Hedge Fund Return Predictability in the Presence of Model Risk

46 Pages Posted: 28 Oct 2019

See all articles by Christos Argyropoulos

Christos Argyropoulos

Lancaster University - Department of Accounting and Finance

Ekaterini Panopoulou

Essex Business School

Nikolaos Voukelatos

University of Kent

Teng Zheng

Barclays PLC

Date Written: October 18, 2019

Abstract

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.

Keywords: Forecasting, Hedge Funds, Dynamic Model Averaging, Model Risk, Fund of Funds

Suggested Citation

Argyropoulos, Christos and Panopoulou, Ekaterini and Voukelatos, Nikolaos and Zheng, Teng, Hedge Fund Return Predictability in the Presence of Model Risk (October 18, 2019). Available at SSRN: https://ssrn.com/abstract=3471829 or http://dx.doi.org/10.2139/ssrn.3471829

Christos Argyropoulos

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Ekaterini Panopoulou

Essex Business School ( email )

Wivenhoe Park
Colchester, CO4 3SQ
United Kingdom

Nikolaos Voukelatos (Contact Author)

University of Kent ( email )

Canterbury, Kent CT2 7PE
United Kingdom
0044 (0) 1227827705 (Phone)

HOME PAGE: http://https://www.kent.ac.uk/kbs/profiles/staff/voukelatos_nikolaos.html

Teng Zheng

Barclays PLC ( email )

1 Churchill Place
London, E14 5HP
United Kingdom

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
37
Abstract Views
276
PlumX Metrics