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arXiv · 2407.19936

Risk management in multi-objective portfolio optimization under uncertainty

Yannick Becker·Pascal Halffmann·Anita Schöbel
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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.

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Yannick Becker, Pascal Halffmann, Anita Schöbel. 2024-07-29. Risk management in multi-objective portfolio optimization under uncertainty. https://doi.org/10.1007/978-3-031-92575-7_22

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