Testing non-linear dependence in the hedge fund industry
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.
|Date of creation:||Mar 2010|
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- 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.
- Antonio Diez de los Rios & René Garcia, 2006. "Assessing and Valuing the Non-Linear Structure of Hedge Fund Returns," Staff Working Papers 06-31, Bank of Canada.
- 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. Full references (including those not matched with items on IDEAS)
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