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.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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," Working Papers 06-31, Bank of Canada.
When requesting a correction, please mention this item's handle: RePEc:bde:wpaper:1007. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mar�a Beiro. Electronic Dissemination of Information Unit. Research Department. Banco de Espa�a)
If references are entirely missing, you can add them using this form.