Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization

Yang Zhao; Charalampos Stasinakis; Georgios Sermpinis; Filipa Da Silva Fernandes

doi:10.1002/ijfe.1742

journal article Aug 05, 2019

Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization

Yang Zhao

Charalampos Stasinakis

Georgios Sermpinis

Filipa Da Silva Fernandes

International Journal of Finance & Economics Vol. 24 No. 4 pp. 1443-1463 · Wiley

View at Publisher Save 10.1002/ijfe.1742

Abstract

AbstractThis 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 skewedtcopula 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.

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Details

Published: Aug 05, 2019
Vol/Issue: 24(4)
Pages: 1443-1463
License: View

Authors

Y

Yang Zhao

Chinese Academy of Finance and Development Central University of Finance and Economics Beijing China

C

Charalampos Stasinakis

Adam Smith Business School University of Glasgow Glasgow UK

G

Georgios Sermpinis

Adam Smith Business School University of Glasgow Glasgow UK

F

Filipa Da Silva Fernandes

Aberdeen Business School University of Aberdeen Aberdeen UK

Cite This Article

Yang Zhao, Charalampos Stasinakis, Georgios Sermpinis, et al. (2019). Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization. International Journal of Finance & Economics, 24(4), 1443-1463. https://doi.org/10.1002/ijfe.1742

Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization

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