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Liquidity shocks, size and the relative performance of hedge fund strategies

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  • Ding, Bill
  • Shawky, Hany A.
  • Tian, Jianbo

Abstract

We examine whether the increase in the flow of capital to hedge funds over the period 1994-2005 had a negative impact on performance. More specifically, we study the relative performance of small versus large funds for each of the hedge fund strategies. Our results indicate that on an absolute return basis, small funds outperform large funds. On a risk-adjusted return basis, however, we find that large funds outperform small funds, and that large funds are also shown to hold less liquid assets and take on less systematic and idiosyncratic risk than small funds. Further, funds that experience positive liquidity shocks generally outperform those that experience negative liquidity shocks. We also find evidence that hedge fund managers that are aggressive in dealing with liquidity shocks perform better than hedge fund managers that are conservative in dealing with liquidity shocks.

Suggested Citation

  • Ding, Bill & Shawky, Hany A. & Tian, Jianbo, 2009. "Liquidity shocks, size and the relative performance of hedge fund strategies," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 883-891, May.
  • Handle: RePEc:eee:jbfina:v:33:y:2009:i:5:p:883-891
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. Giannikis, Dimitrios & Vrontos, Ioannis D., 2011. "A Bayesian approach to detecting nonlinear risk exposures in hedge fund strategies," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1399-1414, June.
    3. Marini, François, 2011. "Financial intermediation in the theory of the risk-free rate," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1663-1668, July.
    4. Schuhmacher, Frank & Eling, Martin, 2012. "A decision-theoretic foundation for reward-to-risk performance measures," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2077-2082.
    5. repec:fau:fauart:v:67:y:2017:i:6:p:512-538 is not listed on IDEAS
    6. Schuhmacher, Frank & Eling, Martin, 2011. "Sufficient conditions for expected utility to imply drawdown-based performance rankings," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2311-2318, September.
    7. Chen, Zhiping & Yang, Li, 2011. "Nonlinearly weighted convex risk measure and its application," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1777-1793, July.
    8. Gygax, André F. & Otchere, Isaac, 2010. "Index composition changes and the cost of incumbency," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2500-2509, October.
    9. repec:eee:finana:v:52:y:2017:i:c:p:27-37 is not listed on IDEAS
    10. Kang, Moonsoo, 2010. "Probability of information-based trading and the January effect," Journal of Banking & Finance, Elsevier, vol. 34(12), pages 2985-2994, December.
    11. Antonio Di Cesare & Philip A. Stork & Casper G. de Vries, 2015. "Risk Measures for Autocorrelated Hedge Fund Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 13(4), pages 868-895.
    12. Kappou, Konstantina & Brooks, Chris & Ward, Charles, 2010. "The S&P500 index effect reconsidered: Evidence from overnight and intraday stock price performance and volume," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 116-126, January.
    13. Elyasiani, Elyas & Mansur, Iqbal, 2017. "Hedge fund return, volatility asymmetry, and systemic effects: A higher-moment factor-EGARCH model," Journal of Financial Stability, Elsevier, vol. 28(C), pages 49-65.

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