Becker, YannickYannickBeckerHalffmann, PascalPascalHalffmannSchöbel, AnitaAnitaSchöbel2025-01-282025-01-282024-07-29https://publica.fraunhofer.de/handle/publica/48299110.48550/arXiv.2407.19936In 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.enMulti-objective optimizationUncertaintyRobustnessPortfolio optimization500 Naturwissenschaften und Mathematikpaper