Robust portfolio optimization: a stochastic evaluation of worst-case scenarios

Abstract

This article presents a new approach for building robust portfolios based on stochastic efficiency analysis, by using the Chance Constrained Data Envelopment Analysis (CCDEA) model and periods of market downturn, i.e. worst-state market. The model is able to accommodate investors who exhibit different risk behaviors and the empirical analysis is done on assets traded on the Brazil Stock Exchange, B3 (Brasil, Bolsa, Balcão). The results confirm that the proposed model achieved portfolios that at the same time reduced systematic risk and maximized portfolio returns when working with worse market state data and higher levels of risk aversion. A higher level of risk aversion also led to better risk-return ratios, which can be seen in higher Sharpe ratio values.

Keywords:

• Robust optimization
• stochastic evaluation
• chance constrained DEA
• worst-case markets
• portfolios

JEL CODES:

• G11
• G14
• C38
• C61

Acknowledgements

This paper is part of a project GEOCEP that has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 870245. The authors would like to thank the Brazilian National Council for Scientific and Technological Development - CNPq Brazil (Processes 308021/2019-3, and 302751/2020-3), and the Coordination for the Improvement of Higher Education Personnel - Capes Brazil. The authors also thank the Czech Science Foundation - Czech Republic (grant number 22-19617S) for the financial support and research incentive. The views expressed here are those of the authors and not necessarily those of our institutions. All remaining errors are solely our responsibility.

Disclosure statement

No potential conflict of interest was reported by the authors.