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Pricing American Options Under Rough Volatility Using Signatures

In: Stochastic Analysis and Applications 2025

Author

Listed:
  • Christian Bayer

    (Weierstrass Institut (WIAS))

  • Luca Pelizzari

    (Weierstrass Institut (WIAS)
    Technische Universität Berlin)

  • Jia-Jie Zhu

    (Weierstrass Institut (WIAS))

Abstract

We extend the signature-based primal and dual solutions to the optimal stopping problem recently introduced in [Bayer et al.: Primal and dual optimal stopping with signatures, to appear in Finance & Stochastics 2025], by integrating deep-signature and signature-kernel learning methodologies. These approaches are designed for non-Markovian frameworks, in particular enabling the pricing of American options under rough volatility. We demonstrate and compare the performance within the popular rough Heston and rough Bergomi models.

Suggested Citation

  • Christian Bayer & Luca Pelizzari & Jia-Jie Zhu, 2026. "Pricing American Options Under Rough Volatility Using Signatures," Springer Books, in: Dan Crisan & Ilya Chevyrev & Thomas Cass & James Foster & Christian Litterer & Cristopher Salvi (ed.), Stochastic Analysis and Applications 2025, pages 375-398, Springer.
    • Handle: RePEc:spr:sprchp:978-3-032-03914-9_13
    DOI: 10.1007/978-3-032-03914-9_13
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