An advanced perspective on the predictability in hedge fund returns
This paper advances the research on the predictability in hedge fund returns, using a broad set of risk factors within a variety of different prediction models. Accounting for the fact that returns are non-normally distributed, heteroscedastic and time-varying in their exposure to pervasive economic risk factors, we advocate a non-parametric backward elimination regression approach. The interdependencies between the monthly changes of envisaged risk factors and the subsequent hedge fund returns remain remarkably stable in terms of the observed direction of impact. Thus, taking into account the specific characteristics of this asset class, we find strong evidence of its return predictability.
Year of publication: |
2010
|
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Authors: | Wegener, Christian ; von Nitzsch, RĂ¼diger ; Cengiz, Cetin |
Published in: |
Journal of Banking & Finance. - Elsevier, ISSN 0378-4266. - Vol. 34.2010, 11, p. 2694-2708
|
Publisher: |
Elsevier |
Keywords: | Return predictability Non-parametric estimation Meta hedge fund indices In-sample break point model Risk factors |
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