4.1 Introduction to Hedge Fund
Nowadays, the numbers of alternative investment funds such as hedge funds are continually increased across the globe. The first hedge fund was established in 1949, there were over 15, 400 single strategy hedge funds and over 6,100 funds of funds (FOFs), with about 800 to 1000 new hedge funds every years (Stavetski, 2009). Today, there are approximately US$1600 billion of assets and more than 9000 funds (Darolles & Gourieroux, 2010). The growth of the hedge funds sector has relatively closed to the development, liberalisation and globalization of financial markets.
Stavetski (2009, p.5) define hedge fund is a business structure, typically a limited partnership or private pool that may be organized in any number of legal jurisdictions. Nevertheless, Garbaravicius & Dierick (2005) argue that there is no common definition in constitute of a hedge fund, instead it can be describe as unregulated in which can be manage freely through multiple investment strategies to capture positive absolute returns. They are able to implement more aggressive strategies and put on positions to pursue the goal, regardless to performance of an index or sector benchmark (Strachman, 2007).
Hedge funds are substantially difference from traditional investment vehicles, for instance bond, stock or mutual fund investment. They can be invested in both cash and derivative markets on a basis of leveraged which had operated and organized off-shore. In general, hedge funds are marketed to wealthy investors. Additionally, hedge funds are fully confidential and largely exempt by regulation. They had being credited as having improved efficiency and adding liquidity to the market place. Their broad diversification across various asset classes included stocks, bonds, commodities, real estate and currencies.
In accordance to Ridley (2004, p.4), there are some characteristics apply to most hedge funds:
Hedge funds are designed to have low correlation, often with a higher return than traditional investment vehicle. However, they are widely varying appetites for risk and having potential instability, for instance, the global financial crisis. They allow the investors to hedge the potential volatility or risk inherent in their investments through multiple investment strategies to generate returns which are uncorrelated to traditional asset classes.
Nevertheless, certain types of hedge funds do not hedge their investments. They are likely to increase instead of to reduce the volatility, particularly in the use of short selling. This may due to the desired of investors in generate absolute returns. The meteoric rise in demand for hedge funds conceal with a number of factors. There was an unprecedented bull-run in the United States (U.S.) financial markets expanded investment portfolios during 1990s, result in the awareness on the demand for diversification.
Consequently, how do the hedge funds make a difference from traditional investment vehicles? Why is it so popular? What is the dark side? They can be identifying as return enhancers, risk diversifiers, or both? These are unknown and uncertainty question.
In order to assess and examine the hedge funds as return enhancers, risk diversifiers, or both, this paper is going to discuss the hedge fund portfolio strategies, classification and performance measure, practical performance issue in performance measure, performance persistence, the risk models, potential risk as well as the case for preserve and against hedge funds.
4.2 Justification for the Chosen Topic
The reason for choosing this topic is not only because of personal interest, but also the important of hedge funds to the investors nowadays. According to Garbaravicius & Dierick (2005) explain the pace of growth of hedge funds reveal that hedge funds are heading towards becoming important non-bank financial intermediaries.
Hedge fund is one of the major alternative investment products today, and as a result of the financial meltdown, many investors attempt to invest in hedge funds. They are aim to generate absolute returns on investment and risk diversification. Despite the essence of hedge fund strategies are generally quite simple when break them down and easy to understand, but the details to execute and evaluate them can be complicated.
Additionally, hedge funds are more exposure to financial market risk than the normal funds. Obviously, hedge funds have a significant impact in financial markets, yet the knowledge of them may be relatively low, partly due to the secrecy exercised by the hedge fund industry.
Therefore, it is necessary to identify the classification and how do the hedge funds influence the world. A good understanding of the hedge funds is required in the process of making investment decisions to avoid some unnecessary risk such as failure of decision making. Moreover, a good understanding is the key to extracting the most benefit from them. Accordingly, the author found it very interesting and exciting to analyse and research on this topic
4.3 Academic Objectives of the Project
The aim of this research is going to research, if the hedge funds appropriate as an alternative investment products for investors, which is classification as return enhancers, risk diversifiers, or both.
5.0 Literature Review
For discovering the hedge funds as return enhancers, risk diversifiers, or both, it is essential to look at literature review with different perspective and point of view about the research. This section provides an in-depth knowledge of hedge funds by various authors that may require further exploration through conducting research.
5.2 Hedge Fund Strategies
According to Fabozzi (2009, p.9) portfolio strategies can be classified as passive or active. A passive portfolio strategy engages minimal expectation input which depends on diversification to match the performance of certain market index. An active portfolio strategy utilizes forecast techniques and available information to achieve a better performance than utilize a simple diversified broadly. Atherton (2007, p.2) describe hedge funds is tricky due to it is an umbrella term for a huge range of multi risk levels and investment strategies.
The highlighted distinguish feature of hedge funds are the investment strategies that investors pursue, thus there is no standard approach to classify it neatly. In another words, there is no widely accepted categorisation of hedge fund strategies. An early survey (Indjic and Heen, 2003) suggested that hedge fund strategies are hardly to classify and the classification system does not necessarily improve matters, as well as the level of transparency will influence the accuracy of the classification approaches.
Traditional broad classifications of hedge funds distinguish between directional and non-directional strategies to capture absolute return goals. First, directional approach dynamically bets that one sector or another will outperform other sector of the market. Those funds will invest in long or sell short securities to generate absolute return from decline and advance. Second, non-directional approach is usually design to exploit temporary misalignments in security valuations and attempts to extract value from a set of embed arbitrage opportunities within and across the securities.
According to the classification by Matthew Ridley (2004, p.9) there are a number of types to be distinguished and divided into five categories: relative value, long-short, event driven, directional and specialists. Diagram 1 represents the classifying of hedge fund strategies and its sub-strategies.
Diagram 1: Classifying of hedge funds strategies and sub-strategies.
Source: Ridley, 2004, p.11.
Relative value strategies attempt to minimise the market risk by taking offsetting long and short positions in relative securities such as bonds and stocks. This strategy enables investors to potentially return from the ‘relative value' between two securities.
Short Selling and Long-Only hedge funds will only invest by shorting or going long respectively, typically with leverage. The portfolio may be net short, net long or neutral. Their position may vary from 100% long in bull market to 100% short in bear market and it enables the investors to understand the general direction of the market.
Event drivenstrategies seek to take advantage of price movements arising from an anticipated or announced corporate event. A best example is to capitalize on merger and acquisition announcements, aimed in increase the corporate share price. A real life example, the share price of Marks & Spencer as shown in diagram 2, rose after the announcement of takeover by Philip Green at May 2004 (their historical share price movement from March to July 2004 is enclosed in appendix).
Diagram 2: Historical share price movement of M&S after the announcement of takeover by Philip Green on May 2004.
Source: Marks & Spencer , 2010.
Additionally, there are some primary databases set up by fund advisors and data vendors. Three primary sub-strategies are discussed as below (further explanations of other sub-strategies are enclosed in Appendix).
Firstly, global or macrostrategies utilize macroeconomic analysis to capitalize on asset price changes is applied on a global level, such as equity, currencies and commodities. These funds incline to be highly leveraged and rely on rapid trading execution. An example on September 1992, George Soross Quantum Fund reputedly invests US$1 billion in a day by speculating the sterling pound may exit from the European Exchange Rate Mechanism.
Secondly, market neutral funds hedge against market risk factors. This strategy profits by speculating on relative price movements between indexes and assets, for instance, long-short equity, fixed income arbitrage etc. Thirdly, arbitrageseeks to capitalize on price inefficiencies between markets and securities on a non-directional basic, where the manager takes the advantage in the pricing of assets.
Atherton (2007) explain certain strategies such as shares or commodities are undoubtedly high risk, hence investors need to be aware of the potential risk, due to hedge funds typically use leverage, this may involves borrowing additional money to increase the size of bet they are taking. Similarly, Morgan Stanley Dean Witter (2000, p.1) reported that hedge funds may have a lower risk profile, in which hedge funds exhibit a low correlation with traditional asset classes, suggested that hedge funds should play an important role in strategic asset allocation.
5.3 Hedge Fund Classification and Performance Measure
Gibson and Gyger (2007) suggest that hedge fund classification is based on a set of global attribute, include investment process, asset class, capitalization, geography and industry. The principal form of hedge fund classification can be classifying in accordance with the investor's use of multiple trading strategy or the markets sector that they invest in.
A research study in 1986 and 1991 by Brinson, Hood and Beebower (Stavetski 2009, p. 12) the contributions of asset allocation over the long term to investment returns has increased concentrate on the need for diversification of investment portfolios. He explained further analysis concluded that the actual result of study was not total return, but volatility.
Hedge funds provide a range of sources of risk and returns (Stanyer, 2010, p.152), their strategies often based on complex mathematical models that work till things change and stop such as the market changes. The language of modeling financial markets engages of probability, which in turn engage of measure theory.
5.3.1 Mean, Variance, Skewness and Kurtosis
Fabozzi (2009, p.21), citing Markowitz's concept of risk utilize well-known statistical measures of variance and covariance (1952, 1959). Fung and Hsieh (1999) commented mean-variance analysis is appropriate when returns are normally distributed or preferences of investors are quadratic. The authors pointed out that when returns are normally distributed, the first two moments such as standard deviation and mean are not sufficient to give an accurate probability. Furthermore, the authors discovered that hedge fund returns are fat-tailed or leptokurtic.
Fund and Hsieh (2001), as well as Agarwal and Naik (2004) reported that hedge fund returns relate to conventional asset class returns and option-based strategy returns. The authors found that a significant part of the variation in hedge fund returns over time can be explained by systematic risk factors.
Many of the hedge fund indices present relatively low skewness and high kurtosis, in particular investment, for instance risk arbitrage, convertible arbitrage and distressed securities. Brooks and Kat (2001) concluded that hedge fund index return is not normally distributed. This can be observed in table 1, Gibson and Gyger (2007) applied a Kolmogorove-Smirnov test at a 5% significance level, they discovered that all the strategies, except long or short strategies, are substantially deviate from a normal distribution.
In addition, Brooks and Kat (2001) argued that it may offer relatively high means and low variances. Therefore, investors may acquire a better mean and a lower variance in return for more negative skewness and higher kurtosis. Similarly, Amin and Kat (2002) suggested the addition of hedge funds to a portfolio improves its mean-variance characteristics, but also induce in greater negative skewness and kurtosis. Generally, certain hedge funds may have low standard deviations which does not indicate that they are relatively ‘riskless', in reality their skewness and kurtosis induce them ‘risky'.
Table 1: Hedge fund net monthly returns statistic reports.
Net monthly returns statistics reports of five primary hedge fund investment strategies and a broad market index (S&P 500) over ten year period ending in April 1999. The monthly average return, standard deviation, Sharpe ratio, skewness, kurtosis and correlation with the S&P 500 Index had been calculated.
Source: Gibson and Gyger 2007.
5.3.2 Correlation of Returns
The correlation structure is fundamental in the point of view of a risk management (Pochon and Teïletche, 2006). According to Wilmott (1998) explains correlation is something that is particularly difficult to predict or calculate thus there is obviously a role to be played by uncertainty and correlations measured from financial time series data are notoriously unstable, which is a very difficult quantity to measure. Accordingly, the hedge rations are likely to be inaccurate. Ennis (2009) describe the correlation of hedge funds with stocks is undoubtedly understood by virtue of the stale pricing that characterizes the asset classes.
Hedge funds are valuable diversification tools to limit the volatility of a conventional portfolio, supposedly to have quite low levels of volatility, hence its low correlation make them doubly valuable. This might because hedge funds often depict as employing skill-based investment strategies in which do not definitely attempt to track a particular index (Schneeweis and Spurgin, 2000). There was further evidence to support researcher's view that hedge fund returns are not highly correlated with each other or with market benchmarks (President's Working Group on Financial Markets, 1999, cited in Brouwer, 2001, p.37). Table 2 exhibits an example of high degree correlation between assets and the market place.
Table 2: An example of high degree correlation between assets and stock market.
The correlation of returns for assets with the S&P 500 on 1 October 2006 to 30 September 2009. The proxies for the assets are based on the daily returns generated in an auction market.
Source: Ennis, 2009.
Another argument is that many hedge funds are inconsistently and continuous poorly or negatively correlated with other assets classes over time (Lavino, 2000). Hedge funds may not have meaningful standard deviations and many of them have distributions with fat-tails, therefore normality assumptions on the distribution of its returns may be incorrect. This indicates hedge funds are inappropriate to use the correlation as a gauge to execute investment portfolio diversification.
Similarly, Lo (2001) reinforced this point of view that many investors involve in hedge funds in order to diversify returns, due to hedge fund returns seem uncorrelated with the market indexes such as the S&P 500. Nevertheless, synchronized in a crisis may arise when there is an uncorrelated events with correlation change from 0 and 1 overnight. Apart from that, hedge funds need to combine with mainstream assets to attain diversification.
Due to their diverse nature, majority of the hedge funds strategies have very low correlations, it bring a feint to the investors. Two important caveats may arise: First, hedge funds are likely a source of returns which bear some relationship with holding assets outright. Even if a fund is managed in an absolute return manner, they may involve with obscure specialization, for instance distressed securities, mainstream markets are bound to have some effect on them. Second, these correlations figures are unstable.
5.4 Practical Performance Issue in Performance Measure
The hedge fund performance is often a subject of considerable debate. It is a reflection of manager skill, leverage and market returns (Stanyer, 2010, p.160). As shown in diagram 3, the cumulative performance of hedge fund industry index has outperformed the U.S. and global stock market indices since 1993 with evidently low volatility.
Diagram 3: The cumulative performance of hedge fund industry index and equities from December 1993 to December 2008.
Source: Stanyer, 2010, p.153.
Generally, hedge funds performance measures are beset by a number of practical issues which result in difficult measurement to fully convey risk and return. They are exposure to high risk based on these issues which confound the return and risk measurement, for example fund size, consistency, use of leverage, style purity, liquidity and asset concentration.
Many of the people assumed that hedge funds have a pure and consistent style, in fact, it is rarely the case. Due to many hedge funds investment strategies may be operated and opportunistic with more than a style and sorted into generic types, therefore many funds do not function efficiently and exactly as their self-reported classifications indicated.
An earlier report of Fung and Hsieh (2001) suggested that a number of strategies may appear as earn their returns due to assuming risk positions in a risk-averse financial world, rather than from inefficiencies in the market place. It indicates that returns are made from a risk transfer (Stanyer, 2010, p.152) instead of the managerial abilities of an individual. This is likely a debate over the years, as the skill of selecting appropriate hedge fund styles and type of managers who execute the styles consistently and how to allocate funds across managers incline to be important to capture absolute returns. Based on this point, it implies that style purity and consistency are important attributes to measure exposure to market risks rather than statistical measures such as variance.
A hedge fund's asset under management (AUM) growth may be due to externally induced because of inflows reason, internally generated through performance, or magnified through the use of higher leverage. Hedge fund size is a dimension which has significant implications for risk and return (Ammann and Moerth, 2005). The fund risk increase proportionately with its AUM due to the used of specialized strategies naturally limits their optimal size which increasingly difficult to maintain the same strategy or have the opportunities for execution. Hedge fund managers will close the funds for further investments when the target size is reached, due to their knowledge of trade-offs between hedge fund performance and size.
Hedge fund managers are expected to drawn the use of leverage to magnify potential returns from small arbitrage opportunities and concentrate on their investible funds in a small subset of potentially rich opportunities. According to Weisman and Abernathy (2000), the importance of guarding against excessive leverage is compounded by lack of liquidity when disastrous event strikes. The authors reported that if one were to construct a non-diversified, illiquid or leveraged portfolio and let it grow over time, it would eventually result in bankruptcy of the fund when a misfortune strikes.
5.5 Hedge Fund Performance Persistence
In general, the investment decisions are mainly on the base of the past performance. Nevertheless, Stanyer (2010, p.155) suggested that investors should not take investment decision based on past performance alone, but expected future performance. Similarly, a study by Baquero, Horst and Verbeek in 2003 (Ridley, 2004, p.64) suggested that before measuring performance it is advisable to model first for hedge fund attrition and look-ahead bias.
However, Bodie, Kane and Marcus (2009, p.113) suggested that investors need to forecast the past values before forecast the future expected returns and risk. The authors cited an old saying that forecasting future is more difficult than forecasting the past.
Some of the returns persistence measurement may not provide appropriate insight into the ability to use historical performance as a means of determining relative future performance, for instance comparing the last month's returns to this month's return. The results of historical data may influence by statistical biases in indices and databases.
Additionally, rebalancing a hedge funds portfolio is constrained by some issues such as the type of managers, lockups, reinvestment assumptions etc. Due to investment portfolio cannot be efficiently rebalanced on a monthly basis, thus the study of hedge funds performance persistent may require a longer ex post holding period than traditional investment vehicles.
5.6 Statistical Biases in Indices and Databases
Hedge fund indices can inherit errors that were inherent in databases, for example Tremont Advisors Shareholder Services (TASS), are subject to certain statistical biases. The published indices overstate the actual experience of investors (Stanyer, 2010, p.155). Uninformed investors may be misled into common misperceptions about the risk and returns of hedge funds. Majority of the bias are spurious. This problems have been noted by Brown, Goetzmann, and Ibbotson (1999), Liang (2000), Aggarwal and Jorion (2010).
5.6.1 Survivorship Bias
Surviviorship arises when a hedge fund sample contains only surviving funds and present at the end of sample period. Funds that perform poorly are likely to be excluded from the database. Fung et al. (2008) classify funds into three categories: alive and reporting, alive but stopped reporting, and liquidated.
Hedge funds managers can stop reporting at their discretion, induce the performance of hedge funds are overstated. It inclines to be one of the major criticisms of hedge fund industry. If funds cease operations typically for poor performance reason, the historical returns of surviving funds in the database is subject to upward bias (Stanyer, 2010, p. 155) with risk and biased downward relatively to the population of hedge funds.
Survivorship bias is well documented and easy to quantify, where the entire fund population is observable and known (Grinblatt and Titman 1989, Brown et al. 1992, Malkiel 1995, cited in Lhabitant, 2002, p.134). However, Aggarwal and Jorion (2010) pointed out that survivorship creates major problems for performance evaluation, including spurious performance persistence. Their study found that bias is substantial averaging more than 5 percent a year. Table 3 represents the descriptive statistics data of survivorship bias from 1995 to 2004. It indicates that the bias had continually increased in averaging each year.
Table 3: The summary statistics data of survivorship bias from 1995 to 2004.
The columns show the total number of funds-of-funds in data at the end of the year, the number of funds that entered the data during the year, the number that were liquidated during the year, the number that stopped reporting during the year, the total AUM in billions of U.S. dollars of the funds alive at the end of each year, and the mean, median, and standard deviation of the annual return at the end of the year across all funds.
The AUM has grown from US $18 billion in FOFs at end of 1995 to around US $190 billion in 2004. The average birth rate is 27%, the average liquidation rate is 4.7% and the average rate of funds that stopped reporting despite being alive is 2.7% per year. The equally weighted mean return across funds is 10.3% over the sample period.
Sources: Fung et al. 2008.
5.6.2 Selection Bias
Selection bias arises if the hedge funds in an observable portfolio are not representative of the universe of hedge funds, due to their voluntary nature of reporting (Lhabitant 2002, p.134). Database vendors impose their own criteria and discretion to enter hedge fund in the database, eventually exclude types of hedge funds that do not meet database vendor's criteria. This bias induces the performance of index downward (Lhabitant 2002, p.135). According to Ammann and Moerth (2005), selection bias is hard to avoid.
5.6.3 Backfill Bias
Backfill bias arise due to hedge funds report returns to database vendors only if they choose to. Funds started with seed capital will open to the public and thus enter standard databases later, presumably following good performance is deemed sufficiently successful to attract investors. A study by Malkiel and Saha in 2005 (cited in Aggarwal and Jorion, 2010) found that backfill bias average 7.3 percent a year.
Accordingly, the prior performance of funds that included in the database may not be reliable and representative of typical performance. Stanyer (2010, p.155) concluded that reporting data in the database do not refer to the rules for eligibility for inclusion in an index, which are designed to exclude backfill bias by ignoring for months before the date the data are first reported.
5.7 Hedge Fund Risk Models
According to Wilmott (1998, p.544), there is so much uncertainty in the subject of finance that elimination of risk is impossible. Thus, hedge funds risk modeling and management is necessary, due to hedge funds experiencing some of the greatest losses ever witnessed by investment community and the establish of new regulatory pressure enforce more stringent hedge fund risk management.
There are several quantitative risk models employed in modeling hedge fund risks, for example Sharpe ratio and the modified Sharpe ratio, three factor model of Fama and French, Jenson's alpha and Treynor ratio. Three significant risk models had discussed as below.
5.7.1 Markowitz Portfolio Theory (MPT)
MPT is applied to portfolios whose return probability distributions approximate to a normal distribution. Fung and Hsieh (1999) applied this theory to rank hedge fund performances and select efficient portfolio (Wilmott, 1998, p. 534). MP analyzes the connection between risk and return by using equally weighted scheme calculating the covariance between securities, means and variances, as well as variances and returns are calculated as an input in investment portfolio optimization.
In addition, the core concept of MPT is based on diversification and rely on the conventional wisdom which advice to avoid putting all eggs in a basket, as a diversification. However, this theory is criticized by many economists (http://www.thecsem.org/content/basics-markowitz-portfolio-theory), they argue that the forecasts are inaccurate due to MPT refer to historical data.
Furthermore, MPT also introduce the idea of efficient frontier represent different portfolio that provides a certain degree of risk and maximum rate of return for the investors to have subjective choice of their risk preference (Wilmott, 1998, p.535) along the efficient frontier curve as shown in diagram 4. A highlight is that MPT shows that certain funds may perform lower than the risk free rate. The main objective of MPT is to have an efficient portfolio in which yields the higher return for a specific level of volatility and risk. Therefore it provides a way for investors to assess the portfolio risk.
Diagram 4: Efficient frontier
An upper concave boundary exists on the maximum portfolio returns possible as risk or variance increases. The concave relation between risk and return incorporates the theory of expected utility concavely increasing with risk.
5.7.2 Capital Asset Pricing Model (CAPM)
CAPM is a centerpiece of modern financial economics which provide a precise prediction of the relationship between risk of asset and its expected return. According to Capocci and Hubner (2004) reported that CAPM was applied to hedge fund risk management in the 1980s. Hedge funds incline to hold more illiquid assets than other institutional investors, for example mutual funds, thus CAPM allow the investors to have the possibility of a return premium to hold less liquid assets.
A cornerstone of asset-pricing theory explain by Ennis (2009) is that investors may look forward to be compensated for market risk and volatility they cannot diversify away. The author suggested that diversification is fundamentally a costless activity.
5.7.3 Value at Risk (VaR)
VaR is a measure of potential loss from extreme negative return, due to the movement in underlying markets. Wilmott (1998, p.338) pointed out a true measure of the risk in a portfolio will answer the question ‘what is the value of any realistic market movement to my portfolio?' to model the cost to a portfolio of a crash in the underlying.
Lhabitant (2002, p.234) as well as Gupta and Liang (2004) used VaR for assessing a hedge fund's sufficient capital adequacy and their study reported that VaR measure is superior to traditional risk measures such as leverage ratios and standard deviation of returns, in capture hedge fund risk. VaR can calculated in conjunction with tracking error which deliver a message to investors in monetary terms how much a portfolio can expect to lose, for a given time horizon and cumulative probability.
5.8 Hedge Fund Risk and Uncertainty
According to Coyle (2001, p.32) hedging often has a cost. Stavetski (2009) explain risk are tricky subjects for the hedge fund industry due to risk is typically viewed in mathematical terms, which makes it convenient to view but not always informative or even accurate. Risk also knows as one of the most misunderstood and overused terms.
According to Stanyer (2010, p.153), hedge funds may assist to diversify equity market risk, however they provide no safe haven. The author suggested that hedge funds have been largely unregulated, thus investors need to consider how this undermine their level of comfort since the industry have some infamous examples of hedge fund fraud and apparent fraud.
Secondly, the operational risk. Investors cannot take granted that their funds are managed to a high standard due to the rapidly evolving and flurry of industry reports on hedge funds risk (Stanyer, 2010, p.173). The author suggested that operational risk is the prime reason for sudden catastrophic closures of hedge funds. The complexity of hedge fund strategies increase the risk of hedge spurious persistence findings induced by model misspecification, stock picking is a tricky endeavor (Stein, 2009, p.180). Lhabitant (2002, p.173) explained the risk factor that drive hedge funds returns are different from the traditional investments.
Thirdly, hedge funds bubble. According to Stein (2009, p.25), whenever there is a bubble, it is a matter of time before it burst.
As shown in table 5, the review for risk and return profile as measured by annual total returns and standard deviation ending 2008, hedge funds have one of the best risks and return profiles of any asset class (Stavetski, 2009).
Table 5: Hedge Fund Risk and Return Comparison
Source: Stavetski, 2009.
5.9 Problems with Hedge Fund Risk Modeling
Many portfolio risk measures make unrealistic modeling assumptions. Firstly, hedge fund survival rates are significantly lower than other funds (Garbaravicius and Dierick, 2005) and substantially vary. The hedge fund's size is relatively close to the cumulative failure rates.
Secondly, different investment strategies have significantly altered the return distribution, particularly the means and standard deviation. Therefore, it is often a debate that hedge funds should apply separate risk management for each hedge fund strategies type, rather than trading all hedge funds in one homogenous class.
Thirdly, the probability distribution of hedge funds monthly returns differ significantly. The returns of hedge funds do not approximate to normal distribution, thus popular portfolio risk measures which assume as a normal distribution are inappropriate. The diverse investment strategies employed by hedge funds result in a non-normal return distribution. This is partly because hedge funds involve in shorter term trading strategies and their substantial leverage.
Furthermore, the free regulation investment environment results in a complex management strategies and high performance incentives that will influence the return of hedge funds.
5.10 The Case for Preserving and Against Hedge Funds
5.10.1 The Case for Preserving Hedge Funds
Hedge funds provide a number of economic benefits to the market place. Particularly in aiding price discovery, for instance the ability to treat market volatility as an investment to be bought and sold and to exploit trends in its pricing.
Hedge funds involve in specialist profitable activities, aid competition and the economic concept of the invisible hand (Danielsson, Taylor and Zigrand, 2005). They thrive on market inefficiencies result in more takeovers, corporate decisions and new issuance. As traders do not have instantaneous and costless access to the market information, asset mispricing or arbitrage opportunities may occur, for instance, an asset trading in two different markets place may have different prices. Therefore, hedge funds capture the advantage of this opportunity to push the prices to their no arbitrage asset price.
One important economic benefit of hedge fund is their liquidity provision. Typically, hedge funds invest in risky assets, therefore it provide more capital for investments that many investors would not consider. Moreover, diversification gains can increase expected returns (Stanyer, 2010, p.158) and the overall market risk can be minimizing by investing in risky investments and volatile markets, absorbing or sharing certain market risk which would absorbed by other funds.
Additionally, hedge funds offer sophisticated investors with another vehicle for high returns that would not be available in traditional investment vehicle. Lhabitant (2002, p.167) concluded the risk-adjusted in hedge fund is superior in asset allocation, which enhances the risk and returns trade off and shifts the set of efficient portfolio upward. However, the author also cited a study of why not invest 100% in hedge funds by McFall in 1999 argued that hedge funds should be use in lieu of bonds as a diversification instrument for conservative investors.
Some of the incident in the stock market has rocked the world of the everyday investors, for instance the meltdown in credit markets, decline in housing prices, and the turmoil (Stein, 2009). Those incidents and the uncertainties of the world economy have led to a general decline in stock markets universal. In turn, it provides fresh impetus for investors to invest in hedge funds, due to its diverse nature provide investors with absolute returns. Hedge funds can achieve this due to they pursue multiple sophisticated investment strategies.
5.10.2 The Case for Against Hedge Funds
During the past decade years, hedge funds have been criticized for doing harm than good. Firstly, according to Danielsson, Taylor and Zigrand (2005) hedge funds engage in herding. Two good examples are the 1992 ERM crisis and the 1997 Asian currency crisis.
Hedge funds have limited liquidity (Lhabitant, 2002, p.16). It was suggested to provide much needed capital to hedge funds by investing in risky assets. This has been blamed for exhausting liquidity in the market place (Danielsson, Taylor and Zigrand, 2005). Due to hedge fund's nature of take part in large positions and the investment strategies they pursue, they are unable to make trades without causing a massive price moves mainly because of illiquidity. This statement had been support by Fung and Hsieh (2000) and Lhabitant (2002). Furthermore, hedge funds are often know as heavily leverage in magnifies profits and losses, increase the likelihood of illiquidity within the fund. Nevertheless, a study by Gupta and Liang (2005) using VaR measures concludes that many hedge funds are adequately funded.
Additionally, hedge funds can prevent efficient market functioning by induce price distortions rather than aiding price discovery. Significant price movements can be induce through large volume trades rather than the price movements occurring due to the economic or company fundamentals. Fung and Hsieh (2000) cites the example of 1992 ERM crisis but argued that hedge funds do not distort market price beyond the economic or company fundamentals.
As a viable alternative investment product, hedge funds have also been heavily disapproved. For example, there are some quotes from leading academics on hedge funds that
‘If there is a license to steal, it is in the hedge fund arena', Burton Malkiel.
‘If you want to invest in something where they steal your money without telling you what they are doing, be my guest', Eugene Fama.
Hedge funds typically needed high management and incentive fees (Lhabitant, 2002, p.17) than other managed investment products. The standard fee payable on an individual fund has been ‘2 and 20' which refer to 2% a year of the value invested is levied as a base fee and 20% of the return earned each year is retained as management fees (Stanyer, 2010, p.156). Furthermore, investors have tougher withdrawal constraints from hedge funds.
Apart from that, hedge funds are fully confidential with poor transparency (Lhabitant, 2002, p.18). Regulatory bodies such as U.S. Securities and Exchange Commission (SEC) do not dictate strict rules for hedge funds. There are no rules and regulations on publishing records on asset holdings and financial performance. Lack of transparency increases the possibility of investors being unable to effectively risk assess hedge funds.
Furthermore, the failure rate of hedge fund is much higher than other alternative investment, accordingly with a higher credit risk. They face less regulation (Lhabitant 2002, p.23, Ridley 2004, p.14) on leveraging and investment strategies therefore are susceptible to a higher probability of default, consequently with less likelihood of capital recovery, for example long-term capital management (LTCM). The authors also concluded that the typical life cycle of hedge funds is quite short.
Hedge funds are frequently fraudulent (Ridley, 2004, p.30). The industry had experience certain unexpected disasters such as corporate scandals, bursting of technology, internet bubbles, mispricing the portfolio etc. There are some real life examples enclosed in the appendix.
The debate about hedge funds usually takes place at a low level with battle lines which reflect the interest groups involved.
According to Stein (2009, p.182), it is better for investors to hold more assets in their portfolio as a diversification.
The degree and existence of hedge fund performance vary among investment strategies and rely on the employed of methodology and performance metric.
None of the foregoing is meant to imply these assets do not belong to diversified portfolios; in fact they can improve portfolio efficiency. If the investors hope to collect the risk premium from the asset allocation, they must bear the risk.
Generally, there are no generic diversification approaches that will meet all the need of investors due to individual's risk preference, investment goals, personal time horizon, financial mean and level of investment experience are difference. These issues would affect their investment portfolio mix.