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Multi-period Mean–Variance Hedging Problem with Model Risk

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  • Koichi Matsumoto
  • Tatsuhiko Suyama

Abstract

This paper studies a mean–variance hedging problem in the presence of model risk. The model risk is represented by a set of candidate models for the true model. We formulate the problem as a best hedging strategy selection problem under worst-case conditions. We show the existence of an optimal hedging strategy and propose a numerical calculation method using deep learning. Furthermore, we confirm the validity of our method with a simple numerical example.

Suggested Citation

  • Koichi Matsumoto & Tatsuhiko Suyama, 2024. "Multi-period Mean–Variance Hedging Problem with Model Risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 31(6), pages 365-384, November.
    • Handle: RePEc:taf:apmtfi:v:31:y:2024:i:6:p:365-384
    DOI: 10.1080/1350486X.2025.2529784
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