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Robust reward-risk performance measures with weakly second-order stochastic dominance constraints

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  • Kouaissah, Noureddine

Abstract

In this paper, we propose a framework for robustifying reward-risk-based portfolio optimization equipped with weak type second-order stochastic dominance constraints that substantially improves upon their conventional versions. In particular, relying on stable sub-Gaussian and Student’s t distributions, we extend a robust optimization technique that is very popular among conventional robust statistical estimation methods and consider a new notion of weak second-order stochastic dominance. Furthermore, we study the effects of the distributional assumptions on optimal portfolios while addressing the estimation errors directly in the portfolio optimization process. The empirical analyses show that the robustified formulations improve the performance measures upon their classic versions for out-of-sample portfolios.

Suggested Citation

  • Kouaissah, Noureddine, 2023. "Robust reward-risk performance measures with weakly second-order stochastic dominance constraints," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 53-62.
    • Handle: RePEc:eee:quaeco:v:88:y:2023:i:c:p:53-62
    DOI: 10.1016/j.qref.2022.12.003
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