,     .0    td ns mpe o            ec n ifrn e h t s o
sinf a t(z = 2.64 p < 0 1). S u e t sa l sh ws a 7 p re tdfee c ta i n t
 g iia t t    ec n g i a c e e
                       i                       y e pe mpe o            ec n
sinfc n a 10 p re tsinfc n e lv l(z = 1.12). La p o l sa l sh ws a -1 p re t
 ifrn e h t s o sinf a t t
                   i
dfee c ta i n t g i c n a 10p re t g iia c lv l = -0 ). Th sl hl n g t e
                             ec n sinf n e e e (z
                                      c             .14      g y
                                                          e i t e ai  v
 ifrn e n a p o l a e nep ee s eo e a t h t r fssin l e o e h
dfee c o ly e pec nb itr rtda z r . Th fc ta p o e o as se m t b temost
 x o d ru a e at x lie y h i g f h r e s.
                     y              mi                e rb d n ci o
e p se go p c n b p rl e pan d b tet n o tesu v y As d scie i se t n 3.1
h    re o dt ni      r me a b o ma u ig h        r e s, sp cal u ig h
                                                             y
te mak t c n i o s wee so wh t a n r l d rn te su v y e e il d rn te
 r fssin l    r e s. e e l d eu n f h sses n h r fssin l
                          z                                  re s   r
p o e o as’ su v y Th raie rtr s o te a t i te p o e o as’ su v y wee
 e ai n
     v       uo      a s. e e e tv rp ri o oh u e t n a p o l s 6.
                                          o
n g t ei 17 o t f18 c se Th rsp ciep o o t n f rb t std ns a dly e pei 1/
  i o ie o h a t h t st f h st e a
                               ma         o tv g         f r fssin l
Ths c mbn d t tefc ta mo o tee i ts h d ap siiesin (92% o p o e o as,
  % f uet n           f a p o l) k s h o ai n ewe n e o d n r u s
80 o std ns, a d 91% o ly e pe ma e te c mp rso b t e rsp n e tgo p
 ifc l. e ag r p ri
dfiut Th lr e p o o t n o p siie sin u d r te p e ald mak t c n io s i
                     o f o t  v g s n e h rv i     e             i
                                                        r e o dt n s
nee i t f t st i l e l r m pi
     n se .      k     s       mi is    ih o v r s o dsc sse ee
itrst gi l I mo l eyrsut fo o t sm ba whc h we e i n t i u dh r.
  e n o aa i t f h r u s o s o o v r e u e h eibl y f h idn h t
            i                                        i
Th ic mp rbl y o te g o p d e n th we e rd c te rla i t o te fn ig ta
n e me t d i r e o a e e d n y o ec ie h msev s en be o rdc sin f
iv st n a vso s se m t h v atn e c t p rev te le b iga l t p e it g s o
 sse rtr s v n h u h t g t o b e l c
                                  st
a t eu n e e to g i mih n t erai i.

     e e e o n lt l hn ig
                 c          a rd y h    e o    g io
                                                  i     C) o e o s o
   Th lv l fa ayia tikn , me su e b teNe df rCo nt n (NF sc r, d e n t
 x li g f eu n fe t i al. a e B o h t oh ih n o
                    n
e pansino rtr efc l e ry P n l sh ws ta b t hg a dlw NF    o e att n
                                                                  i
                                                       C-sc r p ri o s
  o ih r ifrn e ewe n r n e mb rd c e ae h n h
                        u                                d l at in
                                                                t
sh w hg e dfee c b t e t e a d rme ee su c ss rts ta te mide p ri o .
  we e, h ifrn e s o sinfc n f r n f h r u s. e o     ec n NF   mpe
Ho v r tedfee c i n t g iia t o a yo teg o p Th lw 30p re t C sa l
  o    n   ec n ifrn e          0     e d l 0 ec n mpe o            ec n
sh ws a 8 p re td fee c (z = 1.4 ). Th mide 4 p re tsa l sh ws a 4 p re t
 ifrn e
dfee c (z= 0        e ih   ec n sa l o     n ec n dfee c           ). e
            .97). Th hg 30p re t mpesh ws a 8 p re t ifrn e(z= 1.30 Th se
e l r n i
   s       n   t h e l r m h sse lci e n h s o o p o t h
                h      s               o
rsut ae i l e wi te rsut fo te a tsee t n tsta d tu d n tsu p r te
 y oh si h t n lt lhn ig e u e e a irl ise
                 c
h p te s ta a ayia tikn rd c s b h voa ba s.

   n o ta t n ltc l hn ig at n nut n I o e e o x li g f eu n
                                    i
   I c nrst o a ayia tikn , fihi iti o (F ) sc r se ms t e pan sino rtr
 fe t i al. a e C o h e l r m e s n mpe at in d a d n I o e e
      n                     s                  t
efc l e ry P n l sh ws tersut fo tst o sa l p ri o e b se o F -sc r. Th
                                    45


o      ec n I mpe o       ny      ec n ifrn e ewe n r e n e mb rd
lw 30 p re tF sa l sh ws o l a 1 p re tdfee c b t e tu a d rme ee
  c e ae       e ifrn e s o g iia t v n t     ec n g iia c e e
su c ss rts. Th dfee c i n tsinfc n e e a 10 p re tsinfc n elv l(z= 0.26).
  e d l 0 ec n mpe o       n ec n ifrn e h t s o sinf a t t
                                                       i         ec n
Th mide4 p re tsa l sh ws a 8 p re tdfee c ta i n t g i c n a 10p re t
e e (z    4     e ih   ec n sa l o     n    ec n dfee c h t s g i c n a
                                                                 i
lv l = 1.4 ). Th hg 30p re t mpesh ws a 11 p re t ifrn eta i sinf a t t
   ec n g i a c e e (z
            i              9). e h u h h ifrn e r o ey g ii n h
                                                              c
10p re tsinfc n elv l = 3.4 Ev n to g tedfee c s aen tv r sinf a tte
e l n ae
   s            p o t h eai shp ewe n at n nut
                          o            h      o n e a irl ise
rsut i p n lC su p r terlt n i b t e fi i itiin a d b h vo a ba s. The
e l r l ni
    s         n t h e l n sse see t e .
                  h     s          o
rsu t aeasoi l ewi tersut i a t lcintst

     n e e o fe t l n g f eu n fe t a e D o h e l at o e ys    t
   Ge d rse ms t afc asoi sino rt r efc. P n l sh ws tersut p riin db
 e d r e e l mpe o        n ec n dfee c ewe n r e n e mb rd c e
g n e. Th fmaesa l sh ws a 8 p re t ifrn eb t e tu a d rme ee su c ss
ae     e ifrn e s g iia t t    ec n g iia c e e            ). e e etv
rts. Th dfee c i sinfc n a 10 p re tsinfc n e lv l(z = 1.84 Th rsp cie
 ifrn e o   n s ec n whc s o sinfc n a 10 ec n sinf a c e e (z .94
                                                   i
dfee c f rme i 4p re t ihi n t g iia t t p re t g i c n elv l = 0 ).

    i l l o sse lci , h e l r m g f eu n e s n iae h t e pe id
       a             o        s
   S mi ry t a tsee t n te rsut fo sin o rtr tst idc t ta p o l fn
h msev s c e dn   r fe h y cu l o ih p o t h vd n e h t e pe
                                 y
te le su c e ig mo e o tn te a tal d whc su p rs te e ie c ta p o l
  fe r m id g t is. we e, h g i a c s o s ih s t s o sse lci
                                i                                o
su frfo hn sih ba Ho v r te sinfc n e i n ta hg a i i f ra tsee t n
 fe t e r rsig b r ai n r fssin l x o r o g f eu n fe t s au be
                        o
efc. Th su p i n o sev t no p o e o as’ e p su et sino rtr efc i av la l
 idn .
fn ig

     e o h nq a i n f h       r e s e rb d b v ) h fe t f x etse n
   Du t te u e u ltmig o te su v y (d scie a o e te efcs o e p ri a d
 x ein e a n t e b re ei l y o aig h e l f p rt r u s. n re o
                           a                 s
e p re c c n o b o sev d rl byb c mp rn tersut o se aaeg o p I o d rt
 id o x et n x ein e fe t g f eu n fe t u te n lsi s are u.
            se
fn h w e p ri a d e p re c afc sin o rtr efc a f rh ra ay s i c rid o t
  be e o t h me ifrn e ewe n r e n e mb rd c e ae s a l           t
Ta l 8 rp rs tesa dfee c b t e tu a d rme ee su c ss rts a tbe7, wih
h xet    o h t a h f h r fssin mpe r u te at in d a d n x et
                                                  t                 se
te e c p in ta e c o te p o e o sa ls ae f rh rp ri o e b se o e p ri
eae aibe
rltdv ra ls.
                                          46


   le          t ias,         rn       /
Tab 8– Hindsigh b sign of retu effect 22
  be e o t oh u n         me ee rp ri s f o rc sin n h eu n st i a s. u ees
                                       o                         ma o
Ta l 8 rp rs b t Tr ea dRe mb rdp o o t n o c re t g s i tertr e i t ntsk Tr erfr
o h cu l ec na e f o rc sin f eu n ee s me ee ees o h ec na e f g s f eu n
t tea ta p re tg o c re t g s o rtr wh ra Re mb rdrfr t tep re tg o sin o rtr
 ec ie o rc i h e ol t . f. n iae h ifrn e ewe n h wo rp ri s, me ee e
                        e o                                        o
p rev dc re tnterc l cin Dif idc ts tedfee c b t e tet p o o t n Re mb rdlss
  u . e o e f ifrn e n r p ri s -tsts e o td n ae te s.
                                o
Tr e Th sc r o adfee c o p o o t n z e i rp re i p rnh se

                                      e itd o rcl
                                     Prdce c re ty%
                             u
                            Tr e                    me ee
                                                  Re mb rd             f.
                                                                      Dif
 r fssin l
P oe o as
     p re c    er
  Ex ein e< 5 y as          14%                    18 %               4%
                           (N =63)                (N =50)              ,54
                                                                     (0 )
    p re c     er
  Ex ein e> 5 y as          10%                    27 %             17 %***
                          (N = 103)               (N =71)            (2,97)

   ann
  Triig                      5%                    14%                9%
                           (N =39)                (N =21)            (1,22)
     ann
  NoTriig                   13 %                    25 %             12 %**
                          (N = 127)                      0
                                                  (N =10 )            (2,24)

 td ns
Su e t
   ia c    jr
  Fn n eM ao                24%                    31 %               7%
                           (N =72)                (N =36)            (0,78)
   h r jr
  Ote M ao                  15 %                   21 %               6%
                           (N =73)                (N =29)            (0,69)

       p re c
  OwnEx ein e               22 %                   24%                3%
                           (N =74)                (N =29)            (0,28)
         p re c
  NoOwnEx ein e             17 %                   28 %              11 %
                           (N =71)                (N =36)            (1,32)

  y e pe
La p o l
         p re c
  OwnEx ein e               25 %                   21 %               -4%
                           (N =64)                (N =47)               ,4
                                                                     (-0 6)
         p re c
  NoOwnEx ein e             23 %                   26 %               3%
                           (N =53)                (N =31)            (0,33)

 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%




    u te n lsi n x ein e f h r fssin l e e l h t x ein e ’ v r i e r v
   F rh ra ay s o e p re c o tep o e o as rv as ta ‘e p re c d (o e f ey a
  r i o y n e me t d i r r    r x o d o g f eu n fe t h n n x ei c d
                                                                e
wo khstr) iv st n a vso s aemo ee p se t sino rtr efc ta ‘ie p r n e ’
  ie e r r e       e n x ein e ’ n e me t d i r o        ec n dfee c ewe n
(fv y as o lss). Th ‘ie p re c d iv st n a vso s sh w a4p re t ifrn eb t e
r e n e mb rd c e ae        ih s o sinfc n (z .54    e e etv ifrn e
tu a drme ee su c ss rts, whc i n t g iia t = 0 ). Th rsp ciedfe e c
o x ei c d n e me t d i r
         e                          ec n, ih s ihy g ii n (z
                                                        c                .0
f r‘e p r n e ’ iv st n a vso s 17 p re twhc i hg l sinf a t = 2.97, p< 0 1).
                                    47


  i s p o t o a h y oh si g e s n u o ih g i c n e o s r b by o
            e                                        i
Ths i o p si t wh tteh p te s su g st a d d et hg sinf a c d e p o a l n t
e l u ey r m on ie c .  e o i e id hs idn s n la n e ur u te
                                                           e
rsutp rl fo c icd n e Th lgc b hn ti fn ig i u ce ra d rq i s frh r
 n lsi    fru aey h aa f hs u y o s o e a l u te a ay s n hs ssu .
a ay s. Un o tn tl, ted t o ti std d e n t n bef rh r n lsi o ti i e

     e te x et se aibe o n e me t d i r s riig o           r fssin l
   Th oh re p ri v ra l f riv st n a vso s i tann . Th se p o e o as who
 a e at p td n e a irl i n e mia ro o h r e ssin
       c                 n                                   o      ec n
h v p riiae i ab h vo a f a c se n r(p irt tesu v yse o ), sh w a9 p re t
 ifrn e ewe n r e n e mb rd c e ae        ih s o g i c n
                                                    i
dfee c b t e tu a d rme ee su c ss rts, whc i n tsinf a t(z= 1.22). The
e et v ifrn e o r fssin l o a e o at p td n c mia s
                                         c                       ec n
rsp ciedfee c f rp o e o as wh h v n tp riiae i su h se n ri 12 p re t
  ih s g i a t t ec n g i a c e e
          i                 i
whc i sinfc n a 5 p re tsinfc n elv l(z= 0        i p o t h y oh si h t
                                          .86). Ths su p rs teh p te s ta
 x et e u e e a irl ise
     se
e p ri rd c s b h vo a ba s.

   n h u e t mpe jr f h e o d n o s o x li x o r o g f eu n
   I te std n sa l mao o te rsp n e td e n te pan e p su e t sin o rtr
 fe t t i n e n te
          n              jr u e t o rci l mi ifrn e ewe n r e
                                            c y    a
efc. Boh f a c a d oh rmao std ns sh w p a t al si lrdfe e c b t e tu
 n e mb rd c e ae         i r f h ifrn e s g ii n. eso a n e me t
                           h                     c
a d rme ee su c ss rts. Nete o te dfee c s i sinf a t P r n liv st n
 x ein e e o x li h x o r o g f eu n fe t d rtl. td ns h t a e
e p re c se ms t e pantee p su et sino rtr efc mo eaey S u e t ta h v
 eso a iv st n e p re c o        ec n dfee c ,  ih s o sinf a t
                                                           i
p r n l n e me t x ein esh w a3 p re t ifrn e whc i n t g i c n (z= 0.28).
 td ns    o o o h v eso a n e me t x ein e o n         ec n dfee c ,  ih
S u e t wh d n t a ep r n liv st n e p re c sh w a 11 p re t ifrn e whc
 o v r s o g iia t                h ifrn e r o g i a t h p o t f h se
                                                       i
h we e i n tsinfc n (z= 1.32). As tedfe e c s aen tsinfc n, tesu p r o te
e l o h y oh si h t x et n x ein e e u e e a irl ise s ny a .
   s                      se
rsut t teh p te s ta e p ri a de p re c rd c b h vo a ba s i o l we k

     e b r fssin e l f h a p o l mpe r
                     s                        a l fe td y eso a
   Th su -p o e o rsut o te ly e pe sa l ae we ky afce b p r n l
n e me t x ein e sp n e t h t a e eso a iv st n e p re c o        e aiv
iv st n e p re c . Re o d ns ta h v p r n ln e me t x ein esh w an g t e-4
 ec n dfee c ewe n r n e mb rd c e ae
                    u                          i ifrn e s o stt c l
                                                               st y
p re t ifrn eb t e t ea drme ee su c ss rts. Ths dfee c i n t ai ial
 g ic n
    i         .4     sp n e t h t o o a e eso a n e me t x ein e o
sinf a t(z= -0 6). Re o d ns ta d n th v p r n liv st n e p re c sh w a3
 ec n dfee c , ih l s o sinfc n (z .33). Bohdfe e c s aev r co t z r
p re t ifrn e whc asoi n t g iia t = 0     t ifrn e r ey lse o eo
 n h nep eai f h e ai ifrn e s u iu
             o           v                     u h p o t f h se e l o
                                                                   s
a d teitr rtt n o ten g t ed fee c i d bo s. Th s tesu p r o te rsut t
h y oh si h t x ein e e u e e a irl ise s e l be g
teh p te s ta e p re c rd c s b h vo a ba s i n giil.

      h r fssin l mpe s h     st mp ra t at f hs u y n o k re eu n
   As tep o e o as sa l i temo i o tn p r o ti std a dstc mak trtr
 st i a
   ma o     s h  st nee i o h e o d ns
                        n                  p rt n lsi o h se e l s
                                                                s
e i t ntskwa temo itrst gf rtersp n e t ase aaea ay s f rte rsut i
 o e iu e       o h r p ri s f r e
                             o           v me t st e r m h nt l stmae
                                                  ma        i
d n . F g r 5 sh ws tep o o t n o mak tmo e n e i ts fo teii a e i ts
 n r m h e ol t . e e ls n iu e r o aa l s o al r fssin l ru s h
            e o
a dfo terc l cin Th rsut i fg r 5 aec mp rbea f r l p o e o a go p te
eu n f oh o k r es n hs u y r e ai .   v
rtr s o b t stc mak t i ti std ween g t e
                                          48



        re          t ias,         rn
    Figu 5– Hindsigh b sign of retu effect

                      nitial Recol
                      I     vs.  l           et   em
                                  ected m ark m ov ent estim ate

     90 %
                                 83 %
     80 %

     70 %                                                                     66 %

     60 %

     50 %

     40 %
                                                          31 %
     30 %

     20 %
               11 %
     10 %                 6%
                                                                    3%
     0%
                          nt l
                            i
                          Iia                                       ol i
                                                                      ec on
                                                                 Rec l t

                                        Down     u
                                               Eq al Up




       a e e rm i rg      ny      f h r fssin l nt l st e
                                                  i y ma      r p n ae
   As c nb se nfo f u e5 o l 11% o tep o e o as ii al e i tdad o i sh r
 rc s u ig h ist eu n eid   we e, e e al f h eu n eid p o
                                         e e
p ie d rn tefr rtr p ro . Ho v r wh nrc l datrtertr p ro u t 31% of
h r fssin l e o t h t h y r be o rdc h r p u
                  e                                        % f r fssin l
te p o e o as rp r d ta te wee a l t p e itte d o . Th s 20 o p o e o as
e mb r h t h y st e e ai eu n v n h u h h y cu l st e o t e
                 ma     v                        y   ma       i
rme e ta te e i td n g t e rtr s e e to g te a tal e i td p si v
eu n     i p o t h y oh si f id g t is r n l. e e l i nee i ; at f
                                                                n
rtr s. Ths su p rs teh p te s o hn sih ba sto gy Th rsut s itrst g ap r o
n e me t d i r r n be o e o nz h t h y r o g n c          ee a t ssu o
iv st n a vso s ae u a l t rc g ie ta te wee wr n i su h arlv n i e f r
h i p o e o s o k r e rtr . i n a c s h i b l a o th i o
                                             e             a a it n
                                                                ie
ter r fssina stc mak t eu n Ths e h n e ter eif b u ter wnc p bl is a d
e d o eso a v r au t .
                     o    i s ey lse o v ro fd n e n l t b t
                                                         -a r o is.
la s t p r n lo ev lain Ths i v r co t o ec n ie c a d sef t iuin ba
n e me t d i r ase ec pi f h msev s s o d o k r e rdco s fe t l
                           o
I v st n a vso s’ fl p re t n o te le a g o stc mak tpe itr afcs aso
h i l t t s a e o h l t o e o vn e n h ae t f h r fssin l f h y
     e                   e
tercins. I i e sirf rt ecins t b c n ic d o tetlns o tep o e o as i te
 r o f n n h i le
      d                  o f nl e a ig n e me t d i r p e r
                            d y                                r ae td
aec n ie to tersev s. A c n ie t b h vn iv st n a vso a p as mo etlne ,
  ih a e d h l t o a e o i i s a d n h d ie f h r fssin l kn
              e
whc c n la tecin t tk to bg rsk b se o tea vc s o tep o e o a. Ta ig
  jr i s  st i l a ro s mp c o n n iiu l
             k                              ath
mao rsk mo l eyh s seiu i a t na idvd a’s we l .

     oh r nee i b r ai h t a e d r m iu e s h e e f pi
              n         o                                        mi
   An te itrst g o sev t n ta c n b ma e fo fg r 5 i te lv lo o t sm
 mo g n e me t d i r   e a t h t h st e
                                     ma   r ol td u ig h ad st
                                               e
a n iv st n a vso s. Th fc ta te e i ts wee c l ce d rn te h r e
                                  49


 u b ln e n i n il r es o
              n                   v rl e r a k r s   k s h ol t
                                                              e o f
‘tr ue c ’ i f a ca mak t f r a se ea y as b c wad ma e te c l cin o
n e me t d i r pi   mi    au be idn . e n t t h t rv i t h n f
                                               u o         e
iv st n a vso s’ o t sm av la l fn ig Ev ni asi ainta p e alda tee do
 e tmb r 0    ia ca    r e r fssin l e o t c ih pi    mi    rm h
S pe e 20 8, fn n il mak t p o e o as rp r su h hg o t sm. F o te
 r fssin l      x e td h t h eu n f n megn o k re (Ru a r a i) ud
p o e o as 83% e p ce ta tertr o a e rigstc mak t ssi o Brzl wo l
 e o t e u ig h e t o pe e s. e e lz t un d u o e mehn l ; h
      i                               o
b p si v d rn ten x c u l we k Th raiain tre o tt b so tig ese te
  ssin ae rp e 5% a d Brzl n 33%. Li e ig t a iv st n a vso c n b
Ru a sh rs d o p d 4 n    i
                       a ia        stnn o n n e me t d i r a e
 a ad u o n iiu l      ath
h z r o s t idvd a’s we l .



     .
4.1.3 Drift of return

      it f eu n ees o n t b t
                         r o f id g t is   ih g e s h t e pe e d o
    Drf o rtr rfr t a atiuin o hn sih ba whc su g st ta p o l tn t
 du ter nt l eu n st e lse o h e l t
            i        ma            z o f e r ig h uc me e pe h t
                                        e
a jst h i ii a rtr e i t co rt teraiainatrlann teo to . P o l ta
 a e st e ih r eu n h n cu l e l e d o n ee i e h i ii a a swe wh n
       ma                   y   z             ma      i
h v e i tdhg e rtr s ta a tal raietn t u d rst t ter nt l n r e
 sk d f e e l h e l t . i l l e pe o a e st e o r eu n h n
       e     n     z o      a                  ma
a e atrrv aig te raiain S mi ry p o l wh h v e i td lwe rtr s ta
 cu l e l e d v rst e h i nt l n r f e r ig h uc me u h e pe r
     y   z         ma      i         e
a tal raietn o ee i t terii a a swe atrlann teo to . S c p o l ae
 x o d o id g t is.   i o e te x o r f h mpe n hs u y h n r o h
e p se t hn sih ba Todsc v r h e p su eo tesa l i ti std tea swes t te
eu n st i a s n h i e ol t s r b re . e mpe s iie n wo a d
       ma o               e o
rtr e i t n tsk a dterrc l cin aeo sev d Th sa l i dvd do t b se
 n h eai ewe n nt l n r n e l d eun be
       o          i               z                 o h e l f hs e .
                                                             s
o terlt n b t e ii a a swes a d raie rtr . Ta l 9 sh ws tersut o ti tst
  t nt l n e ol td esin f h eu n st e r e o td e x o r o id g t
     i         e                     ma
Bohii a a drc l ce v r o s o tertr e i t aerp re . Th e p su et hn sih
 is s b re n h ifrn e ewe n h se wo i rs.
                                     g        e n rt h ai c lst
ba i o sev d o te dfee c b t e te t f u e To d mo stae te stt ia
 g iia c   ard -tsts are u.
sinfc n eap ie t e i c rido t
                                              50



   le           t ias,          rn
Tab 9 – Hindsigh b drift of retu effect
  be e o t oh nt l n e ol td esin f h eu n st e
                   i        e                     ma      n sih ba s e n rtd s h
Ta l 9 rp rs b t iia a drc l ce v r o s o tertr e i ts. Hid g t is i d mo stae a te
 ifrn e ewe n nt l n e ol td st e
                   i        e
dfee c b t e i i a a d rc l ce e i ts (Re o lcin lss Ii a). Th sc r o a p ie t e i
                                   ma         e o
                                           c l t e nt l  i    e o e f ard -tst s
 e o td n ae te s.
rp re i p rnh se

         nitial estimate h
Panel A: I                        an     ed
                          igher th realiz return
                                                tr st e
                                             Reu ne i tma
                                       nt l
                                      Iia i                 cl te o
                                                          Re olcin      Diff.
 r fssin l
P oe o as                             6,5%                  4 ,8%     -1,7%*
                                                 (N =95)              (-1,643)

 td ns
Su e t                             7,6%                    5,1%       -2,5%**
                                              (N =48)                 (-2,174)

  y e pe
La p o l                           9,3%                    6,7%       -2,6%***
                                              (N =46)                  (-2,682)

         nitial estimate lower th realiz retu
Panel B: I                       an     ed   rn
                                                tr st e
                                                      ma
                                              Reu ne i t
                                       nt l
                                      Iia  i               cl t
                                                              e o
                                                         Re olcin       Diff.
 r fssin l
P oe o as                             -4 ,8%               5,8%        10 ,5%
                                                 (N =2)                (1,105)

 td ns
Su e t                             -2,0%                   3,8%        5,8%*
                                              (N =5)                   (1,985)

  y e pe
La p o l                           5,2%                    4,5%         -0,7%
                                              (N =10)                     ,34
                                                                       (-0 9)

 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%




     e e l n a l n iae h t e pe fe r m id g t is. l e o d n r u s
          s
   Th rsut i tbe9 idc t ta p o l su frfo hn sih ba Al rsp n e tg o p
n ae       o ai c l g i c n n g t
                 st y    i
i p n lA sh w stt ial sinf a t e aied i o rtr . Ths i l ewi teh p te s
                                  v rf f eun i s i
                                       t               n   h
                                                          t h y oh si
 f id g t is; e pe o a e ie o ih st e o g a e h i ec pi b u
                                      ma                    o
o hn sih ba p o l wh h v gv n to hg e i ts d wn rd terp re t n a o t
h i nt l st e o rfssin l h ifrn e ewe n nt l n e ol td eu n
      i    ma                                    i          e
ter ii a e i t. F r p o e o as te dfee c b t e ii a a d rc l ce rtr
 st e rf s
   ma      t
e i ts (d i ) i 1.7%, whc i sinfc n a 10 p re tsinf a c lv l(z = -1.64
                        ih s g i a t t
                                i                  c
                                          ec n g ii n e e e           3).
 td ns o              rft ih s g i c n t ec n g i a c e e
                                    i                  i
S u e t sh w a -2.5% d i , whc i sinf a ta 5 p re tsinfc n e lv l(z= -2.174).
 ial a p o l o
     y                      rft ih s ihy g ii n c                     .0    so
F n l ly e pe sh w a -2.6% d i , whc i hg l sinf a t(z = -2.682, p < 0 1). Al
 c o dn o id g t is y oh si e l n a e
                                  s           r o t e r rci ly eo o
                                                    i          c
a c r ig t hn sih ba h p te s, rsut i p n lB ae p si v (o p a t al z r f r
a p o l). we e te mpe z s r o    lf r n l o cu o s.
                                          d
ly e pe Ho v r h sa l sie aetosmal o a ysoi c n lsin
                                                   51


    i l l o g f eu n n lsi h o k r e st e f n e me t d i r an
       a                                     ma
   S mi ry t sin o rtr a ay s, te stc mak te i ts o iv st n a vso g i
 xr t t .
      e o      e n rt id g t is h nt l o k r e eu n st e n
                                       i                 ma
e ta atnin To d mo stae hn sih ba te ii a stc mak trtr e i ts a d
e ol t s f r fssin l r b r e . e e l r o aa l s o l r fssin l
    e o                                 s
rc l cin o p o e o as’ ae o sev d Th rsut ae c mp rbe a f ralp o e o a
 r u s h eu n f oh o k r es n hs u y r e ai . iu e
                                                 v            o   h
g o p te rtr s o b t stc mak t i ti std wee n g t e F g r 6 sh ws te
 i rb t s f nt l eu n st e n e ol td esin fh se
       o     i          ma       e
dstiuin o ii a rtr e i ts a drc l ce v r o s o to .



         re          t ias,          rn
     Figu 6– Hindsigh b drift of retu effect

                                                         nvestm ent advisors
                      Stock m arket return estim ates of I

     40 %

     35 %

     30 %

     25 %

     20 %

     15 %

     10 %

     5%

     0%
            -30 % -25 % -20 % -15 % -10 %   -5 %   0%   5%   10 %   15 %   20 %   25 %   30 %   35 %

                                               nt l
                                                  i   cl t
                                                        e o
                                               I ia Re ol c i n




    iu e     o   hth ir t b o f nt n r a o t e a 6.9%) a d i
                                   a                i
   F g r 6 sh ws ta te dstiuin o iiila swes h s p si v me n (+ n s
eai l o c nrtd r u d h
   v                       a
rlt ey c n e tae ao n te me n (stn ad d vain 7.7%). Di rb t n o rc l ce
                                a d r e ito                o
                                                     stiui f e ol tde
 n r a       a f % n       a d r e ito f      %. mp rso ewe n h
a swes h s me n o 2.4 a d stn ad d vain o 13.0 Co ai n b t e te
 i rb t s e e l h t h
       o              a f h e ol td i r t
                                  e      b o s o r n h ifrn e
dstiuin rv as ta te me n o te rc l ce dstiuin i lwe a d te dfee c
 ai c ly g i c n -stt
   st       i                 i p o t h vd n e h t l n e me t d i r
stt ial sinf a t(t a 1.92). Ths su p rs te e ie c ta aso iv st n a vso s
  fe r m id g t is. ee r l e ul r h t p o t id g t is. n nt l
                                    i                           i
su frfo hn sih ba Th r ae aso fw o t es ta su p r hn sih ba I ii a
 i rb to b r ain n ih eu n 35%) e i , b tn ti rc l cin M o e v r i
dstiuin o sev to s o hg rtr s (+                  e o
                                 xst u o n e ol t .       ro e, n
e ol td i rb t
    e         o b r ai s n o eu n
                       o                 %) xst v n h u h h o st
rc l ce dstiuin o sev t n o lw rtr s (-30 e i s e e to g te lwe
 b r ai s n nt i r t
       o      a    b o r n       ae o y e mp cs f h eu n rf fe t n
o sev t n i iiildstiuin aei -5% c tg r. Th i a t o tertr d itefc o
h d ie f h n e me t d i r r mi o h mp cs f g f eu n fe t
                                     a
te a vc s o te iv st n a vso s ae si lr t te i a t o sin o rtr efc.
                                   52


n e me t d i r ase ec pi s f o k r e e i t bl is
                           o                  o    t     y a se h i ci t
                                                                     e
I v st n a vso s’ fl p re t n o stc mak t stmaina ii e ma c u ter l ns
o a e o ag i s.
t tk tolr ersk



4.1.4. Strengthof view

      oh r y o b r e id g t is s o u y o e r ig h uc me fe t h
    An te wa t o sev hn sih ba i t std h w lann te o to afcs te
 ec ie etit n n stmai a . n h rme r f hs u y hs s o e y skn h
                      o
p rev dc ranyi a e i t ntsk I tefa woko ti std ti i d n b a igte
e o d ns o lssiy h i nt l o fd n e n lci h et ef r n sse t h se
                      i                 n      e
rsp n e t t ca f teriia c n ie c i see t gteb t rp ro miga ta p a 1
 n l e ol t h i nt l e e f o fd n e t h se
            e n       i                            e h n e ewe n h nt l
                                                                    i
a d aso rc l cig terii a lv lo c n ie c a p a 2. Th c a g b t e teii a
 n e ol td o fd n e s u id
        e                         e n rt id g t is h mpe s iie no
a d rc l ce c n ie c i stde . To d mo staehn sih ba tesa l i dvd d it
wo r u s; h n s  o ei e h y n rd o rcl n h n s
                     e                  y             o ei e h y
                                                          e
t g o p te o e wh b l v te a swee c re t a d te o e wh b l v te
 n rd n o rcl y    c r ig o id g t is e pe o ei e h y n rd o rcl
                                                 e
a swee ic re t . Ac o dn t hn sih ba p o l wh b l v te a swee c re ty
  y v rst e h nt l etit n e pe o ei e h y n rd n o rcl
         ma      i                         e                   y y
ma o ee i t te ii a c rany a d p o l wh b l v te a swee ic re t ma
 n ee i e t
       ma .
u d rst t i

      be    rse t nt l n e ol td v rg rn t f iw o e o a h e o d n
                    i         e
    Ta l 10p e ns ii a a drc l ce a ea este gho ve sc rs f re c rsp n e t
 r u . e ifrn e ewe n a es     n   s h t n a e A h mpe s i e o n r
                                                          mi
g o p Th dfee c b t e p n l A a dB i ta i p n l tesa l i l tdt a swes
  ee h e o d n ei e esh a n rd o rcl
                   e                          y ee s n a e    h mpe s
wh r tersp n e tb l v d h / eh d a swee c re t wh ra i p n lB tesa l i
i e o n r ee h e o d n b l e esh a n rd n o rcl
 mi                             e                          y      e rb d
l td t a swes wh r tersp n e t eiv dh / eh d a swee ic re t . As d scie
h o i n hs s h th e o l t
                      e o  y e fe td y h e l t
                                            z o f h e l e e so
                                                       .
telgci ti i ta terc l cinma b afce b teraiaino tersu tTh ra n
o sig h ei e n r s o l ae h fe t f asey e mb r
            e               mi                      n wn lci .
                                                             o
f ru n teb l v da swes i t ei n t teefc o fl l rme eigo see t n
                                                   53



   le 0         t ias,         iew
Tab 1 – Hindsigh b strengthof v effect
  be     e o t oh nt l n e ol td esin f h rn t f iw o e
                    i        e                                  n sih ba s a rd s
Ta l 10rp rs b t ii a a drc l ce v r o s o teste gho ve sc rs. Hid g t is i me su e a
h ifrn e ewe n nt l n e ol td st e
                     i        e      ma      c l t e nt l e o e f ard -tsts
                                                e o      i
tedfee c b t e ii a a drc l ce e i ts (Re olcinlss Ii a). Th sc r o ap ie t e i
 e o td n ae te s. e mpe s iie n wo a es,         n   a e A n ld s h n r n ih
rp re i p rnh se Th sa l i dvd do t p n l A a dB. P n l icu e tea swes i whc
 a h e o d n b l e h n r o e o rc. a e B n ld s h n r n ih a h e o d n
                   e
c setersp n e t eiv s tea swe t b c re tP n l icu e tea swes i whc c setersp n e t
 ei e h n r o e o rc. e e so o h p rto s n h y oh sie ie t
   e                                                                o f fe t
b l v s tea swe t b c re tTh ra nfrtese aaini i teh p te z ddrcino efc.

Panel A: Asset selection b     ed
                          eliev correct
                                                  rn t f iw
                                                 Ste gho ve
                                       nt l
                                       Iiai                   cl t
                                                                 e o
                                                            Re olcin        f.
                                                                          Dif
 r fssin l
P oe o as                              2,50                    2,56        ,0
                                                                          0 6
                                                    (N =90)              (0,52)

 td ns
Su e t                                    2,95               2,77         -0,18
                                                   (N =56)               (-1,15)

  y e pe
La p o l                                  2,11               2,13          ,0
                                                                          0 2
                                                   (N =47)               (0,12)

Panel B: Asset selection b     ed
                          eliev incorrect
                                                  rn t f iw
                                                 Ste gho ve
                                       nt l
                                       Iiai                   cl t
                                                                 e o
                                                            Re olcin      Dif f.
 r fssin l
P oe o as                              2,34                    2,11      -0 ,23*
                                                    (N =47)              (-1,80  )

 td ns
Su e t                                    2,55               2,26        -0 ,29**
                                                   (N =42)                (-2,14)

  y e pe
La p o l                                  2,39               1,79       -0,61***
                                         (N =38)                            ,0
                                                                         (-4 7)
 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%




       a e e r m a e A e pe o id h i ii a see t o e o rc d o sh w
                                         i     o
   As c nb se nfo P n l p o l wh fn ter nt l lcint b c re t on t o
  la e d n y o v rst e h nt c rany e e l n a e A r o to esil f r
                    ma     a              s
ace rtn e c t o ee i t teiiil etit. Th rsut i P n l aec nr v r a; o
 r fssin l n a p o l mpe h e ol td v rg rn t f iw s ih r h n h
                                   e
p o e o a a d ly e pe sa ls te rc l ce a ea e ste gh o ve i hg e ta te
nt l u f r u e t mpe t s o r h n h nt l l f h ifrn e r eai l lse
  i                                  i                         v
ii a b t o std n sa l i i lwe ta teii a. Al o ted fee c s aerlt eyco
o eo n n g i c n. u o r n o cu o s a e d a d n hs mpe e
              i
t z r a d isinf a t Th s n sto g c n lsin c n b ma e b se o ti sa l. Th
 vd n e o s o p o t h y oh si h t e pe o id h msev s c e dn n a
e ie c d e n tsu p r teh p te s ta p o l wh fn te le su c e ig i atsk
n ra h i ei a o th i ii a c nie c n c e dn .
            e           i
ice seterb l f b u ter nt l o fd n ei su c e ig
                                           54


       r nee i l e pe
               n           o i h i nt l lci o e n o rc eu
                             n        i       o                    o
    M o e itrst gy p o l wh f d ter ii a see t n t b ic re t rf se t
 c n wld e o o f n h y cu l
                  d          y r.    lk n a e A h e l n a e B r o
                                                     s
a k o e g h w c n ie tte a tal wee Uniei P n l tersut i P n l aen t
 o to esil l h e b mpe o          e aie h n e n rn t f iw. o r fssin l
c nr v r a. Al tresu sa ls sh w an g tv c a g i ste gho ve F rp o e o as
h ifrn e s .23, whc i sinf a ta 10 p re tsinfc n e lv l(t= -1.80 F r
te dfee c i -0            i
                  ih s g i c n t             i
                                    ec n g i a c e e            ). o
 td ns h ifrn e s .29, sinf a ta 5 p re tlv l(t= -2.14 F rly e pe te
S u e t te dfee c i -0     i
                        g i c n t ec n e e            ). o a p o l h
 ifrn e s .61, whc i hg l sinfc n (t -4 7, p< 0 1). Th rsut i l ta p o l
dfee c i -0                   i
                 ih s ihy g i a t = .0         .0          s
                                                      e e l mpy h t e pe
e d o n ee i e h e e f etit h y o d n ist h se f h i lci u n u
            ma                                           o
tn t u d rst t telv lo c ranyte sh we i fr p a i tersee t n tr s o t
o e o g e r o ln o a e h n la n r h f en
                        l                     u          o g e al e s
                                                                    u
t b wr n . Th y ae n twi ig t fc te u pe sa tt t o b ig wr n . Th fi r i
 a e o c e t f n hn s I u g e d ah r h n f I d e l stk ”
e sirt a c p i o etik “ jst u sse ”rte ta i “ ma eara mi a e .



4.2. Overconfidence

      ec n ie c s u id n wo t f e s. e ist t f e s b re h        tn o
                                                                  i
    Ov ro fd n ei stde i t ses o tst Th fr se o tst o sev s te‘set gto
 ar w i s’ efc y x miig o h e o d ns st e oai t
      mi                                   ma      ly e c n t f
n ro l t – fe tb e a nn h w te rsp n e t e i t v lt i . Th se o d se o
e s b r e h eai ewe n ec ie o fd n e n cu l bl y o c e n sse
                  o                                    i
tst o sev s te rlt n b t e p rev d c nie c a d a ta a i t t su c ss i a t
  lci a . e e h iu s r i u d n r eal n ci
     o                                            o
see t ntsk Th setc nq e aedsc sse i mo ed tii se t n3.2.2.

    n h ist e te x o r o v ro fd n e s u id y o aig h v rg dh f
    I t efr tst h e p su et o ec n ie c i stde b c mp rn tea ea ewit o
h   % o f ne o n s
         d             ra ) n h ae f c e n o n s t n i   i     %). be
te90 c n ie c b u d (sp e d a d tert o su c ss i b u d set g (ht Ta l 11
 rse t h e l f c o ai n a d n h se n r n e l d eu n
            s                                         z
p e ns tersut o su hc mp rso b se o p a 1 a swes a draie rtr s.



   le 1
Tab 1 – Overconfidence,            ou        /
                       confidence b ndaries 12
   be    e o t h v rg dh f h % o f n e o n s n h ae f c e n o n s tn . e
                                        d                                    i
 Ta l 11 rp rs tea ea ewit o te90 c nie c b u d a dtert o su c ss i b u d set g Th
  e l r r u e a d n sse n e o d n r u . e e l r ac ltd o h n r f h ist
     s                                              s
 rsut ae g o p d b se o a ta d rsp n e tg o p Th rsut aec luae f rte a swes o te fr
  h se
 pa .

                            oe o as
                          Pr fssin l                   y e pe
                                                     La p o l               td ns
                                                                          Su e t
  h se e ls
 P a 1 rsut
                       ped
                      S ra           t
                                   Hi%           ped
                                                S ra          Hi%
                                                                t     ped
                                                                     S ra          t
                                                                                 Hi%
  tc s
 So k                 21,1 %       2,0%         9,3 %         0 %
                                                               ,0    29,1 %       ,0
                                                                                50 %
   re ce
 Cu rn is             7,2 %       26,0%         7,4%         12,0%   17,9 %     35,0%
 Co    dt s
         i
   mmo i e            15,1 %      17,3 %        8,4%         25,0%     ,2
                                                                     20 %         ,0
                                                                                20 %


       h e o d ns r sk d o t % o f n e e es, ai a n r o l t h
                                      d           o
    As tersp n e t weea e t se 90 c n ie c lv l rt n la swes sh udse te
 i lse o %. e vd n e r m h se s n i ua l; o e f h ip re tg s s v n
  %
ht co t 90 Th e ie c fo p a 1 i idsp tbe n n o teht ec na e i e e
 lse o %, h ih st en   %. we e, h nq e r e o dt n ih rv i
                                                 i           e
co t 90 te hg e b ig 50 Ho v r te u iu mak tc n i o whc p e ald
                                          55


 u ig h e s  st e e t n n . o x mpe 5% r p n ssin o k r e u in
d rn tetst mu b k p i mid F re a l a4 d o i Ru a stc mak td r g
 b u he   e s a rl e o siee o eo g o h ni l %. fee c n r e
                                               k
a o ttrewe k c n su eyb c n d rd t b ln t teu l ey10 Difrn ei mak t
 o dt n fe t l h o ai n f e l ewe n e o d n r u s. e eu n u ig
     i                          s
c n io afcs aso tec mp rso o rsut b t e rsp n e tg o p Th rtr s d rn
h r fssin l      re s   r   c    r e aie h n u ig h u e t re ,       ih
te p o e o as’ su v y wee mu h mo e n g tv ta d rn te std n su v y whc
 x lis h ifrn e n ra d a.  e u e h fe t f r e c n io
                                                   i  mi a ay s s
                                                        a
e pan tedfee c i ge t e lTord c teefc o mak t o dt nasi lr n lsi i
 ar l
   e     t h se n r be
          h                        o h me iu e s a l      r m h se
c ridasowi p a 2 a swes. Ta l 12 sh ws tesa fg rs a tbe11 fo p a 2.



   le 2
Tab 1 – Overconfidence,            ou        /
                       confidence b ndaries 12
  be    e o t h v rg dh f h % o f n e o n s n h ae f c e n o n s tn . e
                                      d                                     i
Ta l 12 rp rs tea ea ewit o te90 c nie c b u d a d tert o su c ss i b u d set g Th
 e l r r u e a d n sse a d e o d n g o p e e l r ac ltd o h n r f h c n
    s                                            s
rsut aeg o p db se o a t n rsp n e t r u . Th rsut aec luae f rtea swes o tese o d
 h se
pa .

                           oe o as
                         Pr fssin l                    y e pe
                                                     La p o l                td ns
                                                                           Su e t
 h se e ls
P a 2 rsut
                      ped
                     S ra           t
                                  Hi%            ped
                                               S ra           Hi%
                                                                t      ped
                                                                      S ra        Hi%t
 tc s
So k                 28,5 %       2,3
                                 4 %           10 %
                                                  ,8          7,7 %   21,1 %       0
                                                                                 4 ,0%
  re ce
Cu rn is             8,1 %       11,5 %         8,9 %        11,5 %     ,3
                                                                      14 %       19,0%
Co    dt s
        i
  mmo i e            18,8 %      17,3 %        11,4%          6,2
                                                             4 %      19,8 %        ,3
                                                                                 14 %


     e e l n al
          s          r mia o a l      e e e o h t a n ra d u i i o
                                                %                    l
   Th rsu t i tbe12 aesi lrt tbe11. Th lv l f i h s ice se , b t s stl n t
 lse o %.  i tn ra n v rg ra a e e , ih n iae e r ig we e,
            g
co t 90 A sl h ice sei a ea esp e dc nb se n whc idc ts lann . Ho v r
h h n e n ra s eaie        l o r fssin l n a p o l, o u e t t s e ai .  v
tec a g i sp e d i rltv smalf rp oe o as a d ly e pe f rstd ns i i n g t e
 o hs e so h n ra e l r b by r r m o mai t
                      s                     z o f r e c n io s h n
                                                            i
F rti ra n teice sersut p o a l mo efo n r l ain o mak t o dt n ta
 r m mp o e ra st e
                  ma      e e l ase h u st
                                s          o    eh r h o e es f i%
fo i r v dsp e de i ts. Th sersut ri teq e in wh te telw lv l o ht
e l r m o r oai t st i
                ly   ma o r r m b o ma    r e o dt n
                                                   i        n r hs
rsut fo p o v lt i e i t n o fo a n r l mak t c n i o . To a swe ti
 u st ,
     o    r n e t o ai n e o v lt t st i s are u.
                                   l y ma o
q e in amo ei-d phc mp rso tst f oaii e i t ni c rido t

   n h oai t o ai n e h ra s ol td r m h e o d ns r o v re
            ly                          e
   I te v lt i c mp rso tstte sp e d c l ce fo te rsp n e t ae c n etd
no oai t stmae
       ly           e    o v re oai t st e r o ae o ifrn
                                    ly   ma
it v lt i e i ts. Th se c n etd v lt i e i ts ae c mp rd t dfee t
 oai t s. i e se
    li                mpi ig to f v rgn oai t s,
                         f                       li     ih s e r d n
                                                                b
v lt i e Ths tstu s asi l yn meh d o a ea ig v lt i e whc i d scie i
  r eal n ci    o           e o ai n f n ld s v n ifrn v rg d oai t i
mo e d ti i se t n 3.2.2. Th c mp rso o icu e se e dfee ta ea e v ltl y
 iu e o e c sse. e iu e n ld wo e o d n e i ts f oai t eu n eid
                                                        ly
fg rs f r a ha tTh sefg rs icu et rsp n e t stmae o v lt i (rtr p ro s
   n       n e ol t
                 e o eu n eid       n o r cu l oai t s o o ai n u p se
                                                   li
1 a d 2), o erc l cin (rtr p ro 1) a d fu a ta v lt i e f rc mp rso p r o s
 eu n eid      n       0 a s ro o re n o g em v rg ). be            rse t h
(rtr p ro s 1 a d 2, 10 d y p irt su v y a d ln -tr a ea e Ta l 13 p e ns te
e l f hs o ai n e .
   s
rsut o ti c mp rso tst
                                            56


   le 3
Tab 1 – Ov             v
          erconfidence, olatilityestimation
   be     e o t oai t st e e ol t s n cu l oai t s r m ifrn h se f h s u y e
                   l y ma        e o                 li
Ta l 13 rp rs v lt i e i ts, rc l cin a d a ta v lt i e fo dfee tp a s o ti std . Th
 e o td oai t s r g ne y sse n a es
              li                                   n     e o d n r u n e rpi .  o
rp re v lt i e ae se me td b a t(i p n l A, B a d C), rsp n e tg o p a d d scit n Th e
 e rpi s se r: r l h t ees o v rg o g em oai t
        o                                             ly   0 eo e h t ees o h oait
d scit n u dae ‘No ma’ ta rfr t a ea eln tr v lt i , ‘10 db fr’ ta rfr t tev lt iy l
 ac ltd n       0 a s eid ro o h r e s,      i e
                                             ma     h t ees o h e o d ns’ st e t h se
                                                                            ma
c luae o a10 d y p ro p irt tesu v y ‘Est td1’ ta rfr t tersp n e t e i t a p a
      ai d s e l d oai t t h se
        z          z     l
1, ‘Re l e 1’ i raie v lt iya p a 1, ‘Re olce 1’ i terc l cino ‘Est t 1’, ‘Est t 2’ te
                                        c l td s h e ol t
                                           e              e o f i ema         ma
                                                                             i e h
 h se st e n
          ma         ai d e l d oai t t h se
                       z      z       i
p a 2 e i t, a d‘Re l e 2’ raie v ltl ya p a 2

Panel A: Stocks
                                   0
                                 10 d      i e
                                            ma
                                         Est td     ai d
                                                       z
                                                  Re l e   Re olce
                                                             c l td
                                                                e       i e
                                                                         ma
                                                                      Est td     ai d
                                                                                    z
                                                                               Re l e
                          r l
                       ‘No ma’    eo e
                                 b fr       1        1         1         2        2
 r fssin l
P oe o as               47%      53%      21%     132%       25%       25%      75%

 td ns
Su e t                  47%      73%      34%     118%       20%       15%      69%

  y e pe
La p o l                47%      83%      10%      98%       11%       12%      61%

Panel B: Currencies
                                   0
                                 10 d      i e
                                            ma
                                         Est td     ai d
                                                       z
                                                  Re l e   Re olce
                                                             c l td
                                                                e       i e
                                                                         ma
                                                                      Est td     ai d
                                                                                    z
                                                                               Re l e
                          r l
                       ‘No ma’    eo e
                                 b fr       1        1         1         2        2
 r fssin l
P oe o as                7%       6%      7%       13%       9%        7%       18%

 td ns
Su e t                   7%       7%      19%      13%       15%       11%      18%

  y e pe
La p o l                 7%       8%      8%       16%       11%       9%       19%


Panel C: Commodities
                                   0
                                 10 d      i e
                                            ma
                                         Est td     ai d
                                                       z
                                                  Re l e   Re olce
                                                             c l td
                                                                e       i e
                                                                         ma
                                                                      Est td     ai d
                                                                                    z
                                                                               Re l e
                          r l
                       ‘No ma’    eo e
                                 b fr       1        1         1         2        2
 r fssin l
P oe o as               24%      36%      15%      56%       18%       16%      59%

 td ns
Su e t                  24%      41%      23%      59%       17%       16%      63%

  y e pe
La p o l                24%      43%      10%      62%       11%       12%      62%



       a e e rm a l         stmae oai t
                                      i e r e eal o r h n cu l
   As c n b se n fo tbe 13 e i td v ltl is ae g n rly lwe ta a ta
 oai t s. o eti o iai s f sse n e o d n r u h a ewe n st e
    li                   o                                         ma
v lt i e F rc ran c mbn t n o a ta d rsp n e tg o p te g p b t e e i td
 n e l d oai t s d . r fssin l
      z     ly
a draie v lt i i wie P o e o as, wh mo l eyaemo iv le wi v lt i i
                                   o st i l r
                                        k               h    ly
                                               stn ov d t oai t n
e l i , n ee i e h oai t s f o k n o
    f         ma        li                    dt s o ae o h o ma’
                                                i
ra l e u d rst t te v lt i e o stc s a d c mmo i e c mp rd t te ‘n r l
 oai t s.
    li     l t u rn y eu n st e r fssin l st e oai t lse o h
               h             ma               ma      ly
v lt i e Ony wi c re c rtr e i ts p oe o as e i t v lt i co t te
  o ma’ oai t
           l y e e l f h r fssin l p o t v ro fd n e n h
                      s                                             tn o
                                                                     i
‘n r l v lt i . Th rsut o tep o e o as’ su p r o ec n ie c a d te‘set g to
 ar w o f n e i s’ fe t e a t h t oai t s ro o h r e s
         d    mi                    li                     0 eo e
n ro c nie c l t efc. Th fc ta v lt ie p irt te su v y (‘10 d b f r’)
                                   57


  r b v h i o ma e e rn te s h         p o t f oai t n ee i i
                                                  ly        ma o f
wee a o e ter n r l lv l ste gh n te su p r o v lt i u d rst t n o
 r fssin l    e h u h r fssin l r wae f n ra d oai t, h y r n be o ie
                                                   i
p o e o as. Ev nto g p o e o as aea r o ice se v ltl y te aeu a l t gv
e l c oai t st e o ae v n o o ma, o p e al g oai t
   st     l y ma                              i        ly
rai i v lt i e i ts c mp rde e t n r ln t rv i n , v lt i .

     lt i e r ig f r fssin l s l st e l be t e r ig h e l d oai t
       ly                              g    e            z    ly
   Voai t lann o p o e o as i amo n giil. Af rlann teraie v lt i ,
 n h n fiin y f h i h se stmae r fssin l e eal o o n ra h i
a d te isu fce c o terp a 1 e i ts, p o e o as g n rly d n tice se ter
 st e oai t n
   ma      ly         y n at o r t
e i td v lt i , a d ma i fc lwe i (‘Est td 2’ i c mp rd t ‘Re olce 1’ t
                                      i e
                                       ma     s o ae o          e
                                                             c l td   o
 x ld o be fe t f id g t is).   sut n a ls
                                  s          n       o h t r fssin l
e cu e p ssil efc o hn sih ba Re l i tbe 11 a d 12 sh w ta p o e o as
n ra h i ra stmae r m h se o h se y            l r i.  we e, h y r
ice se tersp e d e i td fo p a 1 t p a 2 b asmalmagn Ho v r te ae
 n be o e o nz h n ra d e gh f st i eid e a l
                                 ma o                 n h s h st e
                                                                ma
u a l t rc g ieteice se ln t o e i t np ro (se tbe1) a dtu tee i td
 oai t s e i t me r v n t o r e e. r fssin l l a e
    li                                                    i tedn y o
                                                           g
v lt i e rman a sa o e e a lwe lv l P o e o as aso h v a sl h tn e c t
 v rst e h i nt l oai t st e t h e ol t
      ma       i      ly
o ee i t ter ii a v lt i e i ts a te rc l cin (‘Est td 1’ c mp rd t
                           ma            e o       ma
                                                  i e      o ae o
   c l td
      e         i s nep ee o e n i n    t h y oh si f id g t is s h
‘Re olce 1’). Ths i itr rtd t b i l e wih te h p te s o hn sih ba a te
 st e oai t s r o o o ae o h e l d n s.
   ma     li                        z
e i tdv lt i e weetolw c mp rdt teraie o e

    t u h n ee i i
     h           ma n oai t r fssin l r i be o du h i oai t
                          ly                 l                    ly
   Al o g u d rst t g v lt i p o e o as ae st la l t a jstter v lt i
 st e a d n h sse.
   ma                  i p rts h m r m h te e o d ns.    e oai t
                                                              i
e i ts b se o te a t Ths se aae te fo te oh rrsp n e t Th v ltl y
 st e f u e t t h se r eaiey ih o l sses. i s ai a o o k n
   ma                                                o
e i ts o std ns a p a 1 aerltv l hg f rala t Ths i rt n lf rstc s a d
 o   dt s u n t o u rn is. e a t h t l v lt i st e f u e t r eai l
       i                                   l y ma                 v
c mmo i e b t o f rc re ce Th fc ta al oai t e i ts o std ns aerlt ey
 ih n iae h t u e t a e p rh n e h t oai t st e u h o e ih u r
                                           l y ma
hg idc ts ta std ns h v a p e e d d ta v lt i e i ts o g tt b hg b tae
 o a l o n e t o ma v lt i e f p rt sses. e du me t f oai t f u e t
              f         li                               ly
n t bet id niyn r l oai t s o se aaea t Th a jst n o v lt i o std ns
 ewe n h se n h se s rai a. td ns o r h i oai t stmae r m h se
                          o                       i
b t e p a 1 a dp a 2 i irt n l S u e t lwe terv ltl ye i ts fo p a 1
o h se    v n h u h h h se stmae    r e eal n fiin. n te        r s, h
t p a 2, e e to g te p a 1 e i ts wee g n rly isu fce t I oh rwo d te
  me a e l c st e f h se
          st   ma            r o are ln o h se        n h s h se
so wh trai i e i ts o p a 1 ae n tc rid ao g t p a 2 a d tu p a 2
 st e f u e t r n ee i e .
   ma                     ma    n esey o r fssin l u e t n ee i e  ma
e i ts o std ns ae u d rst td Co v r l t p o e o as, std ns u d rst t
h i nt l oai t stmae t h e ol t . i s p o t o h y oh si f id g t
     i      ly                e o              e
terii a v lt i e i ts a terc l cin Ths i o p si t teh p te s o hn sih
 is. eal e l f h u e t mpe o o
        ,   s                        k    c n . i g t n iae h t
ba Ov rl rsut o te std n sa l d n tma e mu h se se Ths mih idc t ta
 u e t cu l r o ey a l r t oai t n h s e a e n n n o si e t n r
           y             i    h    ly
std ns a tal aen tv r fmi a wi v lt i a d tu b h v i a ic n stn ma o
 t oai t
  h    ly
wi v lt i .

     y e pe stmai l e o t o o oai t st e n r l o r o du ter
                  c y                i    ma
   La p o l sy e t al rp r to lw v ltl ye i ts a d aeasop o t a jst h i
 st e a d n sse. e h u h oait n ee i i s su ly o siee o n iae
   ma                         ly        ma o
e i ts b se o a tEv nto g v lt i u d rst t ni u al c n d rdt idc t
 v ro fd n e hs g t o e h a ee         jrt f h a p o l n hs u y r o
                                          y
o ec nie c , ti mih n tb tec seh r. M ao i o tely e pei ti std aen t
                                      58


 ey a l r t oai t n o fd n e o n ais.
       i          ly                         u t s i l ht hi o o
                                                     k
v r fmi a wih v lt i a d c n ie c b u d re Th s i i l ey ta ter to lw
 oai t st e e l r m o r n estn ig ah r h n v ro f n e spt f hs,
    l y ma                                        d          e
v lt i e i ts rsutfo p o u d r a dn rte ta o ec n ie c . De i o ti
h i ig h t a p o l n ee i e oai t s au be d rst i f oai t e d
   n                    ma     ly                 ma o       ly
tef dn ta ly e peu d rst t v lt i i v la l. Un ee i t no v lt i la s
o o r n e me t e i o e ade f h uc f t ann f a p o l s e l be te
                                         .                     g
t p o iv st n d csinrg r lss o teso reo i Le r igo ly e pei n giil;h
s rci l o ifrn e ewe n ei e nt l .e e ol td h se
       c y                   e      i           e            n h se
i p a t al n dfee c b t e b l v d ii a (i . rc l ce ) p a 1 a d p a 2
 st e
   ma    so h ifrn e ewe n r e nt l n e ol td st e s l st o e i e t
                                i        e      ma
e i ts. Al tedfee c b t e tu ii a a drc l ce e i ts i amo n n xstn .
  e b r ai s p o t h x ln t h t st a p o l o o u d r a d oai t n
            o                 o                                ly
Th seo sev t n su p r tee pa ain ta mo ly e ped n t n estn v lt i a d
c n ie c b u d re v r wel n tu aeu a l t p o e q e in icu igto .5
                                                   o
 o fd n e o n ais ey la d h s r n be o r c ss u st s n ldn h se

        e v rl o cu o n h e l f a l
                              s          s h t e pe n e ea r n be o ie
      Th o ealc n lsino tersu t o tb e13 i ta p o l i g n rlaeu a l t gv
e l c oait st e y t n
   st     ly
rai i v lt i e i ts b set g 90 c n ie c b u d re Th e i ts gv n ae
               ma       i     % o fd n e o n ais.      ma
                                                   e st e ie r
  stmai l o o
      c y         ann f oai t s l
                             ly        a ; fe e r ig h n fiin y f h i
sy e t al tolw. Le r igo v lt i i asowe k atrlann teisu fce c o ter
 ro st e e pe e d o n ra h i st e u l st n aiby o n u h e
      ma                           ma
p ire i ts, p o l tn t ice se tere i ts, b tamo iv ra l n te o g . Th
e l l mpy h t h r fssin l r h ny h t r l n estn oai t std ns n
   s                                                   ly
rsut asoi l ta tep o e o as aeteo l ta tuyu d r a dv lt i ; u e t a d
apo l s     r u ) e o t c e l h t n iae o r n wld e n oai t
                              s                            l y sut ns
ly e pe(a ag o p rp r su h rsut ta idc t p o k o e g o v lt i . Re l i
al     r nin t h e l n a ls
               h     s           n
tbe12 aei l ewi tersut i tbe 11 a d12.

       so o oai t st i
                 ly   ma o n lsi h r fssin l o k         r e st e r
                                                               ma
      Al f r v lt i e i t n a ay s, te p o e o as’ stc mak t e i ts ae
 ihi td e bl y f n e me t d i r o st e oai t s u id y o aig h i
    g           i                        ma      i
hg l he . Th a i t o iv st n a vso s t e i t v ltl yi stde b c mp rn ter
 st e oai t s t e l d n s. i n lsi se
   ma      li
e i td v lt i e wi raie o e Ths a ay s u s asi lrstu tr ta tbe13, b t
                  h  z                       mia r cu e h n a l    u
 rse t h e l n rp i o m.
            s
p e ns tersut i ag a hcf r




5
      e nu t n f h uh r s n i
           i                n t hs.
                               h
    Th iti o o tea to i i l ewi ti
                                                            59


             re
         Figu 7– Ov             v
                   erconfidence, olatilityestimation

                                               s'           et ol ity
                                    Professional stock m ark v atil estim ation

                   140 %

                                                                 132 %
                   120 %


                   100 %
         Vol ity




                   80 %
           atil




                                                                                                    75 %
                   60 %

                                       53 %
                   40 %     47 %


                   20 %                                                     25 %        25 %
                                                  21 %

                    0%
                           Nor l
                           ' m a'          f e   t td
                                                  m
                                    100d be or Es i a e 1      ai
                                                             Re l d 1
                                                                 ze        c l td
                                                                              e        t td
                                                                                        m
                                                                         Re ol c e 1 Es i a e 2     aize
                                                                                                  Re l d 2




         su t n iu e r n i
            s             n t h e l n al
                              h     s         iv st n d i r n ee i e  ma
       Re l i fg r 7 aei l ewi tersut i tbe13; n e me ta vso s u d rst t
 oai t y
    ly     d   r i . e st e oai t o rtr eid s g iia t o r h n
                         ma    ly                         y
v lt i b awiemagn Th e i tdv lt i f r eu np ro 1 i sinfc nl lwe ta
  o ma’ r rv in
              i      0 eo e oai t ly     lt i e r ig s l o r st e
                                           ly                    ma
‘n r l o p e al g (10 d b fr) v lt i . Voai t lann i aso p o ; e i td
 oai t o eu n eid
    ly                s q a o h e o d ns’ ec ie eid         o ai t .e
                                                               ly
v lt i f rrt r p ro 2 i e u lt te rsp n e t p rev d p ro 1 v lt i (i .
e ol td
    e
rc l ce ). Th dfee c b t e te ii a a d rc l ce v lt i i sl hl p siv ,
             e ifrn e ewe n h nt l n e ol td oai t s i t o t e
                                i          e       ly     g y     i
  ih s i
       n t h y oh si f id g t is.
           h
whc i l ewi teh p te s o hn sih ba

          e nep ei h e l f iu e t o l e oi d h t h o ma’ ees o h
                   n       s                        c
       W h n itr rt g tersut o fg r 7, i sh ud b n t e ta te‘n r l rfr t t e
 v rg oai t s f a i n n
           li        i        ssin o k r e.  e o ma’ n u l o g em
a ea e v lt i e o Brzla a d Ru a stc mak t Th ‘n r l a n a ln tr
v lt i o U.S stc mak ti sinf a t lwe, a o t15%6. I mih b ta iv st n
    ly                     i y
 oai t f . o k r e s g i c nl o r b u            t g t e h t n e me t
 d i r r mpy n be o e ov h n o mai h t megn
                                        o              res r i ir h n
a vso s ae si l u a l t d v le te if r t n ta e r ig mak t ae rske ta
 e eo e    r es, ih h y rl g e n o h i oai t st e
                                            l y ma       e , h idn
d v lp d mak t whc te su eya reo , t terv lt i e i ts. Ev n so tefn ig
h tn e me t d i r n ee i e oai t n r n be o e r s au be e a t h t
                          ma     ly
ta iv st n a vso s u d rst t v lt i a daeu a l t lani v la l. Th fc t a
t od l o stc       re e i e fe t h u l y f n e me t d i r d ie o h i
                         ma            t
i h ls asof r o kmak t st ts afcs teq ai o iv st n a vso s’ a vc s t ter
 u o r       v n h r fssin l r o be o sse i n r p r y t s l st
c stmes. As e e te p o e o as ae n ta l t a ss rsk i p o e wa , i i amo
mp ssil o te l t o a e at n h bl i f h i a vso s. e a th tn e me t
              e           h       ie
i o bef r h cins wh h v fi i tea i t s o ter d i r Th fc ta iv st n
 d i r r n wae f h i e d n y o n ee i e oai t rv ns h m r m o tol g
                                    ma    ly                     i
a vso aeu a r o tertn e c t u d rst t v lt i p e e t te fo c nr ln

6
      w o e n u r l ea e ie n e ewe n
                  i                                  n       0
    Do J n s Id st as Av rg Prc I d xb t e 2.1.1951 a d6.8.20 9
                                    60


h i a vc s.  e l l t f n e me t d i r r o a l o e l h rv i n i s
                 , e                                 z        i
ter d ie As arsu tcins o iv st n a vso s aen t bet raietep e al grsk
 f h i iv st ns n a e o  c i o ae o h i tu i rfl     e
o ter n e me t a dtk tomu hrskc mp rdt ter r erskpo i .

     e c n sp c f v ro fd n e u id s h eai    o ewe n o f n e n
                                                           d
   Th se o d a e t o o ec n ie c stde i te rlt n b t e c n ie c a d
 ef r n e        a r v ro f n e h v rg rn t f iw o e n h ec na e
                             d
p ro ma c . To me su eo ec n ie c tea ea este gh o ve sc r a d tep re tg
 f c e u n r r e o td           o ae v ro f n e ewe n r u s, h e l r
                                             d                     s
o su c ssfla swes aerp re . To c mp r o ec n ie c b t e g o p tersut ae
 r u e a d n a k ru d n o mai .
                              o    c r ig o h y oh si f v ro f n e h
                                                                d
g o p d b se o b c go n if r t n Ac o dn t te h p te s o o ec n ie c te
 r u s t ih r gh f iw o e eai o c e
        h     e                 v              fe r m v ro f n e e
                                                            d
g o p wi hg st n t o ve sc r rlt et su c ss% su frfo o ec n ie c . Th se
e o d ns a e v rst e h i o fd n e f lci h et ef r n sse
                   ma                       n        e
rsp n e t h v o ee i td ter c n ie c o see t g te b t r p ro mig a t
 o ae o h i tu bl y o o h t be
                   i                   o h e l f hs o ai n e .
                                                s
c mp rdt ter r ea i t t d ta. Ta l 14sh ws tersut o ti c mp rso tst



                  le 4
               Tab 1 – Overconfidence,          performance 13
                                      confidence-            /
                                          Strength
               Group                                 Success%
                                           of view
               nv t nt ior
               I esm e advs                 2,44       63 %
               nv t nt ior m
               I esm e advs , wo en         2,40       70 %
               nv t nt ior n
               I esm e advs , m e           2,54       53 %
               nv t nt ior
               I esm e advs , <=5 exp       2,27       65 %
               nv t nt ior
               I esm e advs , >5 exp        2,55       62 %
               nv t nt ior r ni
               I esm e advs , tai ng        2,28       69 %
               nv t nt ior        r ni
               I esm e advs , no tai ng     2,49       61 %
                ay pe
               L peo l                      2,12       45 %
                ay pe, m
               L peo l wo en                1,99       37 %
                ay pe,
               L peo l m e n                2,30       55 %
                ay pe, omm e ca
               L peo l c     r il           2,15       41 %
                ay pe, ec c
               L peo l t hnial              2,14       42 %
                 ud
               St ent                       2,92       44 %
                 ud ,
               St ent wom en                2,83       39 %
                 ud ,
               St entm en                   2,96       46 %
                 ud , ina e
               St ent f nc major            2,75       50 %
                 ud , her o
               St ent ot m ajr              3,03       40 %
                  m n
               Wo e                         2,38       50 %
               Men                          2,73       49 %
               NFC Q1                       2,50       47 %
               NFC Q2                       2,61       60 %
               NFC Q3                       2,49       47 %
               NFC Q4                       2,68       45 %
               FIQ1                         2,37       53 %
               FIQ2                         2,85       49 %
               FIQ3                         2,43       48 %
               FIQ4                         2,73       46 %
               All                          2, 56       9
                                                       4 %
                                                    61


       a e e r m a l , h r r g i c n ifrn e ewe n e o d n r u s
                                   i
   As c n b se n fo tbe14 teeae sinf a tdfee c s b t e rsp n e tgo p
 oh n rn t f iw n c e n hs mpi e n lsi v ro fd n e s
                                        f                          a rd y
b t i ste gh o ve a d su c ss. I ti si l id a ay s o ec n ie c i me su e b
h eai f o f n e rn t f iw) n
      o        d                       ce       mbn to f ih o f n e n
                                                               d
te rlt n o c n ie c (ste gh o ve a d su c ss. Co iain o hg c n ie c a d
o    c e n iae v ro fd n e e r u         t ih st e re f v ro fd n e t hs
                                          h                          h
lw su c ss idc ts o ec n ie c . Th g o pwi hg e d g e o o ec nie c wi ti
  a r s uet t      h    jr te h n ia c      3  0      e o st e re s n
me su e i std ns wi a mao oh rta fn n e (3.0 /4 %). Th lwe d g e i o
n e me t d i r o a e at p td n e a irl ia c riig eo e
                          c                                             n
iv st n a vso s wh h v p riiae i b h vo a fn n etann b f r (2.28 /61%). I
 r e o id u te eai ewe n o f n e n ef r n e h n iiu l r u s f a l
                   o           d
o d rt fn o t h rlt nb t e c n ie c a dp ro ma c , teidvd a g o p o tbe
   r h re n wo i n o a g a h t c e ae n -a i n rn t f iw n -
                              h
14aec atdo at d me sin l rp wi su c ss rt o y xs a dste gho ve o x
 xs.   e n rt h eai o e rssin o e s l rwn iu e         o h e l  s.
a i Tod mo staeterlt narg e o slp i asod a . F g r 8 sh ws tersut



        re
    Figu 8– overconfidence,          performance 12
                           confidence-            /

                                     Confidence & Succes rate by group

                   75 %

                   70 %

                   65 %

                   60 %
    Success rate




                   55 %

                   50 %

                   45 %

                   40 %

                   35 %
                       1,90   2,10         2,30          2,50        2,70   2,90   3,10

                                                  Strength of view




     e a t h t h r e o e e aie o rlt  o ewe n rn t f iw n        ce
   Th fc ta tee se ms t b n g tv c reain b t e ste gh o ve a d su c ss
ae o r u e e l t e st mpi r n v ro fd n e
                  s           e                        ei l b r ai h t
                                                         a          o
rt, f rg o p d rsut a la , i l s sto g o ec n ie c . A rl be o sev t n ta
 e pe o r    r o fd n ae r rn o al ud e ihy au be              h e l n
                                                                    s
p o l wh aemo ec n ie t r mo ep o et fi wo l b hg l v la l. As tersut i
 iu e r o r u s f e pe t o s o e e rl      y a h t h o rlt o f o fd n e
fg r 7 aef rgo p o p o l, i d e n tn c ssai me n ta tec reain o c nie c
 n c e o n iiu l e pe ud e e ai . e e l n iu e
                                        v        s            y l n iae
a d su c ss f ridvd a p o l wo l b n g t e Th rsut i fg r 8 ma aso idc t
h t eti r u s n v rg r       r v ro f n h n tes.
                                       d             e    , ts    au be
ta c ran g o p o a ea e ae mo e o ec n ie tta oh r Ev n so i i a v la l
 idn o i o e     ih ru s f e pe r    r v ro fd n h n tes.    e at h t
fn ig t dsc v rwhc go p o p o l ae mo e o ec n ie tta oh r Th fc ta
                                                       62


e l n iu e
   s           l
rsut i fg r 8 alw te p ssii t ta c n ie c mih b n g t ey c reae wi
                o h o bl y h t o f n e g t e e ai l o rltd t
                           i         d               v            h
  c e al o  s     r n lsi n h eai f o f n e n c e ae o hs u p se
                                  o        d
su c ss, c l f rmo ea ay s o terlt n o c n ie c a d su c ss rt. F rti p r o
h mpe f sse lci n r s iie no ie b ru s a d n h n o n e
                  o
te sa l o a tsee t n a swes i dvd d it fv su go p b se o te a n u c d
 rn t f iw. e ef r n e f a h b ru s h n u id be             o h ae f
ste gho ve Th p ro ma c o e c su go p i te stde . Ta l 15 sh ws tert o
 o rc a swes ru e y h rn t f iw. iu e     o h me n o mai h n a l
                                                         o
c re t n r go p db teste gho ve F g r 9 sh ws tesa if r t nta tbe
   n rp ia f r
15 i g a hc l o m.



    le 5
 Tab 1 – Overconfidence,          performance 23
                        confidence-            /
              be    e o t h rp ri f o rc n r t n h mpe n u st .
                                    o                   h                o    e mpe s iie
            Ta l 15 rp rs te p o o t n o c re ta swes wi i te sa l i q e in Th sa l i dvd d
             a d n h e o td rn t f iw o e              e e l r e o td o h
                                                            s                 oe mpe
            b se o terp re ste gh o ve sc r (1-5). Th rsut aerp re frtewh l sa l (‘Al a ’)
                                                                                       l s
              la o se aae e o d n g o p iu e n ae te s r h u es f n r
            wel s fr p rt rsp n e t r u s. Fg rs i p rnh se aeten mb r o a swes, n

                 te gh f iw
                S rn t o ve      oe o as
                                Pr fssin l            La p o l
                                                        y e pe             u et
                                                                          Std ns         All
                      1          59% (78)              0
                                                      4 % (95)           43% (83)     47% (256)
                      2          57% (87)             52% (91)             %
                                                                         50 (70  )    53% (248)
                      3          55% (83)             56% (4 3)          56% (77)     56% (203)
                      4          73% (67)               %
                                                      34 (29)            57% (105)    59% (201)
                      5            0
                                 10 % (4)             75% (4 )           35% (26)     47% (34 )



    re
Figu 9 – overconfidence,          performance 22
                        confidence-            /

                                      Strength of view and success rate

                         80 %

                         75 %

                         70 %

                         65 %
                                 of s i as
                                Pr e son l
                         60 %
 Success rate




                         55 %
                                   l
                                  Al
                         50 %

                         45 %
                                                                   a pe e
                                                                  L y opl                u ns
                                                                                        St de t
                         40 %

                         35 %

                         30 %
                                  1              2                 3             4         5
                    of s i as
                   Pr e son l    59 %          57 %               55 %         73 %      100 %
                    a pe e
                   L y opl       40 %          52 %               56 %         34 %      75 %
                     u ns
                    St de t      43 %          50 %               56 %         57 %      35 %
                     l
                    Al           47 %          53 %               56 %         59 %      47 %
                                                      Strength of view
                                     63


     e e l n al
          s          n i r
                         g       r me a n o ee t h r s o la eai  o
   Th rsut i tbe 15 a d f u e 9 ae so wh tic h rn;tee i n ce rrlt n
 ewe n rn t f iw n      c e ae o l e o d n s h o rlt       o ewe n
b t e ste gh o ve a d su c ss rt. F r al rsp n e t te c reain b t e
 o f ne n
    d          c e ae h r e       o e o t e ewe n rn t f iw o e n o
                                          i
c n ie c a d su c ss rt tee se ms t b p si v b t e ste gh o ve sc r o e t
o r e pe h t a e e n h      st o fd n, rn t f iw o e i , a e q al o
                                                        v           y
f u . P o l ta h v b e te mo c n ie t ste gh o ve sc r f e h v e u l lw
  c e ae h n e pe t h o st o fd n e rn t f iw o e n . u h a e
                      h
su c ss rt ta p o l wi telwe c n ie c , ste gh o ve sc r o e Th s tesh p
 f h o f n e ce uv ’ e o e o c v .
        d                                       we e, h r r ifrn e ewe n
o te‘c nie c -su c ss c r e se ms t b c n a e Ho v r teeaed fee c s b t e
e o d n ru s n h       a e f h uv . o u e t h       a e s mi o h l
                                                            a
rsp n e t g o p i te sh p o te c re F r std ns te sh p i si lr t te al
e o d ns’ u v . so h a e f h a p o l u v s mi o h l rsp n e t u v
                                             a
rsp n e t c re Al tesh p o tely e pec rei si lrt teal e o d ns’ c re
 u t h x e t h t c e e ra s le d t rn t f iw o e o r y e pe
     h       o
b twi tee c pin ta su c ss d ce se ara y a ste gh o ve sc r f u . La p o l
 t rn t f iw o e ie r o n ld d n h n lsi u o h o
  h                                                            ). o
wi ste gh o ve sc r fv ae n ticu e i te a ay s d e t te lw n (4 F r
 r fssin l h a e f h o f n e c e u v ’ s p o t o h te r u s;t e
                           d                           e
p o e o as tesh p o te‘c n ie c -su c ss c r e i o p si t teoh rg o p i se ms
o e o v x u c ss f r fssin l i t e ra s r m rn t f iw o e n o h e
                                 g y
t b c n e . S c e o p o e o as sl hl d ce se fo ste gho ve sc r o et tre
 u n ra s rn l n rn t f iw oe o r n ie te gh f iw o e ie s
b tice se sto gy i ste gh o ve sc r f u (a d fv ). S rn t o ve sc r fv i
 o v r o n ld d n h n lsi u o h o        ). e ifrn e ewe n e o d n
h we e n ticu e i tea ay s d et telw n (4 Th dfee c s b t e rsp n e t
 r u s mpy h t h eai f o f n e n efr n e g t e n q a o ifrn
                   o        d
g o p i l ta te rlt n o c n ie c a d p ro ma c mih b u e u lf rdfee t
 r u s f e pe
g o p o p o l.

      h e l n al
           s          n iu e o o o fr eibe e ea e pa ai n h eai
                                                           o        o
   As tersut i tbe15 a dfg r 9 d n t fe rla l g n rl x ln t no terlt n
 f o f n e n ef r n e r n lsi s e urd n r e o i o e h r eai
      d                                                            u     o
o c n ie c a d p ro ma c mo e a ay s i rq ie . I o d rt dsc v rte t e rlt n
 ewe n o fd n e n ef r n e     r p i i td e i are u. be
                                       c                           o h
b t e c n ie c a dp ro ma c amo eso hst ae tst s c rido tTa l 16 sh ws te
e l f h o i-rg e o e rb d n ci
   s                               o           e u p se f h e rssin s o
rsut o te lgt e rssin d scie i se t n 3.2.2. Th p ro o te rg e o i t
o e a su c ss n ikn h et ef r n sse.
                        e               i nee i h e rssin s o u y
f rc st c e i pc igteb t rp ro miga tM anitrst nterg e o i t std
h fe t f o fd n e rn t f iw o e n ef r n e           e ai mp c n h
                                                         v
te efc o c nie c (ste gh o ve sc r) o p ro ma c . A n g t e i a to te
 r b b l y o c e d ud e
       i                     r n g f v ro fd n e so h n e e d n y f
p o a i t t su c e wo l b a sto g sin o o ec n ie c . Al te id p n e c o
  c e r m rn t f iw s nep ee s v ro f n e n d i o o h ul mpe
                                          d           i
su c ss fo ste gh o ve i itr rtd a o ec n ie c . I a dt n t te f l sa l
e rssin a h e o d n r u s u id p rtl o b r e h o by ifrn eai       o
rg e o , e c rsp n e tg o pi stde se aaeyt o sev tep ssil dfee trlt n
 f o f n e n efr n e
      d
o c n ie c a dp ro ma c .
                                        64


   le 6
Tab 1 – Overconfidence,          performance 33
                       confidence-            /
  be    e o t h e l r m h o i g e o . e e rssin se h iay aibe f c e s h
                    s           -r
Ta l 16 rp rs tersut fo telgt e rssin Th rg e o u s tebn r v ra l o su c ss a te
 e o se aibe e x ln tr aibe r a d n h ol td a k r u d aa n r ifrn fr a h
                                                  e
rsp n v ra l. Th e pa ao yv ra ls aeb se o tec l ce b c g o n d t a daedfee t o e c
  mpe     r ig ) fe h a      f aibe a s h t h aibe s        u    . e a l s iie no
sa l. M akn (d atrten meo av ra l me n ta tev ra l i ad mmy Th tbei dvd d it
 o r a es, a h o p rt mpe a e         e o t h e l f h ul mpe a e
                                                   s                     f r fssin l
fu p n l e c frse aae sa l. P n lA rp rs te rsut o te f l sa l, p n lB o p oe o a
  mpe a e      f u e t mpe n a e         f a p o l mpe     i e ees o h st e f
                                                            ma
sa l, p n lC o std n sa l a d p n lD o ly e pe sa l. ‘Est t’ rfr t te e i t oma
  xmu i l o , n r
          k h             i q o h ai c l g iia c fh st e
                                     st
ma i m l eio d a d‘P >ChS ’ t testt ia sinfc n eo tee i t.ma

Panel A: Full sample
                             i e
                              ma
                           Est t                 l i ur
                                              W adCh-Sq ae             r
                                                                      P >ChSiq
 te gh f e
S rn t o Viw                 0,12                 4,61                   ,0
                                                                       0 3**
 at n nut n
   h      i
F i i I ti o                -0 3
                              ,0                   1,33                 0,25
  e o Co nt n
          i
Ne dfr g io                 -0 1
                              ,0                    ,0
                                                   0 6                  0,80
   l )
M ae(d                      -0,10                  0,51                  ,4
                                                                        0 8
 r fssin l )
P oe o a (d                   ,4
                             0 6                   7,80                0 1***
                                                                      < ,0
 apo l )
L y e pe(d                    ,0
                            -0 8                   0,20                 0,65
Panel B: Professionals
                              i e
                               ma
                           Est t                 l i ur
                                              W adCh-Sq ae             r
                                                                      P >ChSiq
 te gh f e
S rn t o Viw                 0,24                 4,52                   ,0
                                                                       0 3**
 at n nut n
   h      i
F i i I ti o                -0 5
                              ,0                   1,24                 0,27
  e o Co nt n
          i
Ne dfr g io                  0 1
                              ,0                    ,0
                                                   0 2                  0,89
  p re c
Ex ein e                      ,0
                             0 0                    ,0
                                                   0 2                  0,88
   l )
M ae(d                      -0,90                 10,94                0 1***
                                                                      < ,0
 ann )
Triig(d                      0,14                  0,24                 0,62
Panel C: Students
                              i e
                               ma
                           Est t                 l i ur
                                              W adCh-Sq ae             r
                                                                      P >ChS iq
 te gh f e
S rn t o Viw                  ,0
                             0 7                  0,59                    ,4
                                                                         0 4
 at n nut n
   h      i
F i i I ti o                -0 4
                              ,0                   0,90                 0,34
  e o Co nt n
          i
Ne dfr g io                  0 2
                              ,0                   0,32                 0,57
   l )
M ae(d                        ,0
                             0 9                   0,13                 0,71
n e me t x ein e )
Iv st n e p re c (d          0,31                  1,85                 0,17
 ia c    jr )
F n n emao (d                0 5
                              ,0                    ,0
                                                   0 4                  0,83
Panel D: Laypeople
                              i e
                               ma
                           Est t                 l i q ae
                                              W adCh-S u r             > iq
                                                                     Pr ChS
 te gh f e
S rn t o Viw                 0,10                 0,52                  ,4
                                                                       0 7
 at n nut n
   h      i
F i i I ti o                -0 3
                              ,0                   ,4
                                                  0 0                  0,52
  e o Co nt n
          i
Ne dfr g io                 -0 1
                              ,0                   ,0
                                                  0 5                  0,83
   l )
M ae(d                       0,34                 1,68                 0,19
n e me t x ein e )
Iv st n e p re c (d          0,14                 0,27                 0,60
  l e x et
   e       se
Beiv de p ri                -0,11                 0,33                 0,56

 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%
                                        65


     spt h i ig n al
       e    n          e ci s f hs u y h r e o e o t e o rlt
                             o                              i       o
   De i te f dn s i e rirse t n o ti std , teese ms t b p si v c reain
 ewe n o fd n e n ef r n e n iiu l e pe h t r       r of n r
                                                          d       r i l
                                                                     k
b t e c n ie c a d p ro ma c . I dvd a p o l ta aemo ec n ie taemo el ey
o ce d n h       oe mpe e rssin n n ra n h rn t f iw o e n ra s h
t su c e . I tewh l sa l rg e o a ice sei teste gho ve sc r ice se te
 r b bl y f c e
       i
p o a i t o su c ss ( = 0        e n ra s g iia t t i ec n sinfc n e e e
                                                     v
                         .12). Th ice sei sinfc n a f ep re t g iia c lv l(w
=4        oh r g i a t aibe fe t
                  i             n h r b bl y f c e s h r fssin l
                                             t
  .61). An te sinfc n v ra l afcig te p o a ii o su c ss i te p o e o a
 u     aibe en       r fssin l n ra s h rb bl y f c e
                                               t                .4
d mmy v ra l;b ig a p o e o a ice se te p o a ii o su c ss ( = 0 6). The
n ra s ihy g i a ti            ,     .0     i mpi h t r fssin l up ro m
                                                 e
ice se i hg l sinfc n (w = 7.80 p < 0 1). Ths i l s ta p o e o as o tef r
 te e pe n ia ca     r e eae  n e lci a s. e mp c f at n nut
                                       o                  h     o
oh rp o l i fn n ilmak trltd win rsee t n tsk Th i a to fi i itiin
  I oe n c e          e   o e e ai ; n ra n I o e e ra s h r b bl y f
                                   v                                     i
(F ) sc r o su c ss se ms t b n g t e ice se i F -sc r d ce se te p o a i t o
  ce          .0     e e ra , o v r s o sinf a t
                                               i
su c ss ( = -0 3). Th d ce se h we e, i n t g i c n (w =1.33).

   n h b mpe e rssin rn t f iw a             o t e mp c n h rb bl y f
                                                i                   i
   I te su -sa l rg e o s ste gh o ve h s a p si v i a to te p o a i t o
  c e o l e o d n r u s. e mp c o r fssin l s ih st           .24 g i c n
                                                                     i
su c ss f ralrsp n e tg o p Th i a tf rp o e o as i hg e ( = 0 ), sinf a t
 t h i ec n g iia c e e
     v
a tef ep re tsinfc n elv l(w = 4        r u et       .0 n o a p o l
                                .52). Fo std ns ( = 0 7) a d f rly e pe( =
 .10 h mp c s o r et r en g iia t i mpi h t h fe t f o fd n e n
                       h                      e
0 ), t ei a ti lwe, n i e b igsinfc n. Ths i l s ta teefc o c n ie c i
  c e s ih r o r fssin l h n te e pe u n e me t d i r e o e e
su c ss i h g e f rp o e o as ta oh rp o l. Th s iv st n a vso s se m t b lss
 v ro fd n ta oh r e pe
o ec nie th t te p o l.

   n d io o rn t f iw h r s ny e te a tr fe t h r b bl y f
        i                                          n          i
   I a dt nt ste gho ve teewa o l afw oh rfco s afcigtep o a i t o
  c e h t a e n x ln tr o r e st mp ra t f h se a tr s e d r f
su c ss ta h v a y e pa ao y p we. Th mo i o tn o te fco s i g n e o a
 r fssin l en     l n e me t d i r e ra s h r b bl y f c e o ae o
                                                  t
p o e o a;b ig amaeiv st n a vso d ce se tep o a ii o su c ss c mp rd t
h e l ol g e
           e            .90   e ifrn e s ihy g i c n
                                                i           .94     .0
te fmae c l a u s ( = -0 ). Th dfee c i hg l sinf a t(w = 10 , p < 0 1).
  n e ly oe o a p o l l , u o h p o t ie t .
                                           e    o     l a p o l a e ih r
Ge d rpa s r l f rly e peaso b t n teo p si d rcin M aely e peh v h g e
 r b bl y o c e d
       i                .34 h ifrn e o v r s o g i a ti                o
p o a i t t su c e ( = 0 ), te dfee c h we e i n tsinfc n (w = 1.68). F r
 u e t eso a n e me t x ei c a
                            e           o t mp c n c e
                                           v                   td ns h t a e
std ns, p r n liv st n e p r n e h s a p siie i a to su c ss. S u e t ta h v
  d eso a o k r e n e me t a e ih r rb bl y f c e h n u e t h t
                                             i
ma e p r n lstc mak tiv st ns h v hg e po a i t o su c ss ta std ns ta
 a e o ma e c n e me t
h v n t d su hiv st ns ( = 0        e ifrn e s o sinf a t
                                                     i
                            .31). Th dfee c i n t g i c n (w = 1.87).

     e h u h h eai ewe n o fd n e n ef r n e e o e o t e a tr
                  o                                           i
   Ev n to g terlt nb t e c n ie c a dp ro ma c se ms t b p si v , fco s
 fe tn o fd n e r mp ra t    n ra n o fd n e o me aibe g t n iae
afcig c n ie c ae i o tn. An ice se i c n ie c f rso v ra l mih idc t
 v ro fd n e i od f h me aibe e ra s rb bl y f c e a l
                                                   i
o ec nie c . Ths h ls i tesa v ra l d ce se p o a i t o su c ss (tbe 16). To
u te iv stg t v ro f n e n r iay e st u r e rssin x liig rn t f iw
                     d
f rh r n e iaeo ec n ie c a o dn r la sq aerg e o e pann ste gho ve
                                        66


s o d ce . e u p se f h e rssin s o i o e a tr fe tn o fd n e be
i c n u td Th p r o o terg e o i t dsc v rfco s afcigc n ie c . Ta l 17
  o h e l f h e rssin e e l r o ae o h e l fa l
           s                    s                 s
sh ws tersut o terg e o . Th rsut aec mp rdt tersut o tbe16.



   le 7
Tab 1 – overconfidence,confidence
  be     e o t h e l rm h
                      s         S-rg e o .  e e rssin se h rn t f iw o e s h
Ta l 17 rp rs te rsut fo te OL e rssin Th rg e o u s te ste gh o ve sc r a te
 e o se e e d n) aibe o o f n ed        e se x ln tr n e e d n) aibe r e d r
rsp n (d p n e t v ra l fr c n ie c . Th u d e pa ao y (id p n e t v ra ls ae g n e,
 r fssin n h hn ig ye o e          C n I e g iia c f h e l s e n rtd sig
                                                                 s
p oe o a d te tikn stl sc rs NF a d F . Th sinfc n e o te rsut i d mo stae u n
  a d r -tst    r ig ) f h a
                        e         f aibe a s h t h aibe s u         .    i e ees o
                                                                         ma
stn adt e .. M akn (d atrten meo av ra l me n ta tev ra l i ad mmy ‘Est t’ r fr t
 h st e f e rssin o fiin, n
      ma                          > -stt o h ai c l g iia c f h st e
                                               st
tee i t o rg e o c efce ta d‘Pr t a’ t testt ia sinfc n eo tee i t. ma

                             i e
                              ma
                           Est t                   -stt
                                                   t a                  > -stt
                                                                      Pr t a
 at n nut n
   h      i
F i i I ti o                 0 6
                              ,0                   3,54                0 1***
                                                                      < ,0
  e o Co nt n
          i
Ne dfr g io                  0 0
                              ,0                   0,12                 0,91
   l )
M ae(d                       0,24                  2,29                  ,0
                                                                        0 2**
 r fssin l )
P oe o a (d                    ,4
                             -0 0                  -3,31                0 1***
                                                                       < ,0
 apo l )
L y e pe(d                   -0,79                 -6,39                0 1***
                                                                       < ,0


 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%


     su t n a l
        s         o h t v rl aibe a e g iia tmp c o o fd n e g e
   Re l i tbe17 sh w ta se ea v ra ls h v sinfc n i a t nc n ie c . Hih r
at n nut n I o e n ra s o f n e
  h     i                      d         .0     e n ra s ihy g i a t
                                                                  i
fi i itio (F -sc r) ice se c n ie c ( = 0 6). Th ice sei hg l sinfc n, (t
      ,    .0     i o ie t h a t h t h mp c o F -sc r n c e s e ai ,
                             h                                        v
= 3.54 p< 0 1). Ths c mbn dwi tefc ta tei a t f I o eo su c ss i n g t e
 l u h o sinf a t a l
  h          i             n iae h t e pe t ih I o e r v ro f n.
                                             h                    d
ato g n t g i c n (tbe16), idc ts ta p o l wi hg F -sc r aeo ec n ie tAs
h fe t f n ltc l hn ig s o g i c n et r o o fd n e r c e o o cu o
                              i     h
teefc o a ayia tikn i n tsinf a t i e f rc n ie c o su c ss, n c n lsin
 n ht a e d.       ls e o t ih r o fd n e h n ma    .24 h ifrn e s
o ta c n b ma e M ae rp r hg e c nie c ta wo n ( = 0 ), tedfee c i
 l g ii n t ec n g i c n e e e
        c                i                    n d io
                                                   i     n e ot o r c e
aso sinf a ta 5 p re tsinf a c lv l(t= 2.29). I a dt n me rp r lwe su c ss
h n me ,  ih n iae h t n r    r v ro f n h n me .
                                        d             we e, h
ta wo n whc idc ts ta me ae mo e o ec n ie tta wo n Ho v r te
  c e aibe n a l         s o sinf a t n h s o r n o cu o s a e d .
                                  i
su c ss v ra l (i tbe16) i n t g i c n, a dtu n sto gc n lsin c nb ma e

     e mp c f h r fssin l u       aibe n o f n e s r n
                                              d
   Th i a t o te p o e o a d mmy v ra l o c n ie c i sto g (                       .4 ).
                                                                               = -0 0
 r fssin l r e o fd n ta h a r u , u e t           e ifrn e s ihy g iia t
P o e o as aelss c n ie t h nteb seg o p std ns. Th dfee c i hg l sinfc n
                .0      ro e, h mp c o h r fssin l u      n c e s rn
(t= -3.31, p < 0 1). M o e v r tei a t ftep o e o a d mmyo su c ss i sto g( =
 .4 n ihy g ii n  c            ,     .0     i n iae r n l h t h ifrn e s
0 6) a d hg l sinf a t(w = 7.80 p < 0 1). Ths idc ts sto gy ta tedfee c i
 v ro fd n e ewe n r fssin l n   uet s    d . rfssin l r     c e
o ec nie c b t e p o e o as a d std ns i wie P o e o as ae mu h lss
 v ro fd n ta u e t    e fe t f h a p o l u  n o fd n e s l r n
o ec nie th nstd ns. Th efc o tely e ped mmyo c nie c i asosto g( =
-0      n ihy g iia t =              .0     y e pe r e o fd n ta u e t e
  .79) a dhg l sinfc n (t -6.39, p< 0 1). La p o l aelss c n ie th nstd ns. Th
                                                 67


 fe t f a p o l u  n c e s i t e aie
                                g y              .0    u o g i at u
                                                                i
efc o ly e ped mmyo su c ss i sl hl n g tv ( = -0 8), b tn tsinfc n. Th s
h e l n iae h t a p o l r e v ro fd n ta u e t
     s                                                 e ifrn e o v r
tersut idc t ta ly e peaelss o ec n ie t h n std ns. Th dfee c , h we e,
s o a g iia t s ewe n r fssin l n u e t
i n t s sinfc n a b t e p o e o as a dstd ns.



   .  f- ttrib   ia
4.3 Sel a ution b s

    ef t b t
        r o is s u id n wo e s.   t es    a r l-at b t
                                                     r o is y h
   S l-atiuin ba i stde i t tst Boh tst me su e sef t iuin ba b te
 h n e n ec ie etit f c e ewe n ist n c n o n s. e ifrn e s n h
c a g i p rev dc ranyo su c ss b t e fr a dse o dr u d Th dfee c i i te
 eemi ai f c e
        o              ist e se n iiu l n r      ee s c n e se o ld
d tr n t n o su c ss. F r tstu s idvd a a swes wh ra se o d tstu s p oe
 n r o      n l eso . e e h iu s se r i u d n r ealn ci      o
a swes f rasigep r n Th tc nq e u daedsc sse i mo ed tii se t n3.2.3.

     e i e b se n n t b t
       r               r o f l-at b t
                                    r o is c o dn o ih e pe o
   Th f sttst a s o a atiuin o sef t iuin ba a c r ig t whc p o l wh
 ei e h y a e c e d d n
   e                      n e lci a t b t h msev s n h c e
                                   o     r
b l v te h v su c e e i awin rsee t ntskati uete le o tesu c ss. As a
e l f hs, c e pe v rstmae h i wn a a i t n e o
                                        i                r o fd n.
rsuto ti su h p o l o ee i t ter o c p bl y a d b c me mo e c n ie t
 i l l e pe o ei e h y al n
    a               e       e      n e lci a t b t h msev s n h
                                            o       r
S mi ry p o l wh b l v te fi d i awin rsee t n tsk atiue te le o te
al e n e o
  u             e o fd n.        e n rt l-at b t
                                               r o is h      mpe f sse
fi r a d b c me lss c n ie t To d mo stae sef t iuin ba te sa l o a t
  lci n r f hs u y s iie no wo b mpe a d n h ei e o rcn ss.
     o                                                   e
see t na swes o ti std i dvd dit t su -sa ls b se o teb l v dc re te
 ef tiui is s
   -a    o         a rd y h h n e n rn t f iw o e ewe n h o n s.
S l trb t n ba i me su e b te c a g i ste gh o ve sc r b t e te r u d
  be     rse t h e ls.   e n rt h ai c l g i c n e ard -tst s are .
                                      st     i
Ta l 18 p e ns tersut Tod mo staetestt ia sinf a c ap ie t e i c rid



   le 8     attrib tion b indiv al answers test
Tab 1 – Self-     u      ias,  idu
  be     e o t oh h e ol td h se
                         e            n h se   rn t f iw o e       l-at b t
                                                                      r o is s
Ta l 18 rp rs b t te rc l ce p a 1 a d p a 2 ste gh o v e sc rs. Sef t iuin ba i
  a rd y h ifrn e ewe n h se h se e h se            e o e f ard -tst s e o td n
me su e b te d fee c b t e te (P a 2 lss P a 1). Th sc r o a p ie t e i rp re i
 ae te s. e mpe s iie n wo a es,         n     ae    n ld s h n r n ih a h
p rnh se Th sa l i dvd d o t p n l A a d B. P n lA icu e te a swes i whc c se te
e o d n b l e h n r o e o rc. a e B n ld s h n r n ih a h e o d n b l e
            e                                                                 e
rsp n e t eiv s tea swe t b c re tP n l icu e tea swes i whc c setersp n e t eiv s
h n r o e o rc. e e so o h p rt s n h y oh sie ie t f fe t
                                      o                     o
tea swe t b c re tTh ra nf rtese aaini i teh p te z ddrcino efc.

Panel A: Asset selection b     ed
                          eliev correct
                                             rn t f iw
                                            Ste gho ve
                                h se e ol t )
                                          e o
                               P a 1 (rc l cin           a
                                                       Ph se2          Diff.
 r fssin l
P oe o as                            2,50               2,68           0,18*
                                               (N =90)                (1,666)

 td ns
Su e t                                    2,74             2,80          ,0
                                                                       0 6
                                                 (N =50)                ,4 1)
                                                                      (0 0

  y e pe
La p o l                                  2,09             2,14          ,0
                                                                       0 5
                                                      4
                                                 (N =4 )                ,4 3)
                                                                      (0 4
                                              68



Panel B: Asset selection b     ed
                          eliev incorrect
                                             rn t f iw
                                            Ste gho ve
                                h se e ol t )
                                          e o
                               P a 1 (rc l cin           a
                                                       Ph se2    Diff.
 r fssin l
P oe o as                            2,07               2,11       ,0
                                                                 0 4
                                               (N =45)            ,350
                                                                (0 )

 td ns
Su e t                                 2,21             2,10      -0,10
                                              (N =39)           (-1,0 71)

  y e pe
La p o l                               1,90             1,90        -
                                              (N =39)              (-)

 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%


     su t n a l
        s       n iae h t e pe fe r m l-at b t
                                            r o is. e pe o ei e   e
   Re l i tbe18 idc t ta p o l su frfo sef t i uin ba P o l wh b l v
h y a e c e d d o n ra h i o f n e f e r ig h uc me
                                 d     e                   i od
te h v su c e e d ice se ter c n ie c atr lann te o to . Ths h ls
 sp cal o r fssin l
      y                 o o     .18 ons n ra n rn t f iw     a rd n
e e il f rp o e o as, wh sh w a0 p it ice sei ste gh o ve (me su e o
  ae o         e ifrn e s ai c l g i c n a tn ec n sinf a c e e (t
                             st y    i                   i
sc l 1 t 5). Th d fee c i stt ial sinf a t t e p re t g i c n elv l = 1.67).
 so u e t n a p o l o n n ra n o fd n e u h se ifrn e r o
Al std ns a d ly e pe sh w a ice se i c n ie c b tte dfee c s ae n t
 g iia t t h e ec n g i a c e e.
                          i
sinfc n a te tn p re tsinfc n e lv l Ov rl rsut i p n lA ae i l e wi te
                                       eal e l n a e
                                              s           r n in    h
                                                                   t h
 y oh si    e e l l
                  s       g e h t r fssin l fe h      st f l-at b t
                                                              r o is,
h p te s. Th sersut aso su g stta p o e o as su frtemo o sef t iuin ba
  ih s g isth y oh si h t x et e u e e a irl ise
                              se
whc i a an teh p te s ta e p ri rd c s b h vo a ba s.

     e te e f l t b t
                 -a r o is se h v rl c e f e o d n . e e s
   Th oh rtsto sef t i uin ba u s teo ealsu c ss o a rsp n e t Th tsti
 a d n n t bt
          r o f l-at b t
                       r o is h t e pe o a e c e u n h a
b se o a atiuin o sef t iuin ba ta p o l wh h v su c ssf li te p st
 t b t h msev s n c e
  r                       e l c e u e pe v rst e h i wn a a i t
                                                   ma            i
atiuete le o su c ss. As arsutsu c ssf lp o l o ee i t tero c p bl y
 n eo        r o fd n.       b r e id g t is h mpe s iie no o r b
a d b c me mo e c n ie t To o sev hn sih ba te sa l i dvd d it f u su -
  mpe a d n h ec ie u e f o rc a swes t h se        e h n e n rn t f
sa ls b se o tep rev dn mb ro c re t n r a p a 1. Th c a g i ste gho
 iw s u id be        rse t h e l s.   e n rt h ai c l g iia c
                                                   st             ard
ve i stde . Ta l 19 p e ns tersu t Tod mo staetestt ia sinfc n eap ie
-tsts are . iu e      o h me n o mai s a l
                                     o          u i rp ia f r
t e i c rid F g r 10sh ws tesa if r t na tbe19 b tng a hc l o m.
                                                  69


   le 9     attrib tion b person lev test
Tab 1 – Self-     u      ias,       el
  be    e o t oh h e ol td h se
                         e          n h se    rn t f iw o e       l-at b t
                                                                     r o is s
Ta l 17 rp rs b t te rc l ce p a 1 a d p a 2 ste gh o ve sc rs. Sef t iuin ba i
  a rd y h ifrn e ewe n h se h se e h se           e o e f ard -tst s e o td n
me su e b te d fee c b t e te (P a 2 lss P a 1). Th sc r o a p ie t e i rp re i
 ae te s. e mpe s iie y h ec ie u e f o rc n r t h se                e e so o h
p rnh se Th sa l i dvd d b tep rev d n mb ro c re ta swes a p a 1. Th ra n frte
  p rt s n h y oh sie ie t
      o                     o f fe t
se aaini i teh p te z ddrcino efc.

                                              rn t f iw
                                             Ste gho ve
                                 h se e ol t )
                                           e o
                                P a 1 (rc l cin           a
                                                        Ph se2                Diff.
  . f re t swes
No o Co rc An r = 0                   1,67               1,89                 0 ,22
                                                (N =3)                            0)
                                                                             (1,0 0

  . f re t swes
No o Co rc An r = 1                   2,26                      2,06          -0,19*
                                                  (N =31)                    (-1,871)

  . f re t swes
No o Co rc An r = 2                   2,28                      2,47          0,19*
                                                       0
                                                  (N =4 )                    (1,831)

  . f re t swes
No o Co rc An r = 3                   2,62                      2,82          0 ,20
                                                  (N =15)                    (0,731)

 tt c l g iia c e es:
   st                      %,
S ai ia sinfc n elv l * =10 ** =5%, *** =1%




     re 0     attrib tion b person lev test
 Figu 1 – Self-     u      ias,       el

                                   a g n te h f iw e we n o n s
                                 Ch n ei sr g to ve b t e r u d

                       3


                      2,5
 Av a s r ngt ofviw
                 e




                       2
   er ge te h




                      1,5


                       1


                      0,5


                       0
                            0            1                      2        3

                                       r   ore a wer n ou      bel ed)
                                                                  e
                                  Numbe ofc r ct ns s i r nd 1 ( iv

                                             Round1    Round2
                                      70


      e e l n al
           s          n iu e     mpy h t e pe fe r m l-atiui is.
                                                               o
    Th rsut i tbe 19 a d fg r 10 i l ta p o l su frfo sef trb t n ba
 i l l o h n lsi f id g t is e iu e ) h r e o e eg f o d n
    a
S mi ry t tea ay s o hn sih ba (se fg r 4 teese ms t b av r eo g o a d
 a e l b t e n n wo o rc a swes. f t o hs h h n e n o fd n e r
                                  e n
b drsut ewe no ea dt c re t n r Relcigt ti tec a g s i c nie c ae
ni n t h y oh si o l su -sa ls, e d s eo o rc a swes.
       h                                               ro e, h   o
i l ewi teh p te s f ral b mpe b sie z r c re t n r M o e v r tenf r
 eo o rc n r s o         l    o n eibe n lsi e pe o ei e h y a ny
                                                              e
z r c re ta swes i to smal(3) f ra yrla l a ay s. P o l wh b l v te h do l
 n o rc n r e ra h i rn t f iw o e y .19. Th d ce sei sinfc n a
o ec re ta swe d ce seterste gh o ve sc r b 0             i
                                              e e ra s g i a t t
e ec n g ii n e e e
             c                     k wi , e pe o ei e h y a e wo o rc
                                                     e
tn p re tsinf a c lv l(t= -1.87). Lie se p o l wh b l v te h v t c re t
 n r n ra h i rn t f iw y .19, whc i aso sinf a t a tn p re t
a swes ice se ter ste gh o ve b 0 ih s l     i
                                          g i c n t e ec n
 g ic n e e e
    i                    e pe o ei e h y a e l h e o rc, n ra h i
                                    e
sinf a c lv l(t= 1.83). P o l wh b l v te h v alt re c re t ice se ter
 rn t f iw y .20 i n ra , o v r s o sinf a t = .73). Ov rl tersut
                                             i
ste gho ve b 0 . Ths ice se h we e, i n t g i c n (t 0    ,
                                                       eal h e ls
n al     n iu e     p o t h xstn e f l-atiui is; e pe o r c e u
                                              o
i tbe19 a dfg r 10su p r tee i e c o sef trb t nba p o l wh aesu c ssf l
n h a b c me r o fd n.
i tep st e o mo ec nie t



             e- p        l el th
4.4. Cognitiv ex erientia s f- eory

      e a    cio f h e l ci
                          s     o i u s h n r ol td n h ai a-
                                                         e          o
    Th lst se t n o te rsut se t n d sc sse te a swes c l ce i te rt n l
 x eini iv no y e i e so o n ld e o idvd a tikn n h re
        a
e p re t l n e tr . Th manra nt icu eatst f n iiu l hn igi tesu v ywas
o r vd x ln tr aa o te e s f e a irl ise         we e, h e l f h ai a-
                                                            s      o
t p o iee pa ao yd t f r h tst o b h voa ba s. Ho v r tersut o tert n l
 x eini n e tr r nee i e . e u p se ee s o o ae n iiu l hn ig
        a               n
e p re t liv no yaeitrst gp rse Th p r o h r i t c mp r idvd a tikn
 ye f h ifrn rsp n e t ru s f hs u y o hs u p se h mpe s iie no
stls o tedfee t e o d n go p o ti std . F rti p ro tesa l i dvd dit
  v rl b mpe a d n h a k r u d aibe ol td n h  e          r e s. be
se ea su -sa ls b se o te b c g o n v ra ls c l ce i te su v y Ta l 20
 rse t h v rg o e f h ai a-e p rme tl e . e o
                           o                          g io
                                                         i    C) ees o
p e ns tea ea esc rs o tert n l x ei na tst Ne d f rCo nt n(NF rfr t
h e e f n lt l hn ig ih r C o e
             c                        r n lt l y o hn ). at n
                                             c              h
te lv lo a ayia tikn (hg e NF sc r, mo e a ayia wa t tik F i i
nut n I au al ees o h at n nut
    i            y
I ti o (F ) n trl rfr t te fi i itiin (hg e F sc r, mo e fi ta o
                             h     o    ih r I o e         h
                                                      r at h t wn
nut n s o rc).
   i
itio i c re t
                                        71


                  le 0 ndiv al th ing
               Tab 2 – I   idu   ink
                Group                        NFC     FI     n
                nv t     advs
                I esm ent ior                3,16   2,79    56
                nv t     advs ,
                I esm ent ior wo em n        2,57   3,43    35
                nv t     advs ,
                I esm ent ior m en           4,30   1,70    20
                   pe l
                Lay ope                      4,11   3,87    53
                   pe l    m
                Lay ope, wo en               3,81   3,77    31
                   pe l
                Lay ope, men                 4,38   3,95    21
                   pe l o       ca
                Lay ope, c mmer il           3,82   4,05    22
                   pe l ec nia
                Lay ope, t h c l             4,25   3,75    20
                  ud nt
                St e                         3,75   2,53    89
                  ud nt m
                St e , wo en                 3,29   2,79    28
                  ud nt n
                St e , m e                   3,97   2,41    61
                  ud nt i c
                        na      j
                St e , f n e m aor           4,71   1,86    35
                  ud nt her j
                St e , ot m aor              3,13   2,96    54
                   m n
                Wo e                         3,19   3,35    94
                Men                          4,12   2,59   102
                All                            6
                                             3, 8     9
                                                    2, 6   198


       a e e r m a l , h r r g i c n dfee c s ewe n e o d n g o p n
                                i
   As c nb se nfo tbe20 teeaesinf a t ifrn e b t e rsp n e t r u s i
n iiu l hn ig rb by h     st nee i idn s h t n e me t d i r n v rg
                                 n
idvd a tikn . P o a l temo itrst gfn ig i ta iv st n a vso s o a ea e
 r h e st n lt l e pe f h
              c              mpe   we e, h r s    v r e d r fe t n
ae te la a ayia p o l o te sa l. Ho v r tee i a se ee g n e efc i
 n ltc l hn ig f h r fssin l l rfssin l a k hr f l b r u s    ee s
a ayia tikn o tep o e o as;maep oe o as rn tid o alsu g o p wh ra
e l r fssin l a k a . eal n r r n lt lh n ma u te ifrn e o
                                        c
fmaep o e o as rn lstOv rl me aemo ea ayia ta wo nb th dfee c f r
 te e o d n r u s s o s r n .     t n h u e t mpe
                                   h                   jr f h e o d n
oh rrsp n e tg o p i n ta sto g W i i te std n sa l, mao o te rsp n e t
  e o fe t n ltc l hn ig r gy ia c u e t r h
                          o                            st n lt l b ru
                                                              c
se ms t afc a ayia tikn st n l. F n n e std ns ae te mo a ayia su go p
  ee s u e t t te
               h      jr a k c n a n n lt l hn ig
                                           c            l uet r
wh ra std ns wi oh rmao rn se o d lsti a ayia tikn . M ae std ns ae
  me a mo e n lt l h n e l u e t fee c s t n h a p o l mpe r o
                c                         h
so wh t r a ayia ta fmaestd ns. Difrn e wi i tely e pesa l aen t
 s rn s t n r fssin l n u e t mpe
            h                                n e o e r n lt l h n
                                                                c
a sto g a wi i p o e o a a d std n sa ls. M e se m t b mo e a ayia ta
  me n e pe t e h ia d c t
                 h            o    e o e r n lt l h n e pe t
                                                   c
wo n a d p o l wi tc nc le u ain se m t b mo e a ayia ta p o l wih
 o   ril d c t .
              o
c mmeca e u ain

    fee c s n at n nut n r e eal n i
               h     i          y
   Difrn e i fi i iti o aeg n rl i l ewi tea ayia tikn rsut a d
                                    n   h      c           s
                                       t h n lt l hn ig e l n
h s t h y oh si e p e h t a e ih n lt l hn ig r x e td o a e o at
     h                                 c
tu wi teh p te s. P o l ta h v h g a ayia t ikn aee p ce t h v lw fih
n nut n i y oh si od o p o e o as n u e t u n t o ly e pe y e pe
     i
i iti o . Ths h p te s h ls f r r fssin l a dstd ns b t o f r a p o l. La p o l
e o t ih o e oh n n ltc l hn ig n at n nut .
                                      h     o    wo i n o a rp
rp r hg sc rs b t i a ayia tikn a d fi i itiin A t dme sin lg a h
  iu e      e n rt hs fe tfi n nut n s n -a i n n lt lhn ig n -a i
                             h      i                 c
(F g r 11) d mo staeti efc; at i itio i i y xs a da ayia tikn i x xs.
                                                                        72


      re 1 ndiv al ink
  Figu 1 – I idu th ing

                      5,00

                                                         a peopl, wom a
                                                        Ly     e       n                 a peopl
                                                                                        Ly     e
                      4,50
                                                                                                       a pe e
                                                                                                      L y opl, m en
                                                     a peopl, c m e ca
                                                     Ly    e om r il
                      4,00
                                  n e t n dvs ,
                                  Iv s m e ta ior wom an
                                                               W oman
           ntuition




                      3,50
                                                                                                    a pe e e h ia
                                                                                                   L y opl, t c nc l
  Faith in I




                      3,00
                                                                                            Man
                                 u n, h r j
                                St de t ot e ma or
                      2,50
                                  Iv s m e ta ior
                                  n e t n dvs                                  u n
                                                                              St de t
                                                                                                    u n , ia c     j
                                                                                                   St de t fn n emaor
                      2,00
                                              u n,
                                             St de t wom an
                                                                      u n,
                                                                     St de t m an
                      1,50
                                                                 n e t n dvsor n
                                                                 Iv s m e ta i , m a
                      1,00
                         2,00             2,50          3,00                 3,50        4,00         4,50        5,00
                                                                  Need for Cognition


             iu e     lal o h n o ee c f a p o l hn ig a rs o ae o te
            F g r 11 ce ry sh ws teic h rn eo ly e petikn me su e c mp rd t oh r
 e pe y e pe e o t ih r at n nut
                            h     o o e h n n te b ru v n h u h hs
p o l. La p o l rp r hg e fi i itiinsc rs ta a yoh rsu go pe e to g ti
s o jst id t o n lt l hn ig e o be x ln t o h fe t o l i o
       f     h       c                         o                n
i n tu i e wi lw a ayia tikn . On p ssil e pa ainf rteefc c ud l kt
 v ro fd n e e u st s n h ai a-e p re t n e tr r o o d n
                    o        o         a                       y ht
o ec nie c . Th q e in i tert n l x einiliv no yaec mp se i awa ta
f e o d n o me e so ei e h t ef r n e s
                         e                     a rd a d n h se n r
i arsp n e tfrso ra n b l v s ta p ro ma c i me su e b se o to a swes,
 esh   g t v rst e wn ef r n e y e n wn n r o rs h ec ie
                ma
h / e mih o ee i t o p ro ma c b sk wig o a swes twad te p rev d
 o d ef r n e       x mpe s et o lrf hs o i; n h u st
                              e                       o f ae n: M
g o p ro ma c . An e a l i b t rt caiy ti lgc i teq e in o sttme t “ y
nt l mp e o s f e pe r l st l y ih” t s eai l a o nal o n c
  i                                           v               y
ii a i rssin o p o l aeamo awa s rg t, i i rlt ey e sy t me tl c n e t
 o d ef r n e o ih o e u v ro fd n p o l, h t ei e o e o d ef r r
                                                      e
g o p ro ma c t ahg sc r. Th s o ec n ie t e pe ta b l v t b g o p ro mes,
e d o e o t ih oe     e ae ns    a rn at n nut n i h n b v , o l
                                         h     i    k
tn t rp r hg sc rs. Th sttme t me su igfi i itio , l eteo ea o e c ud
ol hs o i.
   o           we e, e s f v ro f n e n hs u y o o p o t hs; a p o l
                                 d
f l w ti lgc Ho v r tst o o ec n ie c i ti std d n tsu p r ti ly e pe
 r e eal o rp re o a e h ih st e re f v ro fd n e o ti e so o r n
        y
aeg n rl n t e o tdt h v tehg e d g e o o ec nie c . F r hs ra nn sto g
 o cu o s b u te ih at n nut
                     h      o fa p o l a e d .
c n lsin a o th hg fi i itiino ly e pec nb ma e
                                    73



 .
5 Conclusions

     i ci  o
   Ths se t n su   rz s h mpr l u y f hs h si n o cu e h e l n
                             c                                  s.
                mmaie te e iia std o ti te s a d c n ld s te rsut I
 d i o , hs ci i u s h mpi t s f h e ls.
    i         o                c o              e u p se f h h si s o
a dt n ti se t n dsc sse te i l ain o te rsut Th p r o o te te s i t
 u y h e e a irl ise id g t is, v ro f n e n l-atiui is.
                                      d                   o         uy
std treb h vo a ba s;hn sih ba o ec n ie c , a d sef trb t n ba To std
h se ise n mpr l u y s are u. e u p se f h mprc l u y s o n r h
              c
te ba s a e iia std i c rido tTh p r o o tee iia std i t a swe te
ol n e ac u st s:
   o             o
f l wigrse rhq e in



        w o s h id g t is fe t h x o c n e t o f h x ne x e tt ?o
   1. Ho d e tehn sih ba afc tee -p st o c p ino tee -a t e p cain
         x     n e me t d i r fe r m id g t is?
             Doiv st n a vso s su frfo hn sih ba
         x             se
               e x et e u e h id g t is?
             Do s e p ri rd c tehn sih ba
         x                 c            y
                a c aa trst fe th v rt f id g t is?
             W h t h rcei is afc tese ei o hn sih ba


        w o s h v ro f n e fe th tn f o fd n e i s?
                      d            i              mi
   2. Ho d e teo ec n ie c afc teset go c n ie c l t
         x     n e me t d i r to ar w o fd n e i s?mi
             Doiv st n a vso s se ton ro c n ie c l t
         x             se
               e x et e u e v ro fd n e
             Do s e p ri rd c o ec nie c ?
         x                 c            y
                a c aa trst fe th v rt f v ro fd n e
             W h t h rcei is afc tese ei o o ec n ie c ?


        w o s h l-at b t
                    r o is fe t o fd n e n e e td a s?
   3. Ho d e tesef t iuinba afc c n ie c i rp ae tsk
         x                                  d
               n e me t d i r du ter o f n e a d n h e l     s?
             Doiv st n a vso s a jsth i c n ie c b se o tersut
         x             se         -a
               e x et e u e h l tiui is? o
             Do s e p ri rd c tesef trb t nba
         x                 c            y       r o is?
                a c aa trst fe t h v rt f l-at b t
             W h t h rcei is afc tese ei o sef t iuinba


     e mpr l u y f hs h si se
          c                     o tol i d re o ol t aa o h e s.
                                     e e               e
   Th e iia std o ti te s u s ac nr l d f l su v yt c l c d t f rtetst
  e r e s are o h e p rt r u s f e pe i n il r fssin l nv r t
                                               n
Th su v y i c rid f rtre se aae g o p o p o l;f a ca p o e o as, u iesiy
 u e t n mpo e s f n n ie rn o a y e r cu e f h re s wo h se ,
std ns a d e ly e o a e gn eig c mp n . Th stu tr o tesu v y i t -p a d
  ih n be u yn h h e ise       e ise r u id y o ai b r ai s r m
                                                    n         o
whc e a ls std ig tetreba s. Th ba s aestde b c mp r g o sev t n fo
 ifrn h se f h r e s o a h te. n sih is s b r e y ifrn e ewe n
dfee tp a s o tesu v y t e c oh r Hid g tba i o sev db dfee c s b t e
nt l n r n h e ol t s. ec nie c s u id sig nt l n r n e l d
  i                  e o                           i              z
ii a a swes a dterc l cin Ov ro fd n ei stde u n ii a a swes a draie
e ls. ay s f l-atiui is se nt a swes r m ist n c n o n .
                       o        a
rsut An lse o sef trb t nba u iiil n r fo fr a dse o dr u d
                                   74


     e e l n id g t is g e h t l e pe n ldn n e me t d i r fe
          s
   Th rsut o hn sih ba su g stta alp o l, icu ig iv st n a vso s, su fr
 r m t e pe e d o ec ie h i nt l efr n e et h n t cu l s, f e r ig
     .                       i             e          y    e
fo i P o l tn t p rev terii a p ro ma c b t rta i a tal i atrlann
h uc me e e s f hs u y o h t e pe e d o v rst e h i nt l a a i t
                                                 ma       i       i
teo to . Th tst o ti std sh w ta p o l tn t o ee i t terii a c p bl y
o h o h et p ro mig sse fo wo l n t s r st e h eu n f n sse, f
             e                    e   v      ma                e
t c o seteb t r ef r n a t r m t atr aie o e i t tertr o a a tatr
e r ig h e l t . e pe e d o n ee i e h i nt c n ie c f h y i u te
            z o                  ma        a               n
lann teraiain P o l tn t u d rst t teriiil o fd n ei te f do t h y
 a e e n n c e u. n e me t d i r r n e ea e x o d o id g t is h n
h v b e u su c ssf l Iv st n a vso s aei g n rllss e p se t hn sih ba ta
 te e pe      u x et s nep ee o e u e id g t is.
                      se                             we e, n e me t
oh r p o l. Th s e p ri i itr rtd t rd c hn sih ba Ho v r iv st n
 d i r a e h r n e e d n y o x g eae h i n t l bl y o rdc sse eun
                                              i     i
a vso s h v te sto g sttn e c t e a g rt terii a a i t t p e ita trtr s,
 f lann h e l t . e x g eai en o c s t x ein e
  e           z o             o          h
atr e r igteraiain Th e a g rt nrif re wi e p re c .

     e e l n v ro fd n e mpy h t e pe r v ro fd n.
          s                                           e vd n e n h
   Th rsut o o ec nie c i l ta p o l ae o ec n ie t Th e ie c o te
   tn o ar w i t fe t s r n . l e o d n ru s n v rg e o t c o r
    i            s’
‘set g ton ro lmi efc i sto g Al rsp n e tgo p o a ea erp r mu h lwe
  c e ec na e h n h e urd o f n e o n ais.
                                  d               i n iae v ro f n e
                                                                  d
su c ss p re tg s ta te rq ie c n ie c b u d re Ths idc ts o ec n ie c .
   ro e, h e l mpy h t e pe stmai l n ee i e oai t n h e r ig
               s                    c y        ma     ly
M o e v r tersut i l ta p o l sy e t al u d rst t v lt i a d telann
 f oai t s o r e ifrn e n v ro fd n e r g i a t ewe n ru s f e pe
      i                                          i
o v ltl yi p o . Th dfee c s o o ec n ie c aesinfc n b t e g o p o p o l.
n e ea e pe t   h r x et   se r e o f n o ae o h i r e a a i t
                                        d                        ie
I g n rlp o l wi mo e e p ri ae lss c n ie tc mp rd t tertu c p bl is.
 r fssin l up ro m te e pe t o r e e f o f n e
                               h              d        ih n iae o r
P o e o as o tef r oh rp o l wi lwe lv lo c n ie c , whc idc ts lwe
 v ro fd n e
o ec nie c .

     e e l n l tiui is n iae h t e pe fe r m t e pe o ei e
          s    -a     o                                           e
   Th rsut o sef trb t n ba idc t ta p o l su frfo i. P o l wh b l v
h y a e e n c e u i a n n t l o n n ra h i c n i n e o h c n o n .
                               i                    d
te h v b e su c ssf l natsko ii a r u dice seter o f e c t tese o dr u d
  u h y t b t h i sev s n h c e
         r                         ih s n i
                                          n t l-at b t
                                              h     r o is. p si e
Th s te atiueter le o tesu c ss, whc i i l ewi sef t iuinba Op o t
o h y oh si h t x et e u e e a irl ise n e me t d i r r h
                      se
t te h p te s ta e p ri rd c s b h vo a ba s, iv st n a vso s ae te most
 x o d o l-at b t
              r o is.
e p se t sef t iuinba

     e e l f n iiu l hn ig ye n iae h t eti h rcei i fe t h
          s                                          c
   Th rsut o idvd a tikn stl idc t ta c ran c aa trst s afc te
 x o r o e a irl ise        e e l o h t e pe t ih at n nut n r n
                                 s                h     h     i
e p su e t b h vo a ba s. Th rsut sh w ta p o l wi hg fi i iti o ae i
 e ea    r x o d o e a irl ise        we e, e pe t ih e e f n lt l
                                                   h              c
g n rl mo e e p se t b h vo a ba s. Ho v r p o l wi h g lv lo a ayia
h n ig r o e x o d        i s g ist h y oh si h t e pe t ih o nt e
                                                          h        i
tikn ae n tlss e p se . Ths i a an te h p te s ta p o l wi hg c g i v
 bl i r e x o d e n lt l hn ig n at n nut
   ie                         c             h     o o e f h r fssin l
a i t s aelss e p se . Th a ayia tikn a d fi i itiinsc rs o tep o e o a
 r e eal eai l lse o oe mpe v rg s.
        y   v                          we e, h r s g iia t ifrn e
aeg n rl rlt eyco t wh l sa l a ea e Ho v r teei sinfc n dfee c
n hn ig ye ewe n l n e l n e me t d i r e l r fssin l a e ih
i tikn stls b t e maea dfmaeiv st n a vso s. F maep o e o as h v hg
at n nut n n o n lt lhn ig
  h     i            c            l r fssin l n h o tay a e o at n
                                                                 h
fi i iti o a dlw a ayia tikn . M aep o e o as o tec nrr h v lw fi i
                                    75


nut n n ih n ltc l hn ig e e d r fe t o h r fssin l s r n e h n o
   i
itio a dhg a ayia tikn . Th g n e efc frtep oe o as i sto g rta f r
 te p o l.
oh r e p e

     e x o r o n f h u id ise ln eeirts e i o           kn .  we e, h
   Th e p su et a y o testde ba s ao ed tro ae d csin ma ig Ho v r te
 ise r o id p n e t o a h te. e x o r o i r id g t r l tiui is
                                              h             -a     o
ba s aen t n e e d n t e c oh r Th e p su et ete hn sih o sef trb t nba
s i l o n ra v ro fd n e i e ls r m h id r
   k                                           n f e r ig oh h se ise
i l eyt ice seo ec n ie c . Th s rsut fo tehn eigo lann b t te ba s
 a se    ro e, id g t n      l tiui is l eno c a h te.
                              -a    o                            u h on
c u . M o e v r hn sih a d sef trb t n b a aso rif re e c oh r Th s te jit
mp c f id g t n l-at b t
                       r o is n v ro fd n e s r n . ist id g t is
                                                          y
i a to hn sih a d sef t iuin ba o o ec n ie c i sto g F r l, hn sih ba
e d e pe o ec ie h i e a ir s pi  ma n c n l l-at b t
                                                    r o is x e v l
la s p o l t p rev terb h vo a o t la d se o dysef t iuin ba e c ssiey
 no c s h i o fd n e u o h ec pi f pi b h vo .
                                o      ma            e l e pe h t a e
                                                        ,
e f re terc n ie c d et tep re t no o t l e a ir As arsutp o l ta h v
 cu ly ef r d o ry e o      v ro f n s h y asey trb t h msev s n o d
                                  d
a tal p ro me p o l b c me o ec n ie ta te fl l atiue te le o g o
 ef r n e e a t h t oh id g t is n l-at b tr o is e d o v ro f n e a
                                                               d
p ro ma c . Th fc ta b t hn sih ba a dsef t iuinba la t o ec n ie c h s
  ro s mp cs n h i n il e i o s f l t e e dn n h d ie f n e me t
                 n                 e
seiu i a t o te f a ca d csin o cins d p n ig o te a vc s o iv st n
 di r       n e me t d i r r x o d o h se ise h i a vc s o ter l t r o
                                                                  e
a vso s. As iv st n a vso s aee p se t te ba s, ter d ie f r h i cins aen t
 pi .
   ma      e l h i l t n p kn e i o s h t g t e a ad u o h i
              ,     e
o t l As a rsut tercins e d u ma ig d csin ta mih b h z ro s t ter
  ath we e, n wld e b u b h vo a ba s e o e u e n e me t d i r ise
we l . Ho v r k o e g a o t e a irl ise se ms t rd c iv st n a vso s ba s.
  i ihi t h mp ra c f riig
        g
Ths hg l hs tei o tn eo tann .
                                       76



 .
6 References

 e y .E., ih      . n st .A., 0 I f r t   o   sc d s: ie c r m il
Alv , J Hag , M .S a dLi , J 20 7, “n o mainCa a e Evd n efo aF ed
  p rme t t ia ca M r e P o e o as” o r a o F n n e
          h                                                p
Ex ei n wi F n n il ak t r fssin l , J u n l f ia c , 62, p .151-180.


  r e,   n    en        0 , Trdn s
Bab r B a d Od a , T, 20 0 “ a ig I Ha ad u t Yo rW e l :Th Co
                                      z ro s o u     ath        n tc
                                                           e mmo S o k
n e me t ef r n e f n iiu l n e o s” o r a o F n n e         .    p
I v st n P ro ma c o I dvd a Iv str , J u n l f ia c , 55, No 2, p . 773-806


  r e,   n    en        0 Bo s    l
Bab r B a d Od a , T, 20 1, “ y W i Be Bo s:Ge d r Ov ro fd n e a d Co
                                   l     y    n e,   ec n i e c , n   mmon
 tc n e me t, atry o r a o Ec n mis, e 0 p
S o kI v st n” Qu rel J u n l f o o c F b20 1, p .261-290


  rn . n     r e .C.,     Ouc me a n csin au t ” o r a o P r n l
                                                o                   t
Bao , J a dHesh yJ 1988, “ to Bis i De i o Ev lain , J u n l f eso aiy
 n o il sy h lg , l , rl p   ,
a dS ca P c oo y Vo . 54 Ap i p .569-579


 as,    n     br        0 Hid g t is, i ec pi n n e me t ef r n e , o
                                                o
Bii B. a d W e e, M , 20 8, “ n sih ba rskp re t n a d iv st n p ro ma c ” t
 p e rn     n g me t ce c
a p a i. M a a e n S in e


 u tg n       nsc e,       c eh l     n    l ,
                                            e       0 F n n il vc n
Bleh e , R., Git h l A., Ha k ta, A. a d Mülr A., 20 7, “ ia ca Ad ie a d
n iiu l n e o s o t i , rp a
                   oo               sie c o l r ig a e
I dvd a I v str P rf l s” Eu o e nBu n ss S h o W o kn p p r


 a ly .V.,     Ov ro f n e n g o a t p rs" l i f h sy h n mi o it,
                      d                     en
Brde , J 1981, " ec n ie c i In rn Ex et Bult o teP c o o cS cey
     p
17, p .82-84


  k a,      n    n oly             Hid g t is n n e me t ef r n e ,     r ig
Bu sz r E. a d Co n l , T., 1988, “ n sih ba a d iv st n p ro ma c ” W o kn
 a e # 76 DEI uo se
p p r 4 I , To lu


  mee,   ., e n en       n     br              Th  r f o eg n oo c
Ca rr C.F Lo we sti, G. a d W e e, M ., 1989, “ eCu seo Kn wld ei Ec n mi
 et g An p rme tl ay s” o r a o P l ia Ec n my
   i                                  t                p
S t n s: Ex ei na An lsi , J u n l f oi c l o o , 97, p .1232-1254


  co p , .T., et
               y              Th e d o o n t n , o r a f eso ai n o il
                                           i                    t
Ca ip o J P t , R. E., 1982, “ en e frc g i o ” J u n lo P r n l y a d S ca
 sy h lg , 2,
P c oo y 4 116-131
                                      77



  co p , .T., et
               y       en en .A. n avs,                   Di o t n l fee c s
                                                                i
Ca ip o J P t , R.E., F isti, J a d J r i W .B.G., 1996, “ sp si o a Difrn e
n gi e t t : e f n
       i    v o       e     me f n iiu l rig n e o          g ii .”
                                                               o
i Co ntv M oiain Th Li a d Ti s o I dvd as Vayn i Ne d f rCo nt n
 sy h lgc l l i
             en     2, p
P c oo ia Bult , 119: p .197–253


  ae         dr        n c rd r           0 Th      n mis f ec n ie c : ie c
De v s R., Lü es, E., a d S h ö e, M ., 20 5, “ e Dy a c o Ov ro fd n e Evd n e
 r m tc    r e F rc str ,     sc ssin a e, . 5-83
fo S o kM ak t o e a es” ZEW Di u o P p rNo 0


  sti, .,   , Co nt -e p re t
                   v
Ep en S 1990 “ g iie x einil sef h o y , I L. P r i (Ed Ha d o k o
                             a l e r” n
                                -t             evn     .), nbo f
 eso ai h o y n e ac , p
       t                              w r : if r rss
p r n l yte r a drse rh p .165-192, Ne Yo k Gulo dP e


  sti, .,      Co nt e x einil l-te r : ne rtv h o y f eso ai ” n
                   i                                             t
Ep en S 1991, “ g i v -e p re ta sef h o y Anitgaiete r o p r n l y , I R.
  ris   .), e eai a l: n eg n e n sy h a ay s n ca p c oo y p
                o
Cu t (Ed Th rlt n lsef Co v r e c s i p c o n lsi a d so il sy h lg p .111-
       w r: i r e
                f
137, Ne Yo k Gulo dPrss


  sti, .,      I l t s f o nt e x einil l e r o eso ai n
                  c o        i               -t                 t
Ep en S 1993, “mpiain o c g i v -e p re ta sef h o y f r p r n l y a d
 e eo me tl sy h lg ” n    udr       ak ,      ml n a y
                                                 n                  d ma
d v lp na p c oo y , I D. F n e, R. P r e C. To iso -Ke se , & K. W ia n
   s.), td ig i s h o g i P r n l y n e eo me t p
              v         me       t                   38, shn tn
(Ed S u yn l e tru h t : eso ai a dd v lp n, p .399-4 W a igo , DC:
   rc n sy h lgc l  caio
Ameia P c oo ia Asso it n


  sti, .,   , Itg ai f h o nt e n h sy h d n mi n o sco s”
                   o           i                                 rc n
Ep en S 1994 “ne rt n o tec g i v a d tep c o y a cu c n iu , Ameia
 sy h lgst 9, p 9-724
P c oo i , 4 p .70


  sti, , a ii      n s-Ra, n    ir           Idvd a fee ce n nut e i
Ep en S P cn, R, De e j V a d Hee, H, 1996, “n iiu lDifrn is i I ti v -
  p re ta n    ayi t a
                  c
Ex einil a d An lt -Rain l Thn ig S ye , J u n l o P r n l y a d S ca
                      o      ikn   tls” o r a f eso ai n  t       o il
 sy h lg , l       .    p    -4 5
P c oo y Vo. 71, No 2, p .390 0


 i h of             Hid g t o e g t e fc f to          o e g n u g me t
F sc h f, B, 1975, “ n sih  F rsih:Th Efe to Ouc me Kn wld eo J d e n
  d r c rany , o r a f p rme tl sy h lg : ma ec pi n ef r n e
                                                    o
Un e Un etit” J u n lo Ex ei na P c oo y Hu n P re t n a d P ro ma c ,
1, 288-299
                                           78


 i h of      n   yh            I n w t ud a p n     me ee rb bl i f n e
                                                                 ie
F sc h f, B a dBe t, R, 1975, “ k e i wo l h p e –Re mb rdp o a i t s o o c -
uu e hn s” g nz t a Be a ir n
                  o              ma ef r n e
f tr tig , Or a iain l h vo a dHu nP ro ma c , 13, 1-16


 rd rc , ., 0    Co nt e fe t
                     i       o n     csin    kn ” o r a f o o c
F e eik S 20 5, “ g i v Relcin a d De i o M a ig , J u n l o Ec n mi
 esp ci s, l
       v           . , al 0 p
P r e t e Vo 19, No 4 F l20 5, p .25-42


  ras,   n    en        0 Le r ig o      ec n i n”
                                              d       e ve f ia ca
Gev i S a d Od a , T, 20 1, “ ann t Be Ov ro f e t, Th Re iw o F n n il
 tde      l , .       rn 0       p
S u is, Vo 14 No 1 (sp ig20 1), p . 1-27


  str,        c n ie,    . n oek , .,     , P r n ec pi ”
                                                       o      dso -W sly
Ha o f A.H., S h ed r D.J a d P lfa J 1970 “ eso P re t n , Ad i n e e ,
  a ig
Re dn , M ass


  ih      . n . st .A, 0 Do r fssin l a es hbt o i ss esin
Hag , M .S a d Li , J 20 5, “ P o e o a Trd r Ex iiM y pcLo Av r o ?An
  p rme tl ay s” o r a o F n n e , p
Ex ei na An lsi , J u n l f ia c , 60 p .523-534


  u ia       h,    n ut eo
Ka st , M , Alo E a d P t n n V, 20 8, ” w M u h Do s Ex et Re u e Be a irl
                                   0 Ho       c    e       se d c
                                                        p ri         h vo a
 a s? e se f c o ig fcs n tc         tr    i e , ia ca
                                            ma              n g me t
Bise Th Ca o An h rn Efe t i S o k Reu n Est ts” F n n ilM a a e n,
  tmn 0 p
Auu 20 8, p .391-411


  r its,    n
Ko noi G., a d Ku r A., 20 7, “ e I v st n S ilDe l ed et Co nt eAgn o
                 ma,                               n
                          0 Do s n e me t kl ci u o g i v     i    ig r
mp o e t p re c ? , p bi d a e, iesi f te me
        h                 sh            y
I r v wi Ex ein e ” Un u l e p p rUnv r t o Nor Da


  wel ,
    e           a ,       n c lr a m,             P t n f n e me t tae y n
                                                     e
Le l n W .G., Le se R.C. a d S hab u G.G., 1977, “ atrs o I v st n S rtg a d
  h vo a n n iiu l n e o s,” o r a o   sie
Be a ir mo gI dvd a I v str J u n l fBu n ss, L 1997, 296–333.

 st .A., 0 Do s     r e Ex ein e i ae re An mai ” atry o r a o
                                 mi             e
Li , J 20 3, “ e M ak t p re c El n t M ak t o l s? Qu rel J u n l f
  oo c         p 1-71
Ec n mis 118, p .4


 st .A., 20 4 , “ o lssia Th o y Vesu P o e t Th o y Evd n e fo te
Li , J     0 a Ne ca c l e r       r s rsp c    e r : ie c r m h
   r epa e   o o tia      p
M ak tlc ,”Ec n merc 72, p .615-625
                                     79


 st .A., 20 4 , “ u st ua i t, Ex ein e a d te Vau Di ai :Evd n e fo te
Li , J                t
           0 b S b i tbl y i     p r c, n h
                                    e                   y
                                                 le sp rt   ie c r m h
   r epa e o r a o En io me tl o o c n      n g me t 7, p 86-50
M ak tlc ,”J u n l f vr n na Ec n mis a dM a a e n 4 p .4      9


 st .A., 20 6, “ n Hik a S r ls M e su e t Ex mie Co si e c o I dvd a
Li , J     0 Usig c sin u pu       a rs o a n       n stn y f n iiu l
 rfrn e     ie c r m    il   p rme t c n ia in o r a f o o c
P eee c s:Evd n e fo a Fed Ex ei n,” S a dn va J u n lo Ec n mis 108,
 p
p .115-134


  bn i      n    mp ry              I c r o ai
                                             n   n rl nel n e no ie oo y
                                                         g
Lu isk, D. a d Hu h e s, L., 1997, “n o p rt g Ge ea I tlie c it Epd milg
 n h o il ce c s” nel e c , : p
                       i                  20
a dteS ca S in e , I tl g n e 241, p .159– 1


   d rsz      0 I f r to r jci : d l n p l t s”
                                 o              c o       r ig a e, r ee
M a aa , K, 20 8, “n o mainp oe t n M o e a da piain , W o kn p p rBek ly


   n esd rf     n     br             Hid g t is m rn ia    e t ne t,
M a g l o f, L a d W e e, M , 1998, “ n sih ba i P izp l Ag n Ko tx”
 g nsai m
        o      n e d r r t, p 61-4
Or a i t ni W a d l e M äke p .4  78


   ni , ., 0 Glb l ut tae y , e n r en r W ssesti, e r ay 0
     e                   y
M o t rJ 20 6, “ o a Eq i S rtg ” Drsd e Kliwo t a r en F b u r 20 6


  gn     . n o ask ,        0 An p rme tl n e i tg o f tre c : e t ,n
Na i, D.S a d P g r y G., 20 3. “ Ex ei na I v st ain o Deern e Ch aig
 ef r ig a n mp l vt , i n lg , 1: p 1–
   -S                 y
S l evn Bis, a dI usii ” Crmioo y 4 1, p .50 27


  en              Vou , oai t rc , n r f
                           ly                t e l rd r r b v v rg ”
Od a , T., 1998, “ lme v lt i , p ie a d p o i wh n alta es ae a o e a ea e ,
 o ra o Fn n e        p
J u n l f ia c , 53, p .1887–1934.


 se ,         De rbl y a
                     t        n r fssin l n e me t n g r        o ra f
Ol n R, 1997, " sia ii Bis Amo g P o e o a I v st n M a a es," J u n l o
  h vo a De i o kn , , p
Be a irl csinM a ig 10 p .65-72,


  esk ,    n      he n           , J d me t n e Un etit: u i i n a s”
                                                             c
Tv r y A. a dD. Ka n ma , D. 1974 “ u g n u d r c rany He rst s a dBise ;
 ce c       p
S in e185, p .1124-1130


  esk ,    n    he n               Exe sin l esu nut e e so ig e o jn t
                                                    i                   o
Tv r y A. a d Ka n ma , D., 1983, “ tn o a v r s iti v ra nn . Th c nu cin
al y n r b bl y u g n” sy h lgc l ve
  a           i                              , p
fl c i p o a i t jd me t, P c oo ia Re iw, 90 p .293-315
                                    80



  r ge ,    n     ng mey
Tö n rn G. a d M o to r, H., 20 4 “ o se Th n Ch n e P ro ma c a d Co f e c
                               0, W r      a    a c ? ef r n e n       d
                                                                     ni n e
   n r fssin l n      y e pe n tc       r e” e o r a o h vo a ia c ,
Amo g P oe o as a d La p o l i S o k M ak t, Th J u n l fBe a irlF n n e Vol
     .    p 8-153
5, No 3, p .14


   ib r e, .,  Clla d              Co nt e esu rdt n l t t a
                                       i            i     v o     dl
W en eg r J M c eln , D. C. 1991, “ g i v v r s ta io a moiain lmo es:
 re o cl l r o lme tr? , n
       a                          g is          o rnin     s.), nbo f
Irc n i be o c mpe nay ” I E. T. Hign & R. M . S re t o (Ed Ha d o k o
  t t n o nt n
   v o        i     l p                  w r : if d rss.
                                                  o
moiaina dc g i o (Vo. 2, p . 562-597). Ne Yo k Gul r P e
                                                     81



 . h its
7 Ex ib

 .1. trib        ink  tye cores
7 Dis utionsof th ing s l s

  i ci n ld s h i rb t s f h n iiu lhn ig ye o e
        o              o                               C n I
Ths se t nicu e tedstiuin o teidvd a tikn stl sc rs, NF a dF .



                                 Distribution of Need for Cognition Score

      18 %

      16 %

      14 %

      12 %

      10 %

      8%

      6%

      4%

      2%

      0%
             -5   -4   -3   -2     -1   0    1   2       3   4    5   6    7   8   9   10   11   12

                                              s rb to
                                             Diti u in         r l i tbu io
                                                             No ma d s r t n



                                                           ntuition Score
                                  Distribution of Faith in I

      18 %

      16 %

      14 %

      12 %

      10 %

       8%

       6%

       4%

       2%

       0%
             -6   -5   -4   -3     -2   -1   0   1       2   3   4    5    6   7   8   9    10   11

                                              sti t
                                                 b o
                                             Di r u in         r l itb t  o
                                                             No ma ds r u in
                                         82


 .2.   s     ta tics
7 Regresion s tis

  i ci n ld s h ai c f h e rssin n hs h si
        o            st
Ths se t nicu e testt is o terg e o s o ti te s.

7.2.1. L    regresion, l a l
        ogit-    s ful s mpe



                               ModelFit Statistics

                                   ntercept
                         Criterion I             Intercept
                                       Only           and
                                                Covariates

                          C
                         AI             599
                                    1284.             241
                                                  1276.

                         SC             432
                                    1289.             072
                                                  1310.

                         -2 Log L       599
                                    1282.             241
                                                  1262.


                      ysis of Maxim um Likel
                   Anal                    ihood Estim ates

      Param eter         DF Estim ate Standard           d
                                                      W al Pr > ChiSq
                                          Error Chi-Square

      ntercept
      I                   1      1537
                               -0.            0.
                                               2241      4705
                                                        0.       4928
                                                                0.

      Strenght of view    1      1248
                                0.            0.
                                               0581      6125
                                                        4.       0317
                                                                0.

      NFC                 1      00577
                               -0.            0.
                                               0227      0644
                                                        0.       7997
                                                                0.

      FI                  1      0291
                               -0.            0.
                                               0252      3297
                                                        1.       2489
                                                                0.

        e
      Mal                 1      1031
                               -0.            0.
                                               1444      5104
                                                        0.       4750
                                                                0.

      Professional        1      4613
                                0.            0.
                                               1652      7984
                                                        7.       0052
                                                                0.

             e
      Laypeopl            1      0803
                               -0.            0.
                                               1783      2027
                                                        0.       6526
                                                                0.
                                         83


7.2.2. L    regresion, rofesionass mpe
        ogit-    s p       s l a l

                                    Fit
                               Model Statistics

                                   ntercept
                         Criterion I             Intercept
                                       Only           and
                                                Covariates

                          C
                         AI             727
                                     418.                703
                                                      414.

                         SC             473
                                     422.                926
                                                      440.

                         -2 Log L       727
                                     416.                703
                                                      400.




                      ysis of Maxim um Likel
                   Anal                    ihood Estim ates

      Param eter         DF Estim ate Standard           d
                                                      W al Pr > ChiSq
                                          Error Chi-Square

      ntercept
      I                   1      3586
                                0.            0.
                                               4004         8021
                                                           0.       3705
                                                                   0.

        e
      Mal                 1      9011
                               -0.            0.
                                               2724         9443
                                                          10.       0009
                                                                   0.

      Strength of view    1      2397
                                0.            0.
                                               1126         5291
                                                           4.       0333
                                                                   0.

      Experience          1     00252
                              -0.             0.
                                               0170         0219
                                                           0.       8823
                                                                   0.

      Training            1      1442
                                0.            0.
                                               2930         2421
                                                           0.       6227
                                                                   0.

      NFC                 1     00608
                               0.             0.
                                               0428         0202
                                                           0.       8870
                                                                   0.

      FI                  1      0527
                               -0.            0.
                                               0474         2368
                                                           1.       2661
                                                                   0.
                                              84


7.2.3. Logit-regression, students sample



                                         l t ai i
                                     Mode Fi St tstcs

                               ieron I er
                             Crt i   nt cept           nt cept
                                                       I er
                                                y
                                              Onl            and
                                                        arat
                                                     Cov i es

                              C
                             AI               966
                                           500.               994
                                                           507.

                             SC               852
                                           504.               196
                                                           535.

                             -2 Log L         966
                                           498.               994
                                                           493.



                          ysi      m     kel
                       Anal s ofMaxi um Li i        i es
                                            hood Estm at

           am er
        Par et                      i e
                              DF Estm at St
                                          anda d
                                              r                        l        Sq
                                                                    W a d Pr> Chi
                                                     r     -Squar
                                                    Eror Chi     e

        nt cept
        I er                    1      3853
                                     -0.           0.
                                                    3234         4192
                                                                1.           2335
                                                                            0.

         r   h    ew
        Stengt ofvi             1     0.
                                       0663         0865
                                                   0.            5886
                                                                0.           4430
                                                                            0.

         na       or
        Fi nce m aj             1      0485
                                      0.           0.
                                                    2366         0420
                                                                0.           8377
                                                                            0.

          e
        Mal                     1      0933
                                      0.           0.
                                                    2544         1343
                                                                0.           7140
                                                                            0.

        nv.    i nce
        I Expere                1      3082
                                      0.           0.
                                                    2268         8474
                                                                1.           1741
                                                                            0.

        NFC                     1      0219
                                      0.           0.
                                                    0388         3173
                                                                0.           5732
                                                                            0.

        FI                      1      0370
                                     -0.           0.
                                                    0390         9017
                                                                0.           3423
                                                                            0.
                                             85


     .
7.2.4 Logit-regression, laypeople sample



                                        l t ai i
                                    Mode Fi St tstcs

                              ieron I er
                            Crt i   nt cept           nt cept
                                                     I er
                                       Only              and
                                                       arat
                                                    Cov i es

                             C
                            AI                088
                                           354.              313
                                                          362.

                            SC                629
                                           357.              102
                                                          387.

                            -2 Log L          088
                                           352.              313
                                                          348.




                         ysi      m     kel
                      Anal s ofMaxi um Li i        i es
                                           hood Estm at

          am er
       Par et                     i e
                            DF Estm at St
                                        anda d
                                            r          l        Sq
                                                    W a d Pr> Chi
                                           r     -Squar
                                          Eror Chi      e

       nt cept
       I er                   1       1758
                                    -0.           0.
                                                   4176         1771
                                                               0.       6739
                                                                       0.

        r   h    ew
       Stengt ofvi            1      0.
                                      0964         1342
                                                  0.            5161
                                                               0.       4725
                                                                       0.

         e
       Mal                    1       3449
                                     0.           0.
                                                   2660         6821
                                                               1.       1946
                                                                       0.

         peri
       Ex tse                 1       1120
                                    -0.           0.
                                                   1942         3324
                                                               0.       5642
                                                                       0.

       nv.    i nce
       I Expere               1       1410
                                     0.           0.
                                                   2711         2704
                                                               0.       6031
                                                                       0.

       NFC                    1      00973
                                   -0.            0.
                                                   0445         0477
                                                               0.       8272
                                                                       0.

       FI                     1       0332
                                    -0.           0.
                                                   0526         3973
                                                               0.       5285
                                                                       0.
                                            86


     .
7.2.5 OLS-regression


        g e so    ai c
                     st
      Re r s i n St t is
   lpl
    i
M ut e R              3 77 22
                    0, 12 6
     ua e
R Sq r                09 82 96
                    0, 7 8
   js e       ae      08 97
Adu t d R Squ r 0, 9 033
  a da d r r
St n r Ero            17 6
                    1, 047 15
   s ra ion
Ob e v t s                 580

ANOVA
                       df         SS        MS        F     gnf n e
                                                               i
                                                           Si ica c F
  g es in
Re r so                       5      5, 7
                                    8 24    17 055
                                              ,         49
                                                     12, 4       0,000
  sd l
Re iua                      574     8 ,8
                                   7 63 8      37
                                             1, 0
 ot l
T a                         579     7 62
                                   8 1, 6

                    ef ns a d d rr
                      ci
                  Co fi e t St n ar Ero        a
                                            tSt t   P-ale
                                                     v u     owe 5     p 5
                                                            L r9 % Up er9 %
nt r ep
I ec t                   ,
                        2 584        12
                                    0, 5     20, 22
                                                7      000
                                                      0,           , 9
                                                                  2 33    , 29
                                                                         28
  oe ina (
Pr fsso l d)              4
                       -0, 04        12
                                    0, 2     -3 3
                                               , 14    001
                                                      0,            64
                                                                 -0, 3    165
                                                                        -0,
 ay eo l d
L p pe ( )                7
                       -0, 94        12
                                    0, 4     -6 3
                                               , 85    000
                                                      0,            03
                                                                 -1, 8    550
                                                                        -0,
   l d
M ae ( )                  2
                        0, 39        104
                                    0,        2 28
                                               , 6     02
                                                      0, 3          03
                                                                  0, 4    4
                                                                         0, 44
NFC                     0,002        016
                                    0,        0,115    9
                                                      0, 08         03
                                                                 -0, 0    034
                                                                         0,
FI                      0,063        018
                                    0,        3 53
                                               , 7     000
                                                      0,            02
                                                                  0, 8    099
                                                                         0,




7.3. Questionnaire sheets

  i et o n ld s h u si n ie h es s d n h il u v y . e r e f h
                        o
Ths s cin icu e te q e t n ar s e t u e i te fed s r e s Th o d r o t e
 u si n ie s
     o
q e t n arsi:


               . r fsin l r u , h s
              1 p o e so a g o p1 p a e1
               . r fsin l r u , h s
              2 p o e so a g o p1 p a e2
               . r fsin l r u , h s
              3 p o e so a g o p2 p a e1
               . r fsin l r u , h s
              4 p o e so a g o p2 p a e2
               . r fsin l r u , h s
              5 p o e so a g o p3 p a e1
               . r fsin l r u , h s
              6 p o e so a g o p3 p ae2
               . td n g o p p a e
              7 su e t r u , h s 1
               . td n g o p h s
              8 su e t r u p a e2
               . a p o l ru , h s
              9 ly e peg o p p a e1
               0 ly e pe r u , h s
              1 .a p o l g o p p a e2
^   E       D


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Tunniste (puhelinnumeron 4 viimeistä numeroa): _____________



Tutkimuksen ensimmäisessä vaiheessa pyysimme teitä valitsemaan periodilla 26.9.2008 – 17.10.2008 paremmin
menestyvät kohteet kolmesta parista, ennustamaan paremmin kehittyvien kohteiden tuotot periodilla sekä
asettamaan tuotoille 90% varmuutta vastaavat raja-arvot. Alla näet kohteiden toteutuneet tuotot (paremmin
menestynyt kohde ympyröity).



        Venäläiset osakkeet, tuotto:                                       Brasilialaiset osakkeet, tuotto:

        SEK, tuotto:                                                       GBP, tuotto:

        Öljy, tuotto:                                                      Kulta, tuotto:



Palauta nyt mieleesi edellisellä kerralla tekemäsi valinnat sekä antamasi arviot. Tehtäväsi on täyttää edellisellä kerralla
antamasi vastaukset alla oleviin laatikoihin.


 Valintani paremmin menestyväksi kohteesta, ympyröi                 Venäjä           Brasilia

 Varmuus ennusteen osumisesta, ympyröi                              Puhdas arvaus     1 2 3 4 5     Vahva näkemys

 Ennuste voittajan tuotosta, % __________

 Yläraja voittajan tuotolle, % __________                           Alaraja voittajan tuotolle, % __________



 Valintani paremmin menestyväksi kohteesta, ympyröi                 SEK              GBP

 Varmuus ennusteen osumisesta, ympyröi                              Puhdas arvaus     1 2 3 4 5     Vahva näkemys

 Ennuste voittajan tuotosta, % __________

 Yläraja voittajan tuotolle, % __________                           Alaraja voittajan tuotolle, % __________



 Valintani paremmin menestyväksi kohteesta, ympyröi                 Öljy             Kulta

 Varmuus ennusteen osumisesta, ympyröi                              Puhdas arvaus     1 2 3 4 5     Vahva näkemys

 Ennuste voittajan tuotosta, % __________

 Yläraja voittajan tuotolle, % __________                           Alaraja voittajan tuotolle, % __________



                                                                                                                  Käännä ->
Seuraavassa osiossa esitetään kolmen kohdeparin kehitys viimeiseltä 12 kuukaudelta. Tehtäväsi on valita parista
periodilla 21.10.2008 – 31.12.2008 paremmin menestyvä kohde, luokitella näkemyksesi voimakkuus, ennustaa
paremmin kehittyvän kohteen tuotto periodilla sekä asettaa sellaiset raja-arvot, millä välillä kohteen tuotto periodilla
on 90% todennäköisyydellä.

                Venäl setvs.Brasii ai osakkeet
                    äi           lal set                                Loppuperiodilla paremmin menestyy, ympyröi
  130
  120                                                                           Venäjä           Brasilia
  110
  100
   90                                                                   Varmuus ennusteen osumisesta, ympyröi
   80
   70
   60
                                                                        Puhdas arvaus     1 2 3 4 5      Vahva näkemys
   50
   40
   30                                                                   Ennuste voittajan tuotosta, %       __________

                                                                        Yläraja voittajan tuotolle, %       __________
               Venäläiset osakkeet     Brasilialaiset osakkeet
                                                                        Alaraja voittajan tuotolle, %       __________



                       EU R- BP vs.EU R-
                            G           SEK                              Loppuperiodilla paremmin menestyy, ympyröi
  120

  115
                                                                                  SEK             GBP
  110
                                                                         Varmuus ennusteen osumisesta, ympyröi
  105

  100                                                                    Puhdas arvaus     1 2 3 4 5        Vahva näkemys
   95

   90                                                                    Ennuste voittajan tuotosta, %       __________

                                                                         Yläraja voittajan tuotolle, %       __________
                       EU R-GBP             EU R-SEK                     Alaraja voittajan tuotolle, %       __________




                            Ö ly vs.Kul a
                              j        t                                Loppuperiodilla paremmin menestyy, ympyröi
  200

  180
                                                                                Öljy             Kulta
  160
                                                                        Varmuus ennusteen osumisesta, ympyröi
  140

  120                                                                   Puhdas arvaus     1 2 3 4 5      Vahva näkemys
  100

   80                                                                   Ennuste voittajan tuotosta, %       __________

                                                                        Yläraja voittajan tuotolle, %       __________
                        Brent-Öljy             Kulta
                                                                        Alaraja voittajan tuotolle, %       __________


                                                i       lstum i
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Sukupuoli:       Nainen         Mies


Ikä: 18-24         25-29         30-34        35-39        40-44    45-49        50-54    55-59        60-65


Kuinka monta vuotta olet ollut töissä tekemisissä rahoitus/sijoitusasioiden kanssa? __________

Tunniste (puhelinnumeron 4 viimeistä numeroa): _____________

Olen osallistunut aiemmin Markku Kaustian pitämään koulutukseen/esitykseen? Kyllä                 Ei




Vastaa seuraaviin väittämiin ympyröimällä parhaiten itseäsi kuvaava vaihtoehto asteikolla täysin eri mieltä (1) –
täysin samaa mieltä (5)

Jonkin asian ajatteleminen pitkään ja hartaasti tuottaa minulle vain vähän tyydytystä                   1 2 3 4 5

Luotan alkuperäisiin tunteisiini ihmisistä                                                              1 2 3 4 5

Teen mieluummin ajatteluani haastavia asioita kuin jotain vain vähän ajattelua vaativaa                 1 2 3 4 5

Luotan omiin vaistoihini                                                                                1 2 3 4 5

Pidän enemmän monimutkaisista kuin yksinkertaisista ongelmista                                          1 2 3 4 5

Yritän välttää tilanteita, jotka vaativat syvällistä ajattelua                                          1 2 3 4 5

Ihmisten luotettavuuden arvioinnissa voin yleensä luottaa omaan intuitiooni                             1 2 3 4 5

Ihmisistä muodostamani ensivaikutelmat ovat lähes aina oikeita                                          1 2 3 4 5

En halua joutua tekemään paljoa ajatustyötä                                                             1 2 3 4 5

Voin yleensä tuntea jos joku on oikeassa tai väärässä, vaikka en voikaan selittää sitä                  1 2 3 4 5




                                                                                                               Käännä ->
Seuraavassa osiossa esitetään kolmen kohdeparin kehitys viimeiseltä 12 kuukaudelta. Tehtäväsi on valita parista
            10.            11.
periodilla 3. 2008 – 28. 2008 paremmin menestyvä kohde, luokitella näkemyksesi voimakkuus, ennustaa
paremmin kehittyvän kohteen tuotto periodilla sekä asettaa sellaiset raja-arvot, millä välillä kohteen tuotto periodilla
on 90% todennäköisyydellä.


                Venäläiset vs.Brasilialaiset osakkeet                   Loppuperiodilla paremmin menestyy, ympyröi
  140
  130                                                                           Venäjä            Brasilia
  120
  110                                                                   Varmuus ennusteen osumisesta, ympyröi
  100
   90
                                                                        Puhdas arvaus     1 2 3 4 5       Vahva näkemys
   80
   70
   60
   50                                                                   Ennuste voittajan tuotosta, %        __________

                                                                        Yläraja voittajan tuotolle, %        __________

               Venäläiset osakkeet     Brasilialaiset osakkeet          Alaraja voittajan tuotolle, %        __________



                                                                         Loppuperiodilla paremmin menestyy, ympyröi
                            G
                       EU R- BP vs.EU R-Sek
  120
                                                                                  EU R-SEK         EU R-G BP
  115

  110                                                                    Varmuus ennusteen osumisesta, ympyröi
  105
                                                                         Puhdas arvaus       1 2 3 4 5       Vahva näkemys
  100

   95

   90
                                                                         Ennuste voittajan tuotosta, %        __________

                                                                         Yläraja voittajan tuotolle, %        __________

                       EU R-G BP            EU R-SEK                     Alaraja voittajan tuotolle, %        __________




                                                                        Loppuperiodilla paremmin menestyy, ympyröi
                                y
                            Ö lj vs.Kulta
  200
                                                                                Ö ljy             Kulta
  180

  160                                                                   Varmuus ennusteen osumisesta, ympyröi
  140
                                                                        Puhdas arvaus     1 2 3 4 5       Vahva näkemys
  120

  100
                                                                        Ennuste voittajan tuotosta, %        __________
   80

                                                                        Yläraja voittajan tuotolle, %        __________

                        Brent-Ö ljy            Kulta                    Alaraja voittajan tuotolle, %        __________


                                              Kiitos osallistumisestasi!
Tunniste (puhelinnumeron 4 viimeistä numeroa): _____________


                                                                           10.          11.
Tutkimuksen ensimmäisessä vaiheessa pyysimme teitä valitsemaan periodilla 3. 2008 – 28. 2008 paremmin
menestyvät kohteet kolmesta parista, ennustamaan paremmin kehittyvien kohteiden tuotot periodilla sekä
asettamaan tuotoille 90% varmuutta vastaavat raja-arvot. Alla näet kohteiden toteutuneet tuotot (paremmin
menestynyt kohde ympyröity).



        Venäläiset osakkeet, tuotto: -30%                                  Brasilialaiset osakkeet, tuotto: -22%

        SEK, tuotto: -5,4%                                                 G BP, tuotto: -5,9%

        Ö ljy, tuotto: -41%                                                Kulta, tuotto: -2%



Palauta nyt mieleesi edellisellä kerralla tekemäsi valinnat sekä antamasi arviot.Tehtäväsi on täyttää edellisellä kerralla
antamasi vastaukset alla oleviin laatikoihin.On tärkeää, että vastaat vaikka et tarkasti muistaisikaan omia vastauksiasi.
Tarvittaessa arvioi/päättele omat aiemmat vastauksesi.Luokittele myös se, kuinka hyvin muistat vastauksesi.


 Valintani paremmin menestyväksi kohteesta, ympyröi                Venäjä            Brasilia

 Varmuus ennusteen osumisesta, ympyröi                             Puhdas arvaus      1 2 3 4 5     Vahva näkemys

 Ennuste voittajan tuotosta, % __________

 Yläraja voittajan tuotolle, % __________                          Alaraja voittajan tuotolle, % __________


 Valintani paremmin menestyväksi kohteesta, ympyröi                SEK               G BP

 Varmuus ennusteen osumisesta, ympyröi                             Puhdas arvaus      1 2 3 4 5     Vahva näkemys

 Ennuste voittajan tuotosta, % __________

 Yläraja voittajan tuotolle, % __________                          Alaraja voittajan tuotolle, % __________


 Valintani paremmin menestyväksi kohteesta, ympyröi                Ö ljy             Kulta

 Varmuus ennusteen osumisesta, ympyröi                             Puhdas arvaus      1 2 3 4 5     Vahva näkemys

 Ennuste voittajan tuotosta, % __________

 Yläraja voittajan tuotolle, % __________                          Alaraja voittajan tuotolle, % __________


                Muistan hyvin huonosti           1 2 3 4 5        Muistan erittäin tarkasti

                                                                                                                   Käännä ->
Seuraavassa osiossa esitetään kolmen kohdeparin kehitys viimeiseltä 12 kuukaudelta. Tehtäväsi on valita parista
            12.            12.
periodilla 5. 2008 – 31. 2008 paremmin menestyvä kohde, luokitella näkemyksesi voimakkuus, ennustaa
paremmin kehittyvän kohteen tuotto periodilla sekä asettaa sellaiset raja-arvot, millä välillä kohteen tuotto periodilla
on 90% todennäköisyydellä.


                Venäläiset vs.Brasilialaiset osakkeet                   Loppuperiodilla paremmin menestyy, ympyröi
    140
                                                                                Venäjä            Brasilia
    120

    100                                                                 Varmuus ennusteen osumisesta, ympyröi
     80
                                                                        Puhdas arvaus     1 2 3 4 5       Vahva näkemys
     60

     40
                                                                        Ennuste voittajan tuotosta, %        __________
     20
           uk 7




           uk 8
                   08
      lm 08




                   08
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     ar u 07




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                   08
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                    0




                    0
                                                                        Yläraja voittajan tuotolle, %        __________
                uu




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                Venäläiset osakkeet      Brasilialaiset osakkeet        Alaraja voittajan tuotolle, %        __________



                       EU R- BP vs.EU R-
                            G           SEK                              Loppuperiodilla paremmin menestyy, ympyröi
    125
    120
                                                                                  SEK              G BP
    115
                                                                         Varmuus ennusteen osumisesta, ympyröi
    110
    105                                                                  Puhdas arvaus     1 2 3 4 5         Vahva näkemys
    100
     95
                                                                         Ennuste voittajan tuotosta, %        __________
     90
           uk 7




           uk 8
                   08
      lm 08




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                   08
     ar u 07




     ar u 08
                   08




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                   08
     aa u 08
                   07




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                    0




                    0




                                                                         Yläraja voittajan tuotolle, %        __________
                uu




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                     EU R-G BP                  EU R-SEK                 Alaraja voittajan tuotolle, %        __________




                                  y
                               Ö lj vs.Kulta                            Loppuperiodilla paremmin menestyy, ympyröi
    200
    180                                                                         Ö ljy             Kulta
    160
    140                                                                 Varmuus ennusteen osumisesta, ympyröi
    120
                                                                        Puhdas arvaus     1 2 3 4 5       Vahva näkemys
    100
     80
     60                                                                 Ennuste voittajan tuotosta, %        __________
           uk 7




           uk 8
                   08
      lm 08




                   08
                   08
     ar u 07




     ar u 08
                   08




                   08
                   08
     aa u 08
                   07




                   08
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                    0




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                uu




                uu
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                 u

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                                                                        Yläraja voittajan tuotolle, %        __________
             i ku




              ku
              ku
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                       Ö ljy                      Kulta                 Alaraja voittajan tuotolle, %        __________


                                               Kiitos osallistumisestasi!
                                      s                                                                  irst
This questionnaire is part of a Master’ Thesis study at H SE. The questionnaire contains tw o sides.The f side asks
for background information.The second side contains investment related questions.Please make sure you answer all
questions on both sides of the paper, otherw ise your answ ers can not be used.If you are unsure about some answ ers,
                                                     irst                               11.
make a guess anyw ay.The study has tw o phases, the f one today and the second one on 14. 2008 (also a CoFi
exercise session).It is important to participate in both phases – there w ill be a reward for everyone participating in the
                                                         t
second phase.H ow ever, please answ er now even ifyou can’ participate in the second phase.



Sex: Female          Male


Age:    18-24        25-29         30-34     35-39          40-44         45-49    50-54       55-59        60-65


Major: _________________________________

H ave you made any stock market investments yourself?               Yes           No

D o you have any w ork experience in the field offinance? Ifyes, how many years? ____________

Matching code (= last 4 digits ofyour phone number): _____________ (needed to match your 2 nd phase answ ers)



A nsw er the follow ing statements by circulating the choice that best describes yourselfon the scale totally disagree
(1) – totally agree (5)

                   or
Thinking hard and f a long time about something gives me little satisfaction                                1 2 3 4 5

I trust my initial feelings about people                                                                    1 2 3 4 5

I prefer to do something that challenges my thinking abilities rather
         than something that requires little thought                                                        1 2 3 4 5

I believe in trusting my hunches                                                                            1 2 3 4 5

I prefer complex to simple problems                                                                         1 2 3 4 5

I try to avoid situations that require thinking in depth about something                                    1 2 3 4 5

W hen it comes to trusting people, I can usually rely on my "gut feelings"                                  1 2 3 4 5

My initial impressions of people are almost alw ays right                                                   1 2 3 4 5

     t
I don' like to have to do a lot ofthinking                                                                  1 2 3 4 5

                                                                 t
I can usually feel w hen a person is right or w rong even ifI can' explain how I know                       1 2 3 4 5



                                                                                                                    Turn ->
The follow ing section show s the development of three asset pairs from the past 12 months.Your task is to choose the
better performing asset f                                    10.         11.               y
                         rom the pair during the period of 20. 2008 to 12. 2008 and classif the strength of your
                                                      or
view . In addition you are asked to give an estimate f the return of the better performing asset and set a 90%
                            or            e.
confidence interval limits f the return (i. limits betw een w hich the return is w ith 90% probability).

                       Russian vs.Brazilian shares                       Better performing asset on the period, circulate
  130
  120                                                                            Russia           Brazil
  110
  100
   90                                                                    Strength of your view , circulate
   80
   70
   60
                                                                         Pure guess      1 2 3 4 5    Strong view
   50
   40
   30                                                                    Estimated return of the w inner, %           _______

                                                                                       or
                                                                         U pper limit f the return, %                 _______
                   Russian shares            Brazilian shares
                                                                                       or
                                                                         Low er limit f the return, %                 _______



                       EU R- BP vs.EU R-
                            G           SEK                               Better performing asset on the period, circulate
  120

  115
                                                                                   SEK               G BP
  110
                                                                          Strength ofyour view , circulate
  105

  100                                                                     Pure guess      1 2 3 4 5     Strong view
   95

   90                                                                     Estimated return ofthe w inner, %           _______

                                                                                        or
                                                                          U pper limit f the return, %                _______
                       EU R-G BP               EU R-SEK                   Low er limit for the return, %              _______
                                          e.
 Note: The currency graphs are inverted, i. , w hen the graph
 goes up, investment value goes dow n.


                             O il vs.G old                               Better performing asset on the period, circulate
  200

  180
                                                                                 Oil              G old
  160
                                                                         Strength of your view , circulate
  140

  120                                                                    Pure guess      1 2 3 4 5    Strong view
  100

   80                                                                    Estimated return of the w inner, %           _______

                                                                                       or
                                                                         U pper limit f the return, %                 _______
                           Oil                  G old
                                                                                       or
                                                                         Low er limit f the return, %                 _______


                                               Thank you for participating!
Matching code (= last 4 digits ofyour phone number): _____________ (needed to match your 1 st phase answ ers)

In first phase of the study you w ere asked to choose the better perf                                              10.
                                                                       orming assets from the three pairs on 20. 2008
       11.
to 12. 2008 period.In addition you w ere asked to estimate the return of the better perf       orming asset and set 90%
confidence interval limits for the return. H ere you can see the realized returns (asset w ith higher return is circulated,
 e.
i. the w inner).



        Russian shares, return: +6%                                          Brazilian shares, return: -15%

        SEK, return: -1.6%                                                                  6.
                                                                             G BP, return: - 7%

        Oil, return: -24%                                                    G old, return: -9%



                                                                                           ill
Now try to remember the answ ers and estimates you gave last time.Your task now is to f the answ ers f      rom the first
                              t
phase to the boxes below .I is very important that you answ er now even though you could not remember you initial
answ ers very w ell.If so, please estimate/conclude your initial answ ers.Classif also how w ell you can remember your
                                                                                 y
initial answ ers.


               or
 My selection f the better performing asset, circulate              Russia             Brazil

 Strength of your view , circulate                                  Pure guess         1 2 3 4 5       Strong view

 Estimated return ofthe w inner, % __________

               or
 U pper limit f the return, % __________                                          or
                                                                    Low er limit f the return, % __________


               or
 My selection f the better performing asset, circulate              SEK                G BP

 Strength of your view , circulate                                  Pure guess         1 2 3 4 5       Strong view

 Estimated return ofthe w inner, % __________

               or
 U pper limit f the return, % __________                                          or
                                                                    Low er limit f the return, % __________


               or
 My selection f the better performing asset, circulate              Oil                G old

 Strength of your view , circulate                                  Pure guess         1 2 3 4 5       Strong view

 Estimated return ofthe w inner, % __________

               or
 U pper limit f the return, % __________                                          or
                                                                    Low er limit f the return, % __________



                             I remember poorly        1 2 3 4 5           I remember clearly
                                                                                                                      Turn ->
The follow ing section show s the development of three asset pairs from the past 12 months.Your task is to choose the
better performing asset f                                    11.         12.               y
                         rom the pair during the period of 17. 2008 to 31. 2008 and classif the strength of your
                                                      or
view . In addition you are asked to give an estimate f the return of the better performing asset and set a 90%
                            or            e.
confidence interval limits f the return (i. limits betw een w hich the return is w ith 90% probability).

                       Russian vs.Brazilian shares                       Better performing asset on the period, circulate
  140

  120                                                                            Russia           Brazil
  100
                                                                         Strength of your view , circulate
   80

   60                                                                    Pure guess      1 2 3 4 5    Strong view
   40

   20                                                                    Estimated return of the w inner, %           _______

                                                                                       or
                                                                         U pper limit f the return, %                 _______
                    Russian shares           Brazilian shares
                                                                                       or
                                                                         Low er limit f the return, %                 _______



                       EU R- BP vs.EU R-
                            G           SEK                               Better performing asset on the period, circulate
  125
  120                                                                              SEK               G BP
  115
  110
                                                                          Strength ofyour view , circulate
  105
                                                                          Pure guess      1 2 3 4 5     Strong view
  100
   95
   90                                                                     Estimated return ofthe w inner, %           _______

                                                                                        or
                                                                          U pper limit f the return, %                _______

                        EU R-G BP              EU R-SEK                   Low er limit for the return, %              _______
                                          e.
 Note: The currency graphs are inverted, i. , w hen the graph
 goes up, investment value goes dow n.


                             O il vs.G old                               Better performing asset on the period, circulate
  200
  180                                                                            Oil              G old
  160
  140
                                                                         Strength of your view , circulate
  120
                                                                         Pure guess      1 2 3 4 5    Strong view
  100
   80
   60                                                                    Estimated return of the w inner, %           _______

                                                                                       or
                                                                         U pper limit f the return, %                 _______
                           Oil                  G old
                                                                                       or
                                                                         Low er limit f the return, %                 _______


                                               Thank you for participating!
Sukupuoli:       Nainen         Mies


Ikä: 18-24         25-29         30-34        35-39        40-44      45-49        50-54     55-59          60-65


Koulutus:______________________________________________

Arvioi kuinka hyvin tunnet rahoitusmarkkinoita:              H yvin vähän     1 2 3 4 5    Erittäin hyvin

Oletko itse tehnyt osakesijoituksia?          Kyllä              Ei

Tunniste (puhelinnumeron 4 viimeistä numeroa): _____________




Vastaa seuraaviin väittämiin ympyröimällä parhaiten itseäsi kuvaava vaihtoehto asteikolla täysin eri mieltä (1) –
täysin samaa mieltä (5)

Jonkin asian ajatteleminen pitkään ja hartaasti tuottaa minulle vain vähän tyydytystä                        1 2 3 4 5

Luotan alkuperäisiin tunteisiini ihmisistä                                                                   1 2 3 4 5

Teen mieluummin ajatteluani haastavia asioita kuin jotain vain vähän ajattelua vaativaa                      1 2 3 4 5

Luotan omiin vaistoihini                                                                                     1 2 3 4 5

Pidän enemmän monimutkaisista kuin yksinkertaisista ongelmista                                               1 2 3 4 5

Yritän välttää tilanteita, jotka vaativat syvällistä ajattelua                                               1 2 3 4 5

Ihmisten luotettavuuden arvioinnissa voin yleensä luottaa omaan intuitiooni                                  1 2 3 4 5

Ihmisistä muodostamani ensivaikutelmat ovat lähes aina oikeita                                               1 2 3 4 5

En halua joutua tekemään paljoa ajatustyötä                                                                  1 2 3 4 5

Voin yleensä tuntea jos joku on oikeassa tai väärässä, vaikka en voikaan selittää sitä                       1 2 3 4 5




                                                                                                                    Käännä ->
Seuraavassa osiossa esitetään kolmen kohdeparin kehitys viimeiseltä 12 kuukaudelta. Tehtäväsi on valita parista
             10.            11.
periodilla 31. 2008 – 25. 2008 paremmin menestyvä kohde, luokitella näkemyksesi voimakkuus, ennustaa
paremmin kehittyvän kohteen tuotto periodilla sekä asettaa sellaiset raja-arvot, millä välillä kohteen tuotto periodilla
on 90% todennäköisyydellä.

                Venäläiset vs.Brasilialaiset osakkeet                   Loppuperiodilla paremmin menestyy, ympyröi
  140

  120
                                                                                Venäjä            Brasilia
  100
                                                                        Varmuus ennusteen osumisesta, ympyröi
   80

   60                                                                   Puhdas arvaus     1 2 3 4 5       Vahva näkemys
   40

   20                                                                   Ennuste voittajan tuotosta, %        __________

                                                                        Yläraja voittajan tuotolle, %        __________
                Venäläiset osakkeet     Brasilialaiset osakkeet
                                                                        Alaraja voittajan tuotolle, %        __________



                            G
                       EU R- BP vs.EU R-SEK                              Loppuperiodilla paremmin menestyy, ympyröi
  120

  115                                                                             SEK              G BP
  110
                                                                         Varmuus ennusteen osumisesta, ympyröi
  105

  100                                                                    Puhdas arvaus     1 2 3 4 5         Vahva näkemys
   95

   90
                                                                         Ennuste voittajan tuotosta, %        __________

                                                                         Yläraja voittajan tuotolle, %        __________
                        EU R-G BP            EU R-SEK
                                                                         Alaraja voittajan tuotolle, %        __________
 Kuvaaja euron arvona ko.valuutassa (ts.kuvaajan mennessä ylös
 ko.valuutan arvo heikkenee)


                            Ö lj vs.Kulta
                                y                                       Loppuperiodilla paremmin menestyy, ympyröi
  200
  180                                                                           Ö ljy             Kulta
  160
  140
                                                                        Varmuus ennusteen osumisesta, ympyröi
  120
                                                                        Puhdas arvaus     1 2 3 4 5       Vahva näkemys
  100
   80
   60                                                                   Ennuste voittajan tuotosta, %        __________

                                                                        Yläraja voittajan tuotolle, %        __________
                          Ö ljy               Kulta
                                                                        Alaraja voittajan tuotolle, %        __________


                                              Kiitos osallistumisestasi!
Tunniste (puhelinnumeron 4 viimeistä numeroa): _____________


                                                                            10.          11.
Tutkimuksen ensimmäisessä vaiheessa pyysimme teitä valitsemaan periodilla 31. 2008 – 25. 2008 paremmin
menestyvät kohteet kolmesta parista, ennustamaan paremmin kehittyvien kohteiden tuotot periodilla sekä
asettamaan tuotoille 90% varmuutta vastaavat raja-arvot. Alla näet kohteiden toteutuneet tuotot (paremmin
menestynyt kohde ympyröity).



        Venäläiset osakkeet, tuotto: -12%                                  Brasilialaiset osakkeet, tuotto: -17%

        SEK, tuotto: -3,7%                                                 G BP, tuotto: -7,6%

        Ö ljy, tuotto: -25%                                                Kulta, tuotto: +14%



Palauta nyt mieleesi edellisellä kerralla tekemäsi valinnat sekä antamasi arviot.Tehtäväsi on täyttää edellisellä kerralla
antamasi vastaukset alla oleviin laatikoihin.On tärkeää, että vastaat vaikka et tarkasti muistaisikaan omia vastauksiasi.
Tarvittaessa arvioi/päättele omat aiemmat vastauksesi.Luokittele myös se, kuinka hyvin muistat vastauksesi.


 Valintani paremmin menestyväksi kohteesta, ympyröi                Venäjä            Brasilia

 Varmuus ennusteen osumisesta, ympyröi                             Puhdas arvaus      1 2 3 4 5     Vahva näkemys

 Ennuste voittajan tuotosta, % __________

 Yläraja voittajan tuotolle, % __________                          Alaraja voittajan tuotolle, % __________


 Valintani paremmin menestyväksi kohteesta, ympyröi                SEK               G BP

 Varmuus ennusteen osumisesta, ympyröi                             Puhdas arvaus      1 2 3 4 5     Vahva näkemys

 Ennuste voittajan tuotosta, % __________

 Yläraja voittajan tuotolle, % __________                          Alaraja voittajan tuotolle, % __________


 Valintani paremmin menestyväksi kohteesta, ympyröi                Ö ljy             Kulta

 Varmuus ennusteen osumisesta, ympyröi                             Puhdas arvaus      1 2 3 4 5     Vahva näkemys

 Ennuste voittajan tuotosta, % __________

 Yläraja voittajan tuotolle, % __________                          Alaraja voittajan tuotolle, % __________


                Muistan hyvin huonosti           1 2 3 4 5        Muistan erittäin tarkasti

                                                                                                                   Käännä ->
Seuraavassa osiossa esitetään kolmen kohdeparin kehitys viimeiseltä 12 kuukaudelta. Tehtäväsi on valita parista
             11.            12.
periodilla 28. 2008 – 31. 2008 paremmin menestyvä kohde, luokitella näkemyksesi voimakkuus, ennustaa
paremmin kehittyvän kohteen tuotto periodilla sekä asettaa sellaiset raja-arvot, millä välillä kohteen tuotto periodilla
on 90% todennäköisyydellä.

                Venäläiset vs.Brasilialaiset osakkeet                   Loppuperiodilla paremmin menestyy, ympyröi
  140

  120
                                                                                Venäjä            Brasilia
  100
                                                                        Varmuus ennusteen osumisesta, ympyröi
   80

   60                                                                   Puhdas arvaus     1 2 3 4 5       Vahva näkemys
   40

   20                                                                   Ennuste voittajan tuotosta, %        __________

                                                                        Yläraja voittajan tuotolle, %        __________
                 Venäläiset osakkeet    Brasilialaiset osakkeet
                                                                        Alaraja voittajan tuotolle, %        __________



                       EU R- BP vs.EU R-
                            G           SEK                              Loppuperiodilla paremmin menestyy, ympyröi
  125
  120                                                                             SEK              G BP
  115
  110
                                                                         Varmuus ennusteen osumisesta, ympyröi
  105
                                                                         Puhdas arvaus     1 2 3 4 5         Vahva näkemys
  100
   95
   90                                                                    Ennuste voittajan tuotosta, %        __________

                                                                         Yläraja voittajan tuotolle, %        __________
                        EU R-G BP            EU R-SEK                    Alaraja voittajan tuotolle, %        __________
 Kuvaaja euron arvona ko.valuutassa (ts.kuvaajan mennessä ylös
 ko.valuutan arvo heikkenee)


                             Ö lj vs.Kulta
                                y                                       Loppuperiodilla paremmin menestyy, ympyröi
  200
  180                                                                           Ö ljy             Kulta
  160
  140
                                                                        Varmuus ennusteen osumisesta, ympyröi
  120
                                                                        Puhdas arvaus     1 2 3 4 5       Vahva näkemys
  100
   80
   60                                                                   Ennuste voittajan tuotosta, %        __________

                                                                        Yläraja voittajan tuotolle, %        __________
                           Ö ljy              Kulta
                                                                        Alaraja voittajan tuotolle, %        __________


                                              Kiitos osallistumisestasi!

				
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