Features of hedge funds

Introduction

As far as investors are concerned, they always want to pursue high returns at the expense of low risk. Hedge funds came up at the early 1950s in US, which referred to selling short some stocks while buying others. This process could help hedge some market risk (Paudyal, 2009). They are known for "generating high returns by using leverage and derivative to invest in concentrated portfolios" (Liang, 1999). How hedge funds performance as well as generating excess returns is a field worth further exploiting. Some hedge funds could achieve high returns with low risk while others are not. Many empirical evidence indicated ideas about this field.

In order to observe the performance of hedge funds, it should be firstly put analysis about its risk which is always related to returns. Only on the basis of risks, could the returns make sense. Investment can not be without risk, the key issue lies in making maximum returns with little risk. There are various factors could play a part in the performance of hedge funds. Although they could generate excess returns, potential risks come along. Firstly we examine hedge funds' benefits in making profits. Secondly, taking into account risks and factors which could affect them in making returns. Finally, assess their performance by some methods.

Benefits of hedge funds

Hedge funds, regarded as a progressive fund with great flexibility, are one of beneficial factors to generate excess returns. Firstly, investors make use of inefficient market to trade many uncorrelated assets to hedge risk by executing hedge fund strategies such as risk arbitrage, statistical arbitrage, and equity market neutral. Moreover, in any security market over the world, hedge funds are operated, there also fewer limitations in use of derivative securities, short selling and debt leverage. They are of little transparency, little disclosure and regulations are required. So it could take advantage of this situation to avoid global disadvantaged factors. Furthermore, diversify in time makes investors free from worrying about loss, which give them sufficient time to hedge risks. They could either choose long position or short position. They would buy shares in case of price going up in the future, adversely short selling instead. Last but not least, incentive fees motivate fund managers to perform well, typically 20% of fund's profit (Paudyal, 2009). In this situation, owner-manger problem could be reduced, which further improves the performance of hedge funds. Compared with other bonds and equity markets, higher rates of returns can be earned by hedge funds and lower volatility than equity instruments, because hedge funds increase diversification by including new assets with little correlation existing assets.

Risks of hedge funds

There are some examples of poor performance in hedge funds which could result from Illiquidity of assets held by hedge funds which are non-market traded. It takes a long time to find optimal trade, or asset being too large to sell to single buyer (Gudikunst, 2007). Another serious factor is that hedge funds may have high serial correlations with performance in past time periods, which could last for several subsequent months or even years.

However, there are risks and deficiencies of hedge funds. Hedge funds are not completely hedged, because there are some risks and uncertainty that exist. Moreover, disclosures are relatively stable. The data published on performance of hedge funds sometimes did not cover all hedge funds. They usually suffer from illiquidity and infrequent pricing biases, also are full of membership and survivorship biases (Dodd, 2005).

Returns of hedge funds

Strategies are always change over time, so it's difficult to find a fixed style

According to empirical evidence, hedge fund returns are mainly influenced by traditional betas, alternative betas, structural alpha and skill alpha. Among them, traditional betas and alternative betas have basic and direct effect on hedge fund's returns. Specifically, traditional beta comprises stock market beta, Interest rate duration, credit spreads and so on. Alternative beta comes from the risk of liquidity, the risk of merging with other companies, some uncertain volatility factors and correlations. Structural alpha involves inefficiencies of structure, regulatory constraints, the size of funds and so on. Skill alpha is an indicator about whether the managers are skilled or not. It involves the ability of portfolio management, risk management (Harcourt, 2008). Returns of hedge funds combine all of these factors, which further make greater gaps in returns among different hedge fund strategies during different period.

Assess the performance of hedge funds

Hedge funds diversify over time so it could not find a corresponding passive index to benchmark hedge funds. One of the methods to assess the performance is that comparing with other investment tools such as equities, bond, and indices. It is clear that the high allocation to hedge funds is driven by their low correlation, and not by high historical returns. With rising returns on the S&P 500 or High Yield bonds, future hedge fund returns may likely be positively affected.

Another method to measure the returns of hedge funds is linear factor models (LFM). They are used for modeling portfolio risk. Satchell and Knight (2004) gave introduction about LFM. It comprises time-series regression with known factors, and estimated betas, cross-sectional regressions using known fundamental or technical variables as proxies for betas which may vary over time, and estimated factor values, and factor analysis where factor values and betas are both missing and must be estimated

Furthermore, Sharp ratio is one of popular methods to assess the performance of hedge funds. Anson (2002) pointed out that the performance of a hedge fund manager could positively affected by short volatility positions , but if it is a large downside risk, the disadvantaged prediction referring to volatility event would come up. Sharp ratio always overestimates the performance of hedge funds until volatility events happen. Frank and Meer (1991) put forward Sortino ratio which are based on the Sharpe ratio. Sortino ratio differentiates volatility which results from up and down movements. In addition, Excess Downside Deviation as an Adjustment to the Sharpe Ratio presented Johnson (2002) which includes downside deviation. Bernardo and Ledoit (2000) came up with Bernardo-Ledoit gain-loss ratio which is the ratio of the expectation of the positive part of the returns divided by the expectation of the negative part.

Asset based style factors could be a useful way to assess performance if it is permitted to use several numbers. Sharpe (1992) originally used this approach to model mutual fund risk. A current effort by academics is to extend this approach to hedge funds.

Conclusion

In summary, in different journals, hedge fund performance rankings are quite different due to diversified methods in assessing performance. The ability of hedge funds in generating excess returns depends on the choice among the methods. However, investing in hedge funds is growing into a mainstream. Despite its potential risks, benefits generated from them could always meet our expectations. Hedge funds managers could choose to invest in diversified investment portfolios. Also transparency and regulation of hedge funds are improving due to increasing institutionalization. Returns of hedge funds differ from different strategies over different periods, this issue is a relative concept based on empirical evidence. So it is interesting and will continue to attract more attention and research about this controversial topic.

References

  • Anson, M. (2002), 'Symmetrical Performance Measures and Asymmetric Trading Strategies: A Cautionary Example', Journal of Alternative Investments, 5 (1), p. 81.
  • Bernardo, A.E. and Ledoit, O. (2000) 'Gain, Loss and Asset Pricing', Journal of Political Econom ,108(1), pp.144-172.
  • Dodd, R.(2005) 'Prudential Concerns for Pension Fund Investment In
  • Hedge Funds and Derivatives'. Prepared for presentation at ASSA conference [Online]. Available at: http://www.financialpolicy.org/penfund/penfund2005.ppt (Accessed: 12 November 2009)
  • Frank A. and Meer, R. V. (1991) 'Downside Risk'. The Journal of Portfolio Management, 17(4), pp.27-31.
  • Gudikunst, A. C. (2007) 'HEDGE FUNDS: MORE RICHES FOR THE RICH OR TAXES FOR THE GOVERNMENT?' Presentation to CNU Faculty at Teaching, Scholarship, Research and Learning Seminar[Online]. Available at: http://users.cnu.edu/agudikun/hedgefdTSRL07.ppt (Accessed: 12 November 2009)
  • Harcourt (2008) 'Hedge Funds - a new asset class?' Available at: www.harcourt.ch (Accessed: 14 November 2009).
  • Johnson, D, Macleod, N. and Thomas,C.(2002) 'A Framework for the Interpretation of Excess Downside Deviation', AIMA Newsletter.
  • Liang, B. (1999) 'On the performance of hedge funds', Financial analysis journal, 55 (4), pp. 72-85.
  • Paudyal, K.N. (2009) 'Investment Banks and Investment Companies'. Securiity Analysis lecture notes [Online]. Available at: http://duo.dur.ac.uk (Accessed:12 November 2009)
  • Satchell, S.and Knight, J.(2004) LINEAR FACTOR MODELS IN FINANCE Oxford Press, Published by Butterworth-Heinemann
  • Sharpe, W. F. (1992), 'Asset Allocation: Management Style and Performance Measurement', Journal of Portfolio Management, 18(2), pp.7-19.

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