IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v98y2019icp212-229.html
   My bibliography  Save this article

Upside potential of hedge funds as a predictor of future performance

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378426618302437
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbankfin.2018.11.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Brown, Stephen & Goetzmann, William & Liang, Bing & Schwarz, Christopher, 2012. "Trust and delegation," Journal of Financial Economics, Elsevier, vol. 103(2), pages 221-234.
    5. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-386.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Jonathan Ingersoll & Ivo Welch, 2007. "Portfolio Performance Manipulation and Manipulation-proof Performance Measures," The Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1503-1546, 2007 17.
    11. Andrew J. Patton, 2009. "Are "Market Neutral" Hedge Funds Really Market Neutral?," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2295-2330, July.
    12. 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.
    13. 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.
    14. Fung, William & Hsieh, David A, 2001. "The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers," The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 313-341.
    15. 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.
    16. Vikas Agarwal, 2004. "Risks and Portfolio Decisions Involving Hedge Funds," The Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 63-98.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    22. 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.
    23. 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.
    24. 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.
    25. Brown, Stephen J, et al, 1992. "Survivorship Bias in Performance Studies," The Review of Financial Studies, Society for Financial Studies, vol. 5(4), pages 553-580.
    26. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    27. 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.
    28. 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.
    29. Fung, William & Hsieh, David A, 1997. "Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds," The Review of Financial Studies, Society for Financial Studies, vol. 10(2), pages 275-302.
    30. 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.
    31. 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.
    32. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Soumaya Ben Khelife & Christian Urom & Khaled Guesmi & Ramzi Benkraiem, 2022. "American hedge funds industry, market timing and COVID-19 crisis," Journal of Asset Management, Palgrave Macmillan, vol. 23(5), pages 390-399, September.
    3. 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.
    4. 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).
    5. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Agarwal, Vikas & Green, T. Clifton & Ren, Honglin, 2018. "Alpha or beta in the eye of the beholder: What drives hedge fund flows?," Journal of Financial Economics, Elsevier, vol. 127(3), pages 417-434.
    2. 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.
    3. Agarwal, Vikas & Green, Tracy Clifton & Ren, Honglin, 2017. "Alpha or beta in the eye of the beholder: What drives hedge fund flows?," CFR Working Papers 15-08, University of Cologne, Centre for Financial Research (CFR), revised 2017.
    4. 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.
    5. Mustafa Onur Caglayan & Sevan Ulutas, 2014. "Emerging Market Exposures and the Predictability of Hedge Fund Returns," Financial Management, Financial Management Association International, vol. 43(1), pages 149-180, March.
    6. 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.
    7. Turan G. Bali & Florian Weigert, 2018. "Have Hedge Funds Solved the Idiosyncratic Volatility Puzzle?," Working Papers on Finance 1827, University of St. Gallen, School of Finance.
    8. Andrew W. Lo & Mila Getmansky & Peter A. Lee, 2015. "Hedge Funds: A Dynamic Industry in Transition," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 483-577, December.
    9. Bali, Turan G. & Weigert, Florian, 2021. "Hedge funds and the positive idiosyncratic volatility effect," CFR Working Papers 21-01, University of Cologne, Centre for Financial Research (CFR).
    10. 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.
    11. Hwang, Inchang & Xu, Simon & In, Francis & Kim, Tong Suk, 2017. "Systemic risk and cross-sectional hedge fund returns," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 109-130.
    12. Turan G. Bali & Stephen J. Brown & K. Ozgur Demirtas, 2013. "Do Hedge Funds Outperform Stocks and Bonds?," Management Science, INFORMS, vol. 59(8), pages 1887-1903, August.
    13. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    14. Namvar, Ethan & Phillips, Blake & Pukthuanthong, Kuntara & Raghavendra Rau, P., 2016. "Do hedge funds dynamically manage systematic risk?," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 1-15.
    15. Newton, David & Platanakis, Emmanouil & Stafylas, Dimitrios & Sutcliffe, Charles & Ye, Xiaoxia, 2021. "Hedge fund strategies, performance &diversification: A portfolio theory & stochastic discount factor approach," The British Accounting Review, Elsevier, vol. 53(5).
    16. Martin Eling, 2009. "Does Hedge Fund Performance Persist? Overview and New Empirical Evidence," European Financial Management, European Financial Management Association, vol. 15(2), pages 362-401, March.
    17. Rungmaitree, Pattamon & Boateng, Agyenim & Ahiabor, Frederick & Lu, Qinye, 2022. "Political risk, hedge fund strategies, and returns: Evidence from G7 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    18. Ludwig Chincarini, 2014. "The Impact of Quantitative Methods on Hedge Fund Performance," European Financial Management, European Financial Management Association, vol. 20(5), pages 857-890, November.
    19. Vikas Agarwal & Stefan Ruenzi & Florian Weigert, 2018. "Unobserved Performance of Hedge Funds," Working Papers on Finance 1825, University of St. Gallen, School of Finance.
    20. Benoît Dewaele, 2013. "Leverage and Alpha: The Case of Funds of Hedge Funds," Working Papers CEB 13-033, ULB -- Universite Libre de Bruxelles.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbfina:v:98:y:2019:i:c:p:212-229. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbf .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.