Revisiting Fama-French factors’ predictability with Bayesian modelling and copula-based portfolio optimization

Zhao, Y., Stasinakis, C. , Sermpinis, G. and Da Silva Fernandes, F. (2019) Revisiting Fama-French factors’ predictability with Bayesian modelling and copula-based portfolio optimization. International Journal of Finance and Economics, 24(42), pp. 1443-1463. (doi: 10.1002/ijfe.1742)

Abstract

This study is investigating the predictability of the five Fama–French factors and explores their optimal portfolio allocation for factor investing during 2000–2017. Firstly, we forecast each factor with a pool of linear and nonlinear models. Next, the individual forecasts are combined through dynamic model averaging, and their performance is benchmarked by the best performing individual predictor and other forecast combination techniques. Finally, we use the generalized autoregressive score model and the skewed t copula method to estimate the correlation of assets. The generalized autoregressive score performance is also compared with other traditional approaches such as dynamic conditional correlation model and asymmetric dynamic conditional correlation. The performance of the constructed portfolios is assessed through traditional metrics and ratios accounting for the conditional value‐at‐risk and the conditional diversification benefits approach. Our results show that combining Bayesian forecast combinations with copulas is leading to significant improvements in the portfolio optimization process, and forecasting covariance accounting for asymmetric dependence between the factors adds diversification benefits to the obtained portfolios.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Stasinakis, Professor Charalampos and Da Silva Fernandes, Miss Filipa and Zhao, Dr Yang and Sermpinis, Professor Georgios
• Authors: Zhao, Y., Stasinakis, C., Sermpinis, G., and Da Silva Fernandes, F.
• College/School: College of Social Sciences > Adam Smith Business School > Accounting and Finance; College of Social Sciences > Adam Smith Business School > Economics; College of Social Sciences > Adam Smith Business School > Management
• Journal Name: International Journal of Finance and Economics
• Publisher: Wiley
• ISSN: 1076-9307
• ISSN (Online): 1099-1158
• Published Online: 05 August 2019
• Copyright Holders: Copyright © 2019 John Wiley and Sons, Ltd
• First Published: First published in International Journal of Finance and Economics 24(42): 1443-1463
• Publisher Policy: Reproduced in accordance with the publisher copyright policy