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Option Hedging Through Reinforcement Learning

In: New Perspectives in Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Federico Giorgi

    (University of Rome “Tor Vergata”, Department of Economics and Finance)

  • Stefano Herzel

    (University of Rome “Tor Vergata”, Department of Economics and Finance)

  • Paolo Pigato

    (University of Rome “Tor Vergata”, Department of Economics and Finance)

Abstract

We propose a Reinforcement Learning algorithm to hedge the payoff of a European call option. The algorithm is first tested on the Black-Scholes-Merton model, where the problem has a well known solution, so that we can compare the strategy obtained by the algorithm to the theoretical optimal one. Then, in a more realistic case that includes transaction costs, the algorithm outperforms the standard delta hedging strategy.

Suggested Citation

  • Federico Giorgi & Stefano Herzel & Paolo Pigato, 2025. "Option Hedging Through Reinforcement Learning," Springer Books, in: Michele La Rocca & Massimiliano Menzietti & Cira Perna & Marilena Sibillo (ed.), New Perspectives in Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 169-178, Springer.
    • Handle: RePEc:spr:sprchp:978-3-032-05551-4_15
    DOI: 10.1007/978-3-032-05551-4_15
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