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Hedge Fund Return Predictability in the Presence of Model Risk

Argyropoulos, Christos, Panopoulou, Ekaterini, Voukelatos, Nikolaos, Zheng, Teng (2022) Hedge Fund Return Predictability in the Presence of Model Risk. European Journal of Finance, . ISSN 1351-847X. (doi:10.1080/1351847X.2021.2020146) (KAR id:92303)


Hedge funds implement elaborate investment strategies that include a variety of positions and assets. As a result, there is significant time variation in the set of risk factors and their respective loadings which in turn introduces severe model risk in any attempt to model and forecast hedge fund returns. In this study, we investigate the statistical and economic value of incorporating heteroscedasticity, non-normality, time-varying parameters, model selection risk and parameter estimation risk jointly in hedge fund return forecasting and fund of funds construction. Parameter estimation risk is dealt with a time-varying parameter structure, while model selection uncertainty is mitigated by model averaging or model selection. We adopt a dynamic model averaging approach along with the conventional Bayesian averaging technique. Our empirical results suggest that accounting for model risk can significantly improve the forecasting accuracy of hedge fund returns and consequently the performance of funds of hedge funds.

Item Type: Article
DOI/Identification number: 10.1080/1351847X.2021.2020146
Uncontrolled keywords: Forecasting; Hedge funds; Dynamic model averaging; Model risk; Fund of funds
Subjects: H Social Sciences > HG Finance
Divisions: Divisions > Kent Business School - Division > Department of Accounting and Finance
Depositing User: Nikolaos Voukelatos
Date Deposited: 13 Dec 2021 18:24 UTC
Last Modified: 08 Jan 2024 11:25 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Voukelatos, Nikolaos.

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