Johan Christian Hilsted

MASTER THESIS, FALL 2012CAND.MERC. APPLIED ECONOMICS AND FINANCE

COPENHAGEN BUSINESS SCHOOL

AUTHOR: JOHAN CHRISTIAN HILSTEDDATE OF SUBMISSION: DECEMBER 14TH 2012

ACTIVE PORTFOLIO MANAGEMENT AND PORTFOLIO CONSTRUCTION

- IMPLEMENTING AN INVESTMENT STRATEGY

SUPERVISOR: JEPPE SCHOENFELDT

NUMBER OF PAGES: 77

NUMBER OF CHARACTERS: 145.260

SIGNATURE:

Active Portfolio Management and Portfolio Construction Implementing an Investment Strategy

1

Abstract

This thesis aims at creating an investment strategy for active portfolio management to outperform the

MSCI Denmark from 1992 to 2011. The index development of the Danish stock market has been quite

impressive as it has performed remarkably better than other national indices. It is therefore interesting

to investigate whether active portfolio management constitutes a winning strategy superior to investing

in the MSCI Denmark.

There is no generally accepted approach to conduct active portfolio management. This thesis approaches

the subject by comparing two internationally diversified portfolios to the MSCI Denmark as benchmark -

one portfolio submitted to a 20% maximum asset representation restriction, the other portfolio left

unrestricted.

From investment strategy we conclude that combining strategic and tactical asset allocation constitutes

an appropriate investment strategy for active portfolio management, as it limits the long-term portfolio

investment opportunities and allows for short-term portfolio repositioning. The information ratio

constitutes the performance measure of active portfolio management, as it optimizes portfolio

construction by comparing expected returns of portfolio and benchmark the residual return. The Capital

Assets Pricing Model (CAPM) was utilized for return estimations for both investment opportunities and

benchmark. Mean-variance portfolio construction was conducted based upon investment opportunities

expected to outperform the benchmark.

The MSCI Denmark provides realized average monthly return of 0,65%, while the actively managed

portfolios produce average realized monthly return of 0,34% and 0,37%, respectively. In that regard,

active portfolio management has not outperformed the benchmark, and statistical findings cannot suggest

portfolio timing skill. However, considering the systematic risk adjusted return, both portfolios yield

significant alpha, or value added, with the unrestricted portfolio being the best performing portfolio.

In conclusion, active portfolio management cannot produce higher return than the MSCI Denmark, but has

proven to benefit the investor, as the market risk exposure justifies both inferior and superior portfolio

return to the benchmark.


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Table of Contents

Abstract .......................................................................................................................................... 1

1. Introduction ................................................................................................................................ 4

1.1 Research Objectives ................................................................................................................................... 6

1.1.1 Superior Research Objective ................................................................................................................... 6

1.1.2 Subordinate Research Objectives ........................................................................................................... 6

1.2 Structure of Thesis...................................................................................................................................... 7

1.3 Methodology .............................................................................................................................................. 8

1.3.1 Financial Assets and Risk ......................................................................................................................... 8

1.3.2 Applied Theoretical Approach ............................................................................................................... 10

1.3.3 Interviews .............................................................................................................................................. 11

1.4 Assumptions and limitations .................................................................................................................... 12

1.4.1 Assumptions .......................................................................................................................................... 12

1.4.2 Limitations ............................................................................................................................................. 13

1.5 Data .......................................................................................................................................................... 14

1.5.1 Equity Sector Return Data ..................................................................................................................... 14

2.Investment Strategy ................................................................................................................... 18

2.1 Investment Strategy as the Source of Portfolio Performance ................................................................. 18

2.2 Strategic Asset Allocation ......................................................................................................................... 19

2.2.1 Discussing Empirical Findings and Brinson et.al. ................................................................................... 21

2.3 Tactical Asset Allocation ........................................................................................................................... 23

2.4 Professional Views upon Asset Allocation ............................................................................................... 24

2.5 Benchmark and Investment Opportunities .............................................................................................. 25

2.5.1 Benchmark............................................................................................................................................. 26

2.5.2 Investment Opportunities ..................................................................................................................... 27

2.6 Crafting the Investment Strategy ............................................................................................................. 30

3.Active Portfolio Management ..................................................................................................... 33

3.1 Defining Active Portfolio Management .................................................................................................... 33

3.2 Performance Measure and Portfolio Added Value .................................................................................. 34

3.2.1 Information Ratio .................................................................................................................................. 34

3.2.2 Portfolio Value Added ........................................................................................................................... 35


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4.Risk and Return in Active Portfolio Management ........................................................................ 38

4.1 Expected Return in Active Portfolio Management .................................................................................. 38

4.1.1 Asset Pricing in an Active Setting .......................................................................................................... 38

4.2 Risk Management ..................................................................................................................................... 46

4.2.1 Investor Utility ....................................................................................................................................... 47

4.2.2 Professional Views upon Risk and Risk Management ........................................................................... 47

4.2.3 Risk Management and Risk Factors ....................................................................................................... 48

4.2.4 Financial Risk ......................................................................................................................................... 49

5.Portfolio Construction ................................................................................................................ 51

5.1 Objective of Portfolio Construction ......................................................................................................... 51

5.2 Choice of Portfolio Model ........................................................................................................................ 51

5.3 Mean-Variance Application in an Active Setting ...................................................................................... 52

5.3.1 The Model ............................................................................................................................................. 53

5.3.2 Model Short-Comings ............................................................................................................................ 55

5.3.3 Portfolio Repositioning and Transaction Costs ..................................................................................... 60

5.4 Model Performance ................................................................................................................................. 63

5.4.1 Sector Distribution ................................................................................................................................ 63

6.Performance Evaluation of the Investment Strategy ................................................................... 67

6.1 Return-Based Performance Analysis ........................................................................................................ 67

6.1.1 Cross-Sectional Comparison .................................................................................................................. 67

6.1.2 Market Timing ....................................................................................................................................... 69

6.2 Analysis of Value Added ........................................................................................................................... 71

7.Conclusion ................................................................................................................................. 75

8.References ................................................................................................................................. 78

9.Appendix Overview .................................................................................................................... 81

Appendix 1: Glossary ...................................................................................................................................... 82

Appendix 2: Sector Market Value and Correlation Matrix of Sector Return ................................................. 86

Appendix 3: Interview Guide .......................................................................................................................... 87

Appendix 4: Active Return and Testing for Return Stationarity..................................................................... 89

Appendix 5: Expected Residual Return .......................................................................................................... 95

Appendix 6: Portfolio Positions of Investment Opportunities ....................................................................... 97


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1. Introduction A common objective of the portfolio investor is to achieve a higher portfolio risk adjusted return as

opposed to investment in a single asset. Combining assets into a portfolio carries the opportunity of risk

reduction and at the same time acquiring a higher return compared to single asset investment.

As financial markets experience different phases, different regimes reside in the markets and many

investment portfolios incur both losses and gains if it is not managed in accordance with the investors

expectations to future market developments. For long-term investments such as pension investments,

incurring losses in the short term is of little concern as the investment time frame allows for the

opportunity to reduce such losses by gaining future positive returns. However, for some investors, in

practice, this is not a feasible strategy since they are constrained by consumptions and liabilities.

Accordingly, investors need to liquidate some of their investments in order to fulfill financial needs and

obligations. In other words, the investor buys and sells stocks, and the basis of this decision is the

conviction that abnormal investment returns can be gained. However, the efficient market hypothesis,

which can be traced back to Samuelson (1965) and Farma (1970), states that market prices incorporate all

information rationally and instantaneously, eliminating the possibility for the investor to achieve abnormal

returns and should this hypothesis hold in practice, the only optimal portfolio strategy would be to

conduct portfolio investment and hold the portfolio throughout a predetermined time frame1 2.

However, assuming stock markets are not efficient, in terms of market paradigm we turn to the adaptive

market hypothesis by Lo (2004) who acknowledges the problematic issue of the assumption of market

efficiency3. This paradigm carries some implications that necessitate portfolios to be actively managed.

First, a relationship between asset risk and return exists, but is unlikely to be stable over time. Second,

arbitrage opportunities arise over time. A third implication is that investment strategies might not perform

equally well in different economic environments. A fourth implication is survival, which is enabled by

evolving markets and financial technology. This thesis will not seek to investigate the extent of these

implications but yields an important conclusion: a portfolio has to be actively managed. The most

1 Samuelson (1965): p. 43

2 Farma (1970): p. 383

3 Lo (2004): p. 18


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important reasons are the changing market behavior, and the advances in market research which will lead

to improved tools in portfolio management.

Active portfolio management is a widely used concept where investors compare their investment

performance to the market or a benchmark portfolio in order to determine whether their investment

decision has yielded a higher return than either of these. Commonly applied benchmarks in active

portfolio management are large and highly liquid indices such as the S&P 500 or the Dow Jones Index. In

addition, the investment opportunities are usually limited to the underlying stocks of that benchmark

categorized into sectorial based indices. The advantage of this approach is that the benchmarks underlying

indices are likely to follow a somewhat similar return pattern as the overall market, making it less difficult

to allocate portfolio assets. We will in this thesis deviate from this approach, as we apply the MSCI

Denmark as benchmark and ten globally based sectorial indices as investment opportunities subjected to

active portfolio management.

In order to assemble optimal portfolios, Harry Markowitz (1952)4 introduced the concept of efficient

portfolio, which either optimizes the return of an asset or minimizes the risk of the asset for a given level

of return. The concept is realized by diversifying assets in a portfolio, which is achieved by investing in a

variety of different stocks that change differently in relation to each other stocks with low covariance.

Therefore, as the results of this thesis are of a theoretical nature, the aim is to apply financial modeling of

Markowitz modern portfolio theory, in order to solve the optimal portfolio construction problems. With

regards to portfolio optimization another important topic is considered: Portfolio repositioning the

process of over- and underweighting portfolio assets on a periodic basis.

4 Markowitz (1952): p. 82


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1.1 Research Objectives

The following research questions will be answered in this thesis with regards to active portfolio

management.

1.1.1 Superior Research Objective

The research objective of this thesis is to devise an investment strategy by assembling a diversified

portfolio with the aim of outperforming the MSCI Denmark by altering positions of portfolio assets on a

short-term basis over a 20 year timeframe. The purpose of this investigation is to determine whether

return generated from such strategy is warranted by its systematic market risk. In that regard, the aim is

to determine whether active portfolio management is more attractive than high performing benchmark

investing on a long-term basis.

1.1.2 Subordinate Research Objectives

In order to accommodate the superior research objectives, a portfolio will be constructed, subjected to

active portfolio management and compared to the portfolios benchmark the MSCI Denmark. In order to

provide reliable results to support the conclusion, the following subordinate research questions must be

answered.

1. How does the mean-variance portfolio model conduct asset allocation in the context of active

portfolio management?

2. How does active portfolio management perform compared to MSCI Denmark between 1992 and

2011?

3. Does active portfolio management performance indicate investment skill on the part of the

investor?

4. With regards to portfolio and benchmark systematic risk, does active portfolio management add

value to the investor?


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1.2 Structure of Thesis

The approach to this thesis is based upon the structure illustrated in figure 1.1.

Figure 1.1: Structure of the Thesis

Figure 1.1 divides the content of the thesis into four sections, each containing underlying chapters.

References made will be with regards to the underlying chapters. This section will continue by explaining

the thesis methodological approach, the limitations imposed and applied data.

Section 2 will start by discussing of the concepts of strategic asset allocation and tactical asset allocation,

in order to frame the investment strategy necessary for the purpose of active portfolio management. It

will continue by providing theoretical considerations of determining and limiting the investment

opportunities available for portfolio construction. Such limitation is deemed necessary in order for the

mean-variance model to construct stable portfolios. Ten globally assembled sector Indices are considered

for active portfolio construction in addition to the MSCI Denmark. The active portfolio management

strategy attempts to outperform the MSCI Denmark by altering portfolio positions of the investment

opportunities. Based on empirical and practical findings with regards to Strategic and Tactical Asset

Allocation, a definition of active portfolio management is given and the importance of the definition of the

benchmark is highlighted. Additionally, appropriate performance measurements will be presented.

Chapter 1: Introduction Section 1: Introduction

Chapter 2: Investment Strategy

Chapter 3: Active Portfolio Management

Chapter 4: Return and Risk Management

Chapter 5: Portfolio Construction

Section 2: Areas of Focus and Theoretical Framework

Chapter 6: Portfolio Performance Evaluation Section 3: Analysis and Evaluation

Chapter 7: Conclusion Section 4: Conclusion


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The section continues by providing return estimates as input variables for portfolio construction. Based on

theoretical and practical findings, issues regarding the risk active portfolio management are exposed to

will be analyzed and evaluated. The section then concludes by applying the Markowitz mean-variance

portfolio model for portfolio construction. Implementation possibilities with regards to portfolio

repositioning are additionally presented and briefly discussed. The performance of the mean-variance

model in the context of active portfolio management will then be examined. First in terms of asset

allocation, i.e. whether the model has produced stable portfolios during portfolio repositioning. Second,

return estimates will indicate whether outperformance is present on a long-term basis.

Section 3 will present the results of the active portfolio management process. From the portfolio strategy,

the portfolio model presented in section 2 will have assembled portfolios based on the provided risk and

return estimates. This section therefore answers the questions of whether active portfolio management

has added value to the investment and whether these results are due to skill rather than luck.

Section 4 concludes by summarizing the answers to the research questions.

1.3 Methodology

1.3.1 Financial Assets and Risk

An enduring element regarding portfolio performance concerns the relationship between risk and return

on investments. A financial investment, in contrast to a real investment, which involves tangible assets

such as land and production facilities, is an allocation of money whose value is supposed to increase over

time. Therefore a security is a contract to receive prospective benefits under stated conditions like stocks

and bonds.

The two main attributes that distinguish securities are time and risk. Usually the interest rate or rate of

return (depending on whether the security is a bond or stock) is defined as the gain or loss of the

investment relative to the initial value of the investment. An investment always contains some sort of risk,

categorized into two types systematic and unsystematic risk, and the higher such risks the higher return

is demanded by investors.


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Financial assets are divided into two categories; traditional and alternative investments. Figure 1.2

summarizes the considered assets.

Figure 1.2 Financial Assets

The main traditional assets are cash, fixed income, equities real estate and foreign exchange. Cash is

assumed to be stored in a bank account, yielding an interest rate often referred to as the risk free rate.

Fixed income securities, are government or company issued securities with a year to maturity, issued with

the purpose of managing short-term cash needs. Two important money market interest rates are the

London Interbank Offered Rate (LIBOR), which is the interest rate at which large banks in London lend

money to each other. The other interest rate of importance is the Treasury Bill.

The long-term borrowing needs of corporations are met by issuing bonds. A bond contract provides

periodic coupon payments and the principal value at maturity of the bondholder5.

Stocks are issued by corporations which convey rights to the owners, as they can elect the board of

directors and have a claim of the earnings of the company. The shareholders are compensated with cash

dividends, whose amount is determined by the companys Management and Board of Directors. When

referring to stocks, publically traded stocks are considered, which are regulated by governments. The

process of arranging the sale of private stocks to the public market is called an IPO (Initial Public Offering).

In contrast, private equity refers to stocks held by private individuals or organizations.

5 http://www.investopedia.com/terms/b/bond.asp#axzz2CCmQC8CG

Traditional Investments Alternative Investments

Cash Hedge Funds

Fixed Income Managed Funds

Equity (stocks) Private Equity Funds

Real Estate Physical Assets (comodities, art etc)

Foreign Exchange Securitized Products (debt obligations etc)

Source: Own Creation

http://www.investopedia.com/terms/b/bond.asp#axzz2CCmQC8CG


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Real estate investments and foreign exchange derivatives are also found in portfolios, the latter for

hedging against currency risks. Alternative investments emphasize the widening spectrum of investment.

These types of investment are beyond the scope of this thesis.

Risk and return obviously depends upon the type of investment. In order to measure investment return on

a frequent basis we turn to equities, or stocks, as return can be realized at any point in time, preferable for

an investor who favors frequent trading. The risk of such investment is presented when positive or

negative return is realized upon trading. Hence, emphasis on risk and return is important to consider,

particularly in the context of active portfolio management, as the investor takes on the risk of frequently

realizing positive and negative returns.

The emphasis of the relationship between risk and return is reflected in the applied theoretical models.

These models are described below. As the research objective is based upon a practical exercise it

important to also include real-life methods and applications with regards to investment strategies.

Therefore, the methods and information provided by selected theoretical concepts applied is

supplemented by the input of two investment professionals. Their contribution to this thesis is described

subsequently to the applied theoretical approach.

1.3.2 Applied Theoretical Approach

Throughout the analysis the following theories will assist in performing active portfolio management.

The framework of the investment strategy will be established by the concepts of strategic and tactical

portfolio management. The investment opportunity set will be limited and the relevance of the

benchmark discussed.

In order to apply the mean-variance portfolio model, expected return estimates and risk measures for

each of the sector Indices suitable for the purpose of active portfolio management will be outlined. The

former will be calculated by use of the Capital Asset Pricing Model (CAPM) model. The advantage of

applying the CAPM model is that we can separate the market risk, beta and expected market return, of

each sector index, and in that manner compare risk and return of sectors and benchmark.


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Portfolio construction will be conducted by Markowitz mean-variance portfolio model as it optimizes

asset allocation in Excel based on performance ratios appropriate for the purpose of the investment

strategy6. Thus, optimizing with respect to the information ratio, which indicates relative benchmark

performance with regards to its residual risk, alpha, and residual return, beta, will lead to asset allocations

expected to provide the portfolio with a return superior to the benchmark. The asset allocation will be

conducted as a repetitive process.

1.3.3 Interviews

In order to limit the amount of assumptions made and to provide a practical point of view when

processing empirical data and applying theoretical models, interviews were conducted in order to uncover

relevant areas of study. Also, practical reviews were applied, as some exercised concepts of investment

theory carry universal definitions or conditions for execution.

Empirical and practical data have been obtained through interviews and consultation with two investment

professionals, who provided relevant information, relating to the research objective.

Peter Sjntoft, Vice President, Global Banking, Citigroup Global Markets Limited, London United

Kingdom

Peter Sjntoft has provided his personal viewpoints upon issues where elements of investment

theory seem difficult to apply in real-life investment strategies. Furthermore, he has provided

suggestions of where to challenge the application of these theories. He has assisted in adding

practical viewpoints in establishing the framework for active portfolio management, and

discussions regarding the use of investment strategies.

Claus Vorm, Senior Portfolio Manager, Nordea Investment Management, Copenhagen, Denmark

Claus Vorm has been responsible for establishing a team of investment specialists in charge of

managing Nordeas tactical asset allocation, as well as the banks quantitative products.

Furthermore, he has been responsible for managing various balanced portfolios.

Claus Vorm has contributed with insights into the use of the strategic and tactical asset allocation

processes in Nordeas investment strategies, which will be included when forming the investment

6 Benninga (2008): p. 338


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strategy for active portfolio management. His contribution also extends to views upon risk

management.

Peter Sjntoft and Claus Vorm were chosen with the purpose of providing a nuanced representation of

opinions concerning investment decisions, as well as contributing with informational groundwork for the

research objective. Their experiences and information has enabled continuous tightening of the research

objective. The interview with Claus Vorm was recorded and stored on the CD attached. Due to geographic

differences, interviews with Peter Sjntoft were conducted by phone, so no conversation was recorded,

and therefore no specific citations made. For interview guide, see Appendix 3.

1.4 Assumptions and limitations

In order to maintain a clear focus throughout the thesis it is necessary to define some assumptions and

limitations.

1.4.1 Assumptions

The theoretical discussion and the practical calculations with regards to the portfolio construction, will

take the point view of a Danish investor who has funds available for investments. In that regard

differences between investments by pension funds and private funds, including e.g. tax considerations and

consequences will not be discussed.

All calculations are conducted on the basis of monthly data, stated in US dollars from January 1992 to

December 2011. Data have been extracted from Datastream, MSCI Barra and Statistikbanken. Monthly

observations are opted for as opposed to e.g. daily observations as the former provides clear and

adequate information with regards to the development of the index prices and for sufficient data

management. The time period is considered appropriate as it provides a sufficient amount of data and it

covers significant economic events, affecting the financial markets.

With regards to the issue of transaction costs, we will assume that all transactions have equal expense

over the entire period. In addition, in order to limit the constraints to the mean-variance portfolio model,


13

the transaction costs will be deducted from the return on investment subsequent to portfolio

repositioning.

Finally, I will assume that markets are not completely efficient7. However, I will assume that the investor is

rational suggesting that he prefers more to less. Although market efficiency rests on the assumption that

investors are rational, its validity is not undermined by the investor not being rational, given he does not

trade randomly. In addition, all hedging of currency is completed by future contracts, meaning that only

index movement excluding currency behavior is considered. Moreover, the analysis will not incorporate

any tax effects. This is mainly because of the complexities of the Danish tax system. Furthermore, the

introduction of such a system is in conflict with the conditions of portfolio theory that leads to saying that

the investor should buy the market portfolio.

1.4.2 Limitations

1.4.2.1 Theoretical framework

In portfolio theory there are several models and applications appropriate for portfolio construction. Both

Markowitz (1952) and Black Litterman (1992) propose portfolio models applicable for portfolio

construction. The thesis will apply Markowitz mean-variance portfolio model, but argumentation and

justification for the choice of model will be provided. The model will be explained superficially, and

derivations will not be included when explaining the model, as I intend to present the model in the most

comprehensive manner possible.

Short sales will not be introduced throughout this thesis. The reason for this is that the mean-variance

model tends to incorporate extreme values in the asset positions when short sales are included providing

portfolios of poor applicability. Another reason is that major stock exchanges have unique short sales

regulations8. Furthermore, financial gearing is prohibited. Both assumptions contribute to portfolio

robustness, meaning altering investment positions are comparable with changes in return and covariance

estimates.

7 Shleifer (2000): p. 3

8 http://www.sec.gov/spotlight/keyregshoissues.htm

http://www.sec.gov/spotlight/keyregshoissues.htm


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1.4.1.2 Data

In order to construct a globally representative portfolio ten sector indices have been chosen, as they

represent a significant proportion of the world stock market. The indices are presented in chapter 1.5. The

MSCI Denmark and MSCI World Market indices are obtained from MSCI Barra9.

Before selecting the sector Indices I examined their historical returns, variances and covariance along with

the correlation and size of their market capitalization (see Appendix 2). The examination showed a

moderate pattern of a positive risk-return relationship among the sectors. Some of the sectors with the

highest risk-return payoff even had some of the lowest correlations towards other markets. The general

picture, however, showed high correlations among sectors leaving only a few inter-correlations below 0,5

suggesting high integration among sectors (only Technology showed correlation below 0,5). High market

integration is not an attractive property from perspective of investment theory as it constructs portfolios

based upon high return estimations and low covariance, hence low correlations. However, this scenario

highlights whether one major advantage in portfolio management, diversification, can provide the

portfolio with a higher risk adjusted return compared to the benchmark.

1.5 Data

In this chapter the definition and source of the equity sector return applied in the thesis are presented.

1.5.1 Equity Sector Return Data

There is a large industry of providing investors with benchmark data of sectors. They use Global Industry

Classification Standards (GICS) which operates with a ten sector classification (MSCI Barra, 2010): Energy,

Materials, Industrials, Consumer Discretionary, Consumer Staples, Healthcare, Financials, Information

Technology, Telecommunication Services, Utilities. These sector groups can again be classified into 24

industry groups, 68 industries, and 154 sub-industries10.

Equity return data in this thesis is obtained from Datastream and Morgan Stanley Capital International

(MSCI), since they offer data on world sector return covering the needed time periods. With regards to

9 http://www.msci.com/products/indices/country_and_regional/all_country/performance.html

10 MSCI Barra (2010): p. 82

http://www.msci.com/products/indices/country_and_regional/all_country/performance.html


15

Datastream, within each market, stocks are allocated to industrial sectors using the Industry Classification

Benchmark jointly created by FTSE and Dow Jones. The groups are formed from stocks registered on the

largest equity market in 53 countries and all sector Indices consist of 6 sub-indices. The data set divides

the market into 10 sector classifications (somewhat similar to the CICS): Basic Materials (BMATR),

Consumer Goods (CNSMG), Consumer Services (CNSMS), Financials (FINAN), Healthcare (HLTHC),

Industrials (INDUS), Oil & Gas (OILGS), Technology (TECHN), Telecommunications (TELCM) and Utilities

(UTILS)11. The basis for the selection of these sector Indices are based on a preference for global

representation, which is discussed further in chapter 2. Table 1.1 provides summary statistics of the ten

sector Indices along with the MSCI Denmark, based on monthly observations over the time period 1992-

2011.

Table 1.1: Summary Statistics Monthly Return

Table 1.1 indicates that Oil & Gas and Technology has provided the highest average monthly return over

the period. Technology and Basic Materials have been the most volatile sectors with a standard deviation

11

Datastream (2008): p. 3

Mean Std.dev. Max. Min. Obs

Panel A. Sector Indices

Basic Materials 0,43% 6,22% 18,97% -19,65% 240

Consumer Goods 0,47% 4,63% 12,62% -19,11% 240

Consumer Services 0,35% 4,36% 10,54% -30,06% 240

Finance 0,21% 5,64% 17,85% -12,11% 240

Healthcare 0,48% 3,44% 8,95% -27,41% 240

Industrials 0,47% 5,45% 15,70% -26,09% 240

Oil & Gas 0,67% 5,66% 15,53% -31,10% 240

Technology 0,69% 7,58% 19,98% -17,25% 240

Telecommunications 0,33% 5,31% 16,18% -16,89% 240

Utilities 0,26% 3,84% 8,74% -29,67% 240

Panel B. Benchmark Index

MSCI Denmark 0,65% 5,92% 16,79% -29,67% 240

Panel C. Market Index

MSCI World 0,34% 4,47% 10,35% -21,13% 240

Summary Statistics

Source: Own creation, Datastream, MSCI Barra


16

above 7% and 6%, respectively. Note, that market and benchmark indices are two different indices. When

referring to the benchmark, it is the MSCI Denmark targeted for outperformance, while referring to the

market relates to the MSCI World index. The latter will only be applied for return calculations and

systematic risk estimations. From Appendix 4 all indices are concluded to be stationary indicating that

positive monthly returns are likely to be followed by negative return and vice versa, which in fact

complicates active portfolio management, as it makes the decision of market timing rather difficult. This

problem will be addressed with regards to portfolio construction in chapter 5.

Within the literature of stock returns there is no general convention regarding the use of simple and log-

returns. For example Campbell and Thomson (2008) use the simple mean approach while Benninga (2008)

argues log-returns, which is marginally more precise when modeling assets in Excel1213. Therefore, the

monthly return data is calculated as log-returns, and these returns are applied throughout this thesis. The

simple and log-return methods were tested on a few sector indices and only small differences were found.

Thus, we do not expect the conclusions to be significantly different if simple returns had been used

instead.

Equation 1.1 shows the total return of sector i held from time t-1 to time t. The total return constitutes the

dividends and capital gains. Di,t is the dividend from sector i received by the investor during period t.

Dividends for sector indices were incorporated in the return data upon extraction from Datastream.

)1.1(log1,

,,

,

ti

titi

tiP

DPR

The numerical difference between simple and log-returns are usually small for high frequency data. Both

concepts have their advantages and disadvantages in terms of portfolio and time aggregation. The reader

is referred to Tsay (2001) for more details14.

12

Campbell, Thomson (2008): p. 1517 13

Benninga (2008): p. 503 14

Tsay (2001): p. 3


17

The excess return is defined by the return in excess of the risk free asset.

)2.1(,,, tftie

ti RRR

Here, etiR , is the monthly excess return of investment i at time t, tiR , is the return of investment i at time t,

and tfR , is the monthly return of the risk free asset at time t.

Active return is defined by the excess return of an asset or portfolio in excess of the benchmark return at

time t.

)3.1(,,, tBtiti RRR

Here, tiR , is the active return and tBR , the benchmark return at time t. Substituting the right hand side of

equation 1.2 into 1.3 and subtracting the risk free rate from the benchmark return yields the following

calculation for active excess return:

tBti

e

t

tftBtfti

e

t

RRR

RRRRR

,,

,,,, )4.1(

From equation 1.4, active return is identical to active excess return.


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1. Investment Strategy

In order to frame the concept of active portfolio management a specified investment strategy is

required. Investors buy and sell stocks based upon individual incentives such as a desire for abnormal

investment returns or because they are constrained by consumption and liabilities. Hence, there is no

single approach defined to actively manage a portfolio as the allocation of assets differs depending

upon the investment objective. Thus, an investment strategy appropriate for answering the research

objective is called for. We will apply the concepts of strategic and tactical asset allocation, two debated

methodologies to portfolio management, in order to establish a framework for such strategy15.

2.1 Investment Strategy as the Source of Portfolio Performance

The accepted advice about spreading investments on several asset classes in order to minimize risk, and

not let emotions or gut feelings control the continuous portfolio allocation process, has become common

knowledge. Nevertheless, the opinions and expectations of the individual investor still dominates the

decision making process when they assemble portfolios16.

According to Peter Sjontoft, identifying an investor who has managed to outperform a benchmark is not

necessarily rare or difficult, when selecting among investors who base their investment decisions on gut

feelings, emotions or even randomly select stocks to invest in. On average, these investors may in fact

outperform a given benchmark, not because they are smart investors with extensive market insights, but

because the stocks they invest in simply happen to perform better than the market over the given

timeframe. Berk (2005) supports this statement, claiming that little evidence of performance persistence

exists investors that perform well in one year are no more likely to perform as well next year17. One

possible explanation for this is that markets are, as in this case stationary, which opens the possibility for

investor lucky as they happen to buy stocks when markets are down and sell with a positive return. Such

scenario promotes the assumption that investor performance can be due to luck rather than skill and that

active portfolio management could be just as successful as random portfolio management in an

15

Schneeweis et.al. (2010): p. 91 16

http://www.proinvestor.com/finansnyhed/10294074/Fodboldaktier-koebes-som-legetj 17

Berk (2005): p. 30

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19

individual case, not on average. The investor who chose e.g. Novo Nordisk or Apple five years ago would

likely have outperformed most indices18. The question is really if someone who over-performed was lucky

or skilled, i.e. is his chances of repeating the performance next year higher than average? On that basis the

investors management skills is put into context as this constitutes the performance difference between

passive and active portfolio management. In that regard active portfolio return stem from the investment

strategy. The investment strategy constitute the process of asset allocation and security selection, as

these determine what to invest in at which point in time in order to generate positive active return.

2.2 Strategic Asset Allocation

Strategic asset allocation is a static approach to asset allocation where the portfolio assets are allocated

based on a long-term return estimate. Asset positions are retained throughout the period, meaning that

as asset returns change their portfolio weights change correspondingly, and the investor then rebalance

the portfolio by adjusting asset weights back to their initial positions19. Once the assets have been

selected for portfolio construction, no other asset will be introduced at any time.

Markowitz extensive work on the modern portfolio theory has yielded a dimension to the asset

management theory, i.e. diversification. This reward emerges when assets, which correlate negatively or

independently with each other, are assembled into a portfolio20. Strategic asset allocation sets forth long-

term allocations for assets possessing such characteristics.

The allocation process relies on the assumption that markets are efficient, which makes it impossible to

obtain abnormal return on investments, and therefore makes market timing irrelevant. On the contrary

active trading will increase transaction costs, which reduces the realized return more than expected. In

order to illustrate the argument against market timing, Ibbotson Associates made the following analysis21:

18

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Schneeweis (2010): p. 99 20

Markowitz (1959): p.102 21

Spar Invest (2007): p. 17

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20

Figure 2.1 indicates that an investors who invested 1 dollar in the S&P500 in 1926 index and then did

nothing, has achieved a remarkably higher return as opposed to the investor attempting to time the

market and therefore unfortunately has failed to invest during the 35 best months of the period. As a

result, attempting to time the market yielded a return on approximately the same level as T-bills.

Brinson et.al. (1986) conducted an empirical analysis which investigated the extent to which the

investment policy, the market timing and the selection of specific assets, affect the deviations in the total

portfolio return. Based on historic data from US pension funds they investigated which investment

decision had the greatest influence on the observed return and its volatility.

The first studies were conducted based on data from 1974-1983 and they concluded that a better return

could be achieved by solely focusing on a passive strategic asset allocation approach22. By passive is meant

retaining asset position by portfolio rebalancing. Their calculations showed that portfolio managers who

tried to time the market or buy specific stock achieved a lower return compared to the passive investment

strategy. These conclusions emphasize that asset classes with weights comparable to a benchmark

contribute with the largest proportion of the total return of the portfolio. In other words Brinson et.al

(1986) argues for buying a market portfolio, with fixed asset positions which in the long-term will

outperform any other portfolio combination.

22

Brinson et.al (1986): p. 136

2306,45

18,83 26,90

500

1000

1500

2000

2500

S&P500 T-bills S&P500 excl. the best 35 months

Figure 2.1 By how much has 1 dollar increased in value from 1926 to 2006?

Source: Own Creation, Sparinvest (2007)


21

In addition to providing a better return, 93,6% of the deviations of return can be explained by strategic

asset allocation23. Therefore, as regards to long-term investments, literature has proved that in terms of

returns, the best idea is to conduct portfolio investment, and not try to alter investment positions on a

periodic basis. In addition, resources committed to the investment decision should be concentrated

around the strategic decisions the determination of the investment opportunity set - since the risk of the

investment can be observed here.

In order to substantiate these results, Brinson et.al. (1991) conducted a new analysis on behalf of US

pension funds during the period 1977-1987. They reached the same results as just discussed. For this

period 91,5% of the standard deviation of return could be explained from strategic asset allocation. Only

1,8% of the return deviations was explained by tactical asset allocation - the process of over- and

underweight portfolio sectors24.

Aside from explaining a majority of return deviations, the strategic approach to asset allocation

contributes to a better risk adjusted return in contrast to attempting to time the market. Such approach

offers investors the possibility of achieving a higher return at a lower risk. This is in accordance with

Markowitz (1952) portfolio theory, as he developed the efficient portfolio based on long-term historical

data.

2.2.1 Discussing Empirical Findings and Brinson et.al.

The findings supporting the strategic asset allocation as the prevailing investment strategy assumes

market efficiency, which makes it impossible to obtain abnormal returns, and thus makes market timing

irrelevant. However, to believe investors have the same information available and that the full use of this

information is reflected in asset prices is a nave assumption. Empirical findings within the area of

behavioral finance have provided evidence that the assumption of a fully informed rational investor is

rather bold. Grossman and Stiglitz (1980) go even as far as stating that if markets were perfectly efficient

there would be no profit from gathering information, in which case there would be no reason to trade,

leading markets to eventually collapse25. In order to adopt a strategy for active portfolio management,

23

Brinson et.al (1986): p. 137 24

Brinson et.al. (1991): p. 45 25

Grossman and Stiglitz (1980): p. 393


22

trading is thus required and although markets are stationary, we can therefore not assume full efficiency

in the market, but refer to the adaptive market hypothesis instead.

Despite their conclusions, Brinson et al. (1986) have, however, received criticism for their analysis. Jahnke

(1997) criticized their use of the variance as risk measurement as opposed to the standard deviation26. If

the variance were to be replaced with the standard deviation, the strategic asset allocation would instead

explain 79% of the return deviations, which is not nearly as seminal as 93,6%.

In addition, the argument that risk of a passive investment strategy can be more easily identified is rather

obsolete. Only if assets expected returns are constant over time, should the asset weights remain

constant. The problem with such assumption is that stocks perform differently over different timeframes

due to their stages in business cycles and changes in macroeconomic developments. Hence, investors

assume changing risk premiums on stocks, leading expectations of asset prices, and as a result, their

portfolio weight to change. On this basis, investors should consider asset allocation as a dynamic process

which allows asset positions to change as their expected premiums change.

Among the critics towards Brinson et.al are also Statman (2000). He concludes that a portfolio manager

who consequently invests in the appropriate asset classes (stocks, bonds and holds cash as well) every

year between 1980 and 1997, achieves a return 8,1% per year in excess of passive strategic approach27. In

addition, 89,4% of the return deviations could be explained by the investment strategy, and the result is

therefore not far from the analysis of Brinson et.al. (1986). His point is that the investor should not only

focus on the strategic approach, but adopt a more active approach as well.

Regardless of whether the investor believes in the conclusions of Brinson et.al or joins the group of critics,

there is no doubt that the opted investment strategy has major influence upon the portfolio return

deviation. Strategic Asset allocation offers an attractive feature in the asset selection. It is fixed, which

means determining a fixed opportunity is supported by literature and carries practical advantage for

portfolio construction as we dont have to dedicate resources to identifying new opportunities. With

regards to asset allocation we turn to the dynamic approach of tactical asset allocation.

26

Jahnke (1997): p. 2 27

Statman (2000): p. 19


23

2.3 Tactical Asset Allocation

Contrary to strategic asset allocation strategy, another practice within asset allocation assumes a more

active approach to asset management. In order to conduct a thorough investigation of whether active

investment management can outperform a benchmark, a different strategy is considered. The main points

of tactical asset allocation are outlined in the following.

Following a strategic asset allocation approach, changes in the portfolio will exclusively occur ex-post,

meaning that the investor will modify his portfolio as a reaction to events occurred, by rebalancing the

asset weight back to their initial target weights. The initial portfolio composition will therefore be altered

as a result of general market developments. In periods of negative returns for some assets the portfolio

must be rebalanced so the optimal proportion of assets is recreated.

However, asset allocation must be based on expectations of short term future returns in order to

continuously ensure positive active return. In 1971 William Fouse launched the first index fund28. His work

made it possible to control different asset classes simultaneously, and this technique has later been

known as tactical asset allocation. On that basis, compared to strategic asset allocation, tactical asset

allocation is on the other hand an ex-ante investment strategy where the investor proactively adjusts his

portfolio based on market historic developments and expectations29. Thus, the dynamic nature of tactical

asset allocation requires active adjustments to the investment opportunities in response to short-term

changes in the economic environment. Its objective is to adjust the allocation in order to take advantages

of temporary pockets of market inefficiency30.

Contrary to Strategic Asset Allocation the investor has not determined an optimal asset distribution, but

adjusts the portfolio in accordance with his expectations to the market development. Therefore, the

essence of tactical asset allocation is to proactively position portfolio assets based upon changes in

expected returns. Thus, assets with high expected returns are favored, as opposed to the remaining

opportunity set, and assets with low expected returns are less desired. The advantage of the tactical asset

28

Lee (2000): p. 12 29

Picerno (2010): p. 153 30

Schneeweis (2010): p. 101


24

allocation and the main source of its popularity is that it combines Graham and Dodds value investment

strategy together with Markowitz modern portfolio theory31.

The concept of value investing by Graham and Dodd has been an active investment strategy. Investors

seek undervalued stocks with low price-to-earnings ratios. On the other hand, Markowitz considers

investments within a determined timeframe, and hence only the market portfolio can be considered a

risky portfolio. Tactical asset allocation made it possible to combine these two strategies into one, which

enables the possibility of active management and thereby a superior return.

2.4 Professional Views upon Asset Allocation

As described above there is no doubt that strategic asset allocation constitutes a relevant investment

strategy and carries the advantage of a predetermined long-term investment universe. However, from the

viewpoint of the active investor, tactical asset allocation also seems a suitable investment strategy as it

proactively repositions the portfolio on a regular basis in accordance with the investors expectations. The

extent to which investors follow the strategic or tactical approach or even both when constructing optimal

portfolios remains unknown. The following will therefore include a review of Claus Vorms assessment

upon the process of asset allocation and highlight the way Nordea Investment Management applies

portfolio theory.

In relation to balanced portfolios, the initial asset allocation is based on long-term investment decisions

consistent with strategic asset allocation. The asset allocation process begins by considering levels of

equilibrium for interest rate structures, inflation rates etc. From these estimations Nordea attempts to

determine the long-term risk premium on each selected stock. The equilibrium expectations enables

expected return calculations over a strategic default period, which is within a business cycle of

approximately ten years.

Nordea then starts optimizing, by allocating funds into the stocks which are considered below long-term

equilibrium undervalued stocks. On that basis it is reasonable to form a strategy that considers the state

of the economy compared to long-term equilibrium. Claus Vorm considers this a strategic analysis,

31

Value investment involves investing in stocks with low P/E ratio


25

valuable for creating highly diversified optimal portfolios based on estimated expected return and

covariance among assets. Obviously, as other portfolio models, this method carries pitfalls, but Claus

Vorm believes that the results of these models combined with the investors common sense can create

strong diversified portfolios.

On the other hand, Claus Vorm also believes advantages can be utilized in tactical asset allocation. Stocks

may be underpriced as considered in the strategic asset allocation, but they may have to be priced even

lower before returning to equilibrium, hence Nordea will have to purchase the stock e.g. two months

later.

The important conclusion here is that both strategic and tactical asset allocation will not necessarily have

to be present in the same investment strategy. We implement a long-term investment strategy with

changes in short-term portfolio positions, within the boundaries of predetermined risk parameters. This

approach can add value in terms allocating funds on a strategic long-term basis and reposition the

portfolio on a tactical basis. Hence, both the strategic and tactical approach is implemented in a balanced

portfolio, as the portfolio assets are repositioned on a regular basis. Claus Vorm suggests a useful strategy

would be to balance assets within determined boundaries, e.g. portfolio assets can be reweighted 20% of

their initial portfolio weight each month.

Strategic and tactical asset allocation will both be implemented as part of the investment strategy, in

balanced capacities. Strategic asset allocation offers advantages in terms of limiting the investment

opportunities which combined can be submitted to periodic repositioning in accordance with tactical asset

allocation.

2.5 Benchmark and Investment Opportunities

The choice of benchmark is of significant importance, as its performance obviously plays a key role in

determining the success of the investment strategy. Additionally, the investment opportunities must be

given careful consideration as combining such should constitute a more attractive investment compared

to the benchmark.


26

2.5.1 Benchmark

Rationalizing the choice of benchmark, the Danish index has been considered a Safe Haven investment,

which it has proven by retained and even increased returns relative to other major indices in market

turbulences making it a high performing index difficult to outperform32 33. Thus, it remarkable

performance relative to other markets makes successful active portfolio management a challenging task.

Figure 2.2 illustrates its performance against other major national economies.

When applying a small index as benchmark such as the MSCI Denmark, the investor must consider the

case of corporate domestic market dominance in terms of market capitalization. In writing, Novo Nordisk,

constitutes almost half of the basis for the Danish OMXC20 index putting the applicability of MSCI

Denmark as a representative benchmark into question34. On the other hand, the same scenario is likely in

other small or midsize European markets, where few or a single company possesses major influence upon

index development, due to superior market capitalization.

It is evident that MSCI Denmark has performed well relatively to other countries, but for Denmark, high

returns have been followed by high losses, by example of the return development between 2006 and

32

http://borsen.dk/nyheder/investor/artikel/1/229201/udlandet_kaster_sig_over_c20-aktier.html 33

http://borsen.dk/nyheder/investor/artikel/1/221690/udenlandske_investorer_vaelter_ind_over_landets_graenser.html

34 http://borsen.dk/nyheder/investor/artikel/1/240054/novo_nordisks_dominans_mere_end_fordoblet.html

0

100

200

300

400

500

600

700

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

Ind

ex

Figure 2.2 Selected Country Indices (92M1=100)

MSCI Denmark MSCI France MSCI GermanyMSCI UK MSCI USA MSCI World

Source: Own Creation, MSCI Barra

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27

2009. Thus, from its historical performance we can expect the index to carry high market risk beta. Peter

Sjntoft suggests that investing in high beta stocks is indeed one way to achieve high return, but as these

returns comes with high risk, investing in low beta stocks with low returns is not an unwise investment

decision. The MSCI Denmark appear as a difficult benchmark to outperform in terms of realized return,

but relatively low return on investments therefore constitute an equally successful investment strategy

with regards to adding portfolio value, given the condition that low returns are warranted by

correspondingly low market risk. From Claus Vorms comments with regards to portfolio construction,

value added stem from selecting stocks with different levels of systematic risk, thus different levels of

return, and based upon these input data construct portfolios carrying systematic risk at a level justified by

the realize a return. The stock selection is determined and limited by the investment opportunities.

2.5.2 Investment Opportunities

Active portfolio management commonly involves altering portfolio asset positions and compares the

portfolio performance to the overall market, such as S&P 500 or Dow Jones, which constitutes many

international corporations. Thus, the stocks included in the portfolio and benchmark are identical and

potential outperformance occurs by altering asset positions in the portfolio. As the Danish market is

relatively small in terms of capitalization, it represents few companies dominating their respective

industries and in some cases the entire market. To illustrate the point consider the correlation between

MSCI Denmark and four of the largest companies residing in the market.

Table 2.1 Correlation between MSCI Denmark and Four Underlying Stocks

The high level of correlation and market capitalization of these companies suggests that if changes in their

respective industries or even the market occur, such change is likely attributable to these stocks. Selecting

the underlying stock indices of the MSCI Denmark makes active portfolio management a difficult task

indeed, as diversification opportunities are narrow, and the investor might be tempted to select only few

stocks as those above, as their development have great influence on the benchmark development.

Broader investment opportunities for active portfolio management are therefore required.

A.P.Moller Maersk B Carlsberg B Danske Bank Novo Nordisk B

MSCI Denmark 0,89 0,83 0,79 0,85

Source: Own Creation, Datastream, MSCI Barra


28

2.5.2.1 Seeking International Opportunities

A variation of different assets will provide the investor with a variability of return in the portfolio and

reduces its risk. In order to achieve portfolio optimization the investor must allocate different asset classes

to the portfolio. According to Litterman (2003), to find independency among assets, and hence reduce the

risk of the portfolio, the investor must consider different markets35. In addition, Markowitz (1959) claims

that in order to achieve optimization at an international level, it is important to consider different types of

sectors and industries36. Hence, the most beneficial way to allocate assets is to invest globally. Portfolio

optimization traditionally requires independency among a diversified selection of assets, thus allocating

assets in different types of sectors and industries seems beneficial to achieve optimization.

When considering an investment in common stock, investors tend to divide the vast universe of stocks

into categories based on general business lines and by industry within these business lines. One way of

dividing this universe of stocks gives classifications for industrial firms, financial institutions and other

industry sectors. An alternative classification scheme separates US and foreign common stocks. I have

avoided the latter division, because the industry breakdown is more useful when constructing the

portfolio of global common stocks. When stocks are sorted by industries rather than geography they

constitute a more comprehensive illustration of company-level performance. It is easier to identify which

stocks are performing better than others as they not only react to global macroeconomic events, but also

individual sectorial events. Therefore, return patterns are assumed to develop somewhat differently,

which enables the identification of diversification opportunities. With a global capital market the focus

should include all the companies in an industry viewed in a global setting. Extensive market integration

advocates for this decision as it has diminished the importance of the geographic location of major

companies, while their sectorial location is better characterized.

2.5.2.2 The Rise of Sector Importance

Obviously, the asset allocation process refers to the decision process of determining the amount of funds

that should be allocated to each financial asset in the existing opportunity set. It is the investors objective

to obtain the highest risk adjusted return as possible. Our interpretation from Brinson et. al (1986) showed

that the asset allocation decision is by far the most dominant factor of portfolio performance as it explain

35

Litterman (2003): p. 137 36

Markowitz (1959): p. 89


29

more than 91% of the variation in asset returns. Furthermore, Litterman (2003) suggestions that asset

allocation can be divided into two different types of decisions 1) asset allocation between different asset

classes, e.g. stocks and bonds and 2) asset allocation within one asset class, e.g. countries and sectors.

Hopkins and Miller (2001) analyzed these dimensions of global equity portfolios (countries, sectors,

industries and companies). Their analysis concluded that a significant shift seemed to have occurred in the

importance of global sectors and industries at the expense of geography in global investment strategies37.

Although this emphasis is likely to shift through time the reward for global sector allocation, as well as

organizing stock selection on a sectorial basis, seems to justify allocating resources to sector research.

Their tests further suggested that an industry group orientation, rather than a broader sector-level

orientation can add value to asset allocation research. However, in order to maintain track of an

affordable amount of data in addition to a global representation among the investment opportunities,

further investigation of subgroups below the sectorial level will not be considered in this thesis.

Considering the advice of broad diversification from Claus Vorm, this thesis seeks to allocate assets into a

portfolio, which represents a broad global market portfolio, which is solid and easy to measure. Each asset

represents a sector index which embodies a range of industries. As introduced in chapter 1 the further

analysis considers the Datastream World Indices with ten sub-indices, which have been chosen to

represent ten major industry sectors as introduced in chapter 1.5.

2.5.2.3 Market Integration

Only a few decades ago some national markets were considered difficult to gain access to, limiting

investment opportunities to only domestic markets. As globalization has integrated national economies,

companies, consumers and investors now trade across borders, which results in increasing correlation

between markets. Hence, systematic risk arises as economic development in some countries impact that

of others, which to some extend align their return patterns, as they are affected by the same

developments. However, based on historical performance MSCI Denmark stands out as having performed

remarkably better than other major indices. In terms of benchmark comparison, both advantages and

disadvantages for applying the MSCI Denmark as benchmark exist. Table 2.2 shows the correlation

between each sector index, Denmark and four major national economies.

37

Hopkins and Miller (2001): p. 1


30

Table 2.2: Sector Correlation towards Countries

Although the MSCI Denmark does in fact possess the lowest correlation towards all sector indices (with

the exception of MSCI World), correlations are very high, with no correlation below 0,50. Other countries

are likely to have more companies represented in each sector index leading them to follow a more similar

development as these countries, hence their higher correlation. Thus, the development between Denmark

and the sector indices is somewhat less dependent. The relatively low correlated behavior between the

benchmark and sectors provides better opportunities for portfolio diversification with the purpose of

outperforming the MSCI Denmark (as opposed to other national markets) with reliable estimates of

return. On the other hand, high correlation among sectors may result in sectors being selected for

portfolio investment based upon their return estimations as high market integration leads to high

covariance, and hence high correlations between sectors as indicated in Appendix 2.

2.6 Crafting the Investment Strategy

Considering the advantages of strategic and tactical asset allocation in addition to Claus Vorms views

upon active portfolio management, the investment strategy constitutes a combination of both allocation

methods with regards to the investment opportunities. The process of actively managing the portfolio is a

short-term procedure comparable to the tactical asset allocation, but given the extensive empirical

findings of Brinson et.al (1986, 1991) long-term perspectives of strategic asset allocation is included. Thus,

the investment opportunities is limited in the long-term but traded in the short-term, and allocated to the

MSCI Denmark MSCI France MSCI Germany MSCI UK MSCI USA MSCI World

Basic Materials 0,71 0,75 0,73 0,80 0,70 0,13

Consumer Goods 0,66 0,75 0,75 0,76 0,77 0,04

Consumer Services 0,71 0,82 0,81 0,80 0,88 0,12

Finance 0,72 0,81 0,78 0,83 0,83 0,13

Healthcare 0,54 0,64 0,59 0,67 0,72 0,12

Industrials 0,75 0,83 0,82 0,81 0,85 0,14

Oil & Gas 0,67 0,68 0,63 0,77 0,65 0,08

Technology 0,57 0,67 0,69 0,62 0,82 0,12

Telecommunications 0,60 0,72 0,71 0,69 0,76 0,16

Utilities 0,68 0,72 0,67 0,75 0,64 0,15

Source: Own creation, Datastream, MSCI Barra


31

portfolio based upon their expected return and covariance with the other sectors. Figure 2.1 composes

the applied elements of the investment strategy.

By implementing strategic and tactical asset allocation to define different stages of the asset allocation

process, asset allocation is considered an iterative process with a long-term perspective, since a

continuous monitoring of the portfolio characteristics is essential. Figure 2.3 provides an illustration of this

strategy. Note, that the iterative nature of the asset allocation process implies active portfolio

management.

Figure 2.3: Investment Strategy

Source: Own Creation

Figure 2.1 illustrates the four steps of the investment strategy, each introduced in different stages of the

process and thus, is of different lengths. It starts with strategic asset allocation. It is considered the most

Active Portfolio Management Process

Strategic Asset Allocation

Investment Objective: Active Portfolio Management

Investment Opportunities: 10 Global Sector Indices

Benchmark: MSCI Denmark

Tactical Asset Allocation

Modeling Investment Opportunities: Expected Return Estimation

Risk Tolerance and Measure: Tracking Error

Implement Strategy: Portfolio Construction and Repositioning

Strategy Evaluation

Analysis of Realized Return

Benchmark Comparison


32

important part of the success of the investment strategy. It defined the investment objective and the

investment opportunity set. Thus, strategic asset allocation is based on a long-term focus. Therefore, this

part of the strategy has a much lower frequency in terms of asset allocation.

The next step is the modeling of the investment opportunities. For frequent portfolio construction if the

investment opportunities do not comply with the investment objective, i.e. if they are expected to deliver

negative active return, they are excluded from the portfolio at that given time. In that manner, the new

information about the involvement of the prices of the different sectors compared to the benchmark is

incorporated in the optimization problem, i.e. the model parameters are updated and portfolio

repositioning is conducted under the constraints of the investors risk tolerance in addition to the absence

of short sale and financial gearing.

The final step involves the evaluation of the portfolio positions and analysis of its performance in

comparison to the benchmark. No alterations are made from this point as the mean-variance model

ensures no violation of the investment constraints and the portfolio construction is conducted with no

regards to the transaction costs, as they are deducted from the realized portfolio return.


33

2. Active Portfolio Management

In the context of this thesis, active portfolio management involves the dynamic nature of tactical asset

allocation which alters portfolio sector index positions of the investment universe in order to provide a

positive active return compared to benchmark investment. This chapter will provide a formal definition

of the concept and identify performance measurement, which serves the purpose of determining

whether active portfolio management has outperformed the benchmark.

3.1 Defining Active Portfolio Management

Active portfolio management means allocation of funds based on expectations of future market

developments. The strategy is performed against the MSCI Denmark as benchmark. This chapter

introduces the main concept of active portfolio management and its instruments. We begin with the

definition of active portfolio management:

Active portfolio management is the implementation of a dynamic investment strategy that over- and

underweights the predefined investment opportunities over a long-term basis, with the single objective of

outperforming the predefined benchmark at a predefined time in order to add value to the portfolio.

From this definition the importance of the benchmark for active portfolio management is evident. In

terms of risk and performance measures, the use of benchmarks is important in order to obtain clear

measurements in accordance with the investment strategy. In order to evaluate the performance of the

investment strategy we will establish appropriate performance measures which aim at capturing the

systematic risk adjusted return of the portfolio in comparison to that of the benchmark the residual

return and measure whether it in fact adds value to the investor.


34

3.2 Performance Measure and Portfolio Added Value

Several performance measures for portfolio evaluation exist, such as the Sharpe Ratio and Jensens Alpha,

and they are selected based on the purpose of portfolio management38. As portfolio performance in this

thesis must be considered relative to the benchmark a relative rather than an absolute performance

measure is required. Thus, we will employ a performance measure that captures the expected excess

return of the portfolio in comparison to the benchmark the active return. The information ratio provides

such estimation39.

3.2.1 Information Ratio

We denote the active return as the difference between the portfolio returns and the benchmark return,

which is illustrated in the nominator of equation 3.1. The mean of the residual returns is usually called

alpha, and standard deviation the tracking error. The quotient of alpha divided by the tracking error is

called the information ratio:

)1.3()(

BP

BP

S

RRrationInformatio

Where RP is the portfolio return, RB is the benchmark return, thus the numerator is the portfolio active

return. SP-B is the tracking error, or the standard deviation of the residual return, measured as the squared

difference between portfolio and benchmark return. Estimates for each three components are provided in

chapter 4. According to Stotz (2005) with regards to the information ratio, the investment strategy

ultimately seeks to either maximize the expected return of the active portfolio or minimizing the tracking

error40. Since the portfolio is compared to the benchmark, active return determines the comparative

capital gains, while the tracking error indicates how well the portfolio tracks the benchmark. In other

words, active return determines whether the portfolio has outperformed the benchmark and the tracking

error determines whether the information ratio is significant.

38

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http://www.investopedia.com/terms/i/informationratio.asp#axzz24eZnzbHn 40

Stoltz (2005): p. 264

http://www.investopedia.com/terms/s/sharperatio.asp#axzz2ED7A5ucyhttp://www.investopedia.com/terms/j/jensensmeasure.asp#axzz2ED7A5ucyhttp://www.investopedia.com/terms/i/informationratio.asp#axzz24eZnzbHn


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3.2.2 Portfolio Value Added

Obviously, successful execution of the investment strategy involves over- and underweighting of the

investment opportunities expected to perform well and poorly, respectively. The asset selecting approach

only identifies the forthcoming winners and losers. Correspondingly, as shot selling is not allowed, the

investor can allocate a proportion between 0% and 100% to a single asset. Hence, the amount of capital

allocated to each asset need not be sophisticated, as it could just as well be equally weighted. However, if

the mean of the active return of the portfolio is positive, the investor has actually beaten the benchmark,

and whether the outperformance is significant or not is reflected in the information ratio, which will be

investigated in chapter 6. Therefore, the information ratio should rather be seen as an indicator for the

managers skill than a performance meas

Johan Christian Hilsted

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