Risk Management in Multi-objective Portfolio Optimization Under Uncertainty

Yannick Becker (), Pascal Halffmann and Anita Schöbel
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Yannick Becker: Fraunhofer Institute for Industrial Mathematics
Pascal Halffmann: Fraunhofer Institute for Industrial Mathematics
Anita Schöbel: Fraunhofer Institute for Industrial Mathematics

A chapter in Operations Research Proceedings 2024, 2025, pp 157-163 from Springer

Abstract: Abstract In portfolio optimization, decision makers face difficulties from uncertainties inherent in real-world scenarios. These uncertainties significantly influence portfolio outcomes in both classical and multi-objective Markowitz models. To address these challenges, our research explores the power of robust multi-objective optimization. Since portfolio managers frequently measure their solutions against benchmarks, we enhance the multi-objective min-regret robustness concept by incorporating these benchmark comparisons. This approach bridges the gap between theoretical models and real-world investment scenarios, offering portfolio managers more reliable and adaptable strategies for navigating market uncertainties. Our framework provides a more nuanced and practical approach to portfolio optimization under real-world conditions.

Keywords: Multi-objective optimization; Uncertainty; Robustness; Portfolio optimization (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-92575-7_22

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DOI: 10.1007/978-3-031-92575-7_22

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