Research Repository

Hedge fund return predictability; To combine forecasts or combine information?

Panopoulou, Ekaterini and Vrontos, Spyridon (2015) 'Hedge fund return predictability; To combine forecasts or combine information?' Journal of Banking & Finance, 56. pp. 103-122. ISSN 0378-4266

1-s2.0-S0378426615000655-main.pdf - Accepted Version

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While the majority of the predictability literature has been devoted to the predictability of traditional asset classes, the literature on the predictability of hedge fund returns is quite scanty. We focus on assessing the out-of-sample predictability of hedge fund strategies by employing an extensive list of predictors. Aiming at reducing uncertainty risk associated with a single predictor model, we first engage into combining the individual forecasts. We consider various combining methods ranging from simple averaging schemes to more sophisticated ones, such as discounting forecast errors, cluster combining and principal components combining. Our second approach combines information of the predictors and applies kitchen sink, bootstrap aggregating (bagging), lasso, ridge and elastic net specifications. Our statistical and economic evaluation findings point to the superiority of simple combination methods. We also provide evidence on the use of hedge fund return forecasts for hedge fund risk measurement and portfolio allocation. Dynamically constructing portfolios based on the combination forecasts of hedge funds returns leads to considerably improved portfolio performance.

Item Type: Article
Uncontrolled Keywords: Forecast combination; Combining information; Prediction; Hedge funds; Portfolio construction
Subjects: H Social Sciences > HG Finance
Q Science > QA Mathematics
Divisions: Faculty of Science and Health
Faculty of Science and Health > Mathematical Sciences, Department of
Faculty of Social Sciences
Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Essex Finance Centre
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 14 Apr 2015 10:03
Last Modified: 12 Apr 2022 02:46

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