Robust approaches in portfolio optimization with stochastic dominance constraints

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10507987" target="_blank" >RIV/00216208:11320/25:10507987 - isvavai.cz</a>

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=m9Ec82ybar" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=m9Ec82ybar</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00291-025-00814-1" target="_blank" >10.1007/s00291-025-00814-1</a>

Result language

angličtina

Original language name

Robust approaches in portfolio optimization with stochastic dominance constraints

Original language description

The paper deals with a modern approach of stochastic dominance in portfolio optimization. Since the distribution of returns is often just estimated from data, we look for the worst-case distribution that differs from the empirical distribution by no more than some prescribed value. First, we define in what sense the distribution is the worst one for stochastic dominance. Then, using Wasserstein distance, we derive a reformulation for robust second-order stochastic dominance and find the worst-case distribution as the optimal solution of a non-linear optimization problem. Finally, we derive programs to maximize an objective function over the weights of the portfolio with the robust stochastic dominance condition in constraints. We consider robustness in returns for second-order stochastic dominance. We apply all derived optimization programs to real-life data, specifically to returns of assets captured by the Dow Jones Industrial Average, and analyze the problems in detail using optimal solutions of optimization programs with multiple setups. The empirical analysis proceeded with an out-of-sample evaluation of portfolios formulated through the robust optimization program, employing a moving window methodology. The findings of this study indicate that for some of the values of epsilondocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} begin{document}$$varepsilon $$end{document} the robustified portfolios consistently out-of-sample outperform those derived from the non-robust optimization approach.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

OR Spektrum

ISSN

0171-6468

e-ISSN

1436-6304

Volume of the periodical

47

Issue of the periodical within the volume

4

Country of publishing house

DE - GERMANY

Number of pages

33

Pages from-to

1421-1453

UT code for WoS article

001489530200001

EID of the result in the Scopus database

2-s2.0-105005095837