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Risk Management in Multi-objective Portfolio Optimization Under Uncertainty

Author

Listed:
  • Yannick Becker

    (Fraunhofer Institute for Industrial Mathematics
    University of Kaiserslautern-Landau)

  • Pascal Halffmann

    (Fraunhofer Institute for Industrial Mathematics)

  • Anita Schöbel

    (Fraunhofer Institute for Industrial Mathematics
    University of Kaiserslautern-Landau)

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.

Suggested Citation

  • Yannick Becker & Pascal Halffmann & Anita Schöbel, 2025. "Risk Management in Multi-objective Portfolio Optimization Under Uncertainty," Lecture Notes in Operations Research,, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-92575-7_22
    DOI: 10.1007/978-3-031-92575-7_22
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