Robust Portfolio Optimization with Multi-Factor Stochastic Volatility

Authors

Ben Yang
Xiaoping Lu, University of WollongongFollow
Guiyuan Ma
Song-Ping Zhu, University of WollongongFollow

RIS ID

143703

Publication Details

Yang, B., Lu, X., Ma, G. & Zhu, S. (2020). Robust Portfolio Optimization with Multi-Factor Stochastic Volatility. Journal of Optimization Theory and Applications,

Abstract

2020, Springer Science+Business Media, LLC, part of Springer Nature. This paper studies a robust portfolio optimization problem under a multi-factor volatility model. We derive optimal strategies analytically under the worst-case scenario with or without derivative trading in complete and incomplete markets and for assets with jump risk. We extend our study to the case with correlated volatility factors and propose an analytical approximation for the robust optimal strategy. To illustrate the effects of ambiguity, we compare our optimal robust strategy with the strategies that ignore the information of uncertainty, and provide the welfare analysis. We also discuss how derivative trading affects the optimal strategies. Finally, numerical experiments are provided to demonstrate the behavior of the optimal strategy and the utility loss.