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Quantile regression analysis of hedge fund strategies

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  • Meligkotsidou, Loukia
  • Vrontos, Ioannis D.
  • Vrontos, Spyridon D.
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    Abstract

    Extending previous work on hedge fund pricing, this paper introduces the idea of modelling the conditional quantiles of hedge fund returns using a set of risk factors. Quantile regression analysis provides a way of understanding how the relationship between hedge fund returns and risk factors changes across the distribution of conditional returns. We propose a Bayesian approach to model comparison which provides posterior probabilities for different risk factor models that can be used for model averaging. The most relevant risk factors are identified for different quantiles and compared with those obtained for the conditional expectation model. We find differences in factor effects across quantiles of returns, which suggest that the standard conditional mean regression method may not be adequate for uncovering the risk-return characteristics of hedge funds. We explore potential economic impacts of our approach by analysing hedge fund single strategy return series and by constructing style portfolios.

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    File URL: http://www.sciencedirect.com/science/article/B6VFG-4TP49M2-2/2/dc436afc91e5283944a9cea0d4b05825
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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Empirical Finance.

    Volume (Year): 16 (2009)
    Issue (Month): 2 (March)
    Pages: 264-279

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    Handle: RePEc:eee:empfin:v:16:y:2009:i:2:p:264-279

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    Web page: http://www.elsevier.com/locate/jempfin

    Related research

    Keywords: Conditional quantiles Model selection techniques Model uncertainty Hedge funds Bayesian model averaging Risk factors Style portfolio construction;

    References

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    Cited by:
    1. Mattos, Fabio & Garcia, Philip, 2009. "The Effect of Prior Gains and Losses on Current Risk-Taking Using Quantile Regression," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53035, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    2. Ming-Chi Chen & Chi-Lu Peng & So-De Shyu & Jhih-Hong Zeng, 2012. "Market States and the Effect on Equity REIT Returns due to Changes in Monetary Policy Stance," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 364-382, August.
    3. J. Carlos Matallín-Sáez & Amparo Soler-Domínguez & Emili Tortosa-Ausina, 2013. "Does active management add value? New evidence from a quantile regression," Working Papers 2013/01, Economics Department, Universitat Jaume I, Castellón (Spain).
    4. Abdelaati Daouia & Laurent Gardes & Stéphane Girard & Alexandre Lekina, 2011. "Kernel estimators of extreme level curves," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 20(2), pages 311-333, August.
    5. Sofía B. Ramos & Helena Veiga, 2010. "Asymmetric effects of oil price fluctuations in international stock markets," Statistics and Econometrics Working Papers ws100904, Universidad Carlos III, Departamento de Estadística y Econometría.
    6. Lee, Bong Soo & Li, Ming-Yuan Leon, 2012. "Diversification and risk-adjusted performance: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2157-2173.
    7. Amparo Soler Domínguez & Juan Carlos Matallín Sáez & Emili Tortosa-Ausina, 2013. "Does active management add value? New evidence from a quantile regression approach," Working Papers. Serie EC 2013-02, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    8. Olmo, José & Sanso-Navarro, Marcos, 2012. "Forecasting the performance of hedge fund styles," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2351-2365.
    9. 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.

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