Study On The Catagories Of Hedge Funds Finance Essay
Hedge funds have gained a lot of popularity in the last decade and are one of the fastest growing industries. The main aim of most hedge funds is to reduce volatility and risk. It also attempts to preserve capital and deliver positive returns under all market conditions. Not all hedge funds are same therefore it is important to know the difference between them. It differs in terms of its risks, investment returns and volatility among the different hedge fund strategies. The strategies which are correlated to equity markets deliver consistent returns and have low risk while the ones that are not will be more volatile. Main objective of hedge funds is to provide consistency in its returns for investor, lower portfolio volatility and preserve their capital investments, which is the reason why investors such as pension funds, insurance companies, institutional investors and high net worth individuals and families invest in hedge funds.
This thesis reviews various issues relating to the investment in hedge funds, which have become popular with high net-worth individuals and institutional investors, as well as discuss their empirical risk and return profiles. The concerns regarding the empirical measurements are highlighted, and meaningful analytical methods are proposed to provide greater risk transparency in performance reporting. It also discusses the development of the hedge fund industry in Asia.
Asian hedge funds have grown vastly in past few years. It is said to have grown nearly six times as many funds while managing ten times are much in assets since 2000 according to Eurekahedge. The industry is estimated to consist over 1100 funds, and managing roughly $175 billion in assets. International managers are starting up their own Asia-focused funds too. Allocators are increasingly eyeing investment opportunities in Asia. Funds with a global mandate are increasing their allocation to Asia.
The paper presents an overview of hedge funds, describing their development and characteristics. It also discussed the various issues related to the measurement of hedge fund performance, as well as examined alternative performance measures. This thesis ends with some remarks on the development of the hedge fund industry in Asia.
CHAPTER 1. INTRODUCTION
1.1 What Are Hedge Funds?
There has several definition of hedge funds throughout the history. There isn’t one particular sentence that defines what hedge funds really means. However, according to Chicago Board Options Exchange (No Date), hedge funds can be defined as: “A conservative strategy used to limit investment loss by effecting a transaction that offsets an existing position.”
Alfred Winslow Jones was the first person to create hedge fund structure more than 50 years ago. The fund established had following feature:
He created “hedges” by investing in securities that was said to be undervalued and funded these positions by taking short positions in overvalued securities hence creating “market-neutral” position.
He designed an incentive fee compensation arrangement for fund mangers. They were paid a percentage of profit from the clients capital assets; and
He so invested his own investment capital in the fund, to make sure that his capital and that of his investors were coordinated and in line so that it is not just an individual investment but a partnership
Almost all modern hedge funds have above listed features in them, and are set up as limited partnerships with a lucrative incentive-fee structure. In most hedge funds, managers also have a significant portion of their own capital invested in the partnerships. The term “hedge fund” has been generalized to describe investment strategies that range from the original “market-neutral” style of Jones to many other strategies and opportunistic situations, including global/macro investing.
1.2 Catagories of Hedge Funds
There is a large variety of hedge fund investing strategies present today and therefore no standard way to classify hedge funds separately. Many data vendors and fund advisors set up their own major hedge fund styles according to their popularity. Under the classification by Credit Suisse, the categories of hedge funds with 10 differentiated styles and a fund-of-funds category:
(a) Event driven funds are the funds that take positions on corporate events when companies are undergoing re-structuring or mergers. For example, fund managers would purchase bank debt or high yield corporate bonds of companies undergoing the re-organization which is often referred to as 'distressed securities'. Another event-driven strategy is merger arbitrage where the funds seize the opportunity to invest just after a takeover has been announced. They purchase the shares of the target companies and then short these shares of the acquiring companies.
(b) Global funds are categories of funds that invest in non-US stocks and bonds with no specific strategy reference. This fund has the largest number of hedge funds and it includes funds that specialize on the emerging markets.
(c) Global/Macro funds are the funds that rely on macroeconomic analysis and invest in long and short position in order to capitalise on major risk factors and unforeseen markets such as currencies, interest rates, stock indices and commodities.
(d) Market neutral funds refer to hedge fund strategy that involves utilizing strategies such as long-short equity, stock index arbitrage, convertible bond arbitrage and fixed income arbitrage. Long-short equity funds use the strategy of Jones by taking long positions in selective stocks and going short on other stocks to limit their exposure to the stock market. Stock index arbitrage funds trade on the spread between index futures contracts and the underlying basket of equities.
(e)Dedicated Short Bias funds are strategies that take more short positions than long positions and earn returns by maintaining net short exposure in long and short equities. To affect the short sale, the manager borrows the stock from a counter-party and sells it in the market. Short positions are sometimes implemented by selling forward. Risk management consists of offsetting long positions and stop-loss strategies.
(f)Convertible bond arbitrage funds typically capitalize on the embedded option in these bonds by purchasing them and shorting the equities.
(g)Fixed income arbitrage is a strategy that bets on the convergence of prices of bonds from the same issuer but with different maturities over time. This is the second largest grouping of hedge funds after the Global category.
(h) Short/long fund-, shorts focus on engineering short positions in stocks with or without matching long positions. They play on markets that have raised too fast and on mean reversion strategies. Long funds take long equity positions with leverage. Emerging market funds that do not have short-selling opportunities also fall under this category.
(i)Emerging Markets funds invest in currencies, debt instruments, equities and other instruments of countries with “emerging” or developing markets (typically measured by GDP per capita). Such countries are considered to be in a transitional phase between developing and developed status. Examples of emerging markets include China, India, Latin America, much of Southeast Asia, parts of Eastern Europe, and parts of Africa. There are a number of sub-sectors, including arbitrage, credit and event driven, fixed income bias, and equity bias.
(j) Multi Strategy fund refers to a combination of even driven stratgegies, which invest in illiquid stocks and that are raising private equity and high yield investment.
(j) Fund of funds refer to funds that invests in a pool of hedge funds. They specialize in identifying fund managers with good performance and rely on their good industry relationships to gain entry into hedge funds with good track records.
Figure 1: Distribution of Hedge Fund Assets by Strategy
Source: Credit Suisse: Portfolio Strategy, CS/Tremont
1.3 Investing in Hedge Funds
In 1990 the entire hedge fund industry was estimated at $20 billion. At the end of 2008, global hedge fund industry was estimated to be worth $1 trillion with 8350 active funds. It has gained a lot of popularity in the last decade and is one of the fastest growing industries. While hedge funds are well established in US and Europe, they have also been growing rapidly in Asia.
1.3.1 Mean and Standard Deviation of Returns
Jan 2000 – Nov 2009
Standard Deviation (%)
Global / Macro
Dedicated Short Bias
Fixed Income Arbitrage
Source: Credit Suisse/ Tremont hedge index
The mean returns are annually compounded returns over the period 2000 to November 2009,
The annualized standard deviations were computed from of the standard deviation of monthly returns for each investment style.
Risk-adjusted returns are obtained by dividing the mean return by the standard deviation.
Table 1 gives statistics about the various categories of hedge funds and past performance. The global/macro hedge funds provided the best mean return over the period studied, while the event-driven funds had the lowest standard deviation of returns. On a risk adjusted basis which is obtained by dividing the mean return by the standard deviation, the category of fund that ranks highest is the global/macro funds followed closely by event-driven funds. Hedge funds are not required to publicly disclose performance and holdings information unlike the registered insurance companies, which might be construed as solicitation materials. This is the reason why which makes it more difficult for investors to evaluate hedge fund managers
Credit Suisse/Tremont Hedge Fund Index Performance Statistics (as of 2009)
3 Months 1.44%
6 Months -1.73%
1 Year -15.79%
3 Year Annualized Return -0.44%
5 Year Annualized Return 4.07%
Source: Credit/Suisse/Tremont Hedge fund
Standard and Poor’s Global 1200 Index Performance Statistics (as of 2009)
1 Year 31.69%
3 Year Annualized Return -4.56%
5 Year Annualized Return 3.07%
Source: S&P Indices (www.standardandpoors.com)
Hedge funds have posted attractive returns. A five year annualised return of 4.07% posted by Credit Suisse, higher than the S&P 1200 of 3.07% (see table 2 & 3). Hedge funds are seen as natural hedge to control downside risk because they employ investment strategies believed to generate returns that are uncorrelated to traditional asset classes. Hedge funds differ in strategies- a macro fund such as quantum fund generally take a directional view by betting in particular bond market or a currency movement. Other funds specialise in corporate events such as mergers or bankruptcies. They also vary widely in investment strategies and the amount of financial leverage.
In the recent financial crisis, hedge funds have been heavily criticised in terms of their strategies and also for the fact that in 2008, they have had hard time fulfilling their absolute return targets. There have been other criticisms towards hedge fund regarding this particular crisis. Stromqvist (2009) writes that ever since the growth of hedge fund industry there has always been discussions regarding the role of hedge funds in a financial crisis. The main focus of the criticism was on highly leveraged hedge funds and that they may have a large impact on price stability on both currencies and equities.
In an article written in The Times, Dillow (2008) observes that even though average return of hedge funds in 2008 has been poor, “they have not been a serious source of instability in the wider financial system”.
1.3.2 Why Invest in Hedge Funds?
Regardless of the recent financial crisis, hedge funds still generate a growing number of interests all around the world. The information about the hedge funds are of private nature, and therefore it is difficult to obtain information about the operations of individual hedge funds and reliable summary statistics about the industry as a whole.
In 2008, while overall performance in hedge fund industry was negative, not all asset classes performed badly all together at the end of the year. Managed Futures and Dedicated Short mangers posted double digit returns of 18.3% and 14.9% respectively (see table 4).
Broad Index (19.1%)
Convertible Arbitrage (31.6%)
Dedicated Short 14.9%
Emerging Markets (30.4%)
Equity Market Neutral (40.3%)
Event Driven (17.7%)
Fixed Income Arbitrage (28.8%)
Global Macro (4.6%)
Equity Long Short (19.8%)
Managed Futures 18.3%
Multi-Strategy (23.6%) Performing
*YTD Dec 2008
Source: Credit Suisse/Tremont Hedge Fund Index (January 2009)
It is a common belief that investing in hedge funds can have superior returns. Many success stories have emerged in the past and the most popular of which is the George Soros story. In September of 1992, he risked $10 billion on a single currency speculation when he shorted the British pound, which gave him an international fame. He was right, and in a single day he successfully generated a profit of $1 billion – ultimately, it was reported that his profit on the transaction almost reached $2 billion. Therefore, he is famously known as the "the man who broke the Bank of England."
The greates investor: George Soros,
Traditional asset allocation makes the most of the use of equities, bonds, real estate and private equity to invest in a portfolio that maximizes returns and minimizes the portfolio risk. Therefore, in an investment portfolio hedge funds can play a vital role in maximising returns. Moreover, in a bear market, many investment and fund mangers find it dull to just beat the market index, which may have negative returns. They generally prefer to go short or avoid long positions to have positive returns. Choosing an appropriate hedge fund to invest increases the possibility of obtaining positive “absolute returns”.
It is also generally believed that hedge funds have returns that are generally uncorrelated with the traditional asset classes. In fact, hedge funds may even have a lower risk profile. For example, Morgan Stanley Dean Witter (2000) reported that hedge funds “exhibit a low correlation with traditional asset classes, suggesting that hedge funds should play an important role in strategic asset allocation”.
The answer to the question “Why invest in Hedge funds?” simply is “to make money.” The common analogy in all hedge funds strategies and the underlying rationale for investing in hedge funds is the search for absolute returns. This is sometimes called "alpha". "Alpha" is the extra return a skilled manager can produce over and above the market return (or "beta"). Whereas many conventional fund managers aim simply to outperform their chosen benchmark index, hedge fund managers seek to produce positive gains in all market conditions.
1.4 Research Question
By using quantitative study, I will try to answer the following questions:
Why invest in hedge funds?
To answer this question I will be investigating the return, risk and various measures of performance measurement associated with investing in hedge fund. By looking at the annualised return, standard deviation and risk adjusted returns of different styles of hedge funds their performance can be measured.
What are the issues relating the investment in terms of risk, return and performance measurement?
Although hedge funds are popular in terms of an investment vehicle, there are various issues. The issues related are its cost/ management fee structures, collection of data, survivorship bias and selection bias. Various performance measure techniques are available for hedge funds too. I will be looking at some of the performance measurement approaches.
There are several purpose for this paper. First is to give an overview of hedge fund as an investment vehicle with a short description of different characteristics and styles of hedge funds. Second is to describe why hedge funds are attractive for investors and fund managers by presenting different theories where risk and returns of hedge funds are investigated in order to evaluate the performance measures. Third purpose is to investigate the issues related to the investment in hedge funds where several sets of issues are evaluated and various performance measures are identified. Also this paper ends with a brief overview of Asian hedge funds, their recent development into the hedge funds worlds and its characteristics.
CHAPTER 2. LITERATURE REVIEW
There is no one particular definition of hedge fund as mentioned earlier. According to the Investment Company Act 1940 of the US, hedge funds were defined by their low degree of regulatory controls. In comparison to mutual funds, hedge funds were seen to have higher level of risk. This led to a 100-investor limit as well as wealth requirement of the investors. Fung and Hsieh (1999) claim that another reason for 100-investor limit is the use of leverage and short selling in hedge funds. The limit restrictions were later abandoned and wealth requirement lowered.
Many definitions of hedge funds have been cited-most of them mainly based on its characteristics. Some of them are:
“Investment companies that by their charter can buy on margin, sell short, hold warrants, convertible securities and commodities and otherwise engage in aggressive trading tactics in order to profit from forcasting market swings.”- Polhman, Ang and Hollinger (1978)
“A mutual fund that employs leverage and uses various techniques of hedging”- Soros (1987)
“hedge funds are vehicles that allow private investors to pool assets to be invested by a fund manager. Unlike mutual funds, hedge funds are commonly structured as private partnerships and thus subject to only minimal SEC regulation. Moreover, because hedge funds are only lightly regulated their managers can pursue investment strategies involving, for example, heavy use if derivatives, short sales and leverage.”- Bodie, Kane and Marcus (2008).
Murguia and Umemoto (2004) claims that the reason why there is no proper definition of hegdge funds is because they are not classified by the different asset classes but by the type of strategies employed by the fund mangers is what classifies them. Such strategies range from very aggressive to conservative, which is the reason why there is no clear definition.
2.2 Risk and Return
Several studies have been carried out about hedge funds performance and risk issues. Fung and Hsieh (1997a) extend Sharpe (1992) style analysis and conclude that there are more diversified hedge fund strategies and suggested that hedge fund strategies are more dynamic. The literatures also conclude that option-based factors can enhance the power of explaining hedge fund returns. Brown, Goetzmann and Ibbotson (1999) examine the performance of offshore hedge funds and attribute fund performance to style effects rather than managerial skills.
Brown, Goetzmann and Liang (2003) found, in a study using the TASS database, that fund of hedge funds reduce by a third the standard deviation of monthly hedge fund returns, as well as significantly reduce the value at risk of hedge fund investment. Hence, fund of hedge funds can also provide significant diversification potential. A well-diversified fund of hedge fund manager can therefore take advantage of market-specific risks while maintaining low correlations to stock, bond, and currency markets. As a result of which the fund of hedge fund manager can provide superior returns and generate alpha which reflects managerial skills. More generally, since fund of hedge funds deliver more consistent returns with lower volatility than individual hedge funds, they are considered to be ideal for diversifying traditional portfolios. During 1993–2001, fund of hedge funds outperformed the S&P 500 index on a risk-adjusted basis (Gregoriou, 2003a).
Koh, Koh, Lee and Phoon(2004) state that traditional asset allocation optimizes the use of equities, bonds, real estate and private equity to invest in a portfolio that maximizes returns and minimizes the portfolio risk. Thus, hedge funds become vital in enhancing returns in an investment portfolio.
Following the growth in hedge fund industry, fund-of-hedge funds (FOF) have become more and more popular. Liang (2003) states that FOF mixes various strategies and asset classes together and creates more stable long-term investment returns than any of the individual funds. It invests in underlying hedge funds and diversifies the fund specific risks and relieves burdens on investor to select and monitor managers, and providing asset allocation in dynamic market environments. Fund-of-funds require less initial investment as compare to hedge funds and therefore are more affordable for small investors. To participate in the investment, small investors may be willing to pay extra fees as it might be the only way for them.
Previous studies in this area by Brown, Goetzmann and Liang (2002) conclude that combining hedge funds with fund-of-funds not only causes the double counting but also hides the difference in fee structures between hedge funds and fund-of-funds. Liang (2003) state that a hedge funds charges a management fee and incentive fee while a fund-of-funds not only charges these fees at a fund-of-fund level but also passes hedge fund level fees in the form of after fee returns to the fund-of-fund investors whether or not the fund-of-funds make a profit.
Brown, Goetzmann and Liang (2002) examine this issue and propose an alternative fee which provide a better incentive for fund-of-fund managers and reduce the cost for investors under the current fee structure, which is that the fund-of-fund managers absorb the underlying hedge fund fees and establish their own incentive fees at the fund-of-fund level. Liang (2003) conclude that because of the above issues fund-of-funds need to be separated from hedge funds in academic studies and address the difference in performance, risk and fee structures.
However, the FOF mangers can add value to the portfolio through selection, construction and continuous monitoring of the portfolio. They provide professional services and have access to the information that are expensive and difficult to obtain otherwise. The FOF mangers quite often use different investment strategies and styles through a diversified portfolio of individual fund managers. Considering these advantages for an investor, investing in fund of hedge funds is not cheap. The cost can be as high as the cost of buying a building, according to Koh, Koh, Lee and Phoon (2004). This structure allows for more diversified portfolio and much reduced risk at the fund level which comes at a price. More diversified the portfolio is it is more likely that it will incur more incentive fees.
Ackermann et al. (1999) and Liang (1999) who compare the performance of hedge funds to mutual funds and several indices find that hedge funds constantly obtain better performance than mutual funds, although lower than the market indices considered. They also indicate that the returns in hedge funds are more volatile than both the returns of mutual funds and those of market indices. Ackermann and Ravenscraft (1998) emphasize that the stronger legal limitations for mutual funds than for hedge funds hinder their performance. According to Brown, Goetzmann, Hiraki, Otsuki and Shiraishi (2001) and Brown, Goetzmann and Park (2001), hedge funds showing good performance in the first part of the year reduce the volatility of their portfolio in the second half of the year.
Fung and Hsieh (1997) and Schneeweis and Spurgin (1997) prove that the insertion of hedge funds in a portfolio can significantly improve its risk-return profile, thanks to their weak correlation with other financial securities. This low correlation is also emphasized by Liang (1999) and Agarwal and Naik (2000). Amin and Kat (2001) find that stand-alone investment hedge funds do not offer a superior risk-return profile, but that a great majority of funds classified as inefficient on a stand-alone basis are able to produce an efficient payoff profile when mixed with the S&P500. They obtain the best results when 10–20% of the portfolio value is invested in hedge funds. Taking all these results into account, hedge funds seem a good investment tool.
There are many persuasive reasons why investing in hedge funds are considered as “alternative investments”. There is much probability that the incentive fee for fund mangers can be so large that it absorbs all the fund return. Also some uninformed investors may be misled about the risks and returns on hedge funds as it relies heavily on statistical compilation from the database vendors which is filled with data biases such as survivorship bias and selection bias. These biases arises a concern whether the hedge funds indices are a good measure of performance in the hedge funds industry.
2.2.1 Survivorship Bias
Fung and Hsieh (2001a) found that estimates of survivorship biases differed across two commonly used databases, HFR and TASS. The survivorship bias was much higher in TASS than that in HFR. They estimated that survivorship bias would over-report hedge fund mean returns by about 1.5% to 3% per annum.
Brooks and Kat (2001) stated that around 30% of newly established funds do not survive the first three years, primarily due to poor performance. Thus, not including defunct funds (no longer report its returns) is likely to lead to over-estimation of the returns and profile of hedge fund industry. It is an important bias for the hedge fund because according to Malkiel and Saha (2005) the returns earned by currently existing hedge funds are reflected by the databases available during this time. The returns from the hedge funds that existed at some point in the past but nevertheless are non existence at present (i.e. dead funds) or the defunct funds are not included. Malkie and Saha (2005) also conclude that while estimating the survivorship bias by fund categories, a substantial difference between live and defunct funds in all categories was found including the substantial survivorship in fund of fund category, which contradicts the claim of Laam (2003) that survivorship bias in fund of fund category is relatively small.
Because of the short average life of hedge funds survivor bias is a substantial topic of discussion in hedge fund literature. Malkiel and Saha (2005) report that less than 25 percent of funds operating in 1996 were still reporting to databases in 2004. Gregoriou, Hübner, Papageorgiou, and Rouah (2005) discuss the mortality of commodity trading advisers and report that the median fund survived only 4.4 years. A survivorship bias refers to the fact that the returns on non surviving funds are not reported. Generally, these non-surviving fund’s returns are poor and when their returns and the returns earned by their investors are unrecorded, this can exaggerate the returns earned by an average investor. In the literature, authors report a wide range of estimates of survivor bias; the returns to live funds exceed the returns to the combination of live and defunct funds by between 0.6 percent and 3.6 percent per year. By not including failed funds in return calculations, hedge fund returns will be overstated by this amount.
2.2.2 Selection Bias
By selection bias, it means that the fund mangers have the power to select and report only those funds which have good performance. Before the information on the funds can be released to third party, the hedge fund consultant needs the consent of the fund manager, which creates the possibility of selection bias. It is a belief that the hedge fund managers only want to include the funds with good performance, which means that the returns on the database are higher than the returns on all existing funds. Therefore, the database vendors may not have the true picture on the performance of the all the available hedge funds.
Selection bias in hedge funds are said to have no estimates of its size, however Fung and Hsieh (1997a) found evidence of it being limited. Fung and Hsieh (2000) also state that managers with superior performance and who are not interested in attracting more capital opt out to participate in databases. They also gave example of George Soros’s Quantum Fund which has been closed since 1992 despite of its legendary performance. They also later conclude that to study the selection bias in hedge funds accurately, the input from the investors that do not disclose the performance to vendors are needed.
Park (1995) studies a subset of selection bias called “instant history bias” which arises when a new fund is added into a database and its historical performance are “backfilled” by the database vendors. Capocci and Hubner (2004) state this corresponds to the demand of fund managers who market themselves if they have good track record. Fung and Hsieh (2000) found 1.4% difference per year in returns from 1994-1998 using a 12 months incubation period (number of days from inception to entry into database).
Following Park (1995), Brown et al. (1999), and Fung and Hsieh (2000), Capocci and Hubner (2004) estimate the bias in database in two steps. One was called the observable one and the other adjusted observable one (returns after deleting first 12, 24, 36 and 60 months). For the period 1984 -2000, they found observable monthly return averaged 1.49% and the adjustable observable one was approximately 0.9% per year which was much lower that Fung and Hseih (2000) of 1.4%. While estimating for the period of 1994-2000, the found the bias was 1.2% much closer to Fung and Hseih (2000). Capocci and Hubner (2004) conclude the difference can be explained by the difference in time period covered and the database used and that longer the estimation period bigger is the bias.
Amnec and Goltz (2008) claim although there are several problems with hedge fund indices they also find several solutions to construct an investable hedge funds index. The solution includes:
Transparency of the method
A methodology that guarantees a high degree of representativeness as well as precise classification of components
Minimum liquidity of the indices
Prohibition of practices such as backfilling
Information on risk factor exposure
2.3 Performance Measurements
One of the main aims of this paper is to investigate the performance measures of hedge funds. One of the most well known performance measures which I have chosen is the Sharpe Ratio in order to make comparisons easy to interpret. Other alternative performance measures are described in section…..
2.3.1 Sharpe Ratio
Sharpe ratio is a measure of risk-adjusted performance. It is also referred to as “risk-to-volatility” ratio. The measure was first presented by Sharpe (1966) in his article “Mutual Fund Performance” where he evaluated the performance of 34 mutual funds. He defines it as “….simple yet theoretically meaningful measures that considers both average return and risk”.
In analysis of hedge funds, Sharpe ratio is often used as performance measure and comparisons are made between the Sharpe ratio of other funds or indices.
The Sharpe ratio of a portfolio can be calculated as: (Bodie, Kane and Marcus,2008)
Sp = E (r p) – r f_
E (r p) = return on the portfolio
r f = the risk-free rate
δ p = risk of the portfolio measure as standard deviation
According to the above formula, the portfolio that has the highest Sharpe ratio has the most favourable relationship between risk and return, therefore, is mostly preferred by the investors. The Sharpe ratio is easily computed and interpreted and is frequently used in practice and theoretical research (Modigliani and Modigliani, 1997). However, Amin and Kat (2003) state in the performance measurement of hedge funds, Sharpe ratio is not free of heavy criticisms because of the non normal distribution of hedge fund returns.
The Sharpe ratio is appropriate when the portfolio under consideration represents the entire risky investment. Hence, if the Sharpe ratio is calculated for individual hedge fund returns, it is implicitly assumed that all investor’s wealth is allocated to the hedge fund. To measure the hedge fund performance in a portfolio context, that is, only a small portion of investor’s wealth is allocated to the hedge fund, the Sharpe ratio must be calculated on the basis of the portfolio returns including the hedge fund.(Eling and Schuhmacher(2007),p6)
Skewness and Kurtosis
“Skewness” refers to asymmetry of the distribution. A distribution with an asymmetric tail extending out to the right is referred to as “positively skewed” while a distribution with an asymmetric tail extending out to the left is referred to as “negatively skewed” (Wuensch, 2007).
Positive skewness represent the standard deviation will overestimate the risk because positive deviation from expected return also increases the estimation of volatility. Similarly, negative skewness represents the standard deviation underestimating the risk.
“Kurtosis” measures the size of the tails of the return distribution. High kurtosis means the distribution has fat tail. The normal distribution will have skewness of 0 and kurtosis of 3 (Malkiel and Saha, 2005).
Positive kurtosis also known as leptokurtic which has an effect that causes underestimation of extreme events. Mesokurtic is a normal kurtosis while platykurtic is a negative kurtosis.
Skewness and Kurtosis are crucial in the understanding of hedge funds performance measures and how it is applicable to hedge funds. Previous studies show that the traditional asset returns can be characterised by their mean and standard deviation as they are close to normal.
But in contrast to normal asset classes, according to Amin and Kat (2003), hedge funds have abnormal distribution i.e. negative skewness and high kurtosis. Because of which, the risk-averse investors might be worried about their investment as mean-variance fails to consider these high movements in return distribution. Mean- variance analysis is only appropriate when the distribution of return is normal; therefore, the reliability of the analysis depends on the degree of non-normality. Despite the fact that hedge fund returns are not generally normally distributed, many investors still use mean-variance analysis.
According to Fung and Hsieh (1999a), “... when returns are not normally distributed (as it is the case for hedge funds), the first two moments (i.e. mean and standard deviation) are not sufficient to give an accurate probability.” They found that hedge fund returns are fat-tailed.
Brooks and Kat (2001) found that “….while hedge funds may offer relatively high means and low variances, such funds give investors third and fourth moment attributes that are exactly the opposite to those that are desirable. Investors obtained a better mean and a lower variance in return for more negative skewness and higher kurtosis.”
Koh et al. (2004) conclude the dynamic trading strategies of hedge funds render traditional mean-variance measures meaningless. While some hedge funds may have low standard deviations, this does not mean they are relatively “riskless”. In fact, they harbour skewness and kurtosis, which makes them “risky”.
Correlations of Returns
Fung and Hsieh (1997), Liang (1999) and Amin and Kat (2001) state there is a weak or low correlation between hedge funds and other securities. Therefore, by adding hedge funds to a portfolio, the investor can significantly improve risk-return trade-off. Having an asset with a low correlation allows the investor to diversify the risks. However, Koh, et al. (2004) argues correlation-based diversification may not be valid in the case of hedge funds.
Fung and Hsieh (2001) stated that “… Risk management in the presence of dynamic trading strategies is also more complex.” There is a lot of freedom given to edge fund managers to generate returns that are not correlated with those of other asset classes. But, this freedom comes at a price. Dynamic trading strategies influence hedge funds to extreme events. As a result, correlations may come at a cost. They cautioned that “periodically the portfolio can become overly concentrated in a small number of markets” and market exposures converge. They later conclude this would lead to an “implosion” due to diversification.
Lavino (2000, p177) argued that many hedge funds are not consistently and continuously negatively or poorly correlated with other asset classes over time ant that it also may not have meaningful standard deviations. In fact, many hedge funds have distributions with fat-tails, and so normality assumptions on the distribution of hedge fund returns are generally not correct. This means it is not appropriate that the use of correlation as a measure to execute portfolio diversification.
Lo (2001) armoured this view. He discussed one of the main aims of the investors is to diversify their returns, as hedge fund returns seem uncorrelated with market indexes such as the S&P 500. However, uncorrelated events can become synchronized in a crisis, with correlation changing from 0 to 1 overnight. These situations are examples of “phaselocking” behaviour encountered in physical and natural science.
Other Performance Measures
The mere use of means and standard deviations for the measurement of risks and returns for hedge funds are found to be quite inadequate by the above discussions. Skewness and kurtosis statistics would help but when hedge funds are added to a portfolio of other assets simple correlations measures are not sufficient to diversity portfolio risks as it has been mentioned in above discussions.
For above mentioned reasons, Sortino ratio is preferred, which was first presented by Sortino and Price (1994), and has much in common with previously discussed Sharpe ratio. This ratio differentiates between deviations on the upside and on the downside and they are more consistent with an investor’s concern over their risk on losses in their investment. However, they have one major difference- it uses “downside deviation” rather than using standard deviation as the denominator. Downside deviation (DD) is value that represents potential loss that may arise from the risk as measured against Minimum Acceptable Return (MAR). The MAR is usually risk free rate, zero or user defined. The numerator of Sortino ratio is the difference between the return on the portfolio(R) and the MAR (Koh et al. (2004),p 15). The ratio can be calculated as:
Sortino ratio = (R – MAR)/ DD
Sortino and Price (1994) state:
“Performance is not just a matter of who got the highest return, or who took the least risk, but a question of who provides the best risk-adjusted return.”
Lavino (1999) defined another measure to explain how high skewness of a hedge fund returns may be connected to hedge fund manager’s selection of high reward and low variance opportunities. He captured this as follows:
d- Ratio = Abs (d/U)
d = number of returns less than zero times their value
U = number of returns greater than zero times their value
Abs = absolute value
The d-Ratio compares the value and frequency of a manager's winners to losers to capture the skewness in returns. This may be used as a proxy for fund’s risk with d = 0 representing distribution with no downside and d = infinity representing one where the manager does not make any positive return (Koh et al. (2004)).
In order to analyse performance of hedge fund managers, we also need to analyse the manager’s skill. Good performance in hedge funds is viewed as transitory. One of the ways to examine this is to see if it is mean- reverting i.e. whether or not the performance will reverse and converge into some kind of long term value. This can be done with Hurst Ratio which measures the persistence of individual returns directly without a comparison to a median. An advantage of Hurst ratio is that its efficiency is not based on the assumption on the return distribution.
Hurst Ratio is defined as follows: (Koh et al. (2004))
Hurst Ratio = log M / (log N - log a)
M(t) = Max(t) - Min(t))/S(t)
N = length of shorter sub-periods into which a manager's return record
has been subdivided
t = number of sub-periods into which a manager's return record has
been sub divided
S(t) = standard deviation of data over sub-period t
a = constant term that is negligible if track record is five years or less
A Hurst Ratio comprised between 0 and 0.5 indicates reverse persistence. It means that a manager’s return tend to fluctuate randomly but converge to a stable value in long term. A ratio of 0.5 indicates random performance i.e. returns in one period are not affected by the returns in another period. These hedge funds are more riskier as short term gains in one period may be followed by losses in another period. A ratio comprised between 0.5 and 1 indicates positive persistence i.e returns are persistent.
The Sortino, d and Hurst Ratio gives additional insight to the performance and risks in investing in hedge funds, empirical research shows that further work is needed before these methods can be used. The next section examines some practical issues relating performance measurement.
As mentioned earlier in this paper that hedge funds has various data issues as many information are not easily available. Even if one possesses a reliable data it is very difficult to statistically compute measure of risk adjusted return. These issues make it tricky to have a simple evaluation to fully measure risk and return.
Koh, Lee and Phoon (2002) have identified 6 types of practical issues that increase the “riskiness” of hedge funds: style purity, consistency, fund size, use of leverage, liquidity and asset concentration. They also note “some of these problems are closely linked to one another and create extraneous risks, which may not be correctly priced by the usual risk adjusted return measures.”
Hedge funds are thought to have pure and consistent style, which according to Koh et al. (2002) is not true. They do not always function exactly as their classifications specify and therefore it is not viable to classify hedge funds precisely.
Style purity of hedge fund is less consistent compared to mutual funds. Fund and Hsieh (2001b) suggest using factor analysis to differentiate the core “factors” that drive the return for funds which may help distinguish one fund from another. This in turn may enable an investor to detect style purity and consistency.
Till (2001) suggest with a number of alternative investment strategies “investors earn their returns due to assuming risk positions in a risk-averse financial world, rather than from inefficiencies in the market place”. This implies that returns are made from “risk transfer” rather than managerial abilities. And if this is the case then in order to achieve superior returns, the selection skill to choose appropriate hedge fund style and the manager who can implement style consistency becomes important. This leads to a notion that instead of using measures like variance and skewness, style purity and consistency are important to measure exposure to hedge funds risk.
A hedge fund’s size affects its risk and return at a very significant level, and its risk increases proportionately with its asset under management (AUM). The reason behind this is after a hedge fund hits an “optimal size” it becomes very difficult to keep the same strategy or have the “opportunities for execution” i.e. use of leverage (Koh, Lee and Phoon (2002)). They also observe as soon as the target of the fund is reached, the fund managers tend to close the funds for further investments. This behaviour is a clear indication that fund managers understand the trade-offs between size and performance.
One of the main reasons for hedge fund managers to use leverage is to magnify potential returns. According to Weisman and Abernathy (2000) it is important to guard against excessive use of leverage and lack of liquidity. They point out that “if one were to construct a non-diversified, illiquid and/or leveraged portfolio and let it grow over time, it would eventually lead to bankruptcy of the fund, if a misfortune strikes.”
Koh et al. (2002) also identified following to account for various practical risks that was discussed above.
Table 5: Discount to Risk-Adjusted Returns to Account for Various Practical Risk
Source: Koh et al. (2002)
They argue that risk- adjusted return with penalty (as seen in Table 5) is more meaningful to an investor as standard deviations merely fail to alert investors about risks such as liquidity and leverage. According to them, if we were to compare two hedge funds with similar attributes, and want to know which has better risk-adjusted return, the hedge fund with less leverage, is less concentrated, invests in more liquid asset and is more diversified will be preferred than the one which has similar risk adjusted return but has taken more risks to achieve the same result and also because it has more chances of surviving in long term.
The risk- adjusted return has been defined as:
“This measure assumes that all the named variables are observable, measurable and reliable. The benchmark return may be a stock index, a peer measure or the interest rate of the 90-day Treasury bill. The risk measure may be the “tracking error”, “standard deviation”, or some other measure”. (Koh et al.(2002))
In this chapter, a brief overview of hedge funds and its characteristics has been given. It also investigates downside faced by investors to make decisions based on available data from database vendors. It has also been established that commonly used statistics such as mean, standard deviation and correlation is not meaningful because of non-normality of returns of hedge fund distribution. Alternative the use of other performance measures such as Sortino, d and Hurst ratio has been suggested.
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