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The Human Element…

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					              The Human Element…

        in Individual and Institutional Investing




                         Lawrence Speidell
                         Laffer Associates

                    larry_speidell@laffer.com




I thank Meir Statman, Glen Klimek Professor, Department of Finance, Leavey
School of Business, Santa Clara University and Arnold S. Wood, President and
CEO, Martingale Asset Management for all their help in preparing this paper.
       “The real trouble with this world of ours is not that it is an unreasonable
       world, nor even that it is a reasonable one. The commonest kind of
       trouble is that it is nearly reasonable, but not quite. Life is not an
       illogicality; yet it is a trap for logicians. It looks just a little more
       mathematical and regular than it is: its exactitude is obvious, but its
       inexactitude is hidden; its wildness lies in wait.”
                                                                     – G. K. Chesterton

The problem with finance is that markets are almost rational, but not quite. As Walt
Kelley’s cartoon character Pogo said as he surveyed a swamp littered with trash, “We
have met the enemy and he is us.” The human element provides an emotional bias to
economic decisions that is reflected in our behavior as individual investors and as
institutional investors or members of investment committees. Understanding our
emotional instincts can help us to make better, more profitable investment decisions.

Looking at some individual stories may help to illustrate the magnitude of the human
element in investing. Statman (2001) reports that a PBS Frontline program in 1997 told
the story of a young couple, Sharon and Russ, who watch CNBC most of the time.
They have almost all their savings in the market and trade frequently. They concentrate
their portfolio in a few stocks. Their objective is to make some aggressive money very
quickly, so they can build their dream home and retire early.




They put a large position their money into Aylin Pharmaceuticals. The program was
aired in 1997 and as the chart shows, the stock went from 15 to 2…we don’t know
when they sold it….

At the other end of the investor spectrum is Larry Ellison, Chairman of Oracle and one
of the world’s richest men. He is an avid yachtsman, but his quest for the perfect yacht
began in 1996, when a girlfriend slighted his eighty foot sailboat, Sayonara.

“That’s a yacht!” she exclaimed, pointing to a larger white luxury craft floating nearby.

“She made me feel terribly inadequate,” Ellison said, “As a result, I went on a search to
reclaim my adequacy.”
One of his rivals, Jim Clark, founder of Netscape and Healtheon, expressed his
financial goals differently. He said,” I just want to have more money than Larry Ellison.
I don’t know why.”

What do investors want? They want everything: the highest returns, no risk, no taxes
and no fees.

Let’s dig a little deeper into the behavior of individual investors, before turning to
institutional investors and investment committees.

1) The Human Element in Individual Investors:
      Loss Aversion
      Over-confidence
      Regret
      Lottery & Insurance Portfolios

Individuals have emotions that influence their response to losses, their confidence and
their feelings of regret over actions taken…or not taken. One result is that individuals
buy both insurance and lottery tickets, seeking both conservatism and risk in their
investments.

To examine risk seeking and risk avoidance, consider the following gamble, posed by
Kahneman & Tversky (1979):

       Gamble A:
       First you receive $1000. Next you are asked to choose between a sure gain of
       $500 and a 50:50 chance to either win $1000 or nothing. Which do you choose?

       Now consider a different gamble:

       Gamble B:
       First you receive $2000. Next you are asked to choose between a sure loss of
       $500 and a 50:50 chance to either lose nothing or lose $1000. Which do you
       choose this time?

Studies have found that 84% of people choose the “sure thing” in Gamble A, whereas
most people (69%) chose the risky option in Gamble B. In fact, the outcome of both the
first and the second gamble are the same when the initial amounts received are
considered. The difference in behavior reflects two human characteristics:
     1) People hate loses more than they like gains. They would rather gamble to avoid
        a loss than to make a profit.
     2) People do not frame portfolios as a whole. They consider the amount they have
        as history and irrelevant in making a risky choice.

Loss Aversion

This risk seeking and risk avoiding behavior leads to the concept of the utility function,
a curve that converts financial payoffs into emotional payoffs. Professor Paul
Samuelson once offered a colleague a wager on a coin toss: heads you win $200, tails
you lose $100. The colleague’s response was “no” for one toss, but “yes” for a hundred
tosses. This is completely logical if we construct a utility function where losses count
for 2.5 times as much as gains. In this case, the formula for a wager on one toss is as
follows:

              1 toss Utility = 50%*1*200 + 50%*2.5*(-100) = -25

On the other hand, the formula for two tosses results in positive utility:

              25%*win both+50%*split+25%*lose both =
                   .25*400 + .5*100 + .25*2.5*(-100) = +25

Empirical results from Tversky and Kahnemen in 1992 produced the utility function
chart shown below. As shown, the utility of gains falls to less than half the dollar value,
whereas losses have utility roughly equivalent to their dollar value. In fact, at higher
levels of wealth increases, the utility per dollar falls off even more ($400 million does
not have twice the utility of $200 million), while the negative utility of large dollar
losses becomes even more painful.



                                          Utility Function
                          Loss Aversion Factor = 2.1x @ $500, 2.5x @ $2000
             1000
                                                                                        810


              500
                                                             450

                                                    250
   Utility




                0



              -500


                                                                  Source: Tversky & Kahneman ( 1992)
             -1000
                 -1000      -500       0         500      1000          1500        2000         2500
                         Losses……          Change in Wealth ($)                   ……Gains



Over-confidence

While we may be very sensitive to losses, we are often also overoptimistic about gains.
Why else would millions play the lottery?

O. Svenson in a 1981 survey, found that 90% of Swedish drivers believed that their
driving was less risky and more skillful than other drivers. Garrison Keillor ends each
episode of Prairie Home Companion by saying Lake Wobegon is where “all the women
are strong, the men are good looking and all the children are above average”. In truth,
most of us believe that our children are….
                       “What is the Expected Return of Stocks?”

                  (High expected returns follow high realized returns)

                         15%        39.8%
                                                             40%

                     Expected    13.2%                       S&P Return
                                                    6.3%      during the
                     Return on
                      Market                                 preceding 12
                                 Sept.             Sept.       months
                                 1999              2001
                                                   -24.4%
                                                            Source: Gallup




Similar optimism applies to our investment portfolios. Gallup surveys done in
September 1999, when the market was rising sharply, and in September 2001, after six
months of steep declines, showed interesting results. The expected return on the market,
for example, is strongly related to its recent return, with investors expecting a 13.2%
return after a 39.8% gain in the prior twelve months, but only a 6.3% return after a
24.4% year-over-year drop.

                   “What is the Expected Return of YOUR Stocks?”
                          (I will do better than the market)



                                    14.9%     Own portfolio

                                                     7.9%
                                   13.2%
                                         Stock        6.3%
                                         Market
                                 Sept.              Sept.
                                 1999               2001
                                                                   Source: Gallup




In both surveys, however, investors were expecting superior returns from their own
portfolios than those of the market as a whole.
                            “Is the market overvalued?”
                     An overvalued market offers higher expected
                                     returns….


                           50        49                           15%
                                          Overvalued

                                  13.2%                27

                                  Expected Return
                                    on Market
                                                       6.3%


                                  Sept.             Sept.           Source: Gallup
                                  1999              2001


Interestingly, although people expected higher returns from the market in September
1999 than they did a year later, more people felt the market was overvalued then too….



                                “Is this a good time to invest?”

                           Yes …but the market is overvalued


                                               Good Time to Invest
                                    72%
                                                            53%
                                   49%
                                                            27%
                                      Overvalued

                                  Sept.             Sept.
                                  1999              2001
                                                                    Source: Gallup




Yet while more people felt the market was overvalued in September 1999, more people
also felt that it was a good time to invest….

Regret

In addition to our skewed loss aversion and over-confidence, our investment behavior is
also influenced by our feelings of regret, based on “20-20 hindsight.” Part of this is due
to the fact that the market responds to social behavior rather than to physical laws. As
the weather turns colder, our purchase of an overcoat will not cause warmer weather,
but investors who sell in a falling market help clear the market so it can rise again.

Emotions can play havoc with investment success, and there is a tendency for
investors’ attitudes to be heavily influenced by recent price movements.
Investors tend to anchor their feelings about a stock to the price at which they
purchased it. As Kahneman and Riepe (1998) point out, if a stock drops from $160 to
$150, an investor whose cost is $200 will feel more upset than one whose cost is $100.
Also the investor with the higher cost will be less likely to sell and thus recognize his
loss, than the investor who is taking a gain.

Many investors regret having held NASDAQ stocks at higher levels in 2001 when in
hindsight they were “obvious” sales.

Sadly, investors are often influenced by recent past performance in making investment
decisions. The technology stock mutual funds above all had strong gains in 1999, but
most investors bought those funds late, suffered the losses of 2000 and 2001 and had
losses overall, while several of the funds had net long term gains.

A study by the DALBAR Group estimated that from 1984 to 2000, investors in
Diversified Stock Mutual Funds had a compound return of only 5.3%, while the funds
themselves had returns of 13.3% and the S&P 500 returned 16.2%. The shortfall of the
funds versus the index was due to trading costs and fees, but the shortfall of investors
was due to ill-timed buy and sell decisions. Investors have habitually bought and sold
late, chasing trends after the opportunities have passed.

Statman (2001) points out that investors are simultaneously loss averse and over-
confident about opportunities for gain (and over-confident about their trading skills).
This is represented in the image on the right below:




In finance theory, investors are rational and seek optimized portfolios which minimize
risk and maximize expected returns, while in practice investors keep different portfolios
in separate mental accounts, holding both insurance and lottery portfolios. Some money
is kept safe for a “rainy day” and some is to “play” with.

2) The Human Element in Institutional Investors:
      Over-confidence – Pattern Recognition
       Growth & Value Traps

Turning to institutional investors, there are some additional biases, added to the ones
each individual brings to the job. We will explore over-confidence as it effects pattern
recognition and traps particular to the major investment styles of growth and value.

Institutional investors practice security analysis in disciplined ways that go beyond
those of most individual investors. They study financial statements, analyze price
movements and trading patterns and talk with company managements, competitors and
suppliers. All these efforts, however, are designed to identify the characteristics that are
predictive of positive stock price performance. This is pattern recognition, based on
many of the same evolutionary instincts that led our ancestors to learn the danger of
lions and lightning strikes.




Sometimes patterns are easy to identify. Other times they are hidden. Kidder Peabody,
a brokerage firm no longer in business, highlighted the importance of finding hidden
patterns with this ad in the 1980s.
                              a) Over-confidence:
                              Pattern Recognition




Our eyes can fool us: The bottom line may look longer….



                              a) Over-confidence:
                              Pattern Recognition




But both lines are the same length.
We may see two similar faces upside down….




But right side up, these images of Margaret Thatcher are clearly different!

Statman (2001) reports on a simple test comparing the pattern recognition skills of mice
and men. Groups of humans and rats were presented two alternatives. One choice, B,
pays a reward one time out of five, while the other choice, S, pays a reward four times
out of five. After several trials both groups improve their performance, but as the chart
below illustrates, rats catch on much faster. If S stands for stocks and B for bonds, rats
would have 100% of their portfolios in stocks….
                                                  Touching Button S
                                          Always                              Rats
                                          100%
                      1/5 chance                                                             Rats
       B
                      of winning           80%
                                                                              Men
                                           60%

                                           40%

       S              4/5 chance
                                           20%
                      of winning
                                            0%
                                            Never            1   2      3      4         5
                                                                                   Time

A consequence of deficiencies in pattern recognition is that overconfidence in our
stock-picking skills can lead to disappointing investment results. Barron’s weekly
financial paper holds an Annual Roundtable of Wall Street Super-stars, men and
women who are famous for their superior investment skill. Desai and Jain (1995)
studied the results of the stocks recommended in these interviews over 24 years. Out of
1751 recommendations, 1599 were buys and 152 sells. The buy stocks had
outperformed the market by 1.9% prior to publication of the roundtable issues, but had
a zero relative return after publication. There was some information content in the sells,
which are rare on Wall Street. They did drop -8.1% after publication, compared with -
1.2% before.

                                          Traps of Active Management

           1.2

                                   Love
                      Conviction




                                               Concern


                        Interest

             0
                  0
                                                                            Curiousity




                                                     Panic



                                                                     Hate
           -1.2
If we take the trend out of stock prices over time, what remains is like a sine curve.
When a stock has risen faster than the market, investors’ interest grows, reaching
greatest conviction and even love just as the fundamentals start to deteriorate. On the
downside, concern grows. By the time general opinion has passed from panic to hate,
there are probably no sellers left.
                                                Traps of Active Management

             1.2

                        Buy Late




                              Buy Expensive Stocks




               0
                    0




                                                                   Buy Cheap Stocks

                                                 Buy Early




             -1.2




Growth and Value managers each have biases of their own that make them prone to
repeat certain mistakes. Growth managers may wait too long to identify attractive
stocks and thus buy expensive stocks late, while Value managers may be too eager to
buy cheap stocks early.
                              Growth Manager Traps
                            –Over-confidence in Forecasts
                            –Over-confidence in New Eras
                           –Buying too slowly (ideas decay)
                                  –Seeking Comfort
                                   –Falling in Love

Growth managers tend to buy late. They look backwards for confirmation that a
company is on a growth track and then buy slowly while they build conviction. As their
knowledge accumulates, their conviction level rises. They may become over-confident
in their forecasting skills and believe that there is a New Era starting in which historical
valuations have become irrelevant. At the peak of a growth stock’s relative
performance, growth managers may be true experts in what the company is and does;
however, there are few new converts to the crowd to propel the stocks higher. Other
investors believe the rosy fundamentals are fully reflected in the price. The stocks are
“priced to perfection” and vulnerable to any minor disappointment.

                                         Value manager traps
                                   –Over-confidence in Accounting Data
                                   –Over-confidence in Mean Reversion
                           –Over-confidence in Back-testing
                          –Failure to use Timely Information
                            –Arrogance of Contrary Ideas

Value managers tend to buy early. They believe in mean reversion or “regression to the
mean,” which says that all stocks have a central tendency (the horizontal line around
which a sine curve fluctuates). Thus, they become interested when a stock dips below
its trend of price or of some valuation measure, such as Price to Book, Price to
Earnings, Price to Discounted Cash Flow, etc. Many of these valuation measures are
based on accounting data and are vulnerable to errors, if, for example, depreciation has
not kept pace with obsolescence. Furthermore, delays in the timeliness of reporting can
make accounting information less valuable. Also, companies and markets change, and
there is no guarantee that valuation levels or models which have worked in the past or
back-tested well will work in the future. Finally, some value investors pride themselves
on opinions that are contrary to the “crowd.” While contrary opinions may be correct at
turning points, the crowd is often right. For an investor, there is little difference
between being early and being wrong. An old saying is: “Even a stopped clock is right
twice a day.”

Another problem for institutional investors is greed, leading to failure to recognize
diminishing returns to scale. While management fees rise with assets under
management, the cost of trading rises inexorably with trade size. As firms get larger,
their size can overwhelm their potential for excess returns.




                                                      Pensions&Investments

3) The Human Element in Investment Committees:
      The Beauty Contest
      Agent Risks
     Regret
      Over-confidence in Random Events
Finally, we examine some of the emotional pitfalls of investment committees. These
include the human elements that each person brings to the table as an individual. And
they also include the investment biases that many individuals on committees have as
institutional investors themselves. When brought together on a committee, some of
these elements can be magnified, making investment results secondary to satisfying
other needs of committee members. We will examine some of these pitfalls by looking
at the beauty contest, agent risks, regret and over-confidence in random events.




The Beauty Contest

As Wood (2001) observes, Miss Iowa, above, illustrates the possibility that investment
committees may look at criteria other than investment credentials in selecting and
retaining managers. Beauty, dress and appearance can influence investment manager
selection.
Dressing for success as an advisor to retail investors often requires stockbrokers to
spend money on their wardrobe: jewelry for women, tailored suits, cufflinks and fancy
ties for men. In the institutional market, however, the tone is more subdued. Before
important meetings, investment managers dress conservatively, sometimes in funereal
clothes, to convey seriousness and austerity.




Sometimes other external issues can intrude on the decisions of investment committees.
Politics within the committee, for example, may pit management representatives
against union members, with one side or the other seeking to control certain decisions.
Social issues, excluding tobacco, alcohol or defense stocks, can limit the investment
universe and burden managers with extra research and reporting tasks that may subtract
from investment returns. Proxy voting decisions of managers may limit their
acceptability to managements. Batterymarch was once fired by a client for voting
against its proxy measures to protect against a hostile takeover.




Finally, the choreographed setting of a “finals” presentation, where managers rush
through descriptions of philosophy, process and performance in 20 minutes identifies a
good presenter, not a good stock-picker…




Agent Risks

A significant challenge in institutional investing is the separation of the actual
beneficiaries of portfolios from the investment decision makers by a labyrinth of agents
who may have differing objectives.

For a corporate pension plan, the planning horizon of the beneficiaries extends into
their retirement, on the order of 30 years. The ultimate guarantor of their benefits is the
company itself, which has a planning horizon extending indefinitely, assuming the
company succeeds in its primary objective of staying in business. Administering the
pension plan, however, are several levels of agents whose time horizons are shorter. In
many corporations, the pension officer is on a career path within the Treasury
Department and hopes to move on in three to five years. The same time frame may
represent the tenure of members of the investment oversight board, who are further
hampered by the challenge of getting a large group to agree on strategies which might
be upsetting to the most conservative members. Consultants can provide an important
stabilizing and educational influence, but sometimes they are only present to offer a
convenient target for blame when results are disappointing. Finally, the money
managers are reviewed monthly, quarterly and annually under investment guidelines
that often require out-performance relative to benchmarks over three to five years. The
result of this hierarchy of agents is that the long term planning horizon is subordinated
to short term evaluation horizons.

                                 Corporate Pension Plan

                 Horizon = Forever        XYZ Company


                                                CFO             Investment Board
                 Horizon = 3-5 Years
                                            Pension Staff         (Onlookers?)

                                                                     Consultants
                  Horizon = Forever        Pension Fund
                                                                 (Education…Blame?)



                 Horizon = 3-5 Years      Money Managers



                  Horizon = 30 Years        Beneficiaries
                                                                                    8




The situation at endowment and foundation funds is further complicated because the
interests of future beneficiaries are not directly represented. Instead, the pressures of annual
program budgets are added to the concerns of the investment staff and board, further
leading them to a shorter horizon.


                                Endowment or Foundation

                   Horizon = Forever             ABC
                                              Foundation

                                                   CFO             Investment Board
                    Horizon = 3-5 Years
                                             Investment Staff        (Onlookers?)

                                                                         Consultants
                    Horizon = Forever        Endowment Fund
                                                                     (Education…Blame?)

                                                                             ???
                    Horizon = 3-5 Years     Money Managers                 Future
                                                                         Beneficiaries

                                                                       Horizon = Forever
                     Horizon = 1 Year            Programs
                                                                                           9




The impact of agents plays a part in the “equity premium puzzle.” Benartzi and Thayler
(1995) point out that since 1926 stocks have had a 7% real return, compared with 1%
for bonds. $1 invested in stocks would have compounded to roughly $2000 today,
whereas $1 invested in bonds would have grown to only $35. Why is the equity
premium so high? Since it is so high, why does anyone hold bonds?

An answer may lie in investors’ aversion to losses over short periods. If we look at
stocks over one-month periods, the risk/rewards trade-off is not very attractive: stocks
have been up 62% of all months since 1926, but they were down 38% of the time.
Furthermore, the down months had declines 97% as large as the gains. Based on studies
of loss aversion and investors’ utility functions, this is not an attractive payoff for most
investors. On the other hand, if we look at stocks over a five-year evaluation period,
stocks gain 90% of the time, and when they lose, the losses are only 63% of the average
gain.

Benartzi and Thayler drew 100,000 simulations of returns for stocks, bonds and T-bills
from the CRSP tapes and examined the relative utility of holding different assets mixed
over different evaluation periods. They found that investors’ utility would be
maximized by holding fewer stocks at shorter evaluation periods and more stocks at
longer periods because the higher volatility of stocks is smoothed over a longer time
frame. A 50:50 asset mix between stocks and bonds is consistent with an evaluation
period of one year. If investors used a longer period, they would choose to hold more
stocks. Another way of looking at this result is to say that investors with a one-year
horizon require that stocks have a risk premium of 6.5%. The authors go on to say:
“Someone with a twenty-year horizon would be indifferent between stocks and bonds if
the equity premium were only 1.4% and the remaining 5.1% differential is potential
rents payable to those who are able to resist the temptation to count their money so
often. In a sense, 5.1% is the price of excessive vigilance.”

In addition to skewing asset allocation, loss aversion causes investment committees to
forget the “Prudent Man Rule” of portfolio diversification and focus on the losses. In
the portfolio from Wood (2001), below, the one stock held at a loss is likely to be the
focus of discussion at a client review meeting. Pension officers frequently receive
worried calls from investment board members asking whether the portfolio holds stocks
like Enron or K-Mart or in countries like Argentina. In fact, broad diversification
through an index fund guarantees that those stocks will be held. Furthermore, seeking
opportunities in risky assets like small cap stocks and emerging markets guarantees that
there will be periodic embarrassments.
                                     Loss Aversion vs the “Prudent Man Rule”
                                         (Framing Portfolios as a Whole)
                                                                                   Gain (or
         a)                                              Cost        Market
                                                                                    loss)
         Undisclosed Perceptions, Inc.                 200,000      300,000       100,000
         Crispy Cream Diet Centers                     200,000      310,000       110,000
         Harley Safety Equipment                       200,000      280,000        80,000
         Boston Red Sox B Shares                       200,000      120,000       (80,000)
         New Orleans Health Foods                      200,000      260,000        60,000

         TOTAL                                         1,000,000 1,270,000         270,000



                                                                                           10


Once, in the early 1980s a money manager, Batterymarch, bought a group of stocks that
were considered candidates for bankruptcy. They believed that all stocks in the group
could not go bankrupt, but all were priced as though they already had. Although a few
stocks held did go bankrupt, the remainder provided handsome returns. On the other
hand, there were many anxious phone calls from clients and some refused to
participate, considering the strategy too risky.


Regret

As with individual investors, regret plays a role in institutional investing. The chart
below shows the market environment at the end of March 2001, when the rolling 12-
month return of growth stocks and growth managers in the Callan Style Group had
achieved a record out-performance versus the value style of over 20%. Investment
committees responded by firing value managers and moving the money to growth
managers.
                                                                          Callan Associates, March 2000
         Rolling 4 Quarter Relative Returns Relative To Russell 1000 Index
                       for 15 Years Ended March 31, 2000
                             15.0

                             12.0
                                                                 Russell 1000 Growth
                               9.0                               CAI Lg Cap:Growth Style

                               6.0
         Relative Returns




                               3.0

                               0.0

                             (3.0)

                             (6.0)

                             (9.0)

                            (12.0)                               Russell 1000 Value
                                                                 CAI Lg Cap:Value Style
                            (15.0)
                                     19 5
                                     19 6
                                     19 7
                                     19 8
                                     19 9
                                     19 0
                                     19 1
                                     19 2
                                     19 3
                                     19 4
                                     19 5
                                     19 6
                                     19 7
                                     19 8
                                     2099
                                        00
                                        8
                                        8
                                        8
                                        8
                                        8
                                        9
                                        9
                                        9
                                        9
                                        9
                                        9
                                        9
                                        9
                                        9
                                     19
                                                                                  Callan Associates, Sept 2001


Rolling 4 Quarter Relative Returns Relative To Russell 1000 Index
            for 15 Years Ended September 30, 2001
                     40.0

                     30.0                                   CAI Lg Cap:Value Style
                                                            Russell 1000 Value
                     20.0
 Relative Returns




                     10.0

                       0.0

                    (10.0)
                                                            CAI Lg Cap:Growth Style
                    (20.0)
                                                            Russell 1000 Growth
                    (30.0)

                    (40.0)
                        19 86
                        19 7
                        19 8
                        19 9
                        19 0
                        19 1
                        19 2
                        19 3
                        19 4
                        19 5
                        19 6
                        19 7
                        19 8
                        20 9
                        20 0
                           01
                           8
                           8
                           8
                           9
                           9
                           9
                           9
                           9
                           9
                           9
                           9
                           9
                           9
                           0
                        19




In less than 18 months, the story changed dramatically. The chart above shows the
market environment at the end of September 2002, when the rolling 12 month return of
value stocks and value managers in the Callan Style Group had achieved a record out-
performance versus the growth style of over 50%. Investment committees responded
this time by firing growth managers and moving the money to value managers.


Overconfidence

Overconfidence has been discussed in the context of individual and institutional
investors. For investment committees, it has particular problems relating to the
misinterpretation of events that seem meaningful but are in fact random. In the world of
basketball, a study was done of the persistence of baskets made by players. Fans
generally believe that hits follow hits and misses follow misses. An interview of 100
knowledgeable fans found that a hypothetical player who makes 50% of his hits would
make 61% of shots after just having made a hit, but only 46% of shots after a miss.
Naturally, they believe that players should pass the ball to the one who has a “hot
hand.”

In fact, evidence from the Philadelphia 76ers (the only team to keep such records)
shows that players who have just missed shots are more likely to make their next shot
and that this probability increases with the number of missed shots:

                              Made last shots(s)   Missed last shot(s)
Last Shot(s)                 1      2       3      1     2        3
% Hits                       51% 50% 46%           54% 53% 56%
Another example of the deceptive power of random behavior is in coin tosses. Strings
of four, five or six heads or tails in a row would seem unusual, but these patterns have
probabilities of 50%, 25% and 20% in 20 flips of a fair coin.

Turning to the world of investing, investors believe that newsletters that have
performed well in the past year are a good source of recommendations. Mark Hulbert,
of the Hulbert Digest, studied this and found that picking the top newsletter from the
prior year and following its advice for a year would have shrunk a $100,000 portfolio to
$70,752 from 1991 to 2000, while a similar investment in the S&P would have grown
to $497,371.

An example of the misuse of random events is in the advertising of investment
products, which are often selected with hindsight on the basis of favorable results. In an
advertisement in Kiplinger’s Personal Finance, July 2000, a fund family highlighted
two funds with returns of 37% and 33% in the latest year, while six other funds in their
family with similar objectives only had returns ranging from 1.3% to 17.5%. This is
similar to the pattern in ads for lotteries and casinos, 70% of which feature winners.




                                                                         Frank Russell, 1998

Random events can also propel money managers into the limelight in the manager
selection process. In the chart above, out of 41 managers in the top quartile of Frank
Russell Universes for four years ended 1998, only eight had been in the top quartile in
the prior four-year period and 14 had actually been in the bottom quartile. Furthermore,
of the 41 top quartile managers in the earlier period ended 1994, only 8 remained in the
top quartile in the subsequent four-year period.
                                                                      Callan Associates, 2001

A similar study for the Callan Database for the period ended 2001 shows similar
results. Of 127 top quartile managers over four years ended 2001, 64 were in the
bottom half of their universes in the prior four years. Of 129 top quartile managers for
the four years ended 1997, 66 were in the bottom half of their universes in the
following four years. Picking “hot dot” managers is no guarantee of superior results in
the future.

The difficulty of identifying manager skill over short periods is further illustrated by
Wood (2001) using the hypothetical results of dart throwers and managers who have
either skill, an Information ratio = 0.1, or “unskill”, and Information Ratio = -0.1. After
one year, 46 of unskilled managers will outperform, 43 will still outperform after 3
years, 41 after 5 years! Meanwhile, in the skilled managers group, 54 will out-perform
over one year, 57 over two and 59 over three, still 41 will have under-performed after
five years.

A final illustration of the challenge of separating skill from noise is to construct a
simulation of a manager with a constant 3% alpha and a 6% tracking error. For each
year, we generate an excess return relative to the benchmark by scaling a series of
normally distributed random numbers to correspond to the 6% tracking error around the
3% alpha. The results for one hundred years are shown below. With the annual excess
returns in blue bars and the trendline tracking error plotted as well. The trendline is not
flat because this one hundred year sample is not long enough to reveal that the alpha is
in fact constant. More troubling is the series of red bars, which show the draw-down or
shortfall of the manager’s results relative to the last peak relative to the benchmark. In
years 29 through 36, for example, the manager is “underwater” relative to the
benchmark. In year 33, this draw-down is a seemingly insurmountable 14% before a
string of positive years pulls the portfolio ahead. Under most circumstances, the
manager would be terminated by the client sometime during this negative performance
period.

                                                                          Years 2001-2100
 20




 15


                                                                                                                  Annual Difference vs Benchmark
 10




  5




  0




  -5




 -10


                                                                Draw Down vs Benchmark
 -15




 -20
                   10

                        13

                             16

                                  19

                                       22

                                            25

                                                 28

                                                      31

                                                           34

                                                                37

                                                                     40

                                                                          43

                                                                               46

                                                                                    49

                                                                                         52

                                                                                              55

                                                                                                   58

                                                                                                        61

                                                                                                             64

                                                                                                                   67

                                                                                                                        70

                                                                                                                             73

                                                                                                                                  76

                                                                                                                                       79

                                                                                                                                            82

                                                                                                                                                 85

                                                                                                                                                      88

                                                                                                                                                           91

                                                                                                                                                                94

                                                                                                                                                                     97

                                                                                                                                                                          100
       1

           4

               7




We continued our simulation of manager results and found that the combination of a
3% alpha with a 6% tracking error is not sufficient to prevent the manager from being
fired many times over. Performance under-performs the benchmark three years in a row
twenty times, four years in a row eight times and five years in a row three times. And
the portfolio is underwater relative to the benchmark for three years 66 times, for ten
years 10 times and once for 23 years. It is doubtful that any money management firm
could survive such a long dry spell. Yet these are the consequences of the normal
behavior of a portfolio with 6% tracking error. Clearly separating skill from noise is a
challenge for even the most patient client, but the current focus on three to five year
performance records and quarterly evaluations is placing excessive emphasis on short-
term random events that have little information content.
Conclusion

The market is a fierce warrior
         Draw them in with the prospect of gain.
         Take them by confusion.
         Use anger to throw them into disarray.”
               Sun Tzu - “Art of War”, Statman (2001)

The human element in investing presents a challenge to investors and investment
committees. Many of our most basic instincts do not serve us well when we attempt to
make effective long-term investment decisions. There are some lessons we can take
from a review of human behavior in finance.

Loss Aversion

Frame Portfolios as a Whole: We hate losses more than we like gains. By framing
portfolios as a whole, we can view total portfolio risk rather than overemphasizing
small segments.
Follow the Prudent Man Rule: Portfolio diversification, as a “prudent man” would do,
shifts the focus from individual stocks that may decline to the process of investing the
overall portfolio. This is more productive than “second guessing” a manager’s
mistakes, and it allows the portfolio to capture returns in market segments that are
known to be risky.
Stretch Evaluation Horizon toward Planning Horizon: Long-term funds should not be
invested for short term comfort. The highest return assets will be volatile and their
higher risk premiums can only be realized by holding them through difficult periods.
More frequent reviews only heighten the anxiety of fiduciaries and agents, making it
more difficult to maintain a commitment to a long term asset allocation plan.

Over-confidence

Understand the Risks in Pattern Recognition and the Probabilities of Random Events:
We can be easily mislead by events that seem to fit a pattern but that are in fact random.
Both stock-picking techniques and manager selection criteria need to resist easy
solutions and focus on deep understanding of the fundamentals.

Regret

Avoid Crowds: Following fad and fashion is both tempting and comfortable, but it is
rarely rewarding.
Avoid Beauty Contests but Seek Inner Beauty: Appearances can be deceiving, both at
the company and the money manager level. If managers look like they were sent in
from Hollywood by Acme Casting…perhaps they were! There is no substitute for
intimate knowledge to penetrate beyond superficial appearance.



References:
Benartzi, Shlomo, and Richard Taylor, Myopic Loss Aversion and the Equity Premium
Puzzle, Quarterly Journal of Economics February 1995

DALBAR, Leuthold Group, February 2002

Desai, H., and P.C. Jain, Journal of Finance, Sept 1995,

Gilovich, Thomas, How We Know What Isn’t So, The Free Press, 1991

Hulbert, Mark, Hulbert Digest, New York Times, Sunday, Jan 21, 2001

Kahneman, D., & M. Riepe, Aspects of Investor Psychology, Journal of Portfolio
Management, Spring 1998

Kahneman, D. And Amos Tversky, “Prospect Theory: An Analysis of Decision Making
under Risk”, Econometrica, 263-291, 1979

Speidell, Lawrence, Deborah Miller & James Ullman, Portfolio Optimization: A
Primer, Financial Analysts Journal, January/February 1989

Statman, Meir, & Kenneth Fisher, Cognitive Biases in Market Forecasts, The Journal
of Portfolio Management, Fall 2000

Statman, Investor Psychology (Silencing Investment Noise), October 2001

Statman, Lottery Traders, Santa Clara University, July 2001

Statman, Meir, The Psychology of Risk and Taxes, Investment Counseling for Private
Clients, Association for Investment Management and Research, 2001

Svenson, O., Acta Psychologica 1981

“The Technology Peaks of 1999 Become the Valleys of 2001” The New York Times,
Oct. 7, 2001

Wood, Arnold, Behavioral Risks: Anecdotes and Disturbing Evidence, The Journal of
Investing, Spring 1997

Wood, Arnold S. Beauty Contests, hot Hands and manager Selection, Institute of
Psychology & Markets Conference, October 11, 2001
Disclosure:

The Standard & Poor’s 500 Stock Index (S&P 500) is an unmanaged index generally
representative of the U.S. Stock Market, without regard to company size. The Morgan
Stanley Capital International (“MSCI”) Europe, Australasia, Far East Index ("EAFE")
is an unmanaged index of over 900 companies, and is a generally accepted benchmark
for major overseas markets. Index weightings represent the relative capitalizations of
the major overseas markets included in the index on a U.S. dollar adjusted basis. The
Lehman Brothers Government/Credit Bond Index is an unmanaged, market-weighted
index generally representative of intermediate and long-term government and
investment grade corporate debt securities having maturities of greater than one year.
The Russell 1000 Index consists of the 1,000 largest securities in the Russell 3000
Index, which represents approximately 90% of the total market capitalization of the
Russell 3000 Index. It is a large-cap, market-oriented index and is highly correlated
with the S&P 500 Index. Russell 1000 Growth Index measures the performance of
those Russell 1000 companies with higher price-to-book ratios and higher forecasted
growth values. Russell 1000 Value Index measures the performance of those Russell
1000 companies with lower price-to-book ratios and lower forecasted growth values.
Unless otherwise noted, equity index returns reflect the reinvestment of all income
dividends and capital gains, if any, and bond index returns include all payments to
bondholders, if any. Index return calculations do not reflect fees, brokerage
commissions or other expenses of investing. Investors may not make direct
investments into any index. Past performance is no indication of future performance.

				
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