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Risk Measures for Hedge Funds: a Cross-sectional Approach

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  • Bing Liang
  • Hyuna Park

Abstract

"This paper analyses the risk-return trade-off in the hedge fund industry. We compare semi-deviation, value-at-risk (VaR), Expected Shortfall (ES) and Tail Risk (TR) with standard deviation at the individual fund level as well as the portfolio level. Using the""Fama and French (1992)""methodology and the combined live and defunct hedge fund data from TASS, we find that the left-tail risk captured by Expected Shortfall (ES) and Tail Risk (TR) explains the cross-sectional variation in hedge fund returns very well, while the other risk measures provide statistically insignificant or marginally significant results. During the period between January 1995 and December 2004, hedge funds with high ES outperform those with low ES by an annual return difference of 7%. We provide empirical evidence on the theoretical argument by""Artzner et al. (1999)""that ES is superior to VaR as a downside risk measure. We also find the""Cornish-Fisher (1937)""expansion is superior to the nonparametric method in estimating ES and TR." Copyright 2007 The Authors Journal compilation (c) 2007 Blackwell Publishing Ltd.

Suggested Citation

  • Bing Liang & Hyuna Park, 2007. "Risk Measures for Hedge Funds: a Cross-sectional Approach," European Financial Management, European Financial Management Association, vol. 13(2), pages 333-370.
  • Handle: RePEc:bla:eufman:v:13:y:2007:i:2:p:333-370
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    Cited by:

    1. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa Onur, 2012. "Systematic risk and the cross section of hedge fund returns," Journal of Financial Economics, Elsevier, vol. 106(1), pages 114-131.
    2. Mila Getmansky & Peter A. Lee & Andrew W. Lo, 2015. "Hedge Funds: A Dynamic Industry In Transition," NBER Working Papers 21449, National Bureau of Economic Research, Inc.
    3. Boo, Yee Ling & Ee, Mong Shan & Li, Bob & Rashid, Mamunur, 2017. "Islamic or conventional mutual funds: Who has the upper hand? Evidence from Malaysia," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 183-192.
    4. Agarwal, Vikas & Ruenzi, Stefan & Weigert, Florian, 2015. "Tail risk in hedge funds: A unique view from portfolio holdings," CFR Working Papers 15-07, University of Cologne, Centre for Financial Research (CFR).
    5. Bussière, Matthieu & Hoerova, Marie & Klaus, Benjamin, 2015. "Commonality in hedge fund returns: Driving factors and implications," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 266-280.
    6. Lamb, John D. & Tee, Kai-Hong, 2012. "Data envelopment analysis models of investment funds," European Journal of Operational Research, Elsevier, vol. 216(3), pages 687-696.
    7. Auer, Benjamin R., 2014. "Should hedge funds be cautious reporting high returns?," Research in International Business and Finance, Elsevier, vol. 30(C), pages 195-201.
    8. Auer, Benjamin R. & Schuhmacher, Frank, 2013. "Robust evidence on the similarity of Sharpe ratio and drawdown-based hedge fund performance rankings," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 153-165.
    9. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2012. "Bank regulation and stability: An examination of the Basel market risk framework," Discussion Papers 09/2012, Deutsche Bundesbank.
    10. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa Onur, 2011. "Do hedge funds' exposures to risk factors predict their future returns?," Journal of Financial Economics, Elsevier, vol. 101(1), pages 36-68, July.
    11. repec:pal:jorsoc:v:61:y:2010:i:12:d:10.1057_jors.2009.143 is not listed on IDEAS
    12. Martin Eling & Simone Farinelli & Damiano Rossello & Luisa Tibiletti, 2010. "Skewness in hedge funds returns: classical skewness coefficients vs Azzalini's skewness parameter," International Journal of Managerial Finance, Emerald Group Publishing, vol. 6(4), pages 290-304, September.
    13. Eling, Martin & Faust, Roger, 2010. "The performance of hedge funds and mutual funds in emerging markets," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1993-2009, August.
    14. Capitani, Daniel H.D. & Mattos, Fabio, 2015. "Feasibility of new agricultural futures contract: a study in the Brazilian rice market," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205565, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    15. repec:eee:jfinec:v:125:y:2017:i:3:p:610-636 is not listed on IDEAS
    16. repec:eee:empfin:v:42:y:2017:i:c:p:109-130 is not listed on IDEAS
    17. Grau-Carles, Pilar & Sainz, Jorge & Otamendi, Javier & Doncel, Luis Miguel, 2009. "Different risk-adjusted fund performance measures: a comparison," Economics Discussion Papers 2009-54, Kiel Institute for the World Economy (IfW).
    18. Capitani, Daniel Henrique Dario & Mattos, Fabio, 2012. "Risk measurement in commodities markets: How much price risk do agricultural producers really face?," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124761, Agricultural and Applied Economics Association.
    19. El Kalak, Izidin & Azevedo, Alcino & Hudson, Robert, 2016. "Reviewing the hedge funds literature II: Hedge funds' returns and risk management characteristics," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 55-66.
    20. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2012. "When more is less: Using multiple constraints to reduce tail risk," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2693-2716.
    21. Auer, Benjamin R. & Schuhmacher, Frank, 2013. "Performance hypothesis testing with the Sharpe ratio: The case of hedge funds," Finance Research Letters, Elsevier, vol. 10(4), pages 196-208.

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