decision on the Shariah-compliance of a financial product. Instead, Islamic ...... GE Asset Management, Genworth Financial, and GE Insurance Use a. Sequential ...
Strategies, Paradigms and Systems for Shariah-Compliant Portfolio Management Doctoral Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Faculty of Economics, Management and Social Sciences of the University of Cologne
2008
submitted by
Shehab Marzban, MSc. from Cairo - Egypt
Referent: Prof. Dr. Dr. Ulrich Derigs Koreferent: Prof. Dr. Thomas Hartmann-Wendels Tag der Promotion:
To my father and mentor Abdallah Marzban (1947-2007)
iv
Contents 1 Introduction
I
1
1.1
Islamic Finance and Equity Management . . . . . . . . . . . . . .
1
1.2
Motivation and Hypotheses . . . . . . . . . . . . . . . . . . . . .
3
1.3
Structure of the Thesis . . . . . . . . . . . . . . . . . . . . . . . .
6
Fundamentals of Portfolio Management and Shariah
9
2 Portfolio Management 2.1
2.2
11
Introduction to Portfolio Management . . . . . . . . . . . . . . .
11
2.1.1
Portfolio Management Strategies . . . . . . . . . . . . . .
12
2.1.1.1
Active Portfolio Management Strategy . . . . . .
12
2.1.1.2
Passive Portfolio Management Strategy . . . . . .
13
2.1.1.3
Active versus Passive Portfolio Management . . .
14
Portfolio Optimization Modeling . . . . . . . . . . . . . . . . . . .
14
2.2.1
Portfolio Representation . . . . . . . . . . . . . . . . . . .
14
2.2.2
Measuring Portfolio Return and Risk . . . . . . . . . . . .
15
2.2.3
Classical Portfolio Models . . . . . . . . . . . . . . . . . .
17
2.2.3.1
Markowitz Mean-Variance Model . . . . . . . . .
17
2.2.3.2
Index Tracking Model . . . . . . . . . . . . . . .
18
Portfolio Model Extensions . . . . . . . . . . . . . . . . . .
19
2.2.4.1
Constraints . . . . . . . . . . . . . . . . . . . . .
19
2.2.4.2
Rebalancing - Optimization over Time . . . . . .
22
2.2.4.3
Transaction Costs . . . . . . . . . . . . . . . . .
23
2.2.4
v
CONTENTS
3 Shariah Issues in Portfolio Management 3.1
3.2
General Shariah Issues . . . . . . . . . . . . . . . . . . . . . . . .
25
3.1.1
Riba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
25
3.1.2
Gharar, Quimar and Maysir . . . . . . . . . . . . . . . . .
26
3.1.3
Shariah Ruling . . . . . . . . . . . . . . . . . . . . . . . .
28
3.1.4
Shariah-Compliant Fund Management Contracts . . . . . .
31
Shariah Compliance Screening . . . . . . . . . . . . . . . . . . . .
32
3.2.1
Qualitative Screening . . . . . . . . . . . . . . . . . . . . .
33
3.2.2
Quantitative Screening . . . . . . . . . . . . . . . . . . . .
34
3.2.2.1
Liquidity Screens . . . . . . . . . . . . . . . . . .
35
3.2.2.2
Interest Screens . . . . . . . . . . . . . . . . . . .
36
3.2.2.3
Debt Screens . . . . . . . . . . . . . . . . . . . .
36
3.2.2.4
Non-Permissible Income Screens . . . . . . . . . .
36
Analysis of Shariah Screens . . . . . . . . . . . . . . . . .
37
3.2.3.1
Ratio Divisors: Market Cap and Total Assets . .
38
3.2.3.2
Range of Threshold Values
. . . . . . . . . . . .
39
Shariah Purification . . . . . . . . . . . . . . . . . . . . . . . . . .
41
3.3.1
Dividend-based Purification . . . . . . . . . . . . . . . . .
43
3.3.2
Capital Gain and Dividend Purification . . . . . . . . . . .
45
3.3.3
Investment-based Purification . . . . . . . . . . . . . . . .
46
3.2.3
3.3
25
II New Concepts for Shariah-Compliance and Development of an SPMDSS 49 4 New Strategies and Paradigms for Shariah Portfolio Management 51 4.1
Shariah Screening Strategies and Paradigms . . . . . . . . . . . .
51
4.1.1
New Shariah Compliance Strategies . . . . . . . . . . . . .
51
4.1.1.1
Best of Strategy . . . . . . . . . . . . . . . . . .
52
4.1.1.2
Consensus / Ijmaa Strategy . . . . . . . . . . . .
53
4.1.1.3
Liberal Strategy . . . . . . . . . . . . . . . . . .
54
4.1.1.4
Majority / Kasra Strategy . . . . . . . . . . . . .
54
A New Paradigm for Shariah-Compliance . . . . . . . . . .
54
4.1.2
vi
CONTENTS
4.2
Strategies for Shariah Purification . . . . . . . . . . . . . . . . . .
58
4.3
Shariah Sustainability . . . . . . . . . . . . . . . . . . . . . . . .
60
4.4
The Shariah Portfolio Management Process
. . . . . . . . . . . .
62
4.4.1
Shariah Issues in Investment Policy Analysis . . . . . . . .
63
4.4.2
Shariah Issues in Financial Analysis . . . . . . . . . . . . .
65
4.4.3
Shariah Issues in Portfolio Construction . . . . . . . . . .
65
4.4.4
Shariah Issues in Performance Analysis and Portfolio Revision 66
5 Shariah Portfolio Optimization Model 5.1
Modeling the Shariah Portfolio Problem . . . . . . . . . . . . . .
67
5.1.1
Modeling Asset Compliance Strategies . . . . . . . . . . .
70
5.1.1.1
Best of Strategy . . . . . . . . . . . . . . . . . .
70
5.1.1.2
Consensus / Ijmaa Strategy . . . . . . . . . . . .
71
5.1.1.3
Liberal Strategy . . . . . . . . . . . . . . . . . .
71
5.1.1.4
Majority / Kasra Strategy . . . . . . . . . . . . .
72
5.1.2 5.2
67
Modeling Portfolio Compliance Strategies
. . . . . . . . .
72
Solving the Shariah Portfolio Optimization Models . . . . . . . .
74
6 Shariah Portfolio Management DSS 6.1
6.2
6.3
77
Decision Support Systems . . . . . . . . . . . . . . . . . . . . . .
77
6.1.1
DSS Technologies . . . . . . . . . . . . . . . . . . . . . . .
78
6.1.2
DSS Architecture . . . . . . . . . . . . . . . . . . . . . . .
79
6.1.3
DSS for Portfolio Management . . . . . . . . . . . . . . . .
80
DSS for Shariah Portfolio Management . . . . . . . . . . . . . . .
81
6.2.1
Architecture of SPMDSS . . . . . . . . . . . . . . . . . . .
81
6.2.2
Data Component . . . . . . . . . . . . . . . . . . . . . . .
82
6.2.3
Model / Method Component . . . . . . . . . . . . . . . . .
83
6.2.4
Dialog Component . . . . . . . . . . . . . . . . . . . . . .
85
Examples of Specific SPMDSS . . . . . . . . . . . . . . . . . . . .
88
6.3.1
SPMDSS I - A Screening System . . . . . . . . . . . . . .
88
6.3.2
SPMDSS II - Active Portfolio Management . . . . . . . . .
89
6.3.3
SPMDSS III - Passive Portfolio Management . . . . . . . .
91
vii
CONTENTS
III
Empirical Analysis
93
7 Empirical Analysis 7.1
95
Analysis I: Shariah Compliance Comparative Analysis . . . . . . .
95
7.1.1
Basics and Assumptions . . . . . . . . . . . . . . . . . . .
95
7.1.2
Sector Compliance . . . . . . . . . . . . . . . . . . . . . .
97
7.1.3
Financial Compliance . . . . . . . . . . . . . . . . . . . . .
98
7.1.3.1
Size of the Asset Universe . . . . . . . . . . . . .
99
7.1.3.2
Different Classifications among Islamic indexes and funds . . . . . . . . . . . . . . . . . . . . . . . . 100
7.1.4 7.2
Conclusion of Analysis I . . . . . . . . . . . . . . . . . . . 103
Analysis II: Shariah Compliance in Active Portfolio Management . 104 7.2.1
Data and Portfolio Optimization Model . . . . . . . . . . . 105
7.2.2
Performance of Basic Shariah Strategies . . . . . . . . . . 107
7.2.3
Performance of New Asset-based Shariah Compliance Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
7.2.4
Performance of Portfolio-based Shariah Compliance Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
7.2.5 7.3
Conclusion of Analysis II . . . . . . . . . . . . . . . . . . . 115
Analysis III: Purification and Shariah Sustainability . . . . . . . . 116 7.3.1
Impact of Purification on Portfolio Performance . . . . . . 116
7.3.2
Empirical Analysis of Shariah Sustainability . . . . . . . . 117
7.3.3
Conclusion of Analysis III . . . . . . . . . . . . . . . . . . 119
8 Conclusion
121
8.1
Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
8.2
Validating the Hypotheses . . . . . . . . . . . . . . . . . . . . . . 122
8.3
8.2.1
Hypothesis H1 . . . . . . . . . . . . . . . . . . . . . . . . . 122
8.2.2
Hypothesis H2 . . . . . . . . . . . . . . . . . . . . . . . . . 122
8.2.3
Hypothesis H3 . . . . . . . . . . . . . . . . . . . . . . . . . 123
8.2.4
Hypothesis H4 . . . . . . . . . . . . . . . . . . . . . . . . . 123
Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
viii
CONTENTS
A Survey of Shariah Guidelines 125 A.1 Dow Jones Islamic Index Group . . . . . . . . . . . . . . . . . . . 126 A.2 Financial Times Islamic Index Series . . . . . . . . . . . . . . . . 127 A.3 Standard and Poor’s Islamic Group . . . . . . . . . . . . . . . . . 129 A.4 Morgan Stanley Capital International Islamic Index Series . . . . 130 A.5 Dubai Islamic Bank . . . . . . . . . . . . . . . . . . . . . . . . . . 131 A.6 HSBC Amanah Fund . . . . . . . . . . . . . . . . . . . . . . . . . 132 A.7 Meezan Islamic Fund . . . . . . . . . . . . . . . . . . . . . . . . . 133 A.8 Amiri Capital Islamic Fund . . . . . . . . . . . . . . . . . . . . . 134 A.9 Azzad Asset Management Islamic Fund . . . . . . . . . . . . . . . 136 A.10 Malaysian Securities and Exchange Commission . . . . . . . . . . 136 B Glossary of Shariah Terms
141
References
154
ix
CONTENTS
x
Chapter 1 Introduction 1.1
Islamic Finance and Equity Management
One type of investor which is globally present and currently increasing in number as well as in capital value is the Islamic investor. In addition to usual investment requirements and conventional portfolio management practices, Islamic investors are only willing to invest their capital if the investment does not conflict with their religious beliefs, namely with Islam. For an Islamic investor, a number of Islamic rules and laws need to be adhered to. These rules and laws are called Shariah and stem from three sources: the Quran, the Hadith and the Ijtihad. The Quran is the primary source of Islam including the words of God as delivered to the prophet Mohamed whereas the Hadith consists of narrative records of the actions and sayings of the prophet himself. The third Shariah source Ijtihad is the derivation and formulation of Shariah laws or guidelines by qualified scholars to deduct further knowledge from the Quran and Hadith. It is crucial that in Islam, there is no unique higher institution responsible for religious opinions to be followed by all Muslims, like the Catholic Church, for instance. The existence of such an institution would of course simplify the decision on the Shariah-compliance of a financial product. Instead, Islamic funds and index providers have to hire experienced Shariah scholars (Delorenzo, 2000) to interpret the different Shariah sources and to specify a set of checkable Shariah
1
1. INTRODUCTION
guidelines or screens to be used to distinguish between the set of halal (Shariahcompliant) and haram (non-compliant) investments. According to a recent report (Vayanos & Wackerbeck, 2008) the global Islamicbased assets are estimated at USD 400 billion and the potential market for Islamic financial services is close to ten times this number. In another survey done by McKinsey about 70 to 90 percent of investors from the Gulf countries are only willing to invest in Islamic products or prefer Islamic products if in par with conventional products. The demand for Islamic products attracted international financial institutions such as Deutsche Bank, HSBC, Citibank, Barclays, UBS, Dow Jones, FTSE, S&P, MSCI and many others to structure and offer a variety of products tailored for the needs of Islamic investors such as Islamic funds which as stated by Booz & Company (Vayanos & Wackerbeck, 2008) witness a rapid growth (see Figure 1.1).
925
706 539 414 319 183 102
105
126
2000
2001
2002
2003
233
2004
2005
2006
2007
2008E
2009E
NumberofIslamicMutualFunds
Figure 1.1: Growth of Islamic Mutual Funds
Islamic equity funds fall into the category of ethically or socially responsible funds in which investments are restricted to companies which are not involved in for instance the tobacco or weapon industry. Thus, the step of reducing the asset universe to a set of compliant assets is constitutive for Islamic funds.
2
1.2 Motivation and Hypotheses
1.2
Motivation and Hypotheses
The increasing worldwide demand of the Muslim population to invest their capital in financial products that do not conflict with the Shariah as well as the attractive capital value of these investors triggered the development of Shariah-compliant investment products such as Islamic equity funds. Since the area of Islamic finance is relatively new and investment trusts wanted to respond to the rising demand as quickly as possible, Shariah-compliant equity products found their way into practice without being researched in depth (the number of published papers or books analyzing current Shariah-compliance practices used in Islamic asset management is very limited). The main reason for this may be attributable to the fact that the development of such issues was driven by the industry which wanted to gain from the capital value of Islamic investors and therefore was not deeply analyzed and researched by both financial and Islamic researchers. The drawback of the industry-driven definition of Shariah-compliance procedures resulted in the development of different and non-standardized methodologies used across the Islamic equity management industry. Therefore this work focuses on the: Analysis of current industry-driven Shariah procedures The different Shariah-compliance procedures used across Islamic investment trusts are surveyed and analyzed to explore the effect of using diversified procedures on both the size of the asset universe and the constituents considered Shariahcompliant. Through this analysis the superiority of using specific Shariah-compliance procedures on portfolio performance in terms of return and risk are identified and interpreted. Development of research-driven Shariah procedures The conventional portfolio management is adjusted to encompass different Shariahspecific issues so that an Islamic portfolio management process is formalized. Shariah-compliance procedures are analyzed from a research perspective and new paradigms and compliance strategies are developed using currently used Shariah jurisdictions and considering both portfolio return and risk. Additionally, cur-
3
1. INTRODUCTION
rent Shariah-specific measures are redefined and new measures are introduced to enhance the expected performance of Shariah portfolios. Extension of practical portfolio models by Shariah requirements Classical portfolio optimization models, such as the Mean-Variance model introduced by Markowitz (1952) are extended by both practical portfolio requirements as well as Shariah requirements. Practical portfolio requirements include the consideration of internal investment guidelines, manager preferences, initial portfolios that need to be rebalanced based on newly available information and the consideration of transaction costs. From a Shariah-perspective the compliance of a portfolio has to be continuously ensured and therefore a feasible portfolio is identified formulating Shariah-compliance procedures (paradigms and strategies) assigned to the specific fund as constraints embedded within the portfolio optimization model. Development of a DSS prototype for dynamic and customized Portfolio Management Due to the existence of diverse perceptions about Shariah issues, different Shariahcompliance strategies and paradigms are proposed in this research. Based on the existence of different Shariah strategies, the investment strategy employed and internal and legal guidelines the portfolio manager has to comply with, no standardized portfolio optimization model can be used. Thus, we develop a (prototype) DSS with advanced model management functionalities to manage and construct specific portfolio management models to support portfolio managers in the management of the unstructured and dynamic portfolio management process. Portfolio management is unstructured since the results of portfolio optimization models need to be interpreted and refined by portfolio managers and the dynamics of the process stem from the fact that portfolio management is a continuous process in which portfolios have to be revised and rebalanced based on newly available information. Empirical Analysis of Developed Concepts Since current Shariah practices lack standardization, an empirical analysis is per-
4
1.2 Motivation and Hypotheses
formed to quantify the impact of non-standardization on Shariah consistency and portfolio performance. The results are compared with the results achieved using the new concepts, strategies and paradigms developed in this research. Therefore the overall goal of this research is to develop and formalize consistent and justifiable Shariah-compliance paradigms and strategies to be used within a Shariah Portfolio Management Decision Support System (SPMDSS) to support portfolio managers in the definition, manipulation and analysis of advanced Shariah portfolio optimization models using available optimization methods. Thus, this research work is multidisciplinary in nature since it encompasses elements from Operations Research, Information Systems, Finance and Islam. To measure the added value of this research the following hypotheses are tested throughout this work: • Hypothesis H1: Shariah-compliance procedures currently used across the industry are if compared to each other highly inconsistent resulting in different compliant asset universe sizes and different constituents within the compliant asset universes. • Hypothesis H2: The development of new paradigms and strategies for Shariah-compliance checking if considered within portfolio optimization yields better portfolio results and / or less inconsistencies compared to Shariah procedures currently used. • Hypothesis H3: The consideration of existing and newly developed Shariah measures within portfolio optimization results in better portfolio performance compared to an optimization done without these measures. • Hypothesis H4: The development of a Decision Support System with advanced model management capabilities and clear data model independence simplifies the task of portfolio managers to analyze and implement different strategies.
5
1. INTRODUCTION
1.3
Structure of the Thesis
Based on the motivation statement and the hypotheses defined this research consists of three main parts: • Part I: Fundamentals of Portfolio Management and Shariah • Part II: New Concepts for Shariah-Compliance and the Development of SPMDSS • Part III: Empirical Analysis Part I: Fundamentals of Portfolio Management and Shariah In the first part of this research the classical portfolio concept and several Shariah concepts relevant for this research are reviewed. In chapter 2 general portfolio management concepts, the classical investment process and different portfolio management strategies are introduced. Since portfolio modeling is a crucial component of the investment process alternative portfolio models as well as classical and advanced model aspects such as constraints (legal and internal), transaction costs and the consideration of initial portfolios are reviewed and formalized. The Shariah issues relevant for Shariah-compliant portfolio management are reviewed in chapter 3. First, the general characteristics of Shariah-compliant investment practices as found in the different Shariah sources are introduced. Further on, current Shariah interpretations and practices used to deduce quantifiable measures through which Shariah compliance can be identified are discussed in depth. Part II: New Concepts for Shariah-Compliance and the Development of SPMDSS In chapter 4 new strategies, paradigms and indicators for Shariah compliance checking and improved portfolio performance are conceptually developed and introduced. The chapter ends with the definition of a conceptual Shariah Portfolio Management process encompassing both classical investment process concepts and Shariah requirements. Within Chapter 5 the conceptual strategies
6
1.3 Structure of the Thesis
and paradigms are mathematically formulated so that the Shariah requirements can be considered within portfolio optimization. Chapter 6 gives an introduction to the conceptual ideas and the architecture of the developed prototype of a Shariah-compliant Portfolio Management Decision Support System (SPMDSS). Part III: Empirical Analysis In the last part of this research current Shariah practices are evaluated empirically and compared to the results achieved using the new strategies and paradigms developed. The performance of current and new practices is evaluated based on portfolio performance in terms of risk and return and the contribution of the practices to standardization or reduced Shariah inconsistency. The results achieved and the validation of the hypotheses defined are summarized in the conclusion of this research in chapter 8.
7
1. INTRODUCTION
8
Part I Fundamentals of Portfolio Management and Shariah
9
Chapter 2 Portfolio Management 2.1
Introduction to Portfolio Management
Due to the variety of asset classes and the exposure to global markets the portfolio management process is a complex and dynamic process which generally has to be done by professional institutions and not individual investors. Such institutions normally follow a clear multi-stage portfolio management process which consists of planning, implementing and revising portfolios (Auckenthaler, 1994). Within the planning stage the investor’s preferences are formulated in a policy statement in which the investor’s risk and return perceptions, liquidity requirements, preferred investment strategy as well as other requirements such as following specific Shariah guidelines are identified and stated. Based on this policy statement portfolio managers start to define an appropriate asset universe and deduce financial indicators through a detailed financial and economic analysis. Using the policy statement and the results of the financial analysis portfolios are constructed using portfolio optimization models and are then implemented by portfolio managers through placing orders. Due to the dynamic nature of the market (price changes and availability of new information) the portfolio performance and mixture is evaluated based on the
11
2. PORTFOLIO MANAGEMENT
requirements defined in the policy statement and may be revised through placing buy and / or sell orders. The classical portfolio management process extended by Shariah requirements is discussed in depth in section 4.4 of this research. Based on investors’ preference different portfolio management strategies can be used. In the following subsection the major portfolio management strategies used in practice are introduced, evaluated and compared.
2.1.1
Portfolio Management Strategies
Asset allocation and selection is a crucial factor within the portfolio management process. The manner in which asset classes and specific assets are selected for investment is called portfolio management strategy or style. Portfolio management styles can broadly be classified as being either an active or a passive portfolio management strategy. The strategies employed by portfolio managers are mainly attributable to their perception of the validity of the efficient market hypotheses. The efficient market hypothesis (Fama, 1991) states in its three forms (weak, semi-strong and strong) that the analysis of historical market prices, publicly available information (financial statements) and even insider information are already reflected in current asset prices and therefore neither technical nor fundamental analysis is of any practical use. In the following paragraphs active and passive management strategies are shortly described and compared to each other. 2.1.1.1
Active Portfolio Management Strategy
Portfolio managers using active portfolio management strategies do not believe that the efficient market hypothesis holds. Within an active management strategy, portfolio managers make use of fundamental and technical analysis for appropriate asset selection and timing decisions. Portfolio managers use such methods with the purpose to detect mispriced assets so that undervalued assets are added to the portfolio and overvalued assets are liquidated. Through detecting under-
12
2.1 Introduction to Portfolio Management
valued and overvalued assets, active portfolio managers expect to identify the appropriate mixture of assets to perform better than the market or a specific index benchmark.
2.1.1.2
Passive Portfolio Management Strategy
Passive portfolio managers on the other hand are strong believers of the efficient market hypotheses and therefore believe that assets are fairly valued in the market which means that technical and fundamental analysis cannot yield valuable information for asset selection. Since portfolio managers cannot actively detect any valuable information, a passive strategy is employed which focuses on replicating the market rather than selecting specific assets. Index tracking is used to manage a passive portfolio with the purpose to reproduce or mimic the performance of a benchmark portfolio or index (for instance the S&P 500 index). Such a tracking portfolio can be constructed either through full replication or sampling. Poddig et al. (2003) discussed different approaches for constructing a tracking portfolio. The simplest approach is to fully replicate (naive replication) the index with all its constituents and their respective weights in the benchmark index. Full replication eliminates the possibility of having any differences between the tracking portfolio and the index. Beasley et al. (1999) describe as drawbacks of using full replication that the inclusion of assets in the portfolio with low weights increases both transaction costs and the administrative effort and that if an index is revised this implies that the tracking portfolio also has to be revised. Derigs & Nickel (2003) show that full replication is not realistic because such a strategy most likely violates legal investment guidelines imposed on investment trusts by national law. Therefore a more adequate and feasible approach is to approximately replicate the benchmark using a sample of assets which minimizes the dispersion or tracking error between the tracking portfolio and the tracked benchmark. The selection of an adequate sample can be done either using heuristic methods or through using optimization models1 (Poddig et al., 2003) as done within this research work. 1
Poddig et al. (2003) discuss three optimization model formulations (linear optimization, quadratic optimization and constrained regression) which can be used for index tracking
13
2. PORTFOLIO MANAGEMENT
2.1.1.3
Active versus Passive Portfolio Management
There is no consensus whether one of the two strategies is superior to the other. From a cost perspective actively managed portfolios are exposed to higher management fees due to the extensive analytical work done and the frequent trading done by portfolio managers which results in higher transaction costs. Passively managed funds on the other hand are much more cost efficient since the management overheads and costs are much less and trades occur less frequently compared to an actively managed portfolio. Sharpe (1991) argues that the average net return of actively managed portfolios is less than the return of a passively managed portfolio due to higher costs of active management. From a performance perspective if actively managed funds succeed in detecting overvalued and undervalued assets and take right timing decisions the return achieved may be worth the additional costs occurred whereas a passively managed portfolio has as disadvantage that a bearish and decreasing market means that the return of the tracking portfolio decreases at approximately the same level. It is noteworthy that since active managers seek excess return compared to the market such a strategy is anticipated with a higher risk. Beasley et al. (1999) state that passive management is superior because historical analysis revealed that passively managed funds outperformed their actively managed counterparts on the long-run.
2.2
Portfolio Optimization Modeling
In the following subsections the portfolio modeling concepts used within this research are introduced. First alternative portfolio representations are shown and used to model the classical active or passive portfolio management strategy. To ensure the practicality of the classical portfolio models in real-life investment situations relevant constraints, transaction costs and the issue of rebalancing existing portfolios are reviewed and considered within this research.
2.2.1
Portfolio Representation
Consider an asset universe I = {1, ..., n} of n assets from which a portfolio can be constructed. A portfolio can be represented by the number of units or the nominal
14
2.2 Portfolio Optimization Modeling
volume of the assets included in the portfolio. Given the nominal volume yi ∈ of each asset i ∈ I the portfolio can be represented by the vector y = (y1 , ..., yn )
(2.1)
Alternatively, a more frequently used portfolio representation form is to represent the portfolio using the proportional budgets xi invested in each asset i ∈ I. Then the portfolio is represented by the so-called share vector x = (x1 , ..., xn )
(2.2)
Since xi is the proportional budget invested in each asset i ∈ I, xi ∈ [0, 1] holds if short-sellings are not allowed. Most mathematical optimization models are formulated using the share formulation. Yet, there are specific constraints which are more natural to model using the nominal volume formulation. Now it is easy to see that a portfolio represented by its nominal volume formulation can easily be transformed into a share formulation and vice versa. Consider the Price Pi (t)1 of each asset i ∈ I and the net asset value NAV (y, t)2 of the portfolio y at time t then the weight of a given asset i is given by yi · Pi (t) (2.3) xi = NAV (y, t)
2.2.2
Measuring Portfolio Return and Risk
Investments are made to yield return. Therefore the returns of the single assets and their effect on the overall return of the portfolio is a major criterion within
1
Within this research prices are considered to be adjusted for dividends else the return has to be calculated through adding the dividends received in the respective time period 2 The Net Asset Value of a portfolio y at time t ∈ T is given by N AV (y, t) = yi · Pi
15
2. PORTFOLIO MANAGEMENT
the portfolio selection decision problem. The return reti (τ ) of asset i ∈ I for time period τ ∈ {1, ..., t} can be measured using discrete compound returns:1 : reti (τ ) =
Pi (τ ) − Pi (τ − 1) Pi (τ − 1)
τ = 1, ..., t
(2.4)
Portfolio management is about making allocation decisions under risk since the future performance of an asset is uncertain and needs to be predicted. Thus, the future return of an asset i is modeled as a random variable with expected return μi and covariance of returns σi,j where i and j ∈ I. Using the historical price movements of the respective assets, the expected asset return and covariance of each single asset can be estimated by 1 μi = reti (τ ) t τ =1 t
∀i ∈ I
1 = (reti (τ ) − μi ) (retj (τ ) − μj ) t − 1 τ =1
(2.5)
t
σi,j
∀i, j ∈ I
(2.6)
Now, the expected return μ(x) of the portfolio x is a linear function calculated as weighted average of the single expected returns μi (i ∈ I): μ(x) =
n
xi μi
(2.7)
i=1
Additionally, the risk of the portfolio is the variance σ 2 (x) of the portfolio return μ(x) which is calculated as follows: σ 2 (x) =
n n
xi xj σi,j
(2.8)
i=1 j=1
The function σ 2 (x) is a quadratic (nonlinear) function which adds complexity to the overall model. In literature different approaches for estimating return and risk can be found such as estimating asset returns using macroeconomic indica1
ln
An alternative return calculation using continuous compounding is given by reti (t) =
Pi (t−1) Pi (t)
16
2.2 Portfolio Optimization Modeling
tors within a multifactor model (Derigs & Nickel, 2003). Variance is a symmetric risk measure where positive and negative discrepancies are both considered risky. From an investor’s perspective this is not realistic since a positive deviation from the expected return is adding value and therefore is not a real risk. Therefore in literature a number of alternative risk measures are introduced which are asymmetric and consider only negative deviations as risk such as the semi-variance (Poddig et al., 2003), Sharpe ratio (Nickel, 2005), Value at Risk (Gaivoronski & Pflug, 2000) and Conditional Value at Risk (Rockafellar & Uryasev, 2000).
2.2.3
Classical Portfolio Models
Based on the portfolio strategy used and the risk and return preferences of the respective investors different portfolio selection models can be used. For an active management strategy the classical Markowitz Mean-Variance portfolio selection model is introduced whereas an index tracking model is introduced for a passive management strategy. 2.2.3.1
Markowitz Mean-Variance Model
Markowitz (1952) introduced modern portfolio theory and studied the effects of asset risk, correlation and diversification on expected investment portfolio return. One of the basic assumptions of the Mean-Variance approach developed by Markowitz states that investors are rational which means that an investor prefers for a given level of return the lowest possible risk and for a given level of risk the highest possible return. The Mean-Variance theory states that a portfolio is efficient if and only if for a given portfolio return the risk is minimized or vice versa. Therefore it is possible to obtain a set of efficient portfolios through solving the Mean-Variance model for different return values (Guertler & Mendi, 2001). A portfolio model yielding the minimum risk for a given target return tr is given by n xi = 1, xi ≥ 0 ∀i ∈ I (2.9) Min σ 2 (x) | μ(x) = tr, i=1
Since the optimal investment is defined using more than one criterion (risk and return), the problem has to be solved for different return levels rather than for a
17
2. PORTFOLIO MANAGEMENT
single target return. This means that there exists a set of optimal solutions from which the respective investor selects the one which represents his individual risk and return preferences. Such portfolios are called pareto-optimal or efficient portfolios. An efficient portfolio can be constructed minimizing a linear combination of portfolio return μ(x) and portfolio risk σ 2 (x): n xi = 1, xi ≥ 0 ∀i ∈ I, λ ∈ [0, 1] (2.10) Min λ · σ 2 (x) − (1 − λ) · μ(x)
i=1
Here the parameter λ is called risk aversion parameter. Through solving the model for different λ ∈ [0, 1] the efficient frontier of non-dominated portfolios can be constructed.
2.2.3.2
Index Tracking Model
Under a passive portfolio management strategy such as index tracking, a portfolio is constructed which replicates the performance of an underlying benchmark or index. The measurement quantifying the quality of replication is called tracking error. In literature different definitions are found for measuring tracking errors (Beasley et al., 2003). While in the classical approach the tracking error is measured using the covariance of return differences between the index and the tracking portfolio (Franks (1992); Larsen & Resnick (1998); Rudd (1980); Derigs & Nickel (2003)), Beasley et al. (2003) use as tracking error the absolute value of the difference in returns between the benchmark and tracking portfolio. Some approaches extend the index tracking model with excess return requirements (Beasley et al., 2003), so that a tracking portfolio is constructed that yields a return higher than the benchmark. Using the classical index tracking approach, the tracking error T E is formulated using the weights of the assets included in the tracking portfolio x and the weights of the assets included in the benchmark or index portfolio x and the covariance matrix of asset returns C as follows: T E = (x − x)T C(x − x)
18
(2.11)
2.2 Portfolio Optimization Modeling
Based on this tracking error formulation the basic index tracking optimization model is given by n xi = 1, xi ≥ 0 Min T E
∀i ∈ I
(2.12)
i=1
2.2.4
Portfolio Model Extensions
2.2.4.1
Constraints
A major criticism of classical Mean-Variance portfolio optimization models is that the optimal portfolios generated are not well diversified and are concentrated on a limited number of assets (Walters, 2007). A real portfolio can not be constructed solely based on return, risk and budget limitation. In practice a number of additional requirements which take the form of guidelines or mathematical constraints have to be considered so that diversification is assured and feasible and applicable investment portfolios are constructed. Derigs & Nickel (2003) formulated such guidelines in the form of rules to check the legal compliance of actual portfolios. Such guidelines can either be: • Legal Guidelines These are guidelines enforced on funds by the respective capital market authorities. Such guidelines are legally binding and have to be frequently reported to the respective regulatory authority. • Contractual Guidelines In the fund prospectus an investment trust defines the investment strategy to be followed such as target investment markets, sectors and asset classes which constitutes a set of contractual constraints or guidelines to be followed by the respective fund. An example for contractual guidelines is the restriction to social investments or specifically in our case to Shariah-compliant investments. In that case the investment trust contractually ensures that all investments done comply with Shariah based on the Shariah jurisdiction and controlling body defined in the fund prospectus.
19
2. PORTFOLIO MANAGEMENT
• Internal Guidelines This type of guidelines is defined by the respective investment trust and encompasses specific investment and trading strategies which the trust follows based on previous experiences or to meet specific internal requirements concerning risk exposure, minimum diversification in asset classes and maximum transaction costs for instance. In the following paragraphs the most relevant and frequently used constraint types are shortly described and formalized: Budget and Cash Constraint The general budget constraint as used in classical portfolio models (as in Equation 2.10) is given by n xi = 1 ∀i ∈ I (2.13) i=1
Fund managers who are willing to ensure that a minimum liquidity level is maintained can still use the conventional budget constraint through extending the asset universe I by a cash asset with xcash ∈ [0, 1] such that a portfolio x is given by x = (x1 , , xn , xcash ). The minimum and maximum proportion of the budget to be kept in the form of cash can be defined using floor and ceiling constraints. Floor / Ceiling Through using floor / ceiling constraints fund managers are defining their preferences and binding requirements in terms of maximum (ceil) and minimum (floor) permissible investment in each of the assets considered for investment. The floor / ceiling restrictions are formulated as follows li ≤ xi ≤ ui
∀i ∈ I
(2.14)
where li is the lower limit (floor) and ui is the upper limit (ceiling) of asset i. Additionally ceiling constraints can be used to model legal guidelines as shown by Derigs & Nickel (2003). One of the guidelines enforced by the German capital investment companies law (KAGG) on their respective investment trusts states
20
2.2 Portfolio Optimization Modeling
in article 8a of the KAGG that a maximum level of 10 percent can be invested in any asset included in the portfolio. Such a legal guideline is formulated mathematically using a ceiling constraint where the upper bound ui is equal to 0.1 for all assets i ∈ I. A different floor / ceiling guideline used in practice groups assets into different sets, sectors or markets for instance, so that a minimum and maximum investment in specific subsets is assured. Consider the set of assets belonging to a respective sector I Sec ⊂ I. Then the maximum and minimum permissible investments for each sector can be limited by lsec ≤
xi ≤ usec
(2.15)
i∈I Sec
where lsec is the minimum share and usec indicates the maximum share to be invested in the respective sector. Cardinality The cardinality measures the number of assets i ∈ I included in the portfolio x for which xi > 0 holds. A minimum and maximum cardinality can be defined to achieve the minimum required portfolio diversity and to limit the number of assets to be included, respectively. To model this constraint a new binary variable vi for each asset i ∈ I has to be introduced such that vi = 1 if and only if xi > 0 otherwise vi = 0. The cardinality guideline is modeled using the following set of constraints: n CardM in < vi < CardM ax (2.16) i=1
xi ≤ vi
∀i ∈ I
(2.17)
vi ∈ {0, 1} ∀i ∈ I
(2.18)
It is worth mentioning that index tracking models with cardinality restrictions are NP-hard (Coleman et al., 2006) and therefore in section 5.2 a simple approximative algorithm to overcome this problem of computational intractability is introduced. Buy-in Threshold
21
2. PORTFOLIO MANAGEMENT
This constraint defines for each asset i ∈ I the minimum portfolio weight bmini to be invested in if asset i is to be included in the portfolio. Thus, the buy-in threshold is used to ensure that no portfolio is constructed which includes assets with too small, unrealistic and undesired weights. Assets with low weights have a negative impact on transaction costs and increase the overall number of assets included in the portfolio. This set of constraints can be formulated using the previously introduced binary variable vi as follows: xi ≥ vi · bmini
2.2.4.2
∀i ∈ I
(2.19)
Rebalancing - Optimization over Time
Portfolio management is an ongoing management process which means that fund managers take on a highly frequent basis (hourly, daily or weekly) decisions about which assets to keep, reduce, increase or add to their respective portfolio. Even within a passive management strategy tracking portfolios have to be revised and rebalanced if new risk and return information becomes available and if due to price changes the current portfolio structure becomes infeasible with respect to legal, contractual or internal guidelines. The above stated models are useful only for the construction of a portfolio from scratch. But, if within an active or passive investment strategy the composite structure of an existing portfolio is to be changed these models have to be extended. Consider a portfolio y(t − 1) at time t − 1 ∈ T where the volumes of the assets i ∈ I are y(i, t − 1). Assume that the portfolio y(t − 1) has been constructed based on an optimization run made at time t − 1. Let y B (i, t) and y S (i, t) denote the volumes bought and sold of each asset i ∈ I at time t ∈ T . Then we obtain y(i, t) = y(i, t − 1) + y B (i, t) − y S (i, t)
22
∀i ∈ I, t ∈ T
(2.20)
2.2 Portfolio Optimization Modeling
If short sellings are not allowed then it has to be assured that the volume sold is less than the volume available. This requirement can be formulated using the following set of constraints : y S (i, t) ≤ y(i, t − 1)
∀i ∈ I
(2.21)
Another requirement which has to be considered when rebalancing a portfolio is that buying an asset should exclude the possibility of selling it and vice versa to ensure that trading is rationale. Therefore the following conditions have to hold y S (i, t) = 0
if
y B (i, t) ≥ 0
(2.22)
y B (i, t) = 0
if
y S (i, t) ≥ 0
(2.23)
To model this requirements a new binary variable bs(i) for each asset i ∈ I has to be introduced and a parameter M which is a sufficient large number. Then we require: y S (i, t) ≤ M · bs(i) y B (i, t) ≤ M · (1 − bs(i))
∀i ∈ I ∀i ∈ I
(2.24) (2.25)
It is obvious, how these constraints can be transformed using the share formulation. 2.2.4.3
Transaction Costs
Another essential characteristic of practical portfolio management is the consideration of transaction costs. Transaction costs can be in the form of brokerage and commission fees, bid-ask spreads and taxation costs. Transaction costs need to be considered within portfolio revision to ensure that the benefit generated from rebalancing the portfolio exceeds the transaction costs that occur due to the rebalancing. The issue of considering transaction costs within portfolio optimization is excessively discussed in literature. Nickel (2005) for instance uses turnover volume to model transaction costs. Portfolio problems with both linear
23
2. PORTFOLIO MANAGEMENT
and fixed transaction costs are not solvable using convex optimization methods (Lobo et al. (2007) ; Gilli & Kellezi (2001)). Kellerer et al. (2000) review different approaches found in literature to solve portfolio optimization problems with linear and / or fixed transaction costs. Since in the above-stated rebalancing formulation the volumes sold and bought are measured explicitly, it is possible to define different proportional transaction costs for buying and selling an asset i ∈ I respectively. Let cB and cS denote the proportional transaction cost rate of buying and selling an asset i ∈ I, respectively, then the total transaction cost rate T CR of the rebalanced portfolio is n T CR = (cB · y B (i, t) + cS · y S (i, t)) (2.26) i=1
Mitchell & Braun (2002) propose an adjusted objective function to be used for the Markowitz Mean-Variance model to consider proportional transaction costs. Another approach (Nickel, 2005) is to adjust the expected portfolio return μ(x) by the transaction cost rate, i.e. defining μadj (y) = μ(y) − T CR
(2.27)
With respect to an index tracking model, the objective function can be reformulated as a linear combination of tracking error and transaction cost rate (Derigs & Nickel, 2003) and is given by Min {ω · T E + (1 − ω) · T CR}
(2.28)
The parameter ω is used to define the relative relevance of tracking error and transaction costs. Through solving the problem for different ω multiple paretooptimal solutions are identified.
24
Chapter 3 Shariah Issues in Portfolio Management 3.1
General Shariah Issues
An investment trust that offers Shariah-compliant products contractually ensures that the entire investment process and the underlying companies of the assets in which the trust invests comply with Shariah. The Shariah is the legal framework governing the practices and activities of Muslims. Such practices can be classified into ibadat and muamalat. Ibadat refers to the relationship between mankind and God whereas muamalat encompasses activities between man kinds in term of social, economic and political activities. Such economic activities include of course banking and financial activities in which Muslims are involved. Therefore an investment can only be considered Shariah-compliant and accessible to Islamic investors if it does not conflict with the muamalat principles defined by the Shariah. The main requirements of Shariah-compliant investments are to be free from riba, gharar and quimar and maysir.
3.1.1
Riba
The Arabic word riba means usury or excess return and is considered by most scholars’ equivalent to interest rates. Since in Islam excess return such as interest without bearing risk is not halal, Islamic investors are generally not allowed to
25
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
earn or pay interest. The interest ban is stated clearly in a number of verses of the holy Quran such as: ”O you who believe, you shall not take usury (interest), compounded over and over. Observe God that you may succeed.” (Al’Imran 3:130) ”Those who charge usury (interest) are in the same position as those controlled by the devil’s influence. This is because they claim that usury is the same as commerce. However, God permits commerce, and prohibits usury (interest). Thus, whoever heeds this commandment from his Lord, and refrains from usury, he may keep his past earnings, and his judgment rests with God. As for those who persist in usury, they incur Hell, wherein they abide forever.” (AlBaqarah 2:275) Therefore interest-based assets such as conventional interest-based bonds are definitely not compliant under Shariah.
3.1.2
Gharar, Quimar and Maysir
The word gharar refers to high or excessive uncertainty which is attributable to speculative activities. Since conventional derivative instruments are highly speculative in nature they are also considered by most Shariah scholars as being haram. Since every business transaction involves an element of risk and uncertainty, the Islam differentiates between uninformed speculation (gharar) which is comparable to quimar and maysir (Arabic words for gambling and game of chance) and business transactions where the uncertainty is minimized through in-depth analysis of the risks faced. Since the gharar, quimar and maysir characteristics can be attributed to conventional derivative instruments (such as options and future contracts) which are highly speculative in nature they are also to be considered non-compliant under Shariah laws per se (Ketell, 2008). One of the Quran verses banning such speculative practices states: ”They ask thee (O’ Prophet) about khamr (intoxicants) and maysir (gambling). Say: In both of them there is great harm, although there
26
3.1 General Shariah Issues
is some advantage as well in them for men, but their harm is much greater than their advantage.” (Al-Baqarah 2:219) Thus, this verse clearly states that maysir may have advantages such as the advantage provided by derivative products for risk management and diversification purposes but overall the Quran states that the harm is larger than those advantages and therefore such kind of activities are deemed non-compliant. Obaidullah (2002) argues that to claim Shariah-compliance additional Islamic ethics norms have to be considered such as for instance • Ban of price control and manipulation In Islam prices are to be defined by the forces of demand and supply and therefore monopolistic activities (ihtikar) are highly condemned. • Entitlement of equal and adequate information Islam clearly forbids the circulation of incorrect information to mislead (ghish) business participants. The possibility to invest in different asset classes provides investment trusts with diversification and hedging opportunities affecting the overall risk exposure of the portfolio. Equity investments are considered by most Shariah scholars to be a Shariah-compliant asset class since they present a partnership in a company where the investor shares both profits and losses whereas other asset classes such as bonds and derivatives are considered non-compliant due to the existence of elements of riba, gharar, quimar and maysir. To overcome this problem, Shariah scholars worked together with financial institutions to analyze how to overcome the riba, gharar, quimar and maysir characteristics found in conventional interest and speculation-based financial instruments such as bonds, options, futures, forwards and swaps. Using specific Shariah jurisdictions and compliant contract types some of these conventional products were restructured to adhere with the Shariah using specific jurisdictions and compliant contract types. An example for a conventional financial instrument that has been restructured to adhere to Shariah is an Islamic bond or sukuk. Sukuks are asset backed securities were the sukuk holders lease the asset to receive a halal return instead of yielding haram interest as with conventional bonds.
27
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
Irrespective of the compliance of the asset classes (such as equities, bonds or derivatives) another condition which has to be fulfilled is that the business activities and financial operations of the company issuing the assets do not contradict with Shariah. Thus, the issuing company itself has to be operating in a Shariahcompliant manner, i.e. the company has to be free from practices related to riba and gharar for instance. Another essential requirement is that companies considered for investment are not involved in business activities contradicting with the ibadat principles of the Islamic investor. Since Muslims are for instance not allowed to consume or sell alcohol, gamble or provide gambling facilities the companies considered for investment should not be involved in such practices. Since the Shariah-compliance status of asset classes is mainly agreed upon and resolved through categorizing asset classes either as being compliant (such as equities or restructured conventional bonds or sukuks) or non-compliant (such as conventional bonds), the focus of this research is to identify and validate the Shariah-compliance status of the underlying companies within one compliant asset class, i.e. equities. To decide upon the compliance of a specific company experienced Shariah scholars define procedures or strategies with which the involvement in non-compliant practices and business activities can be quantified. Such a strategy consists of a set of qualitative (sector) guidelines and quantitative (financial) guidelines which are discussed in depth in section 3.2 of this research.
3.1.3
Shariah Ruling
Since fund managers normally are not acquainted with Shariah issues and how to define something as being permissible for an Islamic investor or not, it is an essential prerequisite for a trust offering an Islamic product to define a Shariah jurisdiction source on which basis compliant investment practices are defined. This task is normally done by Shariah scholars who are experienced both in Shariah issues and finance. Their task is to interpret the different Shariah sources and to define a strategy or procedure through which Shariah-compliant investments can be identified. So to offer an Islamic investment fund the strategies defined by Shariah scholars need to be considered by the issuing trust and this can be achieved either through
28
3.1 General Shariah Issues
• the appointment of a Shariah Board, • the subscription to an Islamic Index or • the subscription to a flexible Shariah screening system. If an Islamic investment trust appoints a Shariah board their major tasks include the definition of Shariah principles and strategies to follow, the periodic monitoring of fund operations and to certify that the investment procedures and net profits generated comply with Shariah. The major advantage of appointing a Shariah board is the increased credibility since fund management can be consulted and monitored by the Shariah board in the entire investment process (Delorenzo, 2000). Since Shariah scholars with adequate experience in Shariah and finance are a rare resource the cost of appointing a Shariah board is very high which increases the total management cost of the respective fund. Additionally, due to the rarity of scholars some of them supervise a large number of Islamic investment trusts (one of them for example is a member of more than 40 boards) which may affect their capability to actively monitor the on-going compliance of the funds they supervise. Another disadvantage is that Shariah scholars are normally following a specific Islamic school of thought and therefore through the appointment of a Shariah board, investment trusts will only be able to serve Islamic investors following the same school of thought as the one followed by the appointed Shariah board. This of course will hinder the investment trust to provide different Islamic funds tailored for different Islamic groups (the different schools of thoughts and their impact on defining different Shariah strategies is shown in section 3.2) since the same Shariah board cannot issue two different fatwas (Arabic word for religious opinion or interpretation issued by an Islamic scholar) or strategies to follow. The second alternative for an Islamic investment trust is to subscribe to an Islamic index. Professional financial services providers such as Dow Jones (DJ) and Standard and Poor’s (S&P) have observed the market potentials of Islamic products and hired Shariah scholars to develop Islamic indexes. It is worth mentioning that the development of Islamic indexes positively contributed to the enhancement and dissemination of Islamic investments since a large number of Islamic
29
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
trust funds outsource the Shariah jurisdiction of their investments to an index provider such as Dow Jones. Thus, the investment trusts periodically receives a list of companies in which the fund manager can invest. The main advantage of subscribing to an Islamic index is that first the ethical responsibility regarding Shariah compliance moved from the investment trust to the institution and Shariah board issuing the index. Another advantage is that the cost of subscribing to an Islamic index is much lower compared to appointing an own Shariah board. One of the disadvantages of this alternative is that no Shariah scholars can be consulted for questionable Shariah issues and that no on-going Shariah monitoring exists. Another problem is that generally Islamic index constituents are derived from a conventional parent index issued by the same service provider and this means that if for any non-Shariah specific reason constituents are eliminated from the parent index they are automatically excluded from the Islamic index. So companies not included in the Islamic index for reasons different than Shariah requirements cannot be considered for investment. For instance Standard and Poor’s Islamic Index constituents are a subset of the S&P500 index and therefore investment trust funds using the S&P Islamic index to invest in US equities can only diversify their portfolio using a limited number of companies (maximum 500 if all S&P500 constituents are Shariah compliant) whereas the rest of the US market will not be accessible. Similar to the first alternative an Islamic index is based on a single school of thought and therefore also here it is not possible to offer funds for different groups of Islamic investors. The last alternative which we propagate with our research is a flexible Shariah screening system through which alternative Shariah compliance strategies can be defined and used on a global asset universe. Such a system would contain a knowledgebase with all the Shariah strategies defined by different Shariah scholars and different schools of thoughts and based on the investors religious perceptions customized strategies can be employed. The major advantage is that the demands of different Islamic investor groups can be met easily through assigning the appropriate Shariah strategy to the respective fund. Another advantage compared to index subscription is that there is no limitation on the index constituents since the Shariah strategies can be exercised on all companies fund managers are in-
30
3.1 General Shariah Issues
terested in as long as the system has access to the financial data of the respective companies. The major disadvantage is that as in the case of the subscription to an index there is no Shariah consultation accessible. Concluding this comparison the appointment of a Shariah board or the subscription to a flexible screening system is superior to subscribing to an Islamic index which provides fund managers only with the scope of a limited universe and hinders the structuring of alternative perception-based funds. Yet, by appointing a Shariah board only half of the work is done since the Shariah board just defines the Shariah strategies to follow and is not responsible for the operational screening of the companies. Therefore even if a Shariah board is appointed a computerbased system is needed through which the asset universe can be screened for Shariah compliance. And since investment trusts should focus on their primary business which is ”investing” the subscription and use of a flexible Shariah screening system is an efficient and crucial alternative through which the strategies of the appointed Shariah scholars or alternative and customized strategies can be defined and used. Within this research work such a screening system is developed and introduced in section 6.2.
3.1.4
Shariah-Compliant Fund Management Contracts
Since the muamalat principle governs the activities and relations between mankind, it is also used to define the Shariah-compliant contractual agreement between an investor and the investment trust. From a Shariah perspective three different contractual agreements can be made between Islamic investors and the investment trust managing a Shariah-compliant fund: Mudaraba Contract Within a mudaraba contract the investment trust or entrepreneur (mudarib) will manage the capital provided by the investor (rab-ul-maal) whereby the investment trust is compensated based on a previously defined percentage of the profit generated. In the case that loss occurs, the loss is covered by the investor only whereas the investment trust will not be compensated at all. A mudaraba con-
31
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
tract ensures that investment trusts do their best to achieve good results because else they are not rewarded for their work. Wakala Contract A different contractual approach compliant under Shariah is to consider the investment trust acting as an agent for the investors. This type of contract is called wakala contract. The agent (wakeel) can either be compensated on a fixed fee basis or based on the opinion of contemporary Shariah scholars (c.f. Usmani (2002)) the compensation can also be calculated as a percentage of the value of the fund. Mudaraba and Wakala Mix Contract The third option for Shariah-compliant equity funds is a combination of the first two. This means that the compensation of an investment trust consists of a basic fee (monthly or annual) and a performance fee which is only paid if a predefined target growth in the net asset value has been reached or a benchmark return is outperformed (Norman, 2004). Independently from the contract type used, Usmani (2002) clearly states that investment relations have to be based on mutual agreement which have to be stated and agreed upon before the fund is launched, such as the disclosure of compensation procedures in the fund prospectus as done in conventional funds.
3.2
Shariah Compliance Screening
1
As described in the previous sections capital investment institutions and Shariah scholars involved in Islamic investment fund management propose different procedures and guidelines to decide upon the Shariah compliance of an investment. One reason behind these discrepancies is the complexity of modern capital markets, the existence of complex investment instruments and the multidisciplinary and global involvement of companies. Conventional interest and speculation-based financial instruments such as bonds, 1
This section has been partially published in Derigs & Marzban (2008b)
32
3.2 Shariah Compliance Screening
options, futures, forwards and swaps are either not permissible under Shariah or have to be restructured in a Shariah-compliant manner. The focus of this section is to identify Shariah-compliant equity investments which is usually obtained by applying a set of qualitative (sector) screens and quantitative (financial) screens defined by the Shariah scholars who supervise the respective Islamic fund or index.
3.2.1
Qualitative Screening
Qualitative screens are sector screens through which companies operating within specific business areas that are non-permissible under Shariah are excluded. Shariah clearly defines a number of aspects which are not permissible for Muslims such the consumption of alcohol and pork, and thus compliant companies are not allowed to participate in businesses earning primarily or even partially from such activities. The main business activities considered non-compliant under Islam include the manufacturing and sales of alcohol and pork, conventional interestbased financial services, conventional insurances, pornography, casinos and night clubs (Iqbal & Mirakhor, 2007). Since besides Quran and Hadith also Ijtihad (interpretation) is involved, some minor differences may occur among the qualitative guidelines defined by the respective Shariah boards. Especially with respect to defining a company as haram due to the fact that the company is to a certain extend engaged in a non compliant business. An example for a qualitative screen is for instance: • If the company is generating any revenue from the sales of alcohol exclude it from the permissible asset universe. Alternatively a more moderate Shariah board may consider a company being compliant if the proportional revenue generated by the non-compliant activity does not exceed a given threshold level (for example 5 percent). Yet, this relaxation is partially absorbed through the condition that the non-compliant proportion needs to be purified and donated from the income received by the investor.
33
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
3.2.2
Quantitative Screening
After the asset universe has been reduced through applying qualitative screens, in a second step a number of quantitative or financial screens are applied to further clean the asset universe from non-Shariah-compliant assets. This phase is most relevant and debatable for this study since remarkable differences exist between the different financial screening methods used by the Islamic funds and index providers. The reason for using quantitative screening on top of qualitative screening is the fact that Shariah forbids the involvement in riba (the Arabic word for interest) and the trading of money for money and thus it is necessary to analyze how deeply companies are involved in such practices. Since money in itself is not a permissible asset in Islam that can be traded for money, especially the level of cash and cash equivalents of a company has to be measured and compared to a maximum allowable threshold. The reasoning behind this requirement stems from the fact that the value of the company has to be negotiable and this is only possible if the company owns some illiquid assets since in Islam liquid assets can only be traded at par (Iqbal & Mirakhor, 2007). On the other hand, the involvement in riba is measured by how much interest-based income the company receives and how much interest the company pays for its debt. The use of financial guidelines is a relaxation of the puristic application of the riba ban (as stated in the holy Quran) and a tribute paid to today’s complex financial world in which it is almost impossible to find any company that is not involved in any interest payments due to the existence of cash deposits, loans or credits with the consequence that if Islamic scholars are extremely dogmatic and intolerant, Muslim investors would not be allowed to participate in the capital market at all (Wilson, 2004). Instead, Shariah scholars use the different sources of Shariah to further interpret such situations resulting in the definition of thresholds which limit the amount of riba acceptable from an Islamic perspective as well as instructions on what to do with these non-Shariah earnings which will be explained in detail in section 3.3. The rationale for using thresholds is derived from
34
3.2 Shariah Compliance Screening
the fact that in general Islamic investors are only minority shareholders in these companies without voting power to force the company to operate completely in a Shariah-compliant manner. Obviously the Holy Quran and the Hadith do not explicitly state which thresholds for financial analysis are acceptable. Since the thresholds defined are based on interpretation in the form of Ijtihad and Shariah statements that are not directly related to capital markets there is some degree of freedom that scholars might use to specify their quantitative criteria. To quantify to what extent companies are involved in non-compliant activities such as riba, a thorough financial analysis has to be carried out using the financial statements published by the respective companies. Since in most countries companies are only obliged to publish financial results on an annual, semi-annual or at most quarterly basis, the Shariah screening process and compliance duration definition depends highly on the frequency of the reports published. Formally, quantitative Shariah screens are financial ratios which are compared to a maximum allowable threshold level. Those ratios focus on different aspects of an investment like liquidity, interest, debt and non-permissible income. Each Shariah board uses a bundle of ratios for screening the assets and an asset is compliant if and only if it passes all screens included in the bundle. In appendix A an explicit list of financial measures and a precise definition of the most important ratios used by professional Shariah funds is shown. In the following paragraphs the different types of financial screens are described.
3.2.2.1
Liquidity Screens
Liquid assets are current assets and may include cash and cash equivalents, shortterm investments and accounts receivables. For conventional analysts, a high liquidity ratio is generally a positive signal showing that the company is able to cover its short-term financial obligations more easily compared to a company with a lower ratio. But since from a Shariah perspective returns should be gained
35
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
from the illiquid assets only, assets of a Shariah-compliant company should be to a high extent in illiquid form. An example for a Shariah screen measuring the maximum permissible liquidity level of a company is: • The sum of accounts receivables, cash and short-term investments may not represent more than 50% of the total assets of a company. 3.2.2.2
Interest Screens
As described above, earnings from interest are generally not permissible. Yet, since all companies are cooperating with banks and this relationship might generate interest, Islamic scholars defined thresholds indicating to which extent interest is permissible. Interest permissibility is measured in two different ways. Either the amount of interest income generated or the amount of liquid assets (cash and short-term investments) that could generate interest income is limited. A sample interest screen is for instance: • Interest income may not represent more than 5% of the total revenue of a company. 3.2.2.3
Debt Screens
Since not only receiving interest is banned but also interest payments, the level of interest payments for debt is also measured and limited by a threshold level. Here, Islamic and conventional analysis coincide and favor lower debt ratios, since in general a lower leverage level is interpreted as a positive investment signal. An example of a debt screen is: • The proportion of total debt to total assets of a company may not exceed 30%. 3.2.2.4
Non-Permissible Income Screens
Other less-frequently used financial screens measure the level of income generated from Non-Shariah-compliant activities. These screens are important in the case that the qualitative screens which are used exclude only those companies
36
3.2 Shariah Compliance Screening
whose primary business is not Shariah-compliant. Such screens can be applied for instance to measure for a hotel, whose primary business is Shariah-compliant, how much income has been generated by alcohol sales and an associated casino. If this income exceeds a given threshold, then the hotel is marked as being nonShariah-compliant. An example for a screen is for instance: • Income from any Shariah non-compliant activity has to be less than 5% of the total revenue generated by a company.
3.2.3
Analysis of Shariah Screens
To illustrate the wide diversification of Shariah screens, a detailed survey containing the different qualitative and quantitative screens used by the different Islamic funds and indexes can be found in appendix A. The figures contain the Shariah guidelines defined by the Shariah boards of the Dow Jones Islamic Index Group (Dow Jones, 2007), the Financial Times Islamic Index Series (FTSE, 2007), the Standard and Poor’s Islamic Index Group (Standard and Poor’s, 2007), the Morgan Stanley Capital International Islamic Index Series (Morgan Stanley Capital International, 2007), Dubai Islamic Bank (Nisar, 2007), the HSBC Amanah Fund, the Meezan Islamic Fund (Usmani, 2002), the Amiri Capital Islamic Fund (Asaria, 2007) and the Azzad Islamic Fund (Azzad Asset Management, 2007). Another well-known and cited Shariah screening process is the one used by the Malaysian Security and Exchange Commission (Khatkhatay & Nisar, 2006), which differs from the others since the process used is unique to Malaysia. After analyzing the different sector and financial screens used by the Islamic funds and index providers (see section 7.1) it can be noted that only minor differences exist with respect to qualitative sector screens. A minor difference among the providers is whether the weapon and biotechnology industry is to be considered halal or not. Another considerable difference in sector screens is that one group eliminates companies with any involvement in non-compliant activities whereas the other group allows the inclusion of companies whose core business is halal but receive a negligible portion of revenue from non-compliant activities. If companies involved only slightly in non-compliant activities are excluded, the
37
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
Shariah-compliant asset universe is reduced highly in size since businesses such as airlines, hotels and wholesalers, who all sell alcohol, are considered non-compliant. On the contrary, there exist significant differences between the quantitative financial screens used by the different Islamic funds and index providers (c.f. Table A.2 in Appendix A). The major differences are described in the following subsections and concern the type of divisor used in the financial ratios and the range of threshold levels.
3.2.3.1
Ratio Divisors: Market Cap and Total Assets
The most significant difference is whether market capitalization or total assets is selected to value a company and used as divisor for the different financial screens. The funds and indexes using market capitalization as divisor argue that it reflects the real worth of a company as valued by the market and they use a trailing average to smooth the measure and to eliminate any seasonality effects. On the other hand, the funds and indexes that use total assets as divisor consider it as being the more appropriate measure since here companies are valued from a trusted accounting perspective and each measurement is independent from any external market influences or speculations. To overcome this debate, the Dubai Islamic Bank for instance uses both measures as divisors for its screening ratios. A considerable advantage of using market capitalization rather than total assets is that the use of market capitalization enables continuous Shariah screening since market capitalization is independent from the publication of financial statements and can be directly calculated from market prices. This means that if total assets are used, Shariah-compliance can only be defined when detailed financial statements are published, which is most often on an annual basis only. Another advantage of using market capitalization rather than total assets is that if the financial information provided by the different companies is not accumulated using the same accounting principles, the total assets value is not an appropriate measure because depending on the accounting principles used, total assets may
38
3.2 Shariah Compliance Screening
be inconsistently valued. Examples for such problems are the use of either the LIFO or FIFO method to value inventories and the revenue recognition methods used by the company. If for instance a company reports its balance sheet using the LIFO method, in periods of rising prices inventories are undervalued which then also undervalues total assets. The effect on a financial screen, such as total debt over total assets is that the ratio becomes bigger and this may result in the exclusion of a company that was likely to pass the same screen if the FIFO accounting method was used.
3.2.3.2
Range of Threshold Values
As can be seen from Table A.2 in Appendix A the thresholds that are used to limit a common ratio may vary among the different Islamic funds and indexes. Since these thresholds are used to define a Shariah-compliant asset universe it is for an Islamic investor important to understand how those threshold values are deduced, since it is obvious that equity investments and screening processes are not mentioned and quantified explicitly in the holy Quran or Hadith. Concerning the interest ratios and debt ratios, independently from the different screening rules used, the threshold levels used are very close to each other and no large differences exist. The most frequently applied threshold used for interest and debt ratios is at a level of 33 percent. The reasoning behind this rule (Obaidullah, 2005) is most probably based on the • Hadith: The Prophet (peace be upon him) advised Abu Bakr not to donate more than one-third of his wealth, and commented that ”One third is too much”. • Fiqhy (derived knowledge from Shariah) rule: ”Whether a commodity that is part gold and part brass qualifies as gold for purposes of applying the rules of riba is resolved by the percentage of gold in the commodity, i.e., if greater than a third, it is gold”.
39
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
Obaidullah (2005) considers the use of the above stated Hadith and Fiqhy rule as debatable and used out-of-context since the situations described differ widely from the screening processes in which they are used. On the other hand, the use of 5 percent as threshold level for non-compliant income or interest income has no real foundation in the holy Quran or Hadith. It is mainly founded on pure Ijtihad of the Shariah scholars and is based on the fact that the individual Islamic investor has no control over the whole business practices of companies that are managed in a Non-Islamic manner. Since conventional companies usually have cash deposits or short-term investments that generate interest income whereas their core business is completely halal, some of the Shariah scholars agreed to consider this non-compliant income as negligible if it does not exceed 5 percent of the total revenue generated. Only if the portion of non-compliant income generated is purified, the investment is considered halal. Concerning the threshold values used to measure the liquidity level of companies, a larger threshold variance ranging from 33 to 80 percent is found among the different screening guidelines. Independently from the liquidity rule used it is important to understand the reasoning behind this high variance which is discussed by Usmani (2002) in detail and can be summarized and further interpreted as follows: • Liquidity threshold of 33% Is used for instance in the liquidity screens of Dow Jones and is based on the same above-stated Hadith and Fiqhy rule that defines a portion of less than one-third to be insignificant. • Liquidity threshold between 45% and 50% The Shariah boards of the FTSE, S&P, HSBC and Azzad Islamic funds and indexes, have the opinion that the portion of illiquid assets has to be larger than the portion of liquid assets. So, if the illiquid assets are larger than 50% of the total assets (or market capitalization value), the investment in such a company is considered permissible based on the juristic principle: ”The majority deserves to be treated as the whole thing.”
40
3.3 Shariah Purification
• Liquidity threshold of about 70% Based on the approach used by MSCI and Amiri Capital even if only onethird of the assets of a company are in illiquid form, this company is to be considered permissible. The interpretation is most probably based on the above-stated Hadith but in a reverse way since ”one third is too much” or sufficient from the point of view of the Shariah board. • Liquidity threshold of more than 80% This liquidity threshold level is only used by Meezan, which is based on the opinion of Shariah scholars from Pakistan and India who follow the Hanafi school of thought (one of the major and most liberal Islamic schools of thoughts followed mainly in Central Asia) while the scholars of the other Islamic funds and indexes mostly follow the Hanbali school of thought (another major Islamic school of thought dominating in the Arabian Peninsula). The basic argumentation of the scholars using this threshold level is that the proportion of liquid or illiquid assets to total assets is not critical if and only if the illiquid proportion of total assets is not an insignificant quantity (here at least 20 percent) and the value of liquid assets per share of the company is less than the market price of the company. The two requirements ensure that the price difference is a result of the value of the illiquid asset. If the value of liquid assets per share is greater than the market price this is considered non-compliant since money can only be traded at par from a Shariah perspective. Of course it is a relative aspect how liquidity is defined. In the case of Meezan, net liquid assets are used, which is the difference between current assets and current liabilities.
3.3
Shariah Purification
The use of quantitative screens is a relaxation of the absolute ban to generate earnings from interest or any other Shariah non-compliant activities. Since this relaxation which is established to enable Islamic investors to participate in capital markets is generally not compliant with Shariah the fraction of earnings generated from non-permissible activities need to be deducted. This relaxation is only
41
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
of temporary nature and is afterwards corrected. The process of deducting nonpermissible earnings such as interest or the earnings generated from the sales of pork or alcohol from the total investment is referred to as purification. Only after investments are purified from non-compliant earnings they are referred to as being Shariah-compliant. Shariah forbids Islamic investors to take any advantage from the non-permissible income that is to be purified. Therefore Islamic investors are not allowed to use the purified amounts for any tax benefits or to account it as Zakat, which is the Islamic obligation to donate 2.5 percent of certain wealth annually to the poor as stated in the holy Quran. Purification is either reported to the investors, so that they purify the amounts themselves, or are purified by the supervising Shariah board who define for which purpose or humanitarian institution the impure income will be donated. The advantage of reporting purification amounts to investors instead of deducting the amounts directly by the fund is that an Islamic fund may attract other investors interested in ethical investment instruments who consider interest income for instance not being unethical. A major problem with purification is the measurement of non-permissible income. Interest earnings on the one hand are identifiable through the detailed financial statements published by the companies. But, on the other hand the identification of the portion of earnings generated by non-compliant activities such as the sales of alcohol or pork products is a highly complex task and almost impossible to measure if these numbers are not reported by the companies themselves. The lack of standardization found in Shariah screening can also be recognized in purification practices recommended by different Shariah scholars. Purification in itself, a practice that corrects temporary Shariah relaxations, is not debated by the Scholars. The main reason behind discrepancies between Shariah scholars with respect to purification is attributable to the argumentation used in defining from which investment return the non-permissible income is to be deducted. There exist a number of Islamic funds, such as the ones found in Egypt that do not apply quantitative screening for Shariah-compliance checking and base the compliance decision on qualitative screens only. Such funds generally do not purify their earnings. In the following subsections the different existing purification practices are described.
42
3.3 Shariah Purification
3.3.1
Dividend-based Purification
A large number of Shariah scholars and the respective funds they supervise (such as the HSBC Amanah Fund and Standard and Poor’s Shariah Index) purify only return which is directly received in the form of dividends whereas capital gains do not need to be purified since the impact of non-permissible income on capital gain is hard to measure and capital gains are the result of complex and different market influences (Elgari, 2000). Consider the quarterly income statements for each sector-compliant asset i ∈ I for the last trading day in the quarter t ∈ Tquarter where Tquarter ⊂ Tday and let • Di (t): Dividends paid • T Ri (t): Total revenue • NIi (t): Net income • GPi (t): Gross profit • NP IIi (t): Non-permissible income including interest Now we can calulate the Dividend Purification Value DP Vi(t) of i at time t: DP Vi(t) =
Di (t) · NP IIi (t) T Ri (t)
(3.1)
or
DP Vi(t) =
Di (t) · NP IIi (t) NIi (t)
(3.2)
The reason behind having the two possible divisors for DP Vi (t) is that different opinions exist about whether to define the percentage of non-permissible income relative to total revenue or to net income. In practice most funds use total revenue as divisor. Normally, the non-permissible element is comparable to total revenue only if it is also a revenue element. An example for such non-permissible revenue is the financial services revenue generated by some automotive companies. On the other hand interest gained from cash deposits or through holding bonds is
43
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
an income element that has to be compared with net income. If interest income is compared to total revenue, this is a highly moderate approach and a smaller adjusted threshold should be used since the large revenue element is reducing the overall fraction compared to a similar ratio using net income as divisor. Elgari (2000) argues that the reason for using total revenue as divisor is based on the fact that net income is a less reliable measure which could turn negative (Obaidullah, 2005). An alternative purification ratio used by MSCI for instance compares the non-permissible interest income to gross profit as follows: DP Vi(t) =
Di (t) · NP IIi (t) GPi (t)
(3.3)
Through using gross profit the ratio is less affected by total revenue, since gross profit GPi (t) is the difference between total revenue and cost of goods sold. There exist a number of drawbacks to base purification on dividends only. Net income is generally divided into payments made to investors in the form of dividends whereas the remaining amount is added to the retained earnings of the company for reinvestment purposes. This means that using the above-stated formulas only a fraction of impure income is purified whereas a non-compliant portion remains in the company in the form of retained earnings. Additionally, purification of dividends only does not consider the impact of dividend policies. Growth companies for instance usually do not pay out dividends and use the generated income for investment purposes that will help the company to grow and increase its market value. Therefore, based on the dividend only purification approach, a company may have a large portion of impure income that has to be purified but based on its dividend policy it increases in value and provides a high capital gain to the Islamic investor without obligation to purify at all. This problem can be solved if purification is based on the overall earnings of the company instead of dividends only. Using the earnings per share EP Si (t)
44
3.3 Shariah Purification
ratio for a specific asset i at time t, the overall amount which has to be purified is given by EP Si(t) · NP IIi (t) EP SP Vi(t) = (3.4) GPi (t) So independently from the fact that dividends are paid or not, the earnings per share purification amount has to be deducted from the cash deposit of the fund or reported to Islamic investors for purification.
3.3.2
Capital Gain and Dividend Purification
Most Shariah scholars do not require to purify capital gains. They believe that the movement in prices cannot be directly related to the fraction of impure income contained in the retained earnings of the company. Elgari (2000) reviews a simple calculation based on the Net Asset Value NAV (y, t) of a given portfolio y for a given fixed holding period where the Portfolio Purification Ratio P P F (t) at time t considers both capital gains and reinvested dividends: i NP IIi (t) P P F (t) = (NAV (y, t) − NAV (y, t − 1)) · i GPi (t)
(3.5)
Through using the purification formula 3.5, the impact of the proportional weights of the assets included in the portfolio is not taken into account. Consider a portfolio consisting of asset I and II with the date given in Table 3.1.
Asset I ࢚െ Quantity Price adjusted for dividends
Asset II ࢚
࢚െ
࢚
100
100
500
500
$ 10.00
$ 12.00
$ 20.00
$ 30.00
ࡺࡼࡵࡵ ሺ࢚ሻ ࡳࡼ ሺ࢚ሻ
$ 50.00
$ 0.00
$ 1000.00
$ 5000.00
Table 3.1: Example Data
45
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
Then based on the purification formula 3.5 the amount to be purified is given by: i NP IIi (t) P P F (t) = (NAV (y, t) − NAV (y, t − 1)) · i GPi (t) = ($16, 200 − $11, 000) · ($50 + $0)/($1000 + $5000) = $40.833 This formula requires the purification of return from both assets; ignoring the fact that asset II has no non-permissible income at all. Thus, more adequate is the modified purification formula MP P F using the market value MVi (y, t) for each asset i ∈ I at time t ∈ T : NP IIi (t) i (MVi (y, t) − MVi (y, t − 1)) · MP P F (t) = i GPi (t) i∈I = ($1, 200 − $1, 000) · ($50)/($1000) + ($15, 000 − $10, 000) ·
$0 $5000
= $10.00 Using the proposed formula the amount to be purified is much less than the one defined using the conventional formula.
3.3.3
Investment-based Purification
The previously mentioned purification practices force investors to purify if and only if a positive return is generated by the investment. Investment-based purification can be considered the most strict purification approach. Here, purification has to be done even in the case of loss. The reasoning behind this approach can be attributed to the rule that the Islamic investor is not allowed to use the purification amount for tax benefits or Zakat and therefore he should also not be allowed to use impure income to reduce any loss. One of the most prestigious Shariah scholars Mohamed Ali Elgari, recommends investment purification of a portfolio y = (y1 , .., yn ) in the following way(Elgari, 2000):
46
3.3 Shariah Purification
• Step I: For each asset i = 1, .., n identify NP IIi (t) and calculate NP IIT Ni(t) the non-permissible income including interest netted from tax payments as follows:
NP IIT Ni (t) = (1 − tax) · NP IIi (t)
If tax has been paid for the total income including the non-permissible income amount, only the remaining amount is considered for purification. • Step II: For each asset i = 1, .., n calculate (NP IIT Ni(t))/(T CSi (t)), which gives the non-permissible earnings per share that need to be purified. • Step III: For each asset i = 1, .., n calculate the non-permissible amount NP A(i) = yi ·
N P IIT Ni (t) T CSi (t)
• Step IV: Calculate the total amount to be purified NP P =
n i=1
NP A(i).
The different purification approaches described so far are all ex-post accounting calculations. In section 4.2 an approach is proposed in which purification is considered ex-ante, i.e. within portfolio construction.
47
3. SHARIAH ISSUES IN PORTFOLIO MANAGEMENT
48
Part II New Concepts for Shariah-Compliance and Development of an SPMDSS
49
Chapter 4 New Strategies and Paradigms for Shariah Portfolio Management 4.1 1
Shariah Screening Strategies and Paradigms
Generally, Shariah compliance strategies are based on two types or sets of
guidelines: sector guidelines and financial guidelines (Khatkhatay & Nisar, 2006). The Shariah concepts reviewed in Chapter 3 and the empirical analysis reported in Chapter 7 reveal that current Shariah compliance practice is not standardized. In the following subsections current Shariah concepts are used to develop and define new Shariah strategies, paradigms and indicators.
4.1.1
New Shariah Compliance Strategies
Conventionally Islamic investment trusts use a specific Shariah compliance strategy to define a compliant asset universe. Such a Shariah compliance strategy is either defined by an in-house Shariah board supervising the trust or the trust subscribes to the service of an externally-supervised Islamic index such as the S&P Islamic Index. The latter provides them with a frequently updated list of 1
This section has been partially published in Derigs & Marzban (2008c)
51
4. NEW STRATEGIES AND PARADIGMS FOR SHARIAH PORTFOLIO MANAGEMENT
compliant assets which are specified using the Shariah compliance strategy. As will be shown in the empirical analysis in section 7.1 the asset universes resulting from these compliance strategies if compared to each other are characterized by high inconsistencies both in universe size and constituents considered to be compliant. The Shariah scholars who supervise the different Islamic funds and index providers and who defined the different Shariah strategies can be considered as being the major and most qualified Shariah scholars. Thus, the inconsistencies between these strategies as all inconsistencies among expert opinion call for what can be called compromises or view integration. In the following we propose four strategies to combine the expertise of these ”basic” strategies: • Best of Strategy • Consensus / Ijmaa Strategy • Liberal Strategy • Majority / Kasra Strategy The effect of using these new strategies on an asset universe is shown in Figure 4.1. Each of the circles represents a compliant asset universe defined using some basic Shariah strategy such as the ones used by the Islamic index providers Dow Jones, Standard and Poor’s, MSCI and FTSE. The shaded areas represent the compliant asset universes resulting from the new Shariah strategies. 4.1.1.1
Best of Strategy
The basic Shariah strategies are defined by different Shariah boards, with each of these boards claiming that their strategy and the defined guidelines ensure Shariah-compliant asset selection. Now, the Best of strategy selects from the pool of basic compliance strategies the one which results in the best portfolio performance in terms of some objective function based on return and risk. Therefore,
52
4.1 Shariah Screening Strategies and Paradigms
A. Best of Shariah Strategy
B. Ijmaa Shariah Strategy
C. Liberall St Strategy C Lib t
B. B Majority M j it Strategy St t
Figure 4.1: Asset Universes based on diverse Asset Compliance Strategies under this strategy the portfolio optimization model has to be solved individually for each asset universe and then the ”best” among the optimal portfolios is chosen.
4.1.1.2
Consensus / Ijmaa Strategy
The consensus strategy considers an asset to be compliant if and only if all basic Shariah strategies consider the respective asset to be compliant. The Shariah foundation of this compliance strategy can be attributed to the Ijmaa principle, which is the unanimous consensus of all major qualified Shariah scholars on a certain Shariah issue at a given time. Under the Ijmaa strategy, asset compliance is defined through considering all basic Shariah strategies and their respective guidelines simultaneously within the portfolio optimization model. The Ijmaa strategy has the major property that only those assets are compliant for invest-
53
4. NEW STRATEGIES AND PARADIGMS FOR SHARIAH PORTFOLIO MANAGEMENT
ment that are jointly considered compliant by all basic Shariah strategies, hence only the intersecting asset universe is compliant (Figure 4.1) which means that no asset is included in the asset universe which is considered to be non-compliant by any of the basic Shariah strategies. A drawback of this strategy is that the compliant asset universe may be significantly smaller than every asset universe of a basic strategy (Figure 4.1) and this may affect portfolio performance in terms of risk and return. 4.1.1.3
Liberal Strategy
Under the liberal strategy an asset is considered to be compliant if at least one basic Shariah strategy considers the asset to be compliant. The liberal compliance strategy results in a larger asset universe (see Figure 4.1) and therefore higher returns and lower risks can be expected under this strategy. This strategy might seem to be too moderate for some readers/investors, but due to the fact that all basic Shariah strategies claim to discriminate between compliant and noncompliant, every asset considered compliant by at least one basic strategy can be considered to be compliant. 4.1.1.4
Majority / Kasra Strategy
The majority (in Arabic Kasra) strategy is motivated by the Islamic juristic principle which states that ”the majority deserves to be treated as the whole thing”. Thus, an asset is compliant under this strategy if and only if the majority of the basic Shariah strategies consider this asset to be compliant. This strategy is obviously more conservative than the liberal strategy where compliance has to be stated by just one basic Shariah strategy. Some scholars might say that this principle is used out-of-context but most Shariah principles used to justify compliance practices in capital markets are considered as being used out-of-context by some Islamic researchers (Obaidullah, 2005).
4.1.2
A New Paradigm for Shariah-Compliance
The compliance strategies described above consider compliance as an attribute of the single assets. If an asset satisfies the respective guidelines it is considered
54
4.1 Shariah Screening Strategies and Paradigms
compliant, else the asset is deemed non-compliant and has to be eliminated from the asset universe. The following proposal leads to a new paradigm which if accepted by current Shariah scholars will revolutionize Islamic equity management. Based on the Accounting and Auditing Organization of Islamic Financial Institutions (AAOIFI), Islamic investment funds are defined as follows (Norman, 2004): ”Funds are investment vehicles, which are financially independent of the institutions that establish them. Funds take the form of equal participating shares/units, which represent the shareholder’/ unit holders’ share of the assets, and entitlement to profits or losses. The funds are managed on the basis of either Mudaraba or agency contract.”
Management Company Management Shares
ShariahBoard Supervision
Investors Redeemable Shares
LimitedLiability Company
Assets A t (InvestmentPortfolio) Figure 4.2: Structure of Shariah-Compliant Funds Therefore, a fund takes the form of an independent company, such as a limited liability company (Norman, 2004), in which investors act as shareholders (see Figure 4.2). Now, we simply argue that with respect to compliance a fund which itself invests in multiple companies has to be evaluated in the same way as a conventional independent company. This point of view is justified and illustrated it the following example.
55
4. NEW STRATEGIES AND PARADIGMS FOR SHARIAH PORTFOLIO MANAGEMENT
Consider, for example, a hotel, then a critical Shariah guideline is the following: • Income from the casinos, bars, night clubs and alcoholic beverages has to be less than 5% of the total revenue generated by the hotel. Since the core business of the hotel is considered compliant, this guideline is used to restrict the investment to only those hotels with a non-compliant income less than the threshold. Thus, a hotel can be considered as a company operating in three business lines which are: accommodation and Shariah-compliant hotel services, the sale of alcohol and casinos and night clubs. If a hotel has an overall non-compliant income from the second and third business lines which is less than 5 percent of the accumulated revenue generated by the three business lines together, then, according to the guideline, it is considered to be compliant for investment. Accordingly, if the investment in a company like a hotel that generates negligible income (which will also be purified later on) from some noncompliant activities is considered to be compliant as such under some strategy, then analogously an investment in a fund which invests in different companies, should also be considered to be compliant as a whole if the mixture of companies (interpreted as business lines of the fund) does not violate the guidelines of the same Shariah strategy. Also, for the investor of a portfolio the overall portfolio return and portfolio risk is crucial and not the return and risk of the single assets. Using the same argumentation, an Islamic investor should focus on the overall Shariah-compliance of his portfolio and its return netted by purification rather than looking at single asset compliance and returns. The new portfolio compliance paradigm can be used in conjunction with any asset compliance strategy as for instance those described in section 4.1.1, i.e. it can be combined with any basic strategy from an Islamic index, or, the Best of, Ijmaa, liberal or majority compliance strategy, respectively. This results in a large variety of new options for compliance specification as illustrated in Figure 4.3. These combinations vary from very conservative to rather liberal. Obviously, the use of an asset-based compliance strategy may result in a significant reduction of the asset universe but it does not restrict the amount to be invested in a compliant asset. On the other hand, within a portfolio-based
56
4.1 Shariah Screening Strategies and Paradigms
AssetCompliance
Single Provider
BestOf Provider
PortfolioCompliance
Ijmaa Consensus
Liberal
Majority Kasra
Paradigm Strategy
Figure 4.3: Shariah-Compliance Options compliance strategy no asset is excluded from the asset universe per se, but, the control of the entire portfolio through the financial ratios may put limitations on the proportional wealth to be invested in certain assets implicitly. The new paradigm might be considered as too liberal or even non-Islamic, but it is deduced by logical reasoning from current compliance strategies. Of course, this paradigm should be applied only to specific products and after some preprocessing: • First, the fund should only invest in Shariah-compliant asset classes such as equity or products structured in a Shariah-compliant way such as sukuks (Islamic bonds). • Secondly, no investment should be allowed in assets from companies whose primary activities are not compliant with Shariah. Thus the conventional sector guidelines, through which those assets are excluded from the asset universe, should be applied beforehand. As a first summary we claim, that the proposed new strategies do not conflict with the Shariah jurisdictions used for the basic Shariah strategies. On the contrary, most of the proposed strategies (except the liberal strategy) are either more conservative or equally conservative compared to the basic Shariah strategies. The portfolio-based compliance paradigm on the other hand is somewhat ”out of the box” giving new compliance options. After formalizing the new strategies and the new paradigm in section 5.1, the new options are analyzed in section
57
4. NEW STRATEGIES AND PARADIGMS FOR SHARIAH PORTFOLIO MANAGEMENT
7.2 and the results are compared with the basic strategies. These results should then be used and interpreted by Shariah scholars who have to decide upon acceptance of the new approaches. The hotel example reveals a problem which is not only relevant for the new paradigm: the complexity to identify the compliance of companies operating in different business segments. Most Shariah providers use an industry classification standard such as GICS (Global Industry Classification Benchmark) or ICB (Industry Classification Benchmark) through which companies are assigned to a single business segment based on the core business activity they operate in. Using such a classification standard makes it impossible to identify the different compliant and non-compliant business segments companies operate in. Therefore the automated use of GICS or ICB standards if used in the hotel example would result in the classification of the hotel as being compliant since no indication is made to the revenue generated by non-compliant activities such as the sales of alcohol and revenue from casinos and night clubs. This problem can be solved using a different industry classification standard which is the SIC (Standard Industry Classification) classification system through which each company is assigned multiple SIC codes based on the different industries or businesses it is operating in. But, since not all companies report the revenue generated by each SIC segment it is almost impossible to identify the amount of non-permissible revenue generated without further research and analysis.
4.2
Strategies for Shariah Purification
Purification is a crucial element within the Islamic Equity Management process which if done appropriately ensures the overall Shariah-compliance of the investment. Current purification accounting practices and appropriate modifications were presented in section 3.3 of this research. Conventionally, purification is considered after investment and deducted from the Net Asset Value of the portfolio or from dividend payments received from the single assets. Purification is a spiritual obligation to deduct impure income from the total income generated. Therefore purification sounds very similar to taxation, which
58
4.2 Strategies for Shariah Purification
is a legal obligation to purify specific incomes generated. Since the consideration of taxes and their impact on net return within the portfolio construction decision process is highly consequential, one of the hypothesis of this research claims that the ex-ante consideration of purification within portfolio optimization may increase the shareholder value in terms of net return compared to a portfolio construction strategy in which purification is only considered ex-post after investments are done. The actual amount which has to be purified is not known in advance and therefore the proportion ρ(i) to be purified for each asset i ∈ I is estimated using the historical impure incomes by 1 NP II(i, t) ρ(i) = t τ =1 T R(i, t) t
∀i ∈ I
(4.1)
As described in section 3.3 different purification approaches can be found in practice which can be broadly categorized as follows: • Investment-based Purification • Capital Gain and Dividend Purification Given the expected return μ(i) of each asset i ∈ I then the expected purified net ˆ of an asset is as follows return μ(i) Investment-based Purification Approach ⎧ ⎪ ⎨ μ ˆ(i) = min
⎫ ⎪ ⎬
μ(i) · (1 − ρ(i)), μ(i) · (1 + ρ(i)) ⎪ ⎪ ⎩ ⎭ if μ(i)≥0
∀i ∈ I
(4.2)
if μ(i) 0
only if
zi = 1
(5.12)
Since constraints (5.11) ensure that zi is 0 if the guideline (5.7) is not fulfilled i.e. the ratio is above the respective threshold, investment in asset i ∈ I, i.e. xi > 0, is possible only if the guideline is fulfilled. In the following it is shown how these techniques can be used to model the different compliance strategies introduced in section 4.1.
5.1.1
Modeling Asset Compliance Strategies
Consider S as the set of basic Shariah strategies and G as the set of all financial Shariah guidelines defined by the different basic Shariah strategies, then a specific basic Shariah compliance strategy s ∈ S is formulated using a specific subset GS ∈ G and the associated portfolio optimization problem is given by
Min
f (x)
subject to (5.2),(5.3),(5.4),(5.10) and
ri (g) · zi ≤ T (g)
∀i ∈ I, ∀g ∈ GS
(5.13)
In the following subsections we show how the new strategies can be modelled.
5.1.1.1
Best of Strategy
In the best of Shariah strategy model (5.13) has to be solved for each s ∈ S iteratively and the optimal portfolio with respect to this strategy is the one generated by the model yielding the best portfolio performance.
70
5.1 Modeling the Shariah Portfolio Problem
5.1.1.2
Consensus / Ijmaa Strategy
Within the Ijmaa strategy, asset compliance is defined through considering all basic Shariah strategies s ∈ S and their respective guidelines g ∈ GS simultaneously within the portfolio optimization problem. Such a strategy can be formulated within the model by replacing (5.13) by: ri (g) · zi ≤ T (g)
∀i ∈ I, ∀s ∈ S, ∀g ∈ GS
(5.14)
The model is very similar to the model for a basic strategy with the only difference that the constraints for all Shariah strategies s ∈ S are added to the model.
5.1.1.3
Liberal Strategy
The liberal compliance strategy reduces the asset universe by those assets which are jointly defined non-compliant by all basic Shariah strategies considered. The identification of these assets and their exclusion from the solution domain is accomplished through introducing a binary variable ⎧ ⎨1, if i is compliant w.r.t s ∈ S zi (s) = ⎩0, otherwise
(5.15)
and by introducing the following set of constraints: ri (g) · zi (s) ≤ T (g) xi ≤
∀i ∈ I, ∀s ∈ S, ∀g ∈ GS zi (s)
∀i ∈ I
(5.16) (5.17)
s∈S
The constraints (5.17) ensure that xi > 0
only if
zi (s) = 1 for at least one s ∈ S, ∀i ∈ I
(5.18)
and thus if xi > 0 for at least one s ∈ S, s0 say, all constraints from (5.16) for g ∈ Gs0 are fulfilled.
71
5. SHARIAH PORTFOLIO OPTIMIZATION MODEL
5.1.1.4
Majority / Kasra Strategy
This strategy can be modeled using the binary variables zi for i ∈ I and zi (s) for i ∈ I and s ∈ S which have been introduced before as follows: ri (g) · zi (s) ≤ T (g)
∀i ∈ I, s ∈ S, g ∈ Gs
(5.19)
|S| zi (s) ≥ · zi 2 s∈S
∀i ∈ I
(5.20)
The constraints (5.10) and (5.20) ensure that if xi0 > 0
for an asset i0 ∈ I
then zi (s) = 1 for the majority of s ∈ S, (5.21)
0
i.e. i is compliant for the majority of strategies.
5.1.2
Modeling Portfolio Compliance Strategies
A portfolio x fulfills a specific guideline g if the sum of the ratio values weighted by their share values is less than the threshold, i.e.
ri (g) · xi ≤ T (g)
g∈G
(5.22)
i∈I
Now a portfolio x is compliant with respect to a strategy s ∈ S if x fulfills all guidelines g ∈ GS . Thus, for a basic strategy s and the set GS of guidelines the following portfolio optimization model has to be solved: Min
f (x)
subject to (5.2),(5.3),(5.4) and
ri (g) · xi ≤ T (g)
∀g ∈ GS
(5.23)
i∈I
The other portfolio-based compliance strategies can now be modeled as follows: Best of Strategy
72
5.1 Modeling the Shariah Portfolio Problem
Again for the best of strategy the optimal portfolio is the one generated by the basic strategy s yielding the best portfolio performance. Consensus / Ijmaa Strategy To define Shariah-compliance under the Ijmaa strategy, (5.23) has to be replaced by:
ri (g) · xi ≤ T (g)
∀s ∈ S, ∀g ∈ GS
(5.24)
i∈I
Liberal Strategy To model the liberal compliance strategy we intrdocuce the binary variables ⎧ ⎨1, if the portfolio x is compliant for s ∈ S zp(s) = ⎩0, otherwise
(5.25)
and replace (5.23) by: zp(s) ·
ri (g) · xi
≤ T (g)
∀s ∈ S, ∀g ∈ GS and
(5.26)
i∈I
zp(s) ≥ 1
(5.27)
s∈S
Constraints (5.26) are nonlinear and with respect to solvability of the optimization model should be linearized as follows:
ri (g) · xi ≤ (1 − zp(s)) · M + T (g)
∀s ∈ S, ∀g ∈ GS
(5.28)
i∈I
with M a sufficiently large number. Now due to (5.27) at least for one s ∈ S, s0 say, zp(s0 ) = 1 is obtained and thus (5.28) and / or (5.26) holds for at least one s ∈ S.
Majority / Kasra Strategy
73
5. SHARIAH PORTFOLIO OPTIMIZATION MODEL
To model the majority strategy we replace in the model for the liberal strategy (5.27) by |S| zp(s) ≥ (5.29) 2 s∈S This ensures that at least the majority of basic strategies s ∈ S consider the portfolio as being compliant.
5.2
Solving the Shariah Portfolio Optimization Models
Portfolio models are usually computationally complex and therefore they were frequently solved approximatevly using heuristics rather than exact algorithms (Derigs & Nickel, 2003). But, due to the the recent improvements in the area of commercial optimization solvers it is now possible to solve Mean-Variance models with complex constraints (such as cardinality and min-buy-in constraints) exactly in adequate time. Therefore within this research Mean-Variance models with complex constraints have been solved using the ILOG CPLEX solver which is able to solve Mixed Integer Quadratic Optimization problems (MIQP) of the required size. Yet, index tracking models (which are NP-hard if containing with cardinality restrictions (Coleman et al., 2006) and (Derigs & Nickel, 2004b)) can be solved by relaxing the quadratic problem to a linear programming problem using a Sequential Linear Programming approach (SLP). SLP is a general relaxation concept and has been used for instance for solving layout problems (Bhowmik, 2008) and cargo allocation problems (Brosh, 1981). Chalermkraivuth et al. (2005) have presented this approach to solve complex portfolio optimization models for General Electric Asset Management. The algorithm proposed by Chalermkraivuth et al. (2005) assumes a model for
74
5.2 Solving the Shariah Portfolio Optimization Models
constructing an efficient solution of the following form:
Max μ(x) subject to σ(x) ≤ σ target x fulfills constraints in C and works as follows: Algorithm 1 Sequential Linear Programming Algorithm Specify LRisk a lower bound for risk and LReturn a lower bound for return Eliminate risk constraint and solve LP to generate an initial portfolio x0 i←1 i ← small value while σ(xi−1 ) ≥ LRisk and μ(xi−1 ) ≥ LReturn do Compute ∇f (xi−1 ) · xi−1 the tangent to the risk contour at xi−1 Add linear constraint ∇f (xi−1 ) · x ≤ ∇f (xi−1 ) · xi−1 − i to the model Solve the new LP to obtain next portfolio xi on the efficient frontier i←i+1 end while The performance of this algorithm for approximating the efficient frontier depends on the value of . The smaller the closer is the approximation. As shown in Figure 5.1 we have empirically analyzed the results obtained using the SLP algorithm compared to the solution with an exact Quadratic Programming algorithm for the problem of generating the efficient frontier for a Mean-Variance model. The solutions obtained are promising but not yet practical.
75
5. SHARIAH PORTFOLIO OPTIMIZATION MODEL
Quadratic Programming
Return
Sequential Linear Programming Relaxation
60.00%
50.00%
40 00% 40.00%
30.00%
20.00%
10.00%
0.00% 0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Risk
Figure 5.1: Comparison of SLP approximation and exact MIQP solution for constructing an efficient frontier
76
Chapter 6 Shariah Portfolio Management DSS 6.1
Decision Support Systems
One of the main tasks of decision makers is to choose among a set of alternative actions the one through which the organization’s goals are attained and achieved best. Operations Research provides a variety of models and mathematical solvers which can be used to evaluate and select the best alternative course of action such as the optimal portfolio structure in portfolio management problems. But due to the complexity of these mathematical models they did not find their way into practice without the evolvement of model-based Decision Support Systems through which models and methods can be interactively and easily managed and manipulated by decision makers. In the following subsections the main DSS principles (Sprague, 1980) which are also used to develop the Shariah Portfolio Management DSS (SPMDSS) are introduced.
77
6. SHARIAH PORTFOLIO MANAGEMENT DSS
6.1.1
DSS Technologies
Sprague (1980) distinguishes three DSS technologies: DSS Tools, DSS Generators and Specific DSS (see Figure 6.1). On the lowest level of DSS technologies are the DSS tools which are software tools through which system developers can develop DSS Generators or Specific DSS. The tools encompass basic programming languages (such as Visual Basic and C#), Query languages (such as SQL), reporting tools and modeling languages (such as AMPL). The DSS Generator, which is a product of one or multiple DSS tools, is a medium equipped with functionalities that enable the customization and configuration of problem-specific DSS. DSS Generators provide end-users with modules through which specific data sources and instances, models and methods and data views can be easily customized to develop Specific Decision Support Systems. A Specific DSS is the actual system
SpecificDSS
DSSGenerator
DSS Tools DSSTools
Figure 6.1: DSS Technologies or application which is used by an end-user to solve a specific decision problem. It is worth mentioning here that the type of user differs from one technological level to another. Whereas the DSS tools are used by system developers who do not need to be acquainted with the domain knowledge of the decision problem, the users of the Specific DSS are managers who are experts in the problem domain but need not to be familiar with technological aspects.
78
6.1 Decision Support Systems
6.1.2
DSS Architecture
According to the DDM paradigm (Sprague & Watson, 1995) a Decision Support System consists of a Dialog, a Data and a Model / Method subsystem or component (see Figure 6.2). The Data subsystem of a DSS contains all the relevant
Data Subsystem
Model / Method Subsystem
Dialog Subsystem
En nd User r
Figure 6.2: Classical DSS Architecture data required for the decision problem. The data is retrieved from different data sources (internal and external) and stored in the database of the DSS. A Database Management System (DBMS) enables the manipulation and access of the data stored in the database and provides an interface to the model and dialog component so that the end-user can retrieve, store and view the data easily. The Model / Method subsystem of a DSS consists of a Modelbase and a Modelbase Management System (MBMS). The Modelbase contains a set of mathematical models and building blocks as well as a set of mathematical methods or solvers which are used to solve the respective models. Based on the specific decision problem the Modelbase may be equipped with optimization solvers (such as LP or MIP solvers) and statistical and financial evaluators. Analogously to the functionalities provided by the DBMS to handle the databases the MBMS facilitates the management and manipulation of the models / methods stored in
79
6. SHARIAH PORTFOLIO MANAGEMENT DSS
the Modelbase of the system. The MBMS is the core engine of the DSS through which the problem-specific models are created / configured, the relevant data is retrieved from the database, and a solver-readable model is generated and transferred to the appropriate solver. Further on the MBMS facilitates the selection and execution of the problem-specific model and retrieves the solver output and transfers the output to the data subsystem for storage purposes and / or to the dialog subsystem for output presentation, reporting and further model analysis. Through the dialog subsystem the end-user (for example a fund manager) is able to interact with the Decision Support System in a user-friendly manner while the technical and non-trivial aspects of the data and models / methods subsystems are completely hidden. Therefore for an end-user the dialog subsystem represents the whole DSS through which he / she is able to define, execute and analyze the problem-specific and customized models.
6.1.3
DSS for Portfolio Management
The use of Decision Support Systems in portfolio management goes back to the 70’s and its impact is shown for instance by Gerrity (1971) who presents a ManMachine Decision System for portfolio management. Due to the technological progress achieved in the last two decades new DSS types such as web-based Decision Support Systems (Power, 2002) and data-centered DSS using OLAP technologies evolved (Dong et al., 2004) which can be used in portfolio management. This work does not intend to survey the use of Decision Support Systems in portfolio management in depth and therefore only the Portfolio Management Decision Support Systems having a direct impact on this research will be briefly mentioned. At the Department for Information Systems and Operations Research (WINFORS) of the University of Cologne a number of DSS for portfolio management have been developed and found their way into practice. Derigs & Nickel (2004c) developed a model-based Portfolio Management Decision Support System (PMDSS) which solves complex portfolio problems using metaheuristics.
80
6.2 DSS for Shariah Portfolio Management
Influenced by the work of Dong et al. (2004) advanced data analysis features using OLAP technologies were introduced and integrated into the system. In another work of Derigs & Alparslan (2007) a web-based Decision Support Generator PMDSS.Net was developed through which fund managers can easily customize, parameterize and solve specific portfolio models remotely. Finally, Derigs et al. (2007) developed a spreadsheet-based portfolio management DSS focusing on strategic issues for a German bank. The prototype for a Shariah Portfolio Management DSS (SPMDSS) developed within this research is based on these developments and the experiences gained.
6.2
DSS for Shariah Portfolio Management
Using the DSS terminology introduced in the previous sections our Shariah portfolio management Decision Support System can be regarded as a DSS Generator. The reason for designing and implementing the SPMDSS as a DSS Generator is that the portfolio management problem in general as described by Nickel (2005) can be characterized as being highly unstructured such that no standard model can be used for all decision problems faced by the fund managers. Since the problem is unstructured its solution can not be fully automated. The portfolio management process requires fund managers to continuously interact with the system within problem formulation, model construction, interpretation of results especially the analysis of the sensitivity and robustness of the alternative solutions generated as well as re-optimization. Since the users of Specific DSS are managers with no or limited technical background the user interface (or dialog subsystem) needs to be highly user-friendly and easy to use.
6.2.1
Architecture of SPMDSS
The SPMDSS architecture is based on the classical DDM paradigm (Sprague & Watson, 1995) and consists of a data, model / method and dialog component (see
81
6. SHARIAH PORTFOLIO MANAGEMENT DSS
Figure 6.3). In the following subsections the functionalities and subcomponents of each of the DSS components are described.
Figure 6.3: SPMDSS Architecture
6.2.2
Data Component
The data component of the SPMDSS contains all the data required for Shariahcompliant portfolio optimization such as the detailed financial data on the companies and the historical prices of the assets. The data is retrieved from external data sources (such as Thomson and Reuters databases, Bloomberg and others) and stored in the database of the SPMDSS. An SQL-DBMS enables the manipulation and access of the data stored and provides an interface to the model and dialog component so that data can be retrieved, stored and viewed easily. The data contained in the data component can be broadly categorized into:
82
6.2 DSS for Shariah Portfolio Management
• Imported Data This includes mainly the data imported from external systems and encompasses the list of assets to be considered for investment (asset universe) with detailed information regarding the business segments in which the companies operate, detailed financial figures (from the balance sheets and income statements) and historical prices of the company. • Intermediate Data Based on the imported data specific indicators relevant for both Shariahcompliance checking and portfolio evaluation are calculated. Here, relevant portfolio measures such as expected asset returns (such as the arithmetic mean or geometric mean) and expected asset risks (such as the standard deviation) are calculated using historical asset prices. Other indicators which need to be calculated include the Shariah ratios (see section 3.2.2), the expected purification value as well as the Shariah sustainability indicator of each asset. • Output Data The output consists mainly of: 1. The Set of Compliant Assets Index providers are mainly interested in a list of Shariah-compliant assets based on the selected Shariah strategy. Then, index providers can provide their customers, asset management firms, with this list. 2. Optimal Portfolio Mix Portfolio managers who use SPMDSS to construct their portfolios are mostly interested in the nominal volume or shares to be invested in each asset.
6.2.3
Model / Method Component
The model component of the Shariah Portfolio Management DSS is the core engine of the system and consists of following main modules: Compliance Checker
83
6. SHARIAH PORTFOLIO MANAGEMENT DSS
Based on the detailed financial information stored in the data component of SPMDSS and the guidelines and strategies selected the checker module is used to check whether the current portfolio is Shariah compliant. The compliance level of an asset may change either because the relative weights of the assets within the portfolio changed due to price changes or through the availability of new financial information (balance sheet and income statement). If the checker identifies the portfolio as being non-compliant, the portfolio manager has to reoptimize the portfolio using the newly available information. Modelbase The Modelbase consists of two components: a set of portfolio model building blocks or constructs and solvers. The portfolio model building blocks are used by the model constructor to assemble a problem-specific portfolio optimization model. The model building blocks include: • Objectives The user can select either to solve a Mean-Variance model or an Index Tracking model. In the case of Index Tracking models portfolio managers may choose to consider transaction costs. • Constraints Portfolio Managers are provided with a set of constraint types representing guideline types as shown in chapter 2. Examples of these constraints are cardinality constraints, min-buy-in constraints as well as minimum and maximum investment constraints per asset, sector or country. Any selected constraint can be flexibly parameterized by the portfolio manager. • Shariah Paradigms and Strategies The different Shariah strategies and paradigms developed within this research can be selected by the portfolio manager so that the portfolios constructed comply with his / her specific school of thought. The second major component of the Modelbase contains the mathematical methods which are required to solve the specified model. Based on the complexity of the constructed model an adequate mathematical method is to be used to solve
84
6.2 DSS for Shariah Portfolio Management
the model either optimal or approximate. Model Construction Module Model construction and creation is one of the major functionalities of a model management system within a DSS. Through the model construction module portfolio managers are able to flexibly and easily customize a specific portfolio optimization model by choosing from the set of portfolio model building blocks stored in the Modelbase those portfolio constructs matching their requirements. Database Interface Module Since SPMDSS is developed using strict data-model independence, a database interface module has been developed within the model management system to retrieve problem-specific and actual data from the data component of the system so that the mathematical model constructed is initiated with the appropriate data. Model Execution Module This module consists of an execution routine and a modeling language. The execution routine decodes the model constructs selected and data and sets up a complete model using a modeling language (here AMPL). Then the appropriate mathematical solver is identified and the model is passed to the modeling language environment and to an appropriate solver for execution. The results of the solver are then passed to the database and to the dialog component of the SPMDSS.
6.2.4
Dialog Component
To achieve end-user acceptance for the system the dialog component is designed such that the user can access all relevant system functionalities in an easy and user-friendly manner. The major SPMDSS functionalities which end-users can access through the dialog / user interface component include: • Data Manipulation Besides operations through which data can be retrieved, edited and dis-
85
6. SHARIAH PORTFOLIO MANAGEMENT DSS
played portfolio managers are able to calculate portfolio measures (see for instance Figure 6.4) and Shariah ratios through simple dialog forms.
Figure 6.4: Return Calculation in SPMDSS
• Model Manipulation The different model components and functionalities can be accessed through the dialog component easily. Portfolio managers are for instance able to define, add and parameterize different portfolio constraints, Shariah guidelines and measures (see Figure 6.5) as well as alternative objective functions.
• Analysis of Results To evaluate and analyze the generated portfolios SPMDSS provides portfolio managers with summarized table outputs, graphical representations of the results as well as predefined reports (see Figure 6.6).
86
6.2 DSS for Shariah Portfolio Management
Figure 6.5: Return Calculation in SPMDSS
Calculation: 30.06.2007
Optimization Results: Portfolio Details Portfolio Exp. Return Std.Dev. Variance Num.Assets Exp.Return 22.4731% 17.9664% 14.9451% 27.4242% 32.2776% 37.2691% 26.0062% -1.7245% 28.2711% 32.9382% 13.3773% 6.8164% 38.6322% 13.9846% 32.3913% 34.1786% 23.9998% 11.4656% 41.9935% 16.2325% 36.1084% 25.9984% 49.6688% 33.9836% 2.2752% 4.5940% 11.7135% 17.0702% 6.7878% 0 7012% 0.7012% -1.1917% 34.0814% 14.3362%
Std.Dev. 16.4877% 0.00% 18.3107% 0.00% 15.7441% 6.27% 28.7667% 2.07% 28.1156% 0.00% 27.2392% 0.00% 25.9472% 0.00% 3.6528% 10.00% 40.00% 0.00% 21.0337% 41.5430% 0.00% 35.00% 5.25% 20.6446% 19.0472% 10.00% 30.00% 0.00% 27.7553% 15.3454% 0.00% 25.00% 0.00% 29.6780% 34.7911% 0.00% 20.00% 2.30% 24.3456% 23.1817% 4.73% 15.00% 40.4056% 0.00% 22.0376% 2.04% 10.00% 34.7550% 0.00% 22.2421% 0.00% 5.00% 71.7382% 0.00% 38.7177% 0.00% 0.00% 13.9658% 8.17% 15.6108% 0.00% 6.83% 33.6116% 2.00% 18.7629% 2.00% 14.2534% 6.54% 18 9868% 18.9868% 7 35% 7.35% 26.5220% 2.00% 66.5485% 0.00% 25.7991% 0.00%
Expected Return
Asset BARD, (C.R.) INC. JOHNSON CONTROLS SIGMA-ALDRICH CORP EXPRESS SCRIPTS INC COVENTRY HEALTH CARE COACH INC MEDCO HEALTH SOL TYCO ELECTRONICS OCCIDENTAL PETROLEUM SEARS HOLDINGS CORP PUBLIC STORAGE, INC HOSPIRA, INC XTO ENERGY, INC. ECOLAB INC AETNA INC CUMMINS INC. APACHE CORPORATION PATTERSON CO INC TEREX CORPORATION ZIMMER HOLDINGS INC NATL OILWELL VARCO QUESTAR CORPORATION MEMC ELECTRONIC FREEPORT-MCMORAN COP JOHNSON & JOHNSON UNITED PARCEL SVCS SYMANTEC CORP UNITEDHEALTH GROUP WM. WRIGLEY JR. CO CONAGRA FOODS INC MERCK & CO INC ALLEGHENY TECHNOLOGS STARBUCKS CORP
1 6.42% 5.16% 0.27% 24
2 9.49% 5.27% 0.28% 25
3 12.56% 5.60% 0.31% 22
2.00% 8.23% 3.99% 7.48% 8.49% 9.95% 2.80% 3.85% 0.00% 0.00% 0.00% 0.00% 2.00% 2.80% 10.00% 10.00% 0.00% 0.00% 0.00% 0.00% 6.09% 5.89% 9.63% 9.26% 0.00% 0.00% 2.00% 4.00% 0.00% 0.00% 0.00% 0.00% 5.02% 4.31% 5.20% 6.22% 0.00% 0.00% 2.80% 2.39% 0.00% 0.00% 0.00% 2.16% 0.00% 0.00% 0.00% 0.00% 5.97% 0.00% 3.83% 5.00% 2.92% 2.00% 2.43% 3.68% 3.54% 3.44% 2.00% 4 53% 4.53% 0 00% 0.00% 2.53% 2.57% 0.00% 0.00% 0.00% 0.00%
4 15.63% 6.14% 0.38% 21
5 18.70% 6.95% 0.48% 21
6 21.77% 7.89% 0.62% 19
7 24.84% 9.02% 0.81% 18
8 27.91% 10.43% 1.09% 16
Asset-Weight 10.00% 10.00% 10.00% 10.00% 10.00% 10.00% 9.65% 10.00% 10.00% 10.00% 10.00% 3.47% 9.81% 8.00% 8.10% 4.89% 2.00% 0.00% 4.97% 5.99% 6.37% 7.49% 8.97% 9.15% 2.51% 4.95% 7.22% 9.83% 10.00% 10.00% 0.00% 2.00% 3.35% 6.79% 10.00% 10.00% Efficient Frontier 3.55% 5.07% 6.23% 7.33% 7.91% 10.00% 10.00% 9.49% 0.00% 0.00% 0.00% 0.00% 0.00% 5.72% 8.45% 10.00% 10.00% 10.00% 2.00% 2.24% 3.05% 4.29% 5.62% 7.54% 6.02% 6.06% 6.63% 4.97% 3.11% 0.00% 6.78% 3.58% 2.75% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.88% 8.87% 10.00% 5.23% 6.93% 8.46% 7.99% 2.31% 0.00% 0.00% 2.00% 2.00% 2.00% 2.99% 5.86% 0.00% 0.00% 0.00% 2.00% 4.21% 7.68% 5.60% 3.47% 3.81% 2.84% 0.00% 0.00% 4.02% 2.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.11% 2.35% 3.01% 3.69% 2.26% 2.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.00% 2.80% 2.78% 2.44% 2.17% 2.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.18% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10.00% 15.00% 20.00%0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.00%Standard 2.00% Deviation 2.00% 0.00% 0.00% 0.00% 3.17% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Efficient0.00% Frontier 0.00% Initial portfolio 0.00% 0 00% 0.00% 0 00% 0.00% 0 00% 0.00% 0 00% 0.00% 0 00% 0.00% 0 00% 0.00% 3.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.00% 2.00% 2.77% 2.27% 0.00% 0.00%
Figure 6.6: Example Report of SPMDSS
87
9 30.98% 12.24% 1.50% 14
10 34.05% 15.07% 2.27% 14
11 Initial.PF. 37.12% 10.61% 22.81% 17.80% 5.20% 3.17% 10 7
6.69% 0.00% 0.00% 0.00% 0.00% 0.00% 5.23% 0.00% 10.00% 0.00% 10.00% 10.00% 7.21% 0.00% 0.00% 0.00% 4.90% 0.00% 9.69% 10.00% 0.00% 0.00% 0.00% 0.00% 10.00% 10.00% 0.00% 0.00% 6.73% 10.00% 7.13% 10.00% 0.00% 0.00% 0.00% 0.00% 10.00% 10.00% 0.00% 0.00% 6.09% 10.00% 0.00% 0.00% 4.33% 10.00% 2.00% 10.00% 0.00% 0.00% 25.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0 00% 0.00% 0 00% 0.00% 0.00% 0.00% 0.00% 10.00% 0.00% 0.00%
Norm. 6.99% 5.87% 5.23% 5.17% 4.96% 4.74% 4.74% 4.50% 4.46% 4.04% 4.00% 3.82% 3.80% 3.36% 2.87% 2.82% 2.49% 2.02% 2.01% 1.87% 1.64% 1.30% 1.30% 1.29% 1.29% 1.23% 1.13% 1.13% 1.09% 1 08% 1.08% 0.92% 0.91% 0.82%
6. SHARIAH PORTFOLIO MANAGEMENT DSS
6.3
Examples of Specific SPMDSS
Based on the concepts reviewed and developed within this research as well as previous project experiences (Derigs & Nickel, 2004c) different portfolio management requirements can be customized into a Specific DSS using the SPMDSS Generator. Due to the flexibility of the SPMDSS Generator fund managers can easily configure their specific DSS. To show the capabilities of the SPMDSS Generator three examples of specific DSS for different users are described (see Figure 6.7).
SPMDSS I: Ͳ Screening System 1. Asset Compliance 2. All Shariah Schools 3. All Shariah Strategies
SPMDSS II: Ͳ Active Portfolio Mgmt Ͳ Internal Guidelines Ͳ Legal Guidelines Ͳ Shariah Requirements 1. Asset Compliance p 2. Schools: DJ, S&P, MSCI 3. Ijmaa Strategy 4. Purification 5. Shariah Sustainability
SPMDSS III: Ͳ Passive Portfolio Mgmt Ͳ Transaction Costs Ͳ Internal Guidelines Ͳ Legal Guidelines Ͳ Shariah Requirements q 1. Portfolio Compliance 2. InͲHouse Shariah Rules 3. Purification
S ifi SPMDSS SpecificSPMDSS
SPMDSSGenerator
DSSTools
Figure 6.7: Examples of Specific DSS using SPMDSS
6.3.1
SPMDSS I - A Screening System
Shariah service providers and conventional index providers who provide Shariah screening services provide fund managers with a list of assets which based on
88
6.3 Examples of Specific SPMDSS
the specified Shariah guidelines are compliant and can therefore be considered for investment. Through using the SPMDSS Generator a specific screening system (Specific DSS) can be configured and used by either the Shariah service providers or the fund managers directly so that they can interactively screen the asset universe using the Shariah guidelines. This specific screening system (which is named ShariahIntelligence) differs from existing screening systems used by Shariah services providers in • The ability to screen for multiple Shariah schools simultaneously using the new strategies developed in section 4.1 (see Figure 6.8). • The possibility to flexibly define new Shariah guidelines • The interpretation and reasoning explanation for asset compliance / noncompliance (see Figure 6.9) The specific SPMDSS ShariahIntelligence is used within the empirical analysis done in section 7.1.
6.3.2
SPMDSS II - Active Portfolio Management
A classical portfolio optimization problem is the construction of the efficient frontier using the Markowitz Mean-Variance model as described in section 2.2.3. Fund managers can then based on their risk / return preferences select one of the efficient portfolios for investment. The specific SPMDSS II enables fund managers to construct the efficient frontier considering all the conventional portfolio management aspects such as transaction costs, legal as well as internal guidelines.
More over it supports: • Shariah guidelines such as those defined by Dow Jones, Standard and Poor’s and MSCI • Shariah strategies like the Ijmaa strategy etc. (see section 4.1.1) • The newly developed portfolio paradigm (see Figure 6.10)
89
6. SHARIAH PORTFOLIO MANAGEMENT DSS
Figure 6.8: Selection of Shariah Schools and Strategies • Purification-adjusted returns (see section 4.2) • Shariah sustainability (see section 4.3)
This specific SPMDSS II called ”Shariah Optimizer” was used to perform the empirical analysis in sections 7.2 and 7.3.
90
6.3 Examples of Specific SPMDSS
Figure 6.9: Example of Shariah Compliance Reasoning
6.3.3
SPMDSS III - Passive Portfolio Management
Recently a new class of Islamic investment products, the so-called Islamic Exchange Traded Funds (ETFs), has been introduced to the market . ETFs are financial instruments which expose investors to market risk only. Such funds are index trackers which track a specific index (such as the S&P500 or Dax30). SPMDSS III for passive management of Islamic ETFs extends a conventional index tracking model and enables the user to • Customize the set of Shariah guidelines • Consider purification-adjusted returns • Apply the new Shariah-compliance paradigm
91
6. SHARIAH PORTFOLIO MANAGEMENT DSS
Optimization Parameters Optimization Model Compliance Level Consider Purification Min. Number of Assets Max. Number of Assets Shariah Assets Rules to consider: S&P Shariah Rules DJ Shariah Rules FTSE Shariah Rules MSCI Shariah Rules HSBC Shariah Rules Amiri Shariah Rules User-defined Rules Number of Steps Transaction Costs Save Solutions
Markowitz Model Portfolio Level YES 0 40 Consensus / Ijmaa YES YES NO YES NO NO NO 10 NO YES
Figure 6.10: Configuration of SPMDSS Optimizer These three examples show how the SPMDSS Generator can be used to implement different Specific SPMDSS which support different decision problems faced by fund managers or Shariah index providers.
92
Part III Empirical Analysis
93
Chapter 7 Empirical Analysis 7.1
Analysis I: Shariah Compliance Comparative Analysis
1
In the following analysis the quantitative financial screens used by the differ-
ent Islamic funds and index providers are compared. Through this comparative analysis the impact of using different Shariah screening bundles for the definition of the asset universe is identified and interpreted. The objective of this analysis is to identify whether the use of different screening bundles has an impact on the inclusion or exclusion of a single asset and on the overall size of the compliant asset universe.
7.1.1
Basics and Assumptions
Since the analysis targets to identify the impact of using different Shariah guidelines on a representative basis a professional reference asset universe, the Standard and Poor’s 500 index is used. Since the S&P 500 index constituents change over time, a static snapshot with the constituents of 17th of September 2007 has been selected. Due to the fact that detailed financial statements are only available on an annual basis, the screening process and the analysis is based on the five annual financial statements published by each of the companies included in the S&P 1
This section has been partially published in Derigs & Marzban (2008b)
95
7. EMPIRICAL ANALYSIS
500 asset universe from January 2003 until April 2007. The Thomson database retrieved through the software system MarketIQ1 has been used as data-source. Yet, to perform the analysis adequately, financial data from other publicly available data providers had to be added to and merged with the data provided by MarketIQ to overcome the problem of missing data elements. Additionally, a number of data cleansing operations, conditional calculations as well as automated web queries needed to be performed to reach a satisfactory and usable data quality. The reader should be aware that the obtained results are based on the specific data used and are therefore subject to precision errors and deviations from the calculations and results obtained by providers using different data sources. But, since all Shariah screens are calculated using the same data set, the results are consistent, and, also precision errors should not have a significant effect on the analysis. Since relevant differences among screening guidelines are more with respect to the quantitative financial screens rather than the qualitative sector screens, a unified sector screen has been used for all considered funds and indexes to measure the impact of using different financial screens exclusively. An additional assumption of minor importance is that the business activity or industry to which a company belongs stays the same over time instead of being possibly modified through mergers or acquisitions, for instance. A sample of the Islamic indexes and funds listed in appendix A has been selected to be included in the comparative analysis. The Islamic indexes and funds considered are Dow Jones, Standard and Poor’s, FTSE, MSCI, HSBC and Amiri Capital. The reasons for selecting this sample are:
• This subset includes the most prominent indexes and funds in the industry • It includes representative providers using total assets as well as market capitalization as divisors. 1
The same data source, MarketIQ, is used by professional Islamic index and fund providers such as Amiri Capital and FTSE. The data used in this analysis was provided for research purposes by Afkar Consulting and Amiri Capital.
96
7.1 Analysis I: Shariah Compliance Comparative Analysis
• All the indexes and funds selected have at least one Shariah scholar supervising in common. This allows analyzing additional aspects concerning the source of jurisdiction.
7.1.2
Sector Compliance
There are mainly three different industry classification codes used across the industry for Shariah screening. Standard and Poors and MSCI perform screening based on GICS (Global Industry Classification Standard) a standard which was jointly developed by both. Dow Jones and FTSE also use a self-developed coding system ICB (Industry Classification Benchmark) that is very similar to the GICS coding system. A different sector screening approach is used for instance by Amiri Capital, which uses the Standard Industry Classification (SIC) codes. The advantage of using SIC rather than GICS or ICB is that a company can be assigned multiple SIC codes based on the different industries or businesses it is operating in. In the case of GICS and ICB, each company is assigned a single code based on its major business activity. Therefore using GICS or ICB codes would not screen out for instance an automotive company which is at the same time involved to a high extent in financial services. Alternatively, based on SIC codes such a company is screened out more easily since one of its codes indicates a non-compliant activity. The sector screening has been performed based on GICS. In Table 7.1 the non-compliant1 industries / sub-industries are listed. Thus in the analysis every constituent of the S&P 500 asset universe which is assigned one of the GICS codes stated in Table 7.1 has been excluded from any further Shariah-compliant investment consideration. Table 7.2 illustrates the outcome of the sector screening phase with the exclusion of 113 companies out of 500, which is about 23 percent of the S&P 500 asset universe, grouped by sectors. Thus, considering a fund that uses only sector screens such as the Allianz Islamic fund in Egypt, all 387 out of 500 companies passing the above screen would be eligible for investment. 1
The GICS codes used are based on the sector exclusion rules of MSCI Shariah Indexes (MSCI, 2007). From the diversified financial companies all are excluded except Residential and Office Real Estate Investment Fund and Real Estate Management and Development companies
97
7. EMPIRICAL ANALYSIS
GICS Code 20101010 25301010 25301020 25301040 25401020 25401030 30201010 30201020 30203010 4010xxxx 4020xxxx 4030xxxx
Industry / Sub-Industry Aerospace and Defense Casinos and Gaming Hotels, Resorts and Cruise Lines Restaurants Broadcasting and Cable TV Movies and Entertainment Brewers Distillers and Vintners Tobacco Banks Diversified Financials Insurance
Table 7.1: Unified Exclusion Codes Unified Sector Screens Sectors Consumer Discretionary Consumer Staples Energy Financials Health Care Industrials Information Technology Materials Telecommunication Services Utilities S&P 500 Constituents
Halal 71 32 32 14 53 42 75 28 9 31 387
Haram 17 7 78 11
113
S&P 500 Constituents 88 39 32 92 53 53 75 28 9 31 500
Table 7.2: Sector Screening Result
7.1.3
Financial Compliance
In the following sections, the impact of using different financial screening bundles on the size of the Shariah asset universe and the level of classification differences among Islamic funds and indexes is identified and interpreted. Therefore, after reducing the S&P 500 asset universe using the unified GICS sector screens, the individual financial screens used by the different funds and indexes are applied and compared to each other.
98
7.1 Analysis I: Shariah Compliance Comparative Analysis
7.1.3.1
Size of the Asset Universe
Table 7.3 gives an overview on the size of the asset universe after applying the individual financial screens over the period of five years.
S&P 500 Asset Universe Halal Companies S&P DJIM MSCI Amiri FTSE HSBC
2007 271 266 247 246 241 232
2006 274 268 250 247 244 231
2005 265 258 237 235 231 226
2004 231 224 223 221 217 212
2003 217 210 214 211 209 190
Table 7.3: Financial Screening - Asset Universe
It can be seen that using the guidelines of Standard and Poor’s provides a relatively larger asset universe as applying the guidelines of HSBC, for instance. Another remarkable aspect is that S&P and Dow Jones, the two providers who use market capitalization as divisor, have a larger number of halal companies in their asset universe compared to the rest of the providers who all use total assets as divisors. On the other hand, as shown in appendix A (see Table A.1), this greater liberalism is compensated since S&P and Dow Jones are more conservative with respect to sector screens where companies with any involvement in haram activities are excluded compared to other providers that consider only the core business activity for exclusion. The reason why differences in the number of companies classified as being halal exists, using for instance the financial guidelines of HSBC Amanah and MSCI, can be explained as follows: MSCI uses two separate ratios to bound for each asset i at time period t the sum of accounts receivables ARi (t), cash and short-term investments CSIi (t) relative to total assets T Ai (t), i.e. the formulas used are: c=
CSIi (t) ≤ 33.33% T Ai (t)
and
99
a=
ARi (t) ≤ 70.00% T Ai (t)
7. EMPIRICAL ANALYSIS
On the other hand HSBC uses a single ratio for the two denominator elements of the MSCI ratio, i.e. the formula used is: c+a=
ARi (t) + CSIi (t) ≤ 50.00% T Ai (t)
Figure 7.1 illustrates that based on the MSCI guidelines the number of companies passing the financial screen may be significantly larger.
c 0.8 0.7 0.6 MSCI 1
0.5
MSCI 2
04 0.4
HSBC 0.3 0.2 01 0.1 0 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7 a
Figure 7.1: Screening Impact on Asset Universe
7.1.3.2
Different Classifications among Islamic indexes and funds
More consequential and relevant for asset selection, portfolio management and optimization is to compare the different Shariah-compliant asset universes, that are defined as a consequence of using the individual Shariah guidelines. Table 7.4 shows how the set of the remaining 387 candidates which passed the qualitative sector screening are further classified. In the year 2007 for instance, using the guidelines of the sample funds and indexes resulted in a joint agreement on 197 (about 50 percent) companies as being halal and 79 companies (about 20 percent)
100
7.1 Analysis I: Shariah Compliance Comparative Analysis
as being haram. The companies on which the funds and index providers agreed upon as being halal can be regarded as labeled ”green” and the ones on which the providers agreed on as being haram ”red”. The remaining ”gray” companies are those where the funds and index providers differ in their classification and this category contains 109 companies representing a substantial fraction of about 28 percent of the considered universe. The existence of such a large number of companies categorized as being gray is highly problematic and confusing for Islamic investors. Fund managers that follow more moderate Shariah guidelines have a much bigger asset universe to select from compared to managers who have to follow stricter guidelines such as the ones defined by the Shariah board of HSBC Amanah. Table 7.5 gives a pair wise comparison of the difference in classification among S&P 500
S&P Status
DJIM Status MSCI Status
Amiri Status Halal
Halal Halal Halal
Haram Haram
Halal
Halal
Haram
HSBC Status Halal
2007
2006
2005 2004 2003
197
186
187
161
148
Haram
6
13
5
7
7
Haram
Haram
3
4
3
4
3
Halal
Haram
FTSE Status Halal
2
1
1
2
Haram
1
1
1
1
1
Halal
8
12
9
9
6
Haram
51
50
52
41
43
Halal
Halal
5
6
6
7
7
Haram
Haram
Haram
Halal
Haram Haram
Haram
Haram
1
Halal
22
27
22
33
29
Haram
11
10
10
8
16
Haram
2
1
1
1
1
2
2
Halal Haram
79
74
84
107
N/A
2
1
3
5
117 7
Total
387
387
387
387
387
Table 7.4: Funds / Indexes Discrepancies the different funds giving the percentage of assets which are defined halal by one provider and defined at the same time as haram by another provider and vice versa. One major reason for the existence of variations is related to the divisor used to calculate the financial screening ratios. S&P and Dow Jones use average market capitalization as divisor and both use almost similar ratios and
101
7. EMPIRICAL ANALYSIS
thresholds levels. Thus, it is logically consistent that the differences between S&P and Dow Jones are almost negligible with 1.3 percent only. On the other hand comparing Dow Jones or S&P to the rest of the providers who use total assets as divisor, a different level of variation of about 25 percent is noticed. Again, among the providers using total assets as divisor the variation rate is negligible except for HSBC Amanah where a higher variation between 6.5 and 8 percent can be observed. This is due to the more conservative financial ratios used by HSBC. In a final analysis the reasoning behind the differences among the halal asset S&P S&P DJIM
DJIM 1.30%
MSCI
Amiri
FTSE
HSBC
24.40%
24.60%
24.90%
21.60%
25.70%
26.00%
26.20%
22.90%
0.00%
1.60%
8.00%
1.30%
7.80%
MSCI Amiri FTSE
6.50%
Table 7.5: Variation in classification among Funds / Indexes universes defined by the different Islamic funds and index providers is investigated and may be due to the subjective opinion of specific schools or scholars. Therefore a combination of two providers and a set of six Shariah scholars with four of the six scholars serving on both boards is considered. The two providers were selected such that one of them represents providers using market capitalization as divisor whereas the other represents providers that use total assets as ratios divisor (the names of the Shariah scholars and as well as the sample funds / indexes are kept anonymous). Table 7.6 illustrates this sample. This joint supervision by four scholars should logically imply that either no or only neglectable differences exist. Yet, as can be observed in Table 7.7, this is not the case. This specific comparison shows again that the provider using market capitalization has a slightly larger asset universe of assets which are halal although almost the same Shariah board is involved. Thus this indicates that the alternative to choose market capitalization over total assets is systematically offering larger
102
7.1 Analysis I: Shariah Compliance Comparative Analysis
Supervision Sample Shariah Scholar 1 Shariah Scholar 2 Shariah Scholar 3 Shariah Scholar 4 Shariah Scholar 5 Shariah Scholar 6
Provider1 Provider using Market Cap r X X X X
Provider2 Provider using Total Assets X X X X X
X
Table 7.6: Shariah Scholars across Funds / Indexes S&P500Universe–2007 MarketCapRepresentative Halal
TotalAssetsRepresentative Halal Haram
Total
205
61
266
Haram
27
92
119
Total
232
153
385
Table 7.7: Classification Market Cap vs. Total Assets Representatives freedom. Another aspect which is more striking is the outcome that this is not achieved by just shifting haram assets to halal, but that also 27 assets which are halal under market capitalization become haram when calculating total assets. In total the same Shariah scholars defined on average approximately one out of five companies as halal for one product and as haram for the other product.
7.1.4
Conclusion of Analysis I
This analysis demonstrates the impact of using different Shariah guidelines on the definition of a halal asset universe and the analysis provides a deeper understanding of the rationale behind the different existing, most-frequently used Shariah screening guidelines in the industry. The analysis has clearly shown that the use of different guidelines generally results in different classifications of companies into halal and haram among the considered funds and indexes. From the authors’ point of view, such an inconsistency can contribute to insecurity and distrust of Islamic investors into financial products like funds and thereby hinders the further development of the Islamic equity area and the attraction of larger investments. The expertise of Shariah scholars is an essential and crucial
103
7. EMPIRICAL ANALYSIS
element in structuring Islamic financial products and also making conventional financial products accessible to Islamic investors. However, this research has revealed that different classifications by the same scholars occur across funds and indexes. Certainly, the Shariah scholars are not doing the operational work in terms of financial ratio calculations themselves and therefore they are not explicitly defining a specific company once as halal and at the same time as haram for another provider. Yet, the results show that the mathematical formalism may not be able to fully account for the subtle and subjective interpretation of the Islamic sources and that the effect of bundles of such formal constraints may be too complex to be anticipated on every possible asset universe. Therefore, the development of a unified and standardized screening framework which takes into account the different existing Shariah guidelines and allows a controlled and understandable classification will certainly enrich the credibility and consistency of Islamic equity products.
7.2
Analysis II: Shariah Compliance in Active Portfolio Management
1
In the following empirical analysis results concerning the impact of the different
compliance strategies on expected portfolio return, risk and compliance consistency are reported. The main purpose of this analysis is to make the potentials of the new strategies transparent, i.e. to show that the Shariah compliance strategies which have been developed and proposed in section 4.1 perform better than portfolios following one of the basic Shariah strategies. The analysis has been executed using the Shariah Portfolio Management Decision Support Systems (SPMDSS) described in section 6.2, through which the selection of different compliance strategies, data preparation, model parameterizations, model manipulation and model solving as well as graphical representation of results can be performed easily through a user friendly spreadsheet interface. 1
This section has been partially published in Derigs & Marzban (2008c) and Derigs & Marzban (2008a)
104
7.2 Analysis II: Shariah Compliance in Active Portfolio Management
7.2.1
Data and Portfolio Optimization Model
The analysis is based on the assets included in the Standard & Poor’s 500 (S&P500) index on the 17th of September 2007, which will be from now on referred to as the asset universe. To measure the Shariah-compliance of the assets included in the asset universe, the detailed financial figures for the financial year 2006 of the companies issuing the respective assets, as published in their annual financial statements, have been retrieved using the software system MarketIQ. Additionally, the monthly total returns (annualized) and market capitalization values of the considered assets were retrieved from Bloomberg. The following set of basic Shariah strategies S = { S&P, DJIM, FTSE, MSCI, HSBC, ANON } has been considered. Based on the type of financial ratios used these strategies can be categorized into two groups: the set of market-capitalization (MC) based strategies S M C = { S&P, DJIM } and the set of total assets (T A) based strategies S T A = { FTSE, MSCI, HSBC, ANON }. Reflecting the portfolio management strategy (active or passive) different portfolio optimization models with different objective functions have to be formulated and used. Within a passive management strategy so called index tracking models (Coleman et al. (2006); Derigs & Nickel (2003);Derigs & Nickel (2004a)) are common where the objective is to approximate a benchmark index as close as possible. For this study an active portfolio management is assumed and the implementation and comparison is based on the Markowitz Mean-Variance approach (Markowitz, 1952) constructing the efficient frontier and the set of efficient portfolios from which the user can then choose an appropriate portfolio according to his risk profile. Here a portfolio is efficient if it has minimal risk among all portfolios of the same return (or vice versa). In a practical situation the efficient frontier can only be approximated and due to the possibly large number of efficient solutions only a representative subset of efficient portfolios should be constructed and presented to the investor to reduce complexity. This approach is implemented as follows: For every model instance first the possible return spread is calculated by constructing the two extreme portfolios which are efficient: the portfolio with maximal (expected) return and the portfolio with minimal (expected) risk. Then the efficient frontier is approximated by constructing for ten equidistant return
105
7. EMPIRICAL ANALYSIS
values μ∗ between these extreme values the associated portfolios of minimal risk.
Portfolio Problem Extensions and Parameters 2 Standard Model Used: Min{σ (x)| ni=1 xi = 1, μ(x) ≥ μ∗ , xi ≥ 0 ∀i ∈ I} Floor & Ceiling Requirement: No Short-Sellings are allowed and maximum weight of a single asset may not exceed 10% li ≤ xi ≤ ui ∀i ∈ I, with li = 0 and ui = 0.1 Sector Exclusion: The assets assigned to one of the following sector codes are non-complaint: GICS Code 20101010 25301010 25301020 25301040 25401020 25401030 30201010 30201020 30203010 4010XXXX 4020XXXX 4030XXXX
Industry / Sub-Industry Aerospace and Defense Casinos and Gaming Hotels, Resorts and Cruise Lines Restaurants Broadcasting and Cable TV Movies and Entertainment Brewers Distillers and Vintners Tobacco Banks Diversified Financials Insurance
Maximum Cardinality: The number of assets included in a portfolio is limited to 40 assets. This can be modeled as follows: n v i=1 i ≤ CardMax xi ≤ vi ∀i ∈ I vi ∈ {0, 1} ∀i ∈ I with CardMax=40 Table 7.8: Model and Parameter Settings To show that the models are practical, i.e. can be solved within a practical environment two constraints have been included which represent aspects which on top of Shariah compliance have to be considered in real investment situations: a constraint limiting the weight of an asset to at most 10 percent which can be interpreted as an example for a legal guideline (Derigs & Nickel, 2003) and a
106
7.2 Analysis II: Shariah Compliance in Active Portfolio Management
constraint limiting the number of assets to be included in the portfolio to at most 40 assets which is a common internal guideline reducing the complexity of management (Jobst et al., 2001). Also, in a preprocessing step the asset universe is reduced by applying unified Shariah sector guidelines. The complete model and used parameters are summarized in Table 7.8. Now the results of the analysis for the different strategies and paradigms are reported.
7.2.2
Performance of Basic Shariah Strategies
First, the portfolio model was run with the guidelines/constraints from the six basic strategies. The resulting efficient frontiers are depicted in Figure 7.2. As a reference the conventional non-Shariah model was also run i.e. without any further reduction of the asset universe. In section 7.1.3 of this research it is shown that the variations with respect to Shariah compliance among basic strategies belonging to the same class, S M C or S T A , are almost negligible. This explains why in Figure 7.2 the efficient frontiers for the different strategies within one class are almost identical. Due to the fact that the basic strategies s ∈ S M C result in a larger asset universe than the strategies s ∈ S T A (see Table 7.3) all the efficient frontiers of the basic strategies s ∈ S M C are above the efficient frontiers of the basic strategies s ∈ S T A , i.e. with the first class of strategies higher return at lower risk can be obtained. Of course, the frontiers of all basic Shariah strategies are below the frontier from the related conventional model without Shariah compliance guidelines. It is worth noting that strategies s ∈ S M C perform only slightly worse with respect to return. Yet, to realize the maximal possible return much higher risk has to be taken. A closer look at the set of efficient portfolios reveals that the difference in performance is not only attributable to the larger asset universe but stems from the fact that the constituents included in the different asset universes and consequently the assets selected for investment portfolios differ highly among the efficient portfolios of different strategies. This is reflected in Table 7.9. Here the assets of the efficient portfolios are clustered into six representative sectors. Then, for DJIM as representative for a MC-based strategy and MSCI as representative for a T A-based strategy the proportion of investment which is not
107
7. EMPIRICAL ANALYSIS
Return 45.00%
40 00% 40.00%
35.00%
30.00%
Conventional S&P
25.00%
DJIM FTSE
20.00%
HSBC MSCI & AMIRI
15.00%
10.00%
5.00%
0.00% 0.00%
5.00%
10.00%
15.00%
20.00%
25.00% Risk
Figure 7.2: Performance of Basic Shariah Strategies
compliant with respect to the other strategy is calculated and the amount is allocated to the respective clusters. The last line (sum of weights) of the upper part of Table 7.9 shows that overall a significant fraction of the optimal investments under the MC-strategy DJIM are into assets which are not compliant under the T A-strategy MSCI whereas the last line of the lower part shows that the reverse inconsistency is much less. This means that assets which contribute positively to the portfolio performance for DJIM are non-compliant under the MSCI strategy. Considering the individual figures it can be noted that for instance DJIM results for almost all return levels in efficient portfolios with a high proportion of wealth invested in assets belonging to the Information Technology, Health Care and Consumer Staples sectors which are not compliant under the T A-strategy MSCI. To further analyze this phenomenon the percentage of companies whose market capitalization is significantly larger or smaller to total assets is calculated for each sector. As you can see from Figure 7.3, most of the companies belonging to sectors such as Information Technology (85 percent), Health Care (79 percent)
108
7.2 Analysis II: Shariah Compliance in Active Portfolio Management
Table 7.9: Weights of assets aggregated by sector compliant under DJIM and not under MSCI and vice versa and Consumer Staples (72 percent) have a market capitalization value which is larger than their total assets value. Contrary, companies belonging to the utilities (94 percent) and telecommunication (89 percent) sectors have a total assets value larger than their respective market capitalization value. One of the main reasons for this property is that in general the value of intangible assets such as intellectual properties, patents and projects under development is not accounted for in the balance sheet of the respective companies and thus total assets are undervalued. An information technology company such as Microsoft for instance is not capital intensive since most of the assets are in intangible form and currently valued on the market four times the total assets value. The same also applies to companies in the health sector whose in-house developed intellectual property and projects in the pipeline do not appear on the balance sheet. Thus, for such companies market capitalization is usually significantly larger than total assets and if two Shariah guidelines differ in terms of the divisor only, which is almost the case for DJIM and MSCI (see Appendix A), then systematically the use of TA-based guidelines results in an exclusion of companies from intellectual property sensitive sectors from the asset universe which means the exclusion of assets with good return and risk profiles. This exactly could be observed in this analysis where assets of good performance were excluded from the asset universe by TA-based strategies resulting in an overall under performance compared to the MC-based strategies.
109
7. EMPIRICAL ANALYSIS
Utilities
6%
Telecom
94%
11%
89%
Materials
57%
43%
InformationTechnology
85%
Industrials
15%
57%
43% MCLarger
HealthCare
79%
Financials
21%
38%
Energy
63%
ConsumerStaples
38% 72%
ConsumerDiscretionary
28%
63% 0%
10%
20%
TALarger
62%
30%
37% 40%
50%
60%
70%
80%
90%
100%
Figure 7.3: Sector-based Comparison Market Capitalization vs. Total Assets
These sector-specific findings motivate to apply modified screening guidelines in which the type of divisor of the financial ratios is decided upon based on the company’s sector. Thus, this research claims that a more realistic evaluation would be achieved if the financial ratios for companies from Information Technology, Health Care and Consumer Staples are based on their market capitalization value whereas for companies from the Utility and Telecommunication sector their total assets value are used. In Figure 7.4 the impact of this modified screening approach compared to the common approaches is shown which are based on either total assets or market capitalization. As can be seen, the usually total assets based strategy MSCI shows a much better risk/return profile since a number of companies from the formerly excluded sectors are now eligible and contribute positively to the portfolio performance. Such an effect does not show up for the usually market capitalization based strategy DJIM, since the efficient portfolios contain already all favorable companies. In fact, under the modified strategy the performance difference between MSCI and DJIM diminishes.
110
7.2 Analysis II: Shariah Compliance in Active Portfolio Management
Return 45.00% 40 00% 40.00% 35.00% 30.00%
DJIMStandard J Sta da d MSCIStandard
25.00%
MSCINew 20.00%
DJIMNew
15.00% 10.00% 5.00% 0.00% 0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
Risk
Figure 7.4: Effect of using sector-based MC/TA divisor on DJIM and MSCI
7.2.3
Performance of New Asset-based Shariah Compliance Strategies
First, the degree of inconsistency between the new strategies and the base strategies is analyzed i.e. the difference between the asset universes analogously to the analysis shown in Table 7.10 with the only difference that the inconsistency is partitioned into type I error (classifying an asset compliant by a new strategy and non-compliant by a basic strategy) and type II error (classifying an asset non-compliant by a new strategy and compliant by a basic strategy). As can be seen in Table 7.10 the Ijmaa strategy achieves lowest type I error since no asset is included in its asset universe which is considered to be non-compliant by any basic strategy and the majority strategy has a type I error which is lower than the inconsistencies among the basic strategies. With respect to type II error, the liberal strategy shows no inconsistencies and the majority strategy is more or less consistent with the TA-strategies. Figure 7.5 reveals that these different levels of Shariah compliance of the new strategies are reflected in performance, i.e. return and risk profile as expressed by the efficient frontier. Less conservative strategies such as the liberal and Best
111
7. EMPIRICAL ANALYSIS
Type I Error: compliant by new strategy and non compliant r by basic strategy S&P DJIM MSCI Amiri FTSE HSBC Best of Remains the same as in Table 7.5 Ijmaa 197 0% 0% 0% 0% 0% 0% Majority 253 8.57% 9.87% 2.08% 2.34% 3.12% 5.45% Liberal 306 9.09% 10.39% 15.32% 15.58% 16.88% 19.22% Type II Error: non compliant r by new strategy and compliant by basic strategy S&P DJIM MSCI Amiri FTSE HSBC Best of Remains the same as in Table 7.5 Ijmaa 197 19.22% 17.92% 12.98% 12.72% 11.43% 9.09% Majority 253 13.25% 13.25% 0.52% 0.52% 0.00% 0.00% Liberal 306 0% 0% 0% 0% 0% 0%
Table 7.10: Inconsistency in classification of new strategies vs. basic strategies of strategy perform very similar and their frontiers are close to the conventional portfolio model and they clearly dominate the portfolios constructed using the Ijmaa or the majority strategy. As expected, the most conservative Ijmaa strategy performs worst, which is a logical result of the small asset universe (197 assets).
Return 45.00% 40.00% 35 00% 35.00% 30.00%
Conventional Liberal
25.00%
Best of Bestof Majority
20.00%
Ijmaa
15.00% 10.00% 5.00% 0 00% 0.00% 0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
Risk
Figure 7.5: Performance of Proposed Strategies Asset-based
112
7.2 Analysis II: Shariah Compliance in Active Portfolio Management
7.2.4
Performance of Portfolio-based Shariah Compliance Strategies
When analyzing the effect of the new paradigm i.e. considering compliance as an attribute of the portfolio rather than the single assets it can be noted that for every new strategy the portfolios constructed under the portfolio-based compliance paradigm outperform their asset compliance counterparts (see Figure 7.6). Yet, there is a significant difference: while the asset-based Ijmaa and Majority strategies are clearly dominated by their portfolio-based counterpart, it can be observed that such outperformance for the Best of and the liberal strategy occur only on the extreme ends of the spread i.e. for low risk and high return levels.
A. Best of Strategy A.Bestof
B. Ijmaa Strategy B.IjmaaStrategy
45.00%
45.00%
40.00%
40.00%
35.00%
35.00%
30 00% 30.00%
30 00% 30.00%
25.00%
25.00%
20.00%
20.00%
15.00%
15.00%
10 00% 10.00%
10 00% 10.00%
5.00%
5.00%
0.00%
0.00%
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
0.00%
C.LiberalStrategy
5.00%
10.00%
15.00%
20.00%
25.00%
20.00%
25.00%
D.Majority Strategy
45.00%
45.00%
40.00%
40.00%
35.00%
35.00%
30.00%
30.00%
25.00%
25.00%
20.00%
20.00%
15 00% 15.00%
15 00% 15.00%
10.00%
10.00%
5.00%
5.00%
0.00%
0.00%
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
0.00%
5.00%
10.00%
15.00%
Figure 7.6: Asset versus Portfolio-based Compliance Strategy The added-value of the portfolio-based compliance paradigm compared to basic strategies currently used by Islamic funds and index providers can be identified
113
7. EMPIRICAL ANALYSIS
in Figure 7.7. The portfolios of the portfolio-based compliance strategies outperform the basic TA-based strategy MSCI significantly whereas the MC-based strategy DJIM is outperformed slightly. Another effect could be observed which has not been expected at all. Applying
Return 45.00% 40 00% 40.00% 35.00% Conventional
30.00%
LiberalPortfolioͲbased BestofPortfolioͲbased
25.00%
MajorityPortfolioͲbased 20.00%
IjmaaPortfolioͲbased DJIMAssetͲbased
15.00%
MSCIAssetͲbased
10.00% 5.00% 0.00% 0 00% 0.00%
5 00% 5.00%
10 00% 10.00%
15 00% 15.00%
20 00% 20.00%
25 00% 25.00%
30 00% 30.00%
Risk
Figure 7.7: Portfolio-based versus Basic Asset-based Compliance Strategies
the new portfolio-based compliance paradigm the significant differences in performance between the two classes of basic Shariah strategies, s ∈ S M C and strategies s ∈ S T A , diminish (see Figure 7.7). This means that under the new paradigm the use of market-capitalization does not lead to better performance anymore i.e. the total assets based strategies which suffered from eliminating more assets from the universe are now comparable. Also, all frontiers constructed under the new portfolio-based compliance paradigm are much closer to the frontier for the conventional portfolio model. Thus the new paradigm offers investors the opportunity to achieve nearly the same risk-return options as conventional funds but being Shariah compliant.
114
7.2 Analysis II: Shariah Compliance in Active Portfolio Management
7.2.5
Conclusion of Analysis II
Within this analysis the problem of Shariah-compliant portfolio construction has been considered. The analysis revealed that on the same asset universe current basic Shariah-compliance strategies result in much lower portfolio performance than portfolios without considering Shariah compliance. To overcome these short comings a number of new concepts for defining Shariah compliance at different levels have been developed including a new paradigm which considers Shariah compliance as an attribute of the portfolio constructed rather than measuring compliance on an asset level as is done in all current approaches. All concepts have been formalized such that they can be incorporated in every conventional portfolio optimization model by simply introducing appropriate sets of constraints. The empirical analysis has clearly shown that if fund managers stick to the current Shariah strategies then they are better off employing market-capitalization based ratios which outperform strategies which use total assets based ratios. This research proposed new concepts for defining Shariah compliance leading to strategies by which portfolios can be constructed that achieve better portfolio performance than current Shariah strategies. Within this research also a new paradigm which measures compliance on a portfolio level rather than individually for every asset has been proposed and justified. The analysis shows that applying this paradigm results in portfolios which perform much better than their assetbased counterparts in terms of return and risk. Another significant effect of the portfolio-based compliance strategies is that not only the performance differences between market capitalization based and total asset based compliance strategies are almost eliminated but even more important Shariah compliant portfolios can reach the performance of conventional portfolios on the same asset universe. Considering compliance as an attribute of the portfolio forces compliance control to take place during portfolio optimization instead of a preprocessing phase as can be done with the current strategies. This requires a shift from the purely extensional description of compliance in terms of specifying the asset universe to an intentional description of compliance in form of checkable guidelines which can be incorporated into the portfolio optimization model. Besides the necessary provision of such guidelines by the Shariah scholars the availability of tools for
115
7. EMPIRICAL ANALYSIS
modeling and solving the Shariah portfolio optimization problem is an important prerequisite, though not mandatory for applying the new paradigm in practice. Such a supporting system has been developed in this work. Certainly and most importantly, the eligibility of the new portfolio-based compliance paradigm has to be analyzed from a Shariah perspective by experienced Shariah scholars whose opinion and judgment decides on the practical acceptance.
7.3
Analysis III: Purification and Shariah Sustainability
7.3.1
Impact of Purification on Portfolio Performance
Within this analysis the impact of considering purification ex-ante rather than as conventionally done ex-post (after investment decisions have been taken) is investigated and evaluated. To consider purification ex-ante expected purification and net purified return is calculated using the formulas introduced in section 4.2. Expected purification is calculated from the historical purification values deduced from historical financial statements and is given by: 1 NP II(i, t) t τ =1 T R(i, t) t
ρ(i) =
∀i ∈ I
The net purified return using the value increase approach is consequently given by: ⎧ ⎫ ⎪ ⎪ ⎨ ⎬ μ ˆ(i) = μ(i) − max μ(i) · ρ(i), ∀i ∈ I 0 ⎪ ⎩ if μ(i)
