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The Life Cycle of Hedge Funds: Fund Flows, Size, Competition, and Performance

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  • Mila Getmansky

    (Isenberg School of Management, University of Massachusetts, 121 Presidents Drive, Room 308C, Amherst, MA 01003, USA)

Abstract

This paper analyzes the life cycles of hedge funds. Using the Lipper TASS database it provides category and fund specific factors that affect the survival probability of hedge funds. The findings show that in general, investors chasing individual fund performance, thus increasing fund flows, decrease probabilities of hedge funds liquidating. However, if investors chase a category of hedge funds that has performed well (favorably positioned), then the probability of hedge funds liquidating in this category increases. We interpret this finding as a result of competition among hedge funds in a category. As competition increases, marginal funds are more likely to be liquidated than funds that deliver superior risk-adjusted returns. We also find that there is a concave relationship between performance and lagged assets under management. The implication of this study is that an optimal asset size can be obtained by balancing out the effects of past returns, fund flows, competition, market impact, and favorable category positioning that are modeled in the paper. Hedge funds in capacity constrained and illiquid categories are subject to high market impact, have limited investment opportunities, and are likely to exhibit an optimal size behavior.

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  • Mila Getmansky, 2012. "The Life Cycle of Hedge Funds: Fund Flows, Size, Competition, and Performance," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 2(01), pages 1-53.
    • Handle: RePEc:wsi:qjfxxx:v:02:y:2012:i:01:n:s2010139212500036
    DOI: 10.1142/S2010139212500036
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    References listed on IDEAS

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    1. Adam L. Aiken & Christopher P. Clifford & Jesse Ellis, 2013. "Out of the Dark: Hedge Fund Reporting Biases and Commercial Databases," The Review of Financial Studies, Society for Financial Studies, vol. 26(1), pages 208-243.
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    3. Vayanos, Dimitri, 2004. "Flight to quality, flight to liquidity, and the pricing of risk," LSE Research Online Documents on Economics 456, London School of Economics and Political Science, LSE Library.
    4. Agarwal, Vikas & Fos, Vyacheslav & Jiang, Wei, 2010. "Inferring reporting biases in hedge fund databases from hedge fund equity holdings," CFR Working Papers 10-08, University of Cologne, Centre for Financial Research (CFR).
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    Cited by:

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    2. Vikas Agarwal & Stefan Ruenzi & Florian Weigert, 2018. "Unobserved Performance of Hedge Funds," Working Papers on Finance 1825, University of St. Gallen, School of Finance.
    3. Michael Busack & Wolfgang Drobetz & Jan Tille, 2017. "Can investors benefit from the performance of alternative UCITS funds?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(1), pages 69-111, February.
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    7. Braun, Alexander & Ben Ammar, Semir & Eling, Martin, 2019. "Asset pricing and extreme event risk: Common factors in ILS fund returns," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 59-78.
    8. Bae, Jongwan & Haight, Timothy & Kuang, Xin & Yin, Chengdong, 2023. "Advisory firm paths to side-by-side management and mutual fund performance," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 1-21.
    9. Zhiguo He & Arvind Krishnamurthy, 2019. "A Macroeconomic Framework for Quantifying Systemic Risk," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(4), pages 1-37, October.
    10. Cumming, Douglas J. & Monteiro, Pedro, 2023. "Hedge fund investment in ETFs," CFS Working Paper Series 699, Center for Financial Studies (CFS).
    11. George J. Jiang & Bing Liang & Huacheng Zhang, 2022. "Hedge Fund Manager Skill and Style-Shifting," Management Science, INFORMS, vol. 68(3), pages 2284-2307, March.
    12. Hongxian Zhang & Liang Guo & Maggie Hao, 2018. "Corruption, governance, and public pension funds," Review of Quantitative Finance and Accounting, Springer, vol. 51(4), pages 883-919, November.
    13. Ling, Yun & Satchell, Stephen & Yao, Juan, 2023. "Decreasing returns to scale and skill in hedge funds," Journal of Banking & Finance, Elsevier, vol. 156(C).
    14. Arpit Gupta & Kunal Sachdeva, 2019. "Skin or Skim? Inside Investment and Hedge Fund Performance," NBER Working Papers 26113, National Bureau of Economic Research, Inc.
    15. Clemens Sialm & Zheng Sun & Lu Zheng, 2020. "Home Bias and Local Contagion: Evidence from Funds of Hedge Funds," The Review of Financial Studies, Society for Financial Studies, vol. 33(10), pages 4771-4810.
    16. Cumming, Douglas & Monteiro, Pedro, 2022. "Hedge fund sales fees and the flow of funds around the world," Economic Modelling, Elsevier, vol. 112(C).
    17. Mullally, Kevin A., 2022. "Outside ownership in the hedge fund industry," Journal of Banking & Finance, Elsevier, vol. 144(C).
    18. Kooli, Maher & Zhang, Min, 2022. "Not only skill but also scale: Evidence from the hedge funds industry," International Review of Financial Analysis, Elsevier, vol. 83(C).
    19. Viet Do & Robert Faff & Paul Lajbcygier & Madhu Veeraraghavan & Mikhail Tupitsyn, 2016. "Factors affecting the birth and fund flows of CTAs," Australian Journal of Management, Australian School of Business, vol. 41(2), pages 324-352, May.
    20. Hentati-Kaffel, Rania & de Peretti, Philippe, 2015. "Generalized runs tests to detect randomness in hedge funds returns," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 608-615.
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    22. Greg N. Gregoriou & Maher Kooli, 2017. "The profiles of merged hedge funds, funds of hedge funds, and CTA," Journal of Asset Management, Palgrave Macmillan, vol. 18(1), pages 49-63, January.

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