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1 Introduction
This dissertation is a report of a study on indirect property and its diversification benefits
within Europe. The study is based primarily upon data provided by EPRA who provides
indirect property indices for Europe. The first chapter of the dissertation describes the
background of the study, specifies the problem of the study, stresses its significance and
presents an overview of the methodology used.

1.1 Nature of the Problem and Field of this Study
According to Steven Heston from Goldman Sachs and academic Geert Rouwenhorst diver-
sification across countries within an industry is a much more effective tool for risk reduc-
tion than industry diversification within one country. In other words, the first and most im-
portant dimension of portfolio diversification is internationalism. One perceived problem
with international investment is the currency risk. However, this risk had been wiped out in
1999 for the Member States of the EMU. Some international markets are illiquid, costly,
unfamiliar, and generally disadvantageous to trade in. For instance in some markets, for-
eign investors have poorer access to information. However, international diversification
does not require investment in all foreign markets but can and should be limited to the ones
with transparent market structures. In the past three years the European equity market has
experienced major changes. The following will present some examples: On the institutional
side the stock exchanges of Paris, Amsterdam and Brussels merged and formed Euronext.
In some other cases regional exchanges consolidated on a national level and European
countries without a derivate exchange established one. Some stock and derivate exchanges
merged to share trading technology and central clearing counterparties. On the investor side
changes in investment strategies have been observed. Investors have started to diversify
portfolios across the domestic borders. Traditionally, European investors heavily depended
on the domestic market but due to the monetary union the trend has shifted within in the
past three years on the one hand to more cross-border investments within Europe. On the
other hand, especially pension funds have taken the lead for outflows even beyond the
European borders to the US and Pacific markets. Investment funds have increased in asset
invested in pan-European and sector specific equity funds. Nevertheless, the position of
domestic equity has remained strong.
                                              2




Property investment is practicable in two different ways: investment in indirect property or
investment in direct property. Direct property involves the purchase or trading of an actual
property. The focus of this study lies on indirect properties, which are paper assets backed
by property. The public property company trades its shares on the stock market. The in-
vestment in indirect property provides the investor with the possibility to purchase a pool of
property assets, leading to a better diversification. The indirect property market is not only
more liquid than direct property market, it is also more transparent since the shares are pub-
licly traded and the share price is known at any time.
The European countries have experienced major changes in their constitution by joining the
EU. Recently a single currency for almost all the Member States of the EU has been intro-
duced. As the aim of the EU is to conduct one policy for all its Member States, the coun-
tries will be influenced by similar regulations. The EU aims at unifying all the Member
States concerning a common economy, common political aims and common representation
towards other countries. Financial, economic, political, monetary, and cultural barriers are
tried to overcome to bring European countries closer together. ‘This process was further
accentuated by the launch of the single currency which transformed the many, relatively
small, open economies into a large, relatively closed economy‘ (the Directorate General
Economic and Financial Affairs (2001)).
The problem that might arise from the unification of the EU Member States is an elimina-
tion of international diversification benefits. According to the modern portfolio theory, low
correlations between countries or sectors result in diversification benefits. The changes in
correlation structures of equity returns can be caused by the monetary and economic inte-
gration. This integration has been associated with increased correlations between countries
on the one hand and between sectors on the other hand. The unification of the European
countries and the introduction of a single currency might eliminate or reduce country spe-
cific characteristics such as political independency and individual economic trends. In other
words economic shocks in Europe might lead to similar reactions within all the countries.
This development would result in a failure of the modern portfolio theory. For the past
three years the European equity markets have been challenged by the adoption of a single
currency. This timeframe offers good conditions and extensive data material for research on
                                               3



the development and changes experienced in the European equity market, especially in the
real estate sector. This study investigates whether diversification benefits for the European
real estate sector are still achievable after the integration of one currency. By constructing
several international real estate portfolios the author will prove whether investors should
stick to their traditional diversification through indirect real estate and whether the modern
portfolio theory is still applicable for the EU or whether investors will have to search for
new diversification possibilities.

1.2 The Professional Significance
The real estate market is not as transparent as the stock market and especially in Europe it
is difficult to gather real estate data, due to a lack of property indices. The difficult access
to real estate data has deterred experts from conducting research in this field. Consequently,
the number of studies on property in Europe is restricted rendering the purpose of this study
even more significant. However, improvements in the transparency of the real estate market
indicate that European investors have become aware of the importance of real estate as an
investment tool. Recently, Germany has introduced its first indices for real estate called
DIX (Deutscher Immobilien Index) and the EPRA Index was introduced in the Nether-
lands. The DIX is a national index, which might give evidence that the importance of inter-
national diversification with real estate investment is still underestimated. The EPRA Index
has the seldom characteristic of covering European indirect property data. This study aims
to improve the transparency of the indirect property market and widen professional knowl-
edge in this field. Moreover, the study will be a guideline for investors concerning their fu-
ture investing strategies. Investors can use the outcome of this research to support their de-
cisions for or against international diversification of real estate as a tool to create an effi-
cient portfolio. This topic has become relevant due to the worldwide turndown of the stock
markets since September 11th in 2001. Before the tragic terrorism attack European investors
had not experienced any downturns in the stock market for a long time, therefore, they had
been overconfident and used the stock market as a cash machine. Since the downturn, in-
vestors have been more cautious on their investments and have been searching for diversi-
fication tools. The study is going to supply investors with new information on diversifica-
tion tools. Additionally, problems in the pension financing within Europe might lead in
                                               4



some major changes in the future. The pension financing might need to distribute to the
capital markets. A diversification tool such as indirect property is indispensable in order to
secure a long term benefit.

1.3 Methodology
This study analyses the diversification benefits of indirect property in a European portfolio
by using two different scientific approaches: the Modern Portfolio Theory (MPT) and the
Capital Asset Pricing Model (CAPM). The MPT assumes that investors can reduce risk for
equivalent rates of return (or increase rates of return for equivalent levels of risk) by com-
bining assets affected by economic fundamentals in ways that are less than perfectly corre-
lated. Diversification benefits may be captured by combining different asset classes, such as
stocks, bonds, shares and real estate. Further improvements in portfolio performance may
be possible by a reasonable mix of differentiating characteristics within an asset class. For
real estate, refinement often comes by acquiring property in different locations and/or dif-
ferent property types. The acquisition of European property stocks by companies investing
in different property types could lead to international diversification benefits. Although, the
MPT is based upon many assumptions that do not reflect the real world such as the exis-
tence of a perfect capital market, it seems to be an appropriate model for this dissertation as
the MPT supports the approach of diversification. As it is the aim of this dissertation to
analyse risk minimization and return maximization, the MPT seems to be the most appro-
priate approach. The CAPM also has some disadvantages and advantages such as the as-
sumption that an investor may lend and borrow money at a risk-free rate. Moreover, it is
difficult to determine the market risk since no general definition is provided by the model.
In this case the author decided to define the market risk as the risk of the EPRA Total Re-
turn Index as this index represents all European property shares. In order to reduce com-
plexity, the relationship between direct property and indirect property cannot be incorpo-
rated. However, weighing the advantages and disadvantages of the theories, the author con-
cluded that the CAPM and the MPT are the best approaches for this dissertation.
In order to analyse the outcome of the study in more detail and in order to finish with some
useful implications, the average return, the standard deviation, the Sharpe ratio, the tracking
error and the information ratio are calculated and critically dignified. In order to give a brief
                                               5



overview on the past performance of all financial assets a performance trend is created.
Additionally, the relationship between risk and return is represented in a graph. The consis-
tence of the portfolios has been chosen due to the correlation matrix and the risk/return dia-
gram and is described furthermore in chapter 6.1.7. Moreover, the approach of the calcula-
tion of the β is described in chapter 6.2.3.
In order to reduce the complexity of the study, it is necessary to transform the daily data
into monthly data. Moreover, the monthly data is transformed to the 31.12.1998 being the
starting point of the analysis.

1.4 Structure of this Study
In chapter two, the term indirect property is defined and several typologies of property
companies are described.
In the third chapter, the characteristics of the European indirect property market are ana-
lysed. Although indirect property performance is influenced by several variables such as
the economic and direct property development, the author confines the analysis to a brief
overview of the primary and secondary stock market as well as of the risk-free rate market.
No specific information is provided on the European indirect property market because the
market is not transparent and the high profile is limited. The publication of information on
this specific market is not rare. Useful information on the indirect property market is pub-
lished by private banks as a service for their customers.
In the fourth chapter, the author gives an overview on the historical development of the
European Union, in order to emphasize the importance of his study and to stress the present
developments in Europe.
In chapter five, a detailed literature review analyses past researches undertaken on the top-
ics of diversification. The author distinguishes between literature on the diversification ef-
fect with equity, with direct property and with indirect property. No research has been un-
dertaken on the European indirect property market and its diversification benefits. Although
some researches have been undertaken on the German, French and the UK market, there is
a lack on studies that cover the whole European financial market.
In chapter six the MPT and the CAPM are explained in detail as well as the Kennzahlen.
Moreover, the preparation of the data is explained.
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In chapter seven, the sources of the data are described for the EPRA Indices, the Dow Jones
stoxx 600, the GBI and the EURIBOR. The author explains in detail the composition of the
indices in order to provide the reader with enough information to judge the quality of the
data.
In chapter eight the results of the calculation are presented, analysed and discussed. Impli-
cations are given for investors focusing the attractiveness of indirect property in a European
portfolio and its benefits of diversification.
Chapter nine summarizes the main findings and gives an outlook.


2 Indirect Property

2.1 Typologies of Real Estate Property Companies
Property companies are companies that operate in the real estate business. On the one hand
the company’s core competences can be historically in the real estate market or on the other
hand the company’s have changed their historical non-property core business to a property
core business. Publicly traded property companies can be classified into three different
groups:
    1. Property holding companies: The property holding company purchases completed
        buildings and/or lets the building to tenants. Their operative business diversifies to
        its real estate holdings. In order to be successful on the capital market the property
        holding companies usually have to restructure its property holdings.
    2. Operating companies: Operating companies are service providers for private clients
        who changed their traditional core business and transformed into a real estate com-
        pany in order to focus on the exploiting of their property.
    3. Facility management companies: They often come from the field of building service
        installations or belonging to energy suppliers. Their core competence as a facility
        management company lies in the management of commercial, technical or/and in-
        frastructural functions.
    4. Project development companies: Three different kinds of project developers have
        emerged on the market. The trade developer develops for a not specific investor and
        sells a building. The investor developer develops a building with the purpose to
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       hold it as a company asset. The service developer develops a building to the specific
       needs of a client and sells it to the client within or after the construction process.
In general the success of listed real estate companies depends on a various number of fac-
tors. They can be the general expectations and movements on the equity market. Although
some researchers concluded in their study that indirect property is less influenced by the
global or national stock market the effects are not deniable. Indirect property is influenced
by the political, economic and institutional situation in a country (see further more in the
chapter literature review).

2.2 Definition of Indirect Property
Property companies are companies that operate in the real estate business. On the one hand
the company’s core competences can be historically in the real estate market or on the other
hand the company’s have changed their historical non-property core business to a property
core business. Publicly traded property companies can be classified into four different
groups:
   5. Property holding companies: The property holding company purchases completed
       buildings and/or lets the building to tenants. Their operative business diversifies its
       real estate holdings. In order to be successful on the capital market the property
       holding companies usually have to restructure its property holdings.
   6. Operating companies: Operating companies are service providers for private clients
       who changed their traditional core business and transformed into a real estate com-
       pany in order to focus on the exploitation of their property.
   7. Facility management companies: They often come from the field of building service
       installations or belonging to energy suppliers. Their core competence as a facility
       management company lies in the management of commercial, technical or/and in-
       frastructural functions.
   8. Project development companies: Three different kinds of project developers have
       emerged on the market. The trade developer develops for no specific investor and
       sells a building. The investor developer develops a building with the purpose to
       hold it as a company asset. The service developer develops a building to the specific
       needs of a client and sells it to the client within or after the construction process.
                                              8



In general the success of listed real estate companies depends on a various number of fac-
tors. This can be the general expectations and movements on the equity market. Although
some researches concluded in their study that indirect property is less influenced by the
global or national stock market, the effects cannot be denied. Indirect property is influenced
by the political, economic and institutional situation in a country (see further more in the
chapter literature review).


3 Characteristics of the European Indirect Property Market

3.1 The Euro and the European Financial Market
The EMU has already had an impact on the integration process of the EU financial markets
and has lead to some fundamental changes: globalisation, regulatory changes in the frame-
work and financial reforms in the member states. This wave of deregulation and liberalisa-
tion leads to a more homogenous market, new products and techniques as well as consoli-
dations among intermediaries. The first step to create a potential for a more liquid and lar-
ger financial market was the elimination of the currency risk through the implementation of
the Euro. The Directorate General Economic and Financial Affairs (2001) reports that the
cross-border transaction represents more than 60% of the total activity of the largest par-
ticipants in the EMU financial market.
The euro and the dollar represent 80-85 % of the international bond issuance. Nevertheless,
in 2000 the euro-denominated issuance of 36% was below the dollar share of 50% (The Di-
rectorate General Economic and Financial Affairs (2001). Compared to 1999 the domina-
tion of euro-denominated issuance shows a downward trend. The unsecured segments of
the market immediately begun to incorporate. It was mainly the inter-bank and the short-
term derivate market that followed one trend. The unsecured segments of the money market
especially the repo market and the market for short-term securities have been less inte-
grated whereas the bond market is also quite integrated. The Directorate General Economic
and Financial Affairs (2001) concluded that the market was more incorporated in 2001 than
before 1999. Moreover, the equity market has also been stimulated by the EMU. Although
the introduction of the Euro has intensified competition through price transparency, elimi-
nation of domestic competitive advantages and promotion of more liquid securities mar-
                                              9



kets, the merger and acquisition activities were concentrated on the national market and
there were little cross-border consolidations. According to the Directorate General Eco-
nomic and Financial Affairs (2001), cost savings from cross-border mergers were not as
great as in the domestic market. Moreover, significant differences in the legal and regula-
tory environment which still exist, prevent the integration process of financial markets. Ad-
ditionally, cultural factors and differences in the framework of corporate governance as
well as the banks’ mutual status or the government ownership discourage a completely ho-
mogeneous pan-European market (Licht 1997). The Directorate General Economic and Fi-
nancial Affairs (2001) forecasts that the cyclical synchronisation between most economies
in the EU is going to increase as a result of the continuing integration process especially of
the financial market. Movements in various stock indices have been more correlated since
the introduction of the Euro. Therefore, the Directorate General Economic and Financial
Affairs (2001) forecasts an increase in cross-border and sector-based transactions away
from country-based investments. The correlation forecast of the Directorate rises the ques-
tion whether European indirect property correlates with the stock market or if it can be used
as a diversification tool.
The financial markets infrastructure represents an obstacle. The European clearing and set-
tlement infrastructure compromises 30 different systems across the EU which renders
cross-border transactions costly and more complex. Alliances and links between stock mar-
kets have increased the pressure to innovate a pan-European clearing and settlement sys-
tem. This pressure of competition and innovation has led to a move toward the consolida-
tion of the industries leading to lower transaction costs, therefore, rendering an investment
in European indirect property even more attractive. Transaction costs and time might be-
come even more attractive if the M&A activities increase due to the less complex market
regulations.

3.2 The Primary Market
The primary market in the EMU has been stimulated since 1999. The ECB (2001) states
that the issuance in 1999 counted 4% of the market capitalisation and rose to 5% in 2000
compared to an average of 2% for the last decade. The issuance in the US, UK and Japan
stayed at 2.5% during 1999 and 2000. Moreover, the number of listed companies grew at an
                                              10



annual rate of more than 10% between 1999 and 2000. According to the ECB (2001) 20
IPOs with an individual size exceeding 1 billion € were launched between 1999 and 2000.
The capital raised in the Euro area (€ 157 billion) was higher than in the US with € 138 bil-
lion. The sector was dominated by new listings in the technology, media and communica-
tion sector. M&A activities within the EU reached a level of over 10% of market capitalisa-
tion in 2000. Due to higher competition and the tendency towards further deregulations in
the EU, cross-border European activities enjoyed faster growth than all other operations
since 1995.

3.3 The Secondary Market
The equity holding in financial assets almost doubled between 1995 and 1999 as a response
to the favourable market conditions and the new inflows and low interest rates associated
with lower inflation expectations. Additionally, the questionable pension financing which
in most European countries is financed by the current contribution of workers, led to an in-
crease in equity demand because the ratio of elderly people to those of working age is pro-
jected to double by the year 2050. The seeking for higher investment yields has also en-
couraged the demand for equities. Nevertheless, the developments on the financial markets
have been disappointing since the 11th September developments on the financial markets.
Losses on the investor side have led to a decrease in stock investments and to a more pru-
dent investment attitude. Investors have started to search for diversification tools.
Investors seem to change their attitude towards equity exposure and access to an enlarged
European capital market. Institutional investors have shifted their investment to foreign eq-
uities away from the domestic market in order to diversify the portfolio or to gain higher
yields. Investment funds increased their equity holdings and tend to invest in pan-European
and sector-specific equity funds with strong domestic equity funds. Assets held by pan-
European and euro area-only investment funds represented 25% of total assets at the end of
2000 compared to 12% in 1998. The global and domestic funds market share decreased
from 43 and 45% to 24 and 41% for the years 1998 and 2000.
Bankhaus Ellwanger und Geiger (2000) states that listed real estate companies have devel-
oped outstandingly in 1999 compared to the traditional property sector. They expect that
the expenses and the time effort for the purchase and appraisals of single properties will
                                               11



attract foreign investors to invest in indirect property in order to secure their market partici-
pation leading to a stimulation of the share prices.


4 Historical Background of the European Countries
In the following chapter the historical background of the European countries will be ana-
lysed. The differences between the European Union and the European Monetary Union
shall be focused.

4.1 The European Union (EU)
In 1951, the Treaty of Paris which established the European Coal and Steel Community
was signed between France, Germany, the Netherlands, Italy, Luxemburg and Belgium. In
1957, the same countries agreed on the Treaty of Rome which established the EU. The goal
of the agreement was the creation of a single market. The Treaty of Rome was a milestone
and guaranteed the free movements of goods, services, persons and capital within these
countries as well as the establishment of a customs union in 1968. The oil crisis in the 70s
and the increasing number of member states made it difficult to agree on further actions. In
1985, the European Commission established the White Paper as a response to the declining
economic growth in Europe. This document required the removement of restrictions in or-
der to develop a single market. One objective of the White Paper was concerned with fi-
nancial services. Its goal was to create a single market for financial services, to complete
liberalisation and capital movements and to establish a common regulatory structure for
financial institutions. It became the basis of an amendment to the Treaty of Rome: the Sin-
gle European Act (Licht, 1997).
Today the EU has 15 Member States including Belgium, Denmark, France, Germany, the
Netherlands, Luxembourg, Austria, Italy, Ireland, Spain, Greece, Finland, Portugal, the
Netherlands and the UK. Currently, the EU is preparing for the accession of 13 eastern and
southern European countries. The EU is based on the rule of law and democracy. Its mem-
bers delegate sovereignty to common institutions representing the interests of the Union as
a whole on question of joint interests. All decisions and procedures are derived from the
basic treaties ratified by the Member States. Principle objectives of the Union are to estab-
lish European citizenship, to ensure freedom, justice, security, to promote economic and
                                              12



social progress and to assert European’s role in the world. The establishment of a single
market, the approximation of fiscal and economic regulation and a common trade policy
support the principles.

4.2 The European Monetary Union (EMU)
In 1991 at the Maastricht summit, the 11 member states found a consensus on the imple-
mentation of a single currency by 1999: the Euro. Participating countries are Austria, Bel-
gium, Finland, Franca, Germany, Greece, Italy, Ireland, the Netherlands, Portugal, Luxem-
bourg and Spain. Sweden, Denmark and the UK are Members of the EU but do not partici-
pate in the common currency. Switzerland is regarded as a neutral country as it has not
joined the EU nor the EMU. The circulation of the Euro started only 3 years later in 2002.
The European Central Bank (ECB) follows several strategies. Its overriding principle is to
follow a monetary policy strategy to maintain the price stability. Moreover, the fiscal policy
seeks to secure the maintenance of budgetary discipline. As the ECB is entrusted to the
monetary policy responsibilities for other economic policies such as national budgetary pol-
icy and structural policies have been coordinated to the member states. The ECB sets out
the task and requirements as well as its instrument to all national central banks. The single
monetary policy is only appropriate to the average of all member countries (The Directorate
General Economic and Financial Affairs (2001)). As some monetary conditions may be ex-
pansionary to some member states, the ECB’ instruments may prevent the integration of the
economies and the financial markets. The most important challenges for the future will be
the implementation of structural reforms aiming especially on the integration and im-
provement of the product and labour market.
The membership to the EMU is bound to the fulfilment of several criteria. One of them is a
government deficit of no more than 3%. How the requirements can be met are not explicitly
stated. Consequently, the member states took different actions.
According to the Directorate General Economic and Financial Affairs (2001), from a mac-
roeconomic point of view, the single currency has transformed the euro area into a more
closed economy which has become more resistant to external shocks. The Euro eliminated
the risk of intra-euro-area exchange rate variations and has removed the risk of a sub-
optimal resource allocation due to economically-unjustified and protracted movements in
                                              13



the nominal exchange rate. Nevertheless, the US dollar remains the dominant vehicle cur-
rency in foreign exchange markets although the Euro is widely been used as an anchor cur-
rency mainly in central and Eastern Europe and Africa.


5 Literature Review
The number of literature on the real estate as a diversification benefit tool for European in-
vestment portfolios is limited. A much larger body of literature can be found for the inter-
national context. This chapter will present international literature and examine both the
theoretical and empirical studies. The following review was developed through a systematic
research on literature on direct and indirect property as well as on the equity market. More-
over, the literature review was conducted on internet resources and publications.

5.1 The Diversification Effect with Equity
The problem of diversification in a stock portfolio was analysed e.g. by Elton and Gruber
(1977) and Evans and Archer (1968). Johnson et al. (1994), Freiman (1998) and Rouwen-
horst (1999) who conducted researches on the diversification effects in European equity
markets. They concluded that the equity markets have been integrated but that diversifica-
tion benefits through international investment are not absent. Johnson et al. (1994) exam-
ined eight European countries, concluding that an investor can reduce risk by diversifying
his share portfolio across a range of European equity markets. Nevertheless, he also made
clear that the return and risk characteristics are becoming more similar. Like Johnson at el.
(1994), Freiman (1998) completed his research four years later with the assumption that
stock market integration has increased and that it is likely to continue to grow. In his study,
Freiman (1998) analysed the impact of European integration for Spain, Italy, Germany and
the U.K. – at company and macro levels – on correlation between stock market returns. His
data sources covered on the one hand the development of the GDP growth, inflation, gov-
ernment bond yields and exchange rates. On the other hand he examined the equity market
return series based on capitalisation weighed averages of individual stock returns between
1975 and 1996. Since the beginning of the 90s, the average correlation between European
markets has remained above 50 percent. Freiman (1998) conducted the research on diversi-
fication opportunities in Europe because he identified several reasons for a unified stock
                                              14



market: (a) the diversification of sales and production activities across Europe by large
European companies, (b) the drive towards the EMU with fixed exchange rates and interest
levels as well as the harmonisation of fiscal and political policies leading to the synchroni-
sation of business cycles. However, Rouwenhorst (1999) examined the European equity
markets in the EMU. Since 1982, country effects in stock market returns have been larger
than industry effects in Western Europe and Rouwenhorst (1999) concluded that this domi-
nation still existed for the period between 1993 and 1998. The sample for the study con-
tained the returns of the stocks in the MSCI indexes of 12 European countries between
1978 and 1998. Moreover, he focused on seven major industries such as capital and con-
sumer goods. Rouwnehorst (1999) closed his research with three possible explanations for
the low stock correlations in the EMU: First, country indices differ in terms of sector com-
position which plays only a minor role. Second, important economic shocks have different
effects which are specific to the country and national markets. Third, the home bias in port-
folio holdings of investors. The last explanation was analysed more detailed by Cooper
(2001) who examined the reasons, problems, and possibilities of international diversifica-
tion and domestic investment decisions. In his research he analyses past studies on the eq-
uity market. Cooper (2001) concluded that investors remain highly concentrated on their
home markets. German, US and even the U.K. hold almost all their assets in domestic secu-
rities. In his research he refute the identified reasons for domestic investment such as cur-
rency risk, hedge of inflation, the disappearance of diversification benefits in risky times
and the argument that foreign markets are intrinsically risky. International diversification in
investments has been considered by several authors such as Grubel (1968) and Lessard
(1974). Diversification reduces risk without forgoing the expected return as long as markets
do not move parallel. Therefore, Espita and Santamaria (1994) investigated in their research
the interdependence of price formation in different European stock markets in a global con-
text and the weight of the interdependence in each market in relation to others. It was con-
firmed that even in a global context an integration process among stock markets. In their
research they cover a period between 1987 and 1992, using indices of Tokyo, New York,
Frankfurt, London, Madrid, Milan and Paris. Using the VAR analysis the researchers con-
cluded that a high level of correlation exists between daily return time series of all markets.
New York was identified as the most influential market whereas the European markets do
                                              15



not have a significant influence on the other markets. Domestic factors which influence na-
tional markets have been diversified through internalisation of economic activity leading to
a greater correlation among the markets. Therefore, international diversification does not
have an excessive economic rationality. In their study Kempa and Nelles (2001) analyse
more detailed the effects before and after the EMU on the potential returns gained through
international diversification in the European stock market. Therefore, two scenarios are ex-
amined. First, the national stock market indices in national currency without accounting for
FX volatility (sample after the EU) and, second, the national stock market indices in which
exchange rate movements are explicitly incorporated (sample prior the EU). The results
indicate that the gains from diversification are higher with FX volatility. But the higher na-
tional betas indicate also that the EMU is likely to lower the cost of equity in the national
markets.
The studies proved that the EU and the EMU have led to an increased integration of the
European equity markets. As the performance of indirect property is influenced by the eq-
uity market, it might be possible that diversification benefits are not limited due to integrat-
ing indirect property markets.

5.2 The Diversification Effect with Direct Property
Due to a lack of reliable data, quantitative studies on direct property on diversification are
still limited. Researches on the application of the modern portfolio theory to real estate
were conducted by Findlay et al. (1979), Friedman (1970), and Hoag (1979). Like Elton
and Gruber (1977) and Evans and Archer (1968) analysed the effectiveness of portfolio di-
versification as more stocks were included, Brown (1997) conducted a similar research for
direct property. He proved that on the one hand low correlation between returns on individ-
ual properties enable high levels of risk reduction which on the other hand makes it difficult
to construct highly diversified portfolios. Grissom et al. (1991) analysed the geographical
diversification benefits of direct property and examined the rate of returns for office build-
ings in Texas for geographical patterns. He found that geographical pattern do exist in in-
tra- and inter-city basis indicating geographical diversification possibilities, therefore it
could be possible that diversification benefits exist for Europe if the Member States are
classified as inter/intra-city markets. The author concluded that different urban and eco-
                                                 16



nomic environments exist for each submarket. These differences are also present in Europe
as e.g. fiscal and political differences are still existing.
Worzala and Bernasek (1996) and Mueller and Ziering (1992) conducted researches on real
estate diversification benefits in accordance to economic drivers. Worzala and Bernasek
(1996) investigate in their study the effects of the European economic integration on the
real estate market. With a data between 1983 and 1994 gathered from the International
Property Bulletin, they find evidence of less importance for the convergence of the markets.
The core group of the countries were Belgium, France, Germany, the Netherlands, Italy,
Spain and the U.K.. They concluded that the differences in legal systems, fiscal conditions,
financing costs, economic conditions and building costs as well as the lack of significant
convergences in the real estate market determinants such as lease conditions/structures in-
dicate that impediments remain to the creation of a uniform property market. Muller and
Ziering (1992) focus on the correlation between local economic drivers of individual met-
ropolitan areas in the U.S. as the key determinant for more efficient diversification. Cover-
ing a period between 1973 and 1990, the main finding was that economic diversification
can be more effective than geographic diversification.

5.3 The Diversification Effect with Indirect Property
As Brown (1997) for stocks and Grissom et al. (1991) for direct property, Eichholtz (1997)
addresses the problem of diversification by sector. Moreover, he addresses the issue of in-
ternational diversification by region.
Ennis and Burik (1991) and Miles and McCue (1982) proved that real estate improves the
mean variance efficiency of a diversified portfolio. Gordon (1991) and Gilberto (1990) ex-
amined diversified portfolios in an international context on the basis of weak correlations
between international assets. Gordon (1991) examined on the basis of appraisal-based re-
turns efficient frontiers for real estate investments in the US and UK. Although the two
markets have been converging in the past years, he calculated low correlations. Moreover,
Gilberto (1990) studied the potential of international diversification for American investors.
Using property share returns he tried to minimize the investment risk.
Eichholtz (1996) and Conover et al. (2002) conducted a study on foreign indirect property
and its diversification benefits and completed their studies with positive results on property
                                              17



shares as a diversification tool. Eichholtz (1996) examined the effectiveness of international
real estate diversification in relation to international diversification of stock and bond port-
folios. Using the null hypothesis, he proved that correlations between national real estate
returns were lower than its corresponding stock or bond correlation which indicates that
national real estate can be used as a diversification tool. In his study, he covered global
market places such as Singapore and Hong Kong. Moreover, he included countries from
Europe such as the Netherlands and France before the European Monetary Union. The
study comprised a time series of nine years from 1985 to 1994. He concluded that the low
correlations of the real estate investment was a result of the local nature of the real estate
market and the national economic disturbances, whereas the stock and bond markets was
more influenced by global factors. Conover et al. (2002) examined if foreign real estate
provides diversification benefits beyond foreign stocks. It was found that foreign real estate
had lower correlations with U.S. stocks than foreign stocks and that foreign real estate has a
significant weight in efficient international portfolios. Similar to Eichholtz (1996), Conover
et al. (2002) used a data sample surrounding the stock market crash of 1987, therefore the
explanatory power of both studies is questionable as they cover a more exceptional time
period. Whereas Chandrashekaran (1999) used data between1975-1996. Nevertheless, he
also found that indirect property has an important role in dynamic asset allocation strate-
gies. He looked at diversification benefits from another point of view analysing the time-
series behaviour of the volatility of the REIT Index and in the correlation of the REIT Index
with other asset classes (stocks and bonds) that might be exploited for asset allocation pur-
poses. His findings showed that REIT Index variances and covariances with other asset
classes decline after an up-move in the REIT Index and increase after a down-move in the
index.
Geurts and Jaffel (1996) and Eichholtz (1997) analysed the diversification benefits of indi-
rect property. Eichholtz (1997) looked at the diversification benefits for regional property
shares by sector or by region from an American investors point of view, whereas Geurts
and Jaffel (1996) addressed the risk reduction potential through diversification due to dif-
ferences in institutional frameworks in a global perspective. Eichholtz (1997) concluded
that American investors can reduce their investment risks by diversifying to the far East and
Europe. In contrast to Geurts and Jaffel (1996), Eichholtz (1997) also analysed the eco-
                                               18



nomic background in detail and found that the diversification strategy is superior although
economic integration is increasing due to converging macroeconomic factors such as em-
ployment, interest rates, inflation and GDP growth. Due to high transaction and administra-
tion costs and general information advantages as well as information asymmetry unless a
local partner is found for the real estate market, investors avoid cross-border transactions.
Geurts and Jaffel (1996) focused the economic consequences of the institutional frame-
work. He studied the impact of government regulations and used risk assessment variables
e.g. political risk, property right variables, corruption and socio-cultural factors such as life
expectancy and foreign investment variables and the degree of foreign control.
It was Eichholtz (1998) who conducted a research on continental factors in real estate re-
turns. He found that the real estate returns in one European country depend positively and
significantly on real estate returns on other European countries. Due to an existing conti-
nental factor in Europe, Eichholtz (1998) suggests that real estate investors should diversify
outside Europe. Although, Eichholtz (1998) sees no great diversification benefits in Europe,
this study is still of importance because Eichholtz (1998) study was conducted before the
EMU, therefore currency risk was still present and investor’s home loving attitude was
probably still predominating.
So far no specific researches have been conducted on the diversification benefits with indi-
rect property since the European Monetary Union. Even though past studies have found that
the European equity markets tend to integrate and reduce diversification potentials, this
does not have to be the case for the property share market. The indirect property market is
not only influenced by the equity market but also by the direct property market which de-
pends on local circumstances.


6 Methodology

6.1. Modern Portfolio Theory
The Modern Portfolio Theory was developed by Markowitz (1971). Basically the risk and
return of different assets are combined in the most efficient way excluding sub-optimal
portfolios. In the following chapter the basic assumptions of the theory are explained, fol-
                                                19



lowed by the calculation of the combination of assets and the efficient frontier. In the end
the problems and the limits of diversification are discussed.
The Modern Portfolio Theory (MPT) covers decision models which permit the optimum
capital investment in a mixture of possible investments. Hence, the effects of risk diversifi-
cation are a central realization of the MPT. The basic idea of the MPT is the pursuit of cer-
tainty, profitability and risk averse investment attitude. The return is considered to be a sto-
chastic random variable being the condition for the quantification of risk. Due to Perri-
don/Steiner three characteristics of the MPT are that the return is a stochastic random vari-
ables, besides profitability investor’s pursuit the goal of certainty and returns can be sto-
chastically dependent. Markowitz (1971) as the originator of the MPT developed the Port-
folio Selection as a detailed portfolio theory. The Portfolio Selection is a normative capital
market model that describes the attitude of a rational investor with a given input of infor-
mation. Mostly the model refers to information with variables in the future. The variables
are determined with the help of forecast models. Markowitz uses the μ-δ – principle in or-
der to determine the investor’s investment attitude. The expected value E serves as the re-
turn parameter and δ is used for the purpose of the risk parameter. Dependencies in return
developments are calculated with covariances. Markowitz facilitated the effect of diversifi-
cation to be statistically justified and quantifiable.

6.1.1 The Model Assumptions
Investment Object Orientated Assumptions
        The Portfolio Selection considers investment returns as stochastic random variables.
        This assumption enables the formation of an unconditional net yield probability dis-
        tribution as an illustration of a decision under risk.
        The pre-condition for return correlations of different investments to be measurable
        is that returns are assumed to be stochastically dependent. The possible measure-
        ment of return correlations enables the quantification of risk diversification effect.


Investor-Referred Assumptions
        Investors are assumed to aim for risk minimization and return maximization only.
        The assumed attitude of the investors is based on uncertainty of the future and is
                                              20



      considered in the model by the assumption of risk adversity. In this model risk is
      considered to be return fluctuations.


      The investor makes decisions on the basis of the expected portfolio return E(r) and
      the
      expected deviation of the return δ resp. δ2 .


      The investor is able to determine E(r) and δ in order to set the net yield probability
      distribution from 2.2.1. However, this model does not imply the determination of
      the whole probability distribution.


      In order to determine the optimum portfolio it is assumed that the investor aims to
      maximize his benefit based on the Bernouillie principle. The risk benefit depends on
      the parameters E(r) and δ. At least a threefold diversifiable utility function is neces-
      sary.


      The planning-horizon covers one period. Consequently discounting and reinvest-
      ment problems are excluded form the model. Profit distributions of individual
      shares will be considered in the expected return by calculating the present value of
      the individual expected distribution. The model does not consider regrouping or
      Revision after single parts of the period.


      The investor cannot issue securities.


Capital Market-Referred Assumptions
      The Portfolio Selection assumes the existence of a perfect capital market.
      The model assumes endless divisibility of securities, but excludes the Revision or
      regrouping of single securities.
      The model does not consider transaction costs, taxes, trade restrictions and currency
      changes.
                                                    21



        The Portfolio Selection assumes the possibility to acquire and liquidize securities
        immediately in an unlimited quantity without any market entry boundaries.
        It is assumed that the provision of information and the data processing are free of
        charge.
        Returns are independent of the capital assets/fixed assets thus the investor can only
        adjust by quantity.

6.1.2 The Concept of Diversification
The Combination of Assets
A rational and risk averse investor makes a decision on the basis of the expected return and
the risk. Therefore, the expected return of the portfolio needs to be calculated:


E (rp) = ∑ xi E (ri)                with ∑ xi = 1


xi : the proportion of the asset i in the portfolio p
E (rp): the expected return of portfolio p
n: the number of assets


The expected risk of the portfolio is:


σp = √ ∑ ∑ xi xj σi σj ρij


σp : the portfolio risk
σi σj : the risk of asset i and j
ρij : the correlation of the asset i and j


The risk of a portfolio is at its maximum if two assets are correlated with +1, whereas a cor-
relation of -1 gives the greatest risk reduction. According to Hoesli and MacGregor (2000,
P. 129) two assets are barely positively correlated as their returns are affected by different
performance drivers. A portfolio is efficient
    •   If the return of assets is maximised for a given risk, or
                                                  22



    •      If the risk is minimised for a given return.

Markowitz (1971) assumes that the risk of single shares is eliminated through diversifica-
tion if the correlation is ≠ 1.


Nature of the Diversification Effect
The purpose of Markowitz’s approach is either:
           ‛for a given level of risk, to maximise return; or
           for a given return, to minimise risk’ (Hoesli and McGregor, 2000).
In his theory Markowitz acts on the assumption that the risk of individual shares can be
eliminated through diversification, but only under the condition that the correlations be-
tween the assets are unequal “1”. The correlation coefficient is the standardization of the
covariance and measures the nominated dependency of two correlated shares in an interval
[- 1; + 1]. The combination of at least two securities can generate an optimum combination
of risk and return as explained above. Decisive for this strategy are the correlation coeffi-
cients of the assets. Two shares correlated by “1” will diverge from their expected value in
the same relative degree and in the same direction for every economic environment state. In
that case a diversification of risk is not possible. For a correlation between “0” and “1”, the
expected value of two correlated shares will perform nearly equal. Correlated shares with a
correlation coefficient of “0” will have a completely independent development of their
value. Correlation coefficients between “0” and “-1” will affect the expected value of two
correlated shares in a more or less antidromic way. The expected value of two shares that
are correlated by a correlation coefficient of “-1” develop in completely antidromic direc-
tions. A short overview of the correlation coefficients and their interpretation is found in
table 1.

The more correlation coefficients diverge from “1”, the more an investor benefits from the
diversification effect for a portfolio. Figure 1 illustrates the effect of the diversification the-
ory.

Figure 2 illustrates the effect of diversification. The graph clarifies the risk-reducing effect
of portfolios. An investor can realize A by investing his whole capital in the A-share. By
doing so he generates the highest return combined with the highest risk. An investment in
                                                23



B-shares reduces the risk as well as the return. It is obvious that the risk of a portfolio is
less than the weighed average of the single risks. C is the investment that offers the lowest
risk at a given return.

6.1.3 The Efficient Frontier – The Combination of Assets
The efficient frontier is the boundary that gives the optimum combination of assets in a
portfolio. It identifies the optimum combination of risk and return.
The selection of the optimum portfolio depends on the investor’s individual preferences. It
is the investor’s indifference curve that compromises the risk and return among which he is
indifferent. The higher the indifference curve of an investor, the higher his expected return
for a given risk will be. The optimum portfolio is determined where the indifference curve
is tangent to the efficient frontier.
The weighed average of expected returns of combined assets/ the efficient frontier is calcu-
lated by minimizing the portfolio risk with the condition of different given expected re-
turns:


(2.1.) E (rp) = ∑ xi E (ri)
(2.2.) ∑ xi = 1


xi = the proportion of the asset i in the portfolio P
E (ri) = the expected return of the asset i
E (rp) = the expected return of the portfolio P with the asset i and the proportions x
n = number of assets


The variance of the expected return of the portfolio is calculated as followed:


(2.3.) δp2 = ∑ ( xi2δi2 ) + ∑ ∑ xi xj δi δj
(2.4.) δp2 = ∑ ∑ xi xj δi δj
(2.5.) δp = √ ( ∑ ∑ xi xj δi δj )


δi and δj : individual asset risks
                                                 24




The expected risk of the portfolio P including correlation coefficients:


(2.6.) δp = √ ( ∑ ∑ xi xj δi δj ) * pij          with pij = δij / δi δj


pij = the correlation coefficient for the assets i and j
δij = covariance of i and j


The Efficient Frontier with a Risk-Free Parameter
Tobin amplified Markowitz’s model by introducing the supplementary assumption of a risk
free variable (table 2). The consequence by this improvement is that investors are provided
with a wider range of investment options. Therefore, the efficient frontier is calculated dif-
ferently: the return is maximized with a given level of risk. This is achieved if rf tangents
the efficient frontier of the capital market. Consequently, the determination of the optimum
portfolio is independent to the individual preferences of the investor. It is assumed that an
investor has the unlimited possibility (in time and quantity) to do capital investments and
capital borrowing at a risk free interest rate. Tobin focuses on cash as the risk free invest-
ment. (E (rf) = rf and δf = 0)
The supplementary assumption augments the investment quantity. The investor can invest
one part of his capital xA in a risky investment and the other part (1 – xA) in a risk free in-
vestment. The new efficient frontier is determined by repeated application of the μ-δ –
principle. The investor-optimal portfolio is in the osculation point of the straight line rf and
the efficient frontier. Hence, the optimum portfolio (table 3) is independent of the inves-
tor’s risk adversity. The investor’s risk adversity only affects his decision concerning the
proportioning of risk free and risky investment quantity in the portfolio. Tobin’s Separation
Theorem results in an optimum portfolio which is defined by a higher indifference curve
and therefore guaranteeing a better level of utility. Rational investors will chose portfolio T
regardless of their individual preferences. They invest their whole capital in this portfolio
constellation. Consequently, T is considered to be the optimum portfolio fraught with risk.
The choice of the mixed portfolio M is risk dependent. In this case the investor will invest
parts of his capital in the risk free investment possibility and parts in the risky investments,
                                                25



whereas beyond the portfolio T any investor will borrow money at the risk free rate in order
to invest the whole capital in portfolio T. Compare visually figure 3. The enhancement of
the Modern Portfolio Theory is also defines as Tobin’s Seperation Theorem.


The mathematical approach:
(2.9.) E (rp) = ( 1 – xA ) rf + xA E (rA)
        ↔ E (rp) = ( 1 – xA ) rf + xA E (rA)
(2.10) δp2 = xA2 δA2
        ↔ xA = δp / δA
These formulas serve to calculate the return and the variance of the portfolio P which is on
an arbitrary straight line through rf . The straight line will be defined by the following for-
mula:
(2.11.) E (rp) = rf + δp / δA ( E (rA) - rf )         (xA, δp, δA > 0 )
The efficient frontier is calculated with the formula (2.11.) utilizing the tangential portfolio
T in the variable rA .
(2.12.) E (rp) = rf + δp / δA ( E (rT) - rf )         also known as security market line

6.1.4 Limits of Diversification
The limits of diversification are graphically illustrated in figure 4. With an increasing num-
ber of weightily shares in a portfolio the risk of a portfolio will approach a lower bound of
diversification. This limit is also called average covariance. In case of equal weightening
the right part of the equation equals an unsystematical or diversifiable risk and the left part
of the equation illustrates the systematical or not diversifiable risk. Last is also defined as
the market risk. In the figure above the surface below the diversification limit demonstrates
the market risk. Here it concerns itself with ‘economic wide perils which threaten all busi-
nesses’(Brealey and Myers, 2000). Unsystematic risk covers all risks that threaten compa-
nies and their competitors.
The area E (r) and δ shows all feasible portfolios. The assumption of investors having a risk
averse attitude and the μ-δ – principle limit the feasible portfolios to a reduced number of
portfolios which are all on the efficient frontier. These portfolios offer the investors the
                                                26



highest return with a steady risk. Due to the μ-δ – decision principle, efficient portfolios
may not follow the following rules:
                                 μp = μep and δp < δep
                                 δp = δep and μp > μep
                                 μp > μep and δp < δep
Portfolios that fulfil any of these rules are inefficient.
Portfolios that cannot be found on the efficient frontier are inefficient. The concave trend of
the curve occurs if the assets or shares are correlated by a correlation coefficient unequal to
“1”.


In the figure 4 the share combination D is the portfolio with the lowest risk profile. It gen-
erates the highest possible return and is defined as the upper boundary but only if Leerkäufe
may not be undertaken. Constraints limit the number of feasible portfolios and displace the
curve to the right and down. Considering the Bernouille benefit maximization principle as
an assumption, it is possible to determine the optimum portfolio from all the efficient port-
folios. In order to find the optimum portfolio for an individual investor it is necessary to
formulate a utility function U that expresses the investors individual degree of risk adver-
sity. Risk averse utility function typically show a positive decreasing increase U’ > 0 and
U’’ < 0. The utility function is represented in the graph by a indifference curve. The risk
averse attitude of the investors is represented by the curves’ convex characteristics. With
his individual preferences the investor can determine his individual optimum portfolio.
The mathematical approach:


(2.7.) min δp2 = ∑ ∑ xi xj δij
(2.8.) with the condition E (rp) = ∑ xi E (ri) and ∑ xi = 1


The portfolio variance is minimized for a defined level of return E with the condition that
the investors’ portfolio investment comprises 100%. Successively it is possible to calculate
the whole efficient frontier with these formulas. Therefore, it is necessary to calculate every
single return stage of the interval [B; A].
                                               27



The efficient frontier can be calculated with the critical line algorithm (CLA) as well. The
theory of CLA which was also developed by Markowitz belongs to the groups of iteration
principles. The applicability of this model is especially appropriate for quadratic variance
minimization that have linear utility condition and not a negative condition.

6.1.5 Problems
The Modern Portfolio Theory limits the investors to concentrate their business decision on
risk and return. Therefore, it is difficult to determine the individual indifference curve of
each investor because investors objectives are more complex than just an optimization of
risk and return (Hoesli and MacGregor (2000)). Other performance drivers and investment
goals are excluded. These could be economical goals e.g. to liquidate and manage as well
as non economical goals e.g. co-determination, prestige and speculation. One of the reasons
for not considering economical goals is the difficulty to measure them, whereas non-
economical goals cannot be defined exactly.
As the theory is based on a return which is adjusted from taxes and costs, it does not in-
clude transaction costs and taxes. In the real world it is difficult to determine the individual
tax rate and the transaction costs.
Moreover, the Modern Portfolio Theory assumes that each investment only covers one time
period. This requires that every period the portfolio needs to be rebalanced to achieve the
optimum portfolio. This leads to a massive workload, to high transaction costs due to the
substantial selling and buying. These transaction costs should be included to the model.
Moreover, the model assumes that an investor may borrow and invest capital without any
restrictions. In the real world investors may not borrow capital without restrictions and the
interest rate for capital investment and borrowing differs and does not equal rf.
To use the Modern Portfolio Theory appropriately the availability and quality of data is
necessary. In the USA and the UK historical and current data is now available to some ex-
tent, whereas in some geographical regions such as parts of Europe e.g. the Baltic States
barely no data for indirect property is available.

6.1.6 Application of the Model in this Case
In order to analyse the diversification benefits of indirect property in a European portfolio a
basis portfolio (portfolio A) is constructed which consists of bonds (GBI Indices) and
                                               28



stocks (stoxx 600). Both indices include financial assets covering the relevant European
countries (see chapter 7). The efficient frontier is calculated and shown graphically for the
following steps.
a) In the first step indirect property from Germany is included to the portfolio in order to
examine the diversification benefits (portfolio B).
b) In the second step several portfolios are constructed in order to examine the effects of
diversification if a German investor diversifies his investment internationally.
- Portfolio C = portfolio B + indirect property from the Netherlands
- Portfolio D = portfolio B + indirect property from the UK
- Portfolio E = portfolio B + indirect property from Sweden
- Portfolio F = portfolio B + indirect property from Switzerland
- Portfolio G = portfolio B + indirect property from Italy
- Portfolio H = portfolio B + indirect property from Ireland
- Portfolio I = portfolio B + indirect property from Norway
- Portfolio J = portfolio B + indirect property from Denmark
- Portfolio K = portfolio B + indirect property from France
- Portfolio L = portfolio B + indirect property from Portugal
- Portfolio M = portfolio B + indirect property from Spain
c) In the third step two efficient frontiers are compared, the efficient frontier of the portfolio
B and the efficient frontier of the portfolio N. Portfolio N consists of the financial assets of
B as well as Italy and the Netherlands.
d) The average return and the standard deviation are calculated for several portfolios. The
combination of the portfolios consist of stocks, bonds, indirect property in Germany and on
the one hand international indirect property due to its negative correlation with the German
indirect property performance, due to the highest average return and due to the lowest risk.
It is very difficult to chose the optimum asset portions within a portfolio because the weigh-
ing of a portfolio depends on several aspects. The investors risk attitude is important. A risk
averse investor invests only a small portion of his capital in the stock market. The portions
of the assets within the portfolio also depends on the current economic situation and on the
capital market movements. In times of recession an investor searches investment assets
with low volatility whereas in times of economic growth and innovation investors might be
                                                29



more willing to accept higher risks for higher returns. To conclude there is no general rule
for a optimal portfolio combination. In this study an investment portion of 30% is assumed
for the stoxx 600.

6.2 Capital Asset Pricing Model (CAPM)
The CAPM is another form of an equilibrium model. It is based on the MPT and it was de-
veloped 12 years later by Sharpe, Lintner and Mossin.

6.2.1 The Model Assumptions
The CAPM is based on several assumptions to reduce its complexity. Due to Elton et al.
(2003) the restrictions made have a minor effect on the models and investors behaviour.
The CAPM assumes that an investor decides on his portfolio with regard to the expected
values and standard deviations of the asset’s return. Their investment decisions are based
on the Markowitz portfolio selection model. Therefore, all assumptions made for the MPT
are also valid for the CAPM. To develop the CAPM additional requirements have to be set.
First, the investor may lend and borrow money at a risk-free rate which fully anticipates
inflation. Second, the model assumes that all publicly traded financial assets are marketable
including e.g. human capital. Third, all investors have homogeneous expectations concern-
ing the inputs to the portfolio decision: all investors use the same expected returns and co-
variance matrix of security returns to decide on their optimal portfolio. Fourth, all informa-
tion is free ad available to all investors.

6.2.2 The Market Portfolio, Capital Market Line and Beta
The market portfolio (M) is the sum of all portfolios hold by all investors (ignoring lending
and borrowing). The value of this portfolio equals the wealth of the economy. According to
Bodie et al. (2002) the portion of every stock in the market portfolio equals the value of the
stock divided by the sum of the market value of all stocks. The market model proposed that
all expected return on a security can be expressed as a linear function:


                                      E (Ri) = αi + βi E (Rm)


E (Ri): the expected return on asset i
                                                      30



Rm: the expected market return
αi and βi: constants specific to the asset


The random error is given by:


                                      E (Rit) = αi + βi Rmt + eit


Rit: return on asset i in period t
Rmt: market return in period t
eit: random error in period t


The regression line can be calculated with the historical market date and from asset i, where
ai and bi are estimates from αi and βi:


                                               Ri = ai + bi Rm


For an individual period t, the following regression is required:


                                            Rit = ai + bi Rmt + rit


rit: residual for the asset i in period t


If the analysis is extended to portfolios, the following equations are valid:


                                       E (Rp) = αp + βp E (Rm)
                                        Rpt = αp + βp Rmt + εpt
E (Rp): the expected return on portfolio p
Rm :the expected market return
αp and βp: constants specific to the portfolio
εpt: random error for the portfolio in period t
                                                31



This approach assumes that the portfolio and thus the return is not affected by economic or
sector factors but only by the market return.
The CAPM assumes that all investors hold the market portfolio in their attempt to optimize
their stock portfolio. If the stock A is weighted with 1% in an individual portfolio, it will
compromise 1% in the market portfolio due to homogeneous expectations of the market
participants. If a stock B is not included in a portfolio its market price will fall. As its price
falls, at some point the stock will become more attractive and it will be added to the market
portfolio. The price adjustment process guarantees that all stocks are included in the market
portfolio. The market portfolio is on the efficient frontier. The Capital Market Line (CML)
joins the risk-free rate and the M. The optimal portfolio depends on the investors risk atti-
tude which decides on the combination of investment in M and the risk-free rate which de-
termines the expected return:


                                E (Rp) = rf + (E (Rm) – σp) / σm


If market participants invest in the market portfolio, they will earn a risk premium which
compensates them for the additional risk of the market portfolio compared to the risk-free
investment in Treasury bills. The expected risk premium is calculated on the β and the ex-
pected risk premium on the market.


                                       r – rf = β (rm – rf)




In competitive markets, the expected risk premium varies in direct portion to ß. Therefore,
it is assumed that each investment lies on the security market line. This line connects the
Treasury bills and the market portfolio.
The β being a measurement of the sensitivity of the indirect property returns to the market
return. Is β >1 stocks tend to amplify the overall movements of the market. Is 0< β <1
stocks move in the same direction as the market but not as far.
                                               32



6.2.3 Application for the Model in this Case
The β is calculated using the EPRA Total Return Index as the market risk because it covers
the European indirect property market.

6.3 Additional Figures

6.3.1 Average Return
The average return for portfolios has already been described in this chapter. The average
return for the monthly data of the EPRA Indices, the GBI and the stoxx 600 is calculated as
arithmetic averages. The arithmetic average return is slightly higher than the compounded
average return. Although, a more cautious calculation is advantageous, the arithmetic ap-
proach is used because the calculation is based on historical returns (Brealey and Meyers
(2000), P. 157).

6.3.2 Standard Deviation
The standard deviation for portfolios has already been described in this chapter. The stan-
dard deviation for the monthly data of the EPRA Indices, the GBI and the stoxx 600 is the
square root of the variance:


                                     rm = √ variance (rm )
                       variance (rm ) = the expected value of (rm – rmm)2
                                  = 1 / (N – 1) ∑ (rm – rmm)2


N : number of observations
∑ : sum from t = 1 to N
rm : market return
rmm : mean of the market return rm
(Brealey and Meyers (2000))
In order to stress the importance of the relationship between risk and return, a risk and re-
turn diagram is analysed for all financial assets.
                                               33



6.3.3 Sharpe Ratio
The Sharpe ratio provides risk-adjusted excess returns. The larger the Sharpe ratio, the bet-
ter the risk-adjusted performance. It is the investment standard for assessing risk-adjusted
performance. It is a direct measure of reward to risk.


                                                    _
                                  Sharpe index = (R – Rf) / s
_
R : average return for investment
Rf : average risk-free rate
s: risk for investment option

6.3.4 Tracking Error
The tracking error is a measure of volatility compared to the benchmark. A financial asset
with a low tracking error is more likely to create returns similar to the benchmark than the
financial asset with a higher tracking error. The formula for the tracking error is:


Tracking error = (standard deviation of asset A * standard deviation of benchmark B *
                   correlation between asset A and benchmark B)1/2


For this study two different benchmarks have been chosen:
a) The EPRA Total Return Index because it is assumed that European indirect property per-
forms similar. This assumption is based on the correlation matrix.
b) On the other hand indirect property is also influenced by the performance of the capital
market. Therefore, a second benchmark, the stoxx 600, has been chosen.

6.3.5 Information Ratio
The information ratio gives the amount of excess return generated per unit of risk or track-
ing error added. The higher the ratio, the better for the investor.
The formula for the information ratio is:
                                                   34



                                          _
                 Information ratio = (R – standard deviation) / tracking error


The information ratio is calculated for two different benchmarks (see chapter 6.3.4).

6.4 Data Preparation
For this study the relevant time period is defined between January 1999 and today. Due to
limited data the research beriod is limited from January 1999 to April 2002.

6.4.1 Transformation into Monthly Data
The EPRA, the risk-free rate, the bond and the stoxx 600 Indices have been published on a
daily basis. In order to reduce the complexity of the calculation, the daily data is trans-
formed into monthly data. Therefore, the published data is divided through the number of
trading days. Although the research period was defined between January 1999 and April
2002, the data for December 1998, which was published in Euro, is also part of the calcula-
tion because this month will represent the base of the indexation.
The transformation into monthly data decelerates the reflection of upward and downward
trends but also eliminates coincidental and therefore irrelevant deviation from the stock
price.

6.4.2 Indexation
The indexation is done on the monthly data. The base data is December 1998 with a value
of 1000 for all Indices.
The following formula is used:


                                    Vn, t+1 = Vt+1 / Vt * 1000 t


Vn, t+1 : value of the indexation indices in t+1
Vt+1 : value of the original indices in t+1
Vt : value of the original indices in t
1000 t : base value of the indexation indices
                                            35



6.5.3 Performance graph
In order to give a brief overview of the general performance of the indices, two perform-
ance diagrams are constructed:
   1. The performance trend of all relevant EPRA indices
   2. The performance trend of the EPRA Total Return Index, EPRA Total Return Index
       excluding the UK, EPRA Euro Zone Return Index, EPRA Germany Return, GBI
       and stoxx 600.


7 Sources of Data

7.1 EPRA Indices

7.1.1 The Company
EPRA Index is the only representative and independent European real estate index avail-
able in Europe. It was created due to the demand from investment managers for an inde-
pendently and real-time managed pan-European real estate equity benchmark.
EPRA aims at providing European public real estate companies with effective and continu-
ous leadership in matter of common interest. EPRA pursuits the development of general
and acceptable reporting disclosure, ethics, and industry practices. EPRA is not a discipli-
nary body but it will actively encourage its members, the government and regulatory bodies
to comply with its policies. According to Cohen (2002) its most continuous recommenda-
tion is that income statements should include unrealised gains and losses on property and
that the recommendations by EPRA are most welcome especially after the bankruptcy of
Enron. As Cohen, Norma (1999) states EPRA´s goal is to make the financial statements of
European public real estate companies clearer, more transparent and comparable across
Europe in order to approve the acceptance amongst the investment community. Those im-
provements will lead to an improving insight in the real estate performance which will en-
hance the popularity of investing in real estate and thus increase market capitalization. To
encourage a better reporting quality EPRA introduced the Award for the Best Annual Re-
port. (www.epra.com)
                                              36



7.1.2 The EPRA Europe Series
The EPRA Europe Series publishes price and total return indices mainly in US Dollar, Euro
and GBP:
EPRA UK,
EPRA Schwitzerland,
EPRA Sweden,
EPRA Spain,
EPRA Portugal,
EPRA Norway,
EPRA Netherlands,
EPRA Italy,
EPRA Ireland,
EPRA Germany,
EPRA France,
EPRA Finland,
EPRA Denmark,
EPRA Belgium, and
EPRA Austria.
Moreover, the EPRA Total Return Index, the EPRA Euro Zone, and the EPRA Ex UK are
published.
In order to get included to the EPRA European Series a European real estate company has
to meet some basic rules:
First, the company must have a total free float market capitalization above 50m € for
Europe. Second, the company must have a traded volume, over a three month annualized
period, above 25 m €. Third, the real estate company must drive at a 75 % of EBITDA from
relevant real estate related activities and set of annual accounts must be produced in Eng-
lish. Fourth, all companies must be publicly traded on an official stock exchange in one of
the countries listed in Europe.
Special criteria’s are set for some real estate companies:
Companies engaged in the operation of hotels or serviced offices are excluded from the
EPRA European Series. Companies engaged in the ownerships of hotels or nursing homes
                                                37



are only included if at least 75% of last years EBITDA was received from rents paid by, or
of shares of profits made by unrelated operators. Companies engaged in the ownership of
hotels are included if 50% of the last years EBITDA was earned from relevant real estate
activities, or if at least 50% of the companies assets is accounted for by real estate other
than land held for the development of homes for sale. Companies engaged in the credit-bail
leasing of real estate are only included if at least 75% of their last years EBITDA was de-
rived from relevant real estate activities.


The value of the EPRA Europe Series is calculated using the official closing share prices
from the home exchanges of all securities. The Indices are weighed by the market capitali-
zation of a company’s ordinary shares without accounting any potential dilution. To
achieve the fee float weight adjustment, the weight of the company is adjusted to take into
account the freely traded portion of the company’s market capitalization.
The capital index calculation method:
                n

Index value = ∑ xi * wi * fi * xri / d
               i=1


n: number of securities in the index
xi : latest trade price of the ith component security
wi : weighting for the ith component stock
fi : free float weighting adjustment
xri : exchange rate for the ith component security
d: total issued share capital of the index at the base date
The market capitalization of the member companies in the EPRA Index is different from
the current amount quoted on the local stock exchange since the EPRA Index committee
only meets on a quarterly basis to review the constituents and their weights.


The total return index calculation method:
                          n

Gross Xd Adjustment = ∑ gi * wi * fi * xri / d
                          i=1
                                              38



gi : gross dividend per share of the ith component security


TRt = TRt-1 ((IVt + XDG) / IV t-1)


TRt = total return index value today
TRt-1 = total return index value yesterday
IVt = underlying capital index today
IV t-1 = underlying capital index yesterday
XDG = gross Xd adjustment to underlying capital index

7.2 Dow Jones (DJ) Stoxx 600

7.2.1 The Company
STOXX Limited provides and services the Dow Jones StoxxSM indexes. It is Europe's lead-
ing regional equity indexes and was launched in 1998. The indexes cover the European
equity markets in several complementary ways, i.e. by region, by size, by sector, and now
also by style.
The DJ stoxx 600 was launched as a response to the EMU. It aims to provide a complete
and fully integrated family of market indicators for the European market in order to in-
crease the liquid measurement of the pan-European market. The development and delivery
of these indexes enhance the investment, tradability and transparency of financial assets.
STOXX Limited is a joint venture between Deutsche Börse AG, Dow Jones & Company,
and SWX Swiss Exchange.

7.2.2 The Dow Jones (DJ) Stoxx 600 Index
This Index is used as a benchmark because it is representative for all European countries as
it is produced from 600 companies: 200 large, 200 mid, and 200 small companies of the
Dow Jones Stoxx TMI. The DJ stoxx 600 covers
Austria,
Belgium,
Denmark,
Finland,
                                                39



France,
Germany,
Greece,
Ireland,
Italy,
Luxembourg,
The Netherlands,
Norway,
Portugal,
Spain,
Sweden,
Switzerland, and
the UK.
It serves as the basis for four regional sub indices: the Dow Jones EURO Stoxx, the Dow
Jones Stoxx ex UK, the Dow Jones Stoxx Nordic and the Dow Jones Stoxx ex EURO.
The DJ STOXX 600 is weighed at a free-float market capitalisation. The adjusted free-float
counts € 3,388.57 bill. The index is reviewed on a quarterly basis.
The index formula is:


Indext = Mt / Bt * base value


Base value: 1,000 for style and blue chip indexes; and 100 for all other indexes on the rele-
vant base date
Mt : free float market capitalization of the index time t
Bt : adjusted base data market capitalization of the index at time t
 B




         n

Mt = ∑ pit * qit * xit * fit
     i=1


pit : stock price i at time t
qit : number of shares of company i at time t
                                                     40



xit : cross rate: domestic currency in euros of company i at time t
fit : free float factor of company i at time t


          n

Bt = Ct * ∑ (pi0 * qi0 * xi0 * fi0 )
 B




          i=1


Ct : adjustment factor for base data market capitalization
pi0 : closing price of stock i on the base date
qi0 : number of shares of company i at time t


Index divisor adjustment:


D t+1 = Dt * (∑ (pit * qit * fit ) +/- ∆ MCt+1) / (∑ (pit * qit * fit ))


D t+1 : divisor at time t+1
Dt : divisor at time t
∆ MCt+1 : free float market capitalization calculated with adjusted closing prices and new
number of shares at time t+1 minus free float market capitalization calculated with closing
prices and number of shares at time t (only for companies with corporate actions effective
at time t+1)


The input data sources for the index calculation include trading platforms, related service
providers, regulatory agencies and companies in the investable stock universe.
(www.stoxx.com)

7.3 Bond Indices
JPMorganís European Government Bond Index ‘was first launched in 1989 and has since
grown to be the most widely used benchmark and vehicle for global investors in developed
government bond markets. The GBI Index consists of issues from 13 international bond
markets and its constituents have remained unchanged over time. Chart 1 shows the com-
position of the GBI Global in December 2001. The JPMorgan Government Bond Indices
                                               41



consist of regularly traded, fixed-rate, domestic government bonds of countries that offer
opportunity to international investors. These countries have liquid government debt mar-
kets, which are stable, actively traded markets with sufficient scale, regular issuance and
are freely accessible to foreign investors.
The universe of bonds specifically excludes:
- floating rate notes
- perpetuals
- bonds with less than one year to maturity
- bonds targeted at the domestic market for tax reasons
- bonds with callable, puttable or convertible features to international investors’ (JP Mor-
gan, 2002)

7.4 The Risk-Free Rate
As the risk-free rate the EURIBOR sets the prime rates for the European private banks. The
risk-free rate was identified for the research period and the medium average was calculated.


8 Results and Discussion

8.1 Empirical Results

8.1.1 Performance Trends
Performance Trend of the EPRA Indices:
From figure 6 it can be concluded that the European EPRA indices range between € 800
and € 1.200. The EPRA Italy Return Index has been outperforming with its peak of €
2,124.27 in January 2001. After a slight performance decrease between November 2001
and March 2002, the EPRA Italy Return Index has been increasing again and was the best
performer in April 2002. The EPRA Sweden Return Index and the EPRA UK Return Index
closed as top performers in April 2002 as well. The performance of the EPRA Denmark
Return Index and the EPRA Germany Return Index has been above average until July
2001. Ever since the indices have experienced a downward trend. The EPRA Denmark Re-
turn Index closed with € 818.45 in April 2002 as the worst European EPRA Index, although
the indices outperformed Italy with € 1,900.93 in June 2001. Belgium, Portugal, Norway,
                                             42



Finland and Switzerland have constantly ranged around € 1,200. The EPRA Total Return
Index and the EPRA Total Return ex UK have steadily been growing, whereas the EPRA
Total Return ex UK has been performing worse than the EPRA Total Return Index.


Performance Trend of Financial Assets:
The performance trend of all financial assets (compare figure 7) includes the GBI, stoxx
600, EPRA Total Return Index, EPRA Total Return ex UK, EPRA Euro Zone Return Index
and the EPRA Germany Return Index. The EPRA Germany Return Index and the stoxx
600 have a similar trend although indirect property has been performing better between Mai
1999 and January 2000 as well as between February 2001 and April 2002. In April 2002,
the highest total return was derived from the EPRA Total Return Index, followed by the
EPRA Germany Return Index and the EPRA Total Return ex UK. The stoxx 600 followed
by the GBI closed with the lowest total return indices.

8.1.2 The Capital Asset Pricing
The β of the European Indices compared to the EPRA Total Return Index as the representa-
tive market return are shown in table 2. It is noticeable that the β of many indices is higher
than “1”, therefore, Italy, Belgium, Finland, Norway, Spain, France, Germany and Ireland
tend to amplify the overall movements of the EPRA Total Return Index. This can be advan-
tageous if the market is on an upward trend but it can be risky if the market is on a down-
turn. The UK, Sweden, Denmark and the Netherlands have a β that is smaller than “1” but
higher than “0”. In these countries the indirect property performance moves in the same
direction as the market return but not as far. This can be advantageous if the general market
is on a downward trend.

8.1.3 Additional Figures
Risk and Return
In the risk and return diagram shows the average return and the standard deviation of the
assets between January 1998 and April 2002 (compare table 3 and figure 8). The EPRA It-
aly Return Index has the highest average return of 2.06% with the highest standard devia-
tion of 6.64%, followed by Sweden with an average return of 1.67% and the UK with
1.48% but both with a lower standard deviation. As expected the GBI has the lowest stan-
                                              43



dard deviation combined with a low average return. Belgium and Norway have lower aver-
age returns than the GBI. The three countries have a higher standard deviation than the
GBI, although their average return is similar to the GBI. In the diagram Denmark has the
highest average risk of 6.96% and a negative average return. The stoxx 600 has a similar
standard deviation to Denmark but it compensates the investors with a higher average re-
turn then the EPRA Denmark Return Index.
The risk/return ratio is positive for all the financial assets except for the EPRA Denmark
Return Index, which counts -27,38%.


Sharpe Ratio
The Sharpe ratio is negative for all assets in the study (compare table 4).


Tracking Error
a) The Benchmark is the EPRA Total Return Index
Sweden, the UK, Spain and Ireland have the highest tracking error around 3% (compare
table 4). An indirect property investment in those countries has the highest volatility around
the EPRA Total Return Index. However, a higher volatility might also lead to a higher re-
turn which can be attractive if the assets are not bought for diversification as the average
return of the EPRA Total Return Index is only 1.02%. The EPRA Portugal Return Index,
the EPRA Belgium Return Index and the EPRA Switzerland Return Index have a tracking
error under 2%, therefore, an investment in those countries offers the lowest volatility and
is more likely to create returns similar to the EPRA Total Return Index. A financial asset
with a low tracking error is more likely to create returns similar to the benchmark


b) The Benchmark is the stoxx 600
The calculation of the tracking error using the stoxx 600 as the benchmark led to a result
slightly under 4% for the EPRA Denmark Return Index, EPRA Italy Return Index and the
EPRA Germany Return Index (compare table 5). Therefore, an investment in those assets is
more likely to create returns different from the stoxx 600. On the one hand this could be
advantageous if the investment in the indirect property exceeds the average return of the
stoxx 600 with only 0.87%, on the other hand the deviation might also be unattractive if the
                                              44



asset’s performance behaves in reverse (negative return) like Denmark. The lowest tracking
error has been identified for the EPRA UK Return Index, EPRA France Return Index,
EPRA Finland Return Index, the EPRA ex UK Return Index and EPRA Sweden Return
Index. Therefore, an investment in those assets is more likely to create similar returns to the
stoxx 600. No tracking error could be calculated for Belgium and Switzerland because it is
mathematically not possible to calculate a root out of a negative figure.


Information Ratio:
a) Information ratio for the EPRA Total Return Index as benchmark
The information ratio is negative for all investment options in indirect property. The lowest
information ratio was found for the EPRA UK Return Index and for the EPRA ex UK In-
dex.


b) Information ratio for the stoxx 600 as benchmark
The information ratio is negative for all investment options in indirect property. The lowest
information ratio was found for the EPRA Germany Return Index and for the EPRA Neth-
erlands Return Index. Due to the missing result of the tracking error, no information ratio
could be calculated for Belgium and Switzerland.

8.1.4 Correlation Matrix
The correlation matrix was calculated for all investment possibilities (compare table 6). A
negative correlation was found for the combination of the stoxx 600 with indirect property
in Spain, Belgium, Finland or Portugal. The EPRA Belgium Return Index has a negative
correlation with all investments except for Switzerland, Spain and the Netherlands. The
correlation between Belgium und the stoxx 600 of nearly -0.8 is the most negative correla-
tion in the matrix. If an investor aims to diversify the risk of the GBI, he should not invest
in the stoxx 600 and to the EPRA Norway Return Index because they are positively corre-
lated to the GBI. The performance of the EPRA Norway Return Index is reverse to the ma-
jority of the investment possibilities with the most advantageous correlation of -0.49 for
Portugal. The highest positive correlation of almost 1 was found for the EPRA ex UK In-
dex in combination with Sweden, France, Ireland, the UK and the Netherlands. An invest-
                                               45



ment combination of those financial assets is not likely to diversify investment risk. The
EPRA UK Return Index combined with the EPRA Sweden Return Index, EPRA France
Return Index, EPRA Netherlands Return Index, EPRA Ireland Return Index, EPRA ex UK
Index and the EPRA Total Return Index has also a correlation of nearly “1”. Indirect prop-
erty in Germany is only negatively correlated to Portugal, Finland and Belgium.

8.1.5 The Result of the CAPM
Figure 30 to 31 demonstrate the efficient frontiers and asset allocations of all combinations.
In figure 32 it is obvious that the combination of indirect property from Italy, Germany and
the Netherlands with the stoxx 600 and the GBI creates an efficiency curve that is higher
than the efficiency curve of GBI, stoxx 600 and EPRA Germany Return Index. A higher
return with a constant portion of risk can be derived from investing in Italy, Germany, the
Netherlands, the stoxx 600 and the GBI.
The combination of the assets leads to a minimization of risk and a maximization of re-
turns, compare table 7. The highest average return for the portfolio was derived from sev-
eral asset combinations:
1. the stoxx 600, the GBI, the EPRA Germany Return Index and the EPRA Sweden Return
Index,
2. the stoxx 600, the GBI, the EPRA Germany Return Index and the EPRA UK Return In-
dex, and
3. the stoxx 600, the GBI, the EPRA Germany Return Index and the EPRA Italy Return
Index.
The lowest risk was identified for the following portfolios:
1. the stoxx 600, the GBI and the EPRA Total Return Index,
2. the stoxx 600, the GBI, the EPRA Germany Return Index and the EPRA Finland Return
Index, and
3. the stoxx 600, the GBI, the EPRA Germany Return Index, the EPRA Finland Return In-
dex, the EPRA Belgium Return Index and the EPRA Portugal Return Index.
The third portfolio offers an investor the lowest risk of all.
Compared to a portfolio that consist only of the stoxx 600 and the GBI, it is more advanta-
geous for an investor to invest in a diversified portfolio.
                                              46



8.2 Practical Implications
The results of the study are that indirect property can serve indeed as a diversification tool.
The indirect property performance varies between the countries. In Italy, Sweden and the
UK an upward trend was identified. However, indirect property in those countries is also
more risky. A downward trend was identified for Denmark and Germany. Germany has an
average return and standard deviation that is moderate, whereas Denmark’s average return
is even negative.
On average, the performance of indirect property was better than the performance of the
stoxx 600 and the GBI. Although the stoxx 600 consists of a high number of companies
from different industries and countries, it does not perform better than European indirect
property. The reason could be the economic downturn since September 11th in 2001. There-
fore, it is even more impressive. An investor can diversify his stock market risk through
adding indirect property to his portfolio. Indirect property in Belgium, Portugal, Finland
and France is negatively correlated to the stoxx 600 and will perform positively in a market
downturn. Furthermore, the remaining indirect property indices have a low positive correla-
tion to the stoxx 600.
To conclude, an investor can benefit from indirect property in his portfolio. He can render
his investment less volatile and/or more profit-yielding. Although experts expected capital
markets to grow to a common European market, the conclusion of this analysis is that di-
versification tools are still available.
Although the result of the analysis is able to identify diversification benefits, the applied
models have a number of unrealistic assumptions such as the existence of a perfect market.
This may lead to a bias of the results. Moreover, the data sample is limited. On the one
hand, the research period covers only two years, on the other hand the number of indirect
property companies participating in the EPRA Index is limited because the importance of
indirect property has been misconceived by many investors. Additionally, the data is not
representative because indirect property is basically hold by institutional investors or ma-
jority shareholders. This has an effect on the trading volume which is limited, therefore the
liquidity of indirect property is also limited. As the shares are not traded frequently, the
transaction costs might be higher than in general. This factor is not incorporated in the
CAPM nor in the MPT. The transactions costs might eliminate the benefits of diversifica-
                                               47



tion. Moreover, a limited trade volume influences the share prices. Those changes in the
share price might be higher than in the stock market. However, they have been eliminated
through the transformation from daily data into monthly data and are not incorporated in
this analysis. Therefore, an investor has to consider this effect if he invests in indirect prop-
erty.

8.3 Conclusion
The diversification benefits of indirect property in a European portfolio have been analysed
in this research. The importance of this study is justified due to recent economic and politi-
cal changes in Europe. The European Union and the European Monetary Union have influ-
enced the performance of financial assets on the capital market. Removed trade barriers and
eliminated currency risk offer investors new investment strategies. The downturn of the
market since September 11th 2000 has rendered investors more cautions, searching for new
diversification tools.
Using the MPT and the CAPM, the studies result is that diversification benefits in the
European indirect property market exist and that they can be useful tools for investors to
increase their return and/or reduce their portfolio risk. Although, the EU and the EMU have
had an impact on the economy, legal and political situation of the member states, it has not
eliminated diversification benefits and turned the capital markets to one common European
market. Nevertheless, an investor has to take transaction costs into account when investing
in indirect property. Transaction costs might be relatively higher for some investments as
the trading volume might be restricted.
The question is how long diversification tools will be available to investors. This question
implicates the need for further studies in this area and the need to observe future develop-
ments on the stock and indirect property market. Moreover, an analysis that compares the
benefits of diversification before and after the EMU would be a good approach to predict
future developments.

				
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