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Testing non-linear dependence in the hedge fund industry

Author

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  • Javier Mencía

    (Banco de España)

Abstract

This paper proposes a parsimonious approach to test non-linear dependence on the conditional mean and variance of hedge funds with respect to several market factors. My approach introduces non-linear dependence by means of empirically relevant polynomial functions of the factors. For comparison purposes, I also consider multifactor extensions of tests based on piecewise linear alternatives. I apply these tests to a database of monthly returns on 1,071 hedge funds. I find that non-linear dependence on the mean is highly sensitive to the factors that I consider. However, I obtain a much stronger evidence of nonlinear dependence on the conditional variance.

Suggested Citation

  • Javier Mencía, 2010. "Testing non-linear dependence in the hedge fund industry," Working Papers 1007, Banco de España.
  • Handle: RePEc:bde:wpaper:1007
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    References listed on IDEAS

    as
    1. Antonio Diez De Los Rios & René Garcia, 2011. "Assessing and valuing the nonlinear structure of hedge fund returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(2), pages 193-212, March.
    2. Giovanni Barone Adesi & Patrick Gagliardini & Giovanni Urga, 2004. "Testing Asset Pricing Models With Coskewness," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 474-485, October.
    3. 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.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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