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Strategies with minimal norm are optimal for expected utility maximisation under high model ambiguity

Author

Listed:
  • Laurence Carassus

    (Université Paris-Saclay)

  • Johannes Wiesel

    (Carnegie Mellon University
    Copenhagen University)

Abstract

We investigate an expected utility maximisation problem under model uncertainty in a one-period financial market. We capture model uncertainty by replacing the baseline model ℙ with an adverse choice from a Wasserstein ball of radius k $k$ around ℙ in the space of probability measures and consider the corresponding Wasserstein distributionally robust optimisation problem. We show that solutions converge to a strategy with minimal norm when uncertainty becomes large, i.e., when the radius k $k$ tends to infinity.

Suggested Citation

  • Laurence Carassus & Johannes Wiesel, 2025. "Strategies with minimal norm are optimal for expected utility maximisation under high model ambiguity," Finance and Stochastics, Springer, vol. 29(2), pages 519-551, April.
    • Handle: RePEc:spr:finsto:v:29:y:2025:i:2:d:10.1007_s00780-025-00558-4
    DOI: 10.1007/s00780-025-00558-4
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    Keywords

    Utility maximisation; High model uncertainty; Wasserstein distance; Uniform diversification;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

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