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Distributionally robust portfolio maximization and marginal utility pricing in one period financial markets

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  • Jan Obłój
  • Johannes Wiesel

Abstract

We consider the optimal investment and marginal utility pricing problem of a risk averse agent and quantify their exposure to model uncertainty. Specifically, we compute explicitly the first‐order sensitivity of their value function, optimal investment policy and Davis' option prices to model uncertainty. To achieve this, we capture model uncertainty by replacing the baseline model P with an adverse choice from a small Wasserstein ball around P in the space of probability measures. Our sensitivities are thus fully non‐parametric. We show that the results entangle the baseline model specification and the agent's risk attitudes. The sensitivities can behave in a non‐monotone way as a function of the baseline model's Sharpe's ratio, the relative weighting of assets in the agent's portfolio can change and marginal prices can both increase or decrease when the agent faces model uncertainty.

Suggested Citation

  • Jan Obłój & Johannes Wiesel, 2021. "Distributionally robust portfolio maximization and marginal utility pricing in one period financial markets," Mathematical Finance, Wiley Blackwell, vol. 31(4), pages 1454-1493, October.
  • Handle: RePEc:bla:mathfi:v:31:y:2021:i:4:p:1454-1493
    DOI: 10.1111/mafi.12337
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    3. Laurence Carassus & Johannes Wiesel, 2023. "Strategies with minimal norm are optimal for expected utility maximization under high model ambiguity," Papers 2306.01503, arXiv.org, revised Jan 2024.
    4. Michail Anthropelos & Paul Schneider, 2021. "Optimal Investment and Equilibrium Pricing under Ambiguity," Swiss Finance Institute Research Paper Series 21-78, Swiss Finance Institute.
    5. Alexander M. G. Cox & Annemarie M. Grass, 2023. "Robust option pricing with volatility term structure -- An empirical study for variance options," Papers 2312.09201, arXiv.org.
    6. Daniel Bartl & Ariel Neufeld & Kyunghyun Park, 2023. "Sensitivity of robust optimization problems under drift and volatility uncertainty," Papers 2311.11248, arXiv.org.
    7. Daniel Bartl & Johannes Wiesel, 2022. "Sensitivity of multiperiod optimization problems in adapted Wasserstein distance," Papers 2208.05656, arXiv.org, revised Jun 2023.

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