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Upside potential of hedge funds as a predictor of future performance

Author

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  • Bali, Turan G.
  • Brown, Stephen J.
  • Caglayan, Mustafa O.

Abstract

This paper investigates the relationship between upside potential and future hedge fund returns. We measure upside potential based on the maximum monthly returns of hedge funds (MAX) over a fixed time interval, and show that MAX successfully predicts cross-sectional differences in future fund returns. Hedge funds with strong upside potential generate 0.70% per month higher average returns than funds with weak upside potential. After controlling for alternative risk and performance measures, funds’ market-timing ability, and a large set of fund characteristics, the positive link between MAX and future returns remains highly significant. We conclude that MAX, as a simple proxy for realized noln-normalities in hedge funds, offers incremental information on future hedge fund returns above and beyond provided by standard risk, performance, and market-timing measures.

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  • Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa O., 2019. "Upside potential of hedge funds as a predictor of future performance," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 212-229.
  • Handle: RePEc:eee:jbfina:v:98:y:2019:i:c:p:212-229
    DOI: 10.1016/j.jbankfin.2018.11.003
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    as
    1. Mark Mitchell & Todd Pulvino, 2001. "Characteristics of Risk and Return in Risk Arbitrage," Journal of Finance, American Finance Association, vol. 56(6), pages 2135-2175, December.
    2. Henriksson, Roy D & Merton, Robert C, 1981. "On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills," The Journal of Business, University of Chicago Press, vol. 54(4), pages 513-533, October.
    3. Andrew J. Patton, 2009. "Are "Market Neutral" Hedge Funds Really Market Neutral?," Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2295-2330, July.
    4. 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.
    5. Stephen Brown & William Goetzmann & Bing Liang & Christopher Schwarz, 2008. "Mandatory Disclosure and Operational Risk: Evidence from Hedge Fund Registration," Journal of Finance, American Finance Association, vol. 63(6), pages 2785-2815, December.
    6. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    7. Andrew J. Patton & Tarun Ramadorai, 2013. "On the High-Frequency Dynamics of Hedge Fund Risk Exposures," Journal of Finance, American Finance Association, vol. 68(2), pages 597-635, April.
    8. Agarwal, Vikas & Ruenzi, Stefan & Weigert, Florian, 2017. "Tail risk in hedge funds: A unique view from portfolio holdings," Journal of Financial Economics, Elsevier, vol. 125(3), pages 610-636.
    9. Cao, Charles & Chen, Yong & Liang, Bing & Lo, Andrew W., 2013. "Can hedge funds time market liquidity?," Journal of Financial Economics, Elsevier, vol. 109(2), pages 493-516.
    10. Brown, Stephen & Goetzmann, William & Liang, Bing & Schwarz, Christopher, 2012. "Trust and delegation," Journal of Financial Economics, Elsevier, vol. 103(2), pages 221-234.
    11. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-386.
    12. Jonathan Ingersoll & Ivo Welch, 2007. "Portfolio Performance Manipulation and Manipulation-proof Performance Measures," Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1503-1546, 2007 17.
    13. Bali, Turan G. & Gokcan, Suleyman & Liang, Bing, 2007. "Value at risk and the cross-section of hedge fund returns," Journal of Banking & Finance, Elsevier, vol. 31(4), pages 1135-1166, April.
    14. Agarwal, Vikas & Arisoy, Y. Eser & Naik, Narayan Y., 2017. "Volatility of aggregate volatility and hedge fund returns," Journal of Financial Economics, Elsevier, vol. 125(3), pages 491-510.
    15. Carl Ackermann & Richard McEnally & David Ravenscraft, 1999. "The Performance of Hedge Funds: Risk, Return, and Incentives," Journal of Finance, American Finance Association, vol. 54(3), pages 833-874, June.
    16. Jakub W. Jurek & Erik Stafford, 2015. "The Cost of Capital for Alternative Investments," Journal of Finance, American Finance Association, vol. 70(5), pages 2185-2226, October.
    17. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    18. Brown, Stephen J, et al, 1992. "Survivorship Bias in Performance Studies," Review of Financial Studies, Society for Financial Studies, vol. 5(4), pages 553-580.
    19. Liang, Bing, 2000. "Hedge Funds: The Living and the Dead," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(3), pages 309-326, September.
    20. Getmansky, Mila & Lo, Andrew W. & Makarov, Igor, 2004. "An econometric model of serial correlation and illiquidity in hedge fund returns," Journal of Financial Economics, Elsevier, vol. 74(3), pages 529-609, December.
    21. 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.
    22. Bollen, Nicolas P. B. & Pool, Veronika K., 2008. "Conditional Return Smoothing in the Hedge Fund Industry," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(2), pages 267-298, June.
    23. Vikas Agarwal, 2004. "Risks and Portfolio Decisions Involving Hedge Funds," Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 63-98.
    24. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    25. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    26. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa O., 2014. "Macroeconomic risk and hedge fund returns," Journal of Financial Economics, Elsevier, vol. 114(1), pages 1-19.
    27. Agarwal, Vikas & Naik, Narayan Y., 2000. "Multi-Period Performance Persistence Analysis of Hedge Funds," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(3), pages 327-342, September.
    28. Bali, Turan G. & Brown, Stephen J. & Murray, Scott & Tang, Yi, 2017. "A Lottery-Demand-Based Explanation of the Beta Anomaly," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(6), pages 2369-2397, December.
    29. Aggarwal, Rajesh K. & Jorion, Philippe, 2010. "The performance of emerging hedge funds and managers," Journal of Financial Economics, Elsevier, vol. 96(2), pages 238-256, May.
    30. Fung, William & Hsieh, David A, 2001. "The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers," Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 313-341.
    31. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    32. Fung, William & Hsieh, David A, 1997. "Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds," Review of Financial Studies, Society for Financial Studies, vol. 10(2), pages 275-302.
    33. Jagannathan, Ravi & Korajczyk, Robert A, 1986. "Assessing the Market Timing Performance of Managed Portfolios," The Journal of Business, University of Chicago Press, vol. 59(2), pages 217-235, April.
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    2. Papathanasiou, Spyros & Vasiliou, Dimitrios & Magoutas, Anastasios & Koutsokostas, Drosos, 2022. "Do hedge and merger arbitrage funds actually hedge? A time-varying volatility spillover approach," Finance Research Letters, Elsevier, vol. 44(C).
    3. George O. Aragon & Ji-Woong Chung & Byoung Uk Kang, 2023. "Do Prime Brokers Matter in the Search for Informed Hedge Fund Managers?," Management Science, INFORMS, vol. 69(8), pages 4932-4952, August.
    4. Ekaterini Panopoulou & Nikolaos Voukelatos, 2022. "Should hedge funds deviate from the benchmark?," Financial Management, Financial Management Association International, vol. 51(3), pages 767-795, September.
    5. Gupta, Nilesh & Mishra, Anil V & Jacob, Joshy, 2022. "Prospect theory preferences and global mutual fund flows," Journal of International Money and Finance, Elsevier, vol. 125(C).

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    More about this item

    Keywords

    Hedge funds; Upside potential; Return predictability; JEL classification:; G10; G11; C13;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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