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Reinforcement Learning for Credit Index Option Hedging

Author

Listed:
  • Francesco Mandelli
  • Marco Pinciroli
  • Michele Trapletti
  • Edoardo Vittori

Abstract

In this paper, we focus on finding the optimal hedging strategy of a credit index option using reinforcement learning. We take a practical approach, where the focus is on realism i.e. discrete time, transaction costs; even testing our policy on real market data. We apply a state of the art algorithm, the Trust Region Volatility Optimization (TRVO) algorithm and show that the derived hedging strategy outperforms the practitioner's Black & Scholes delta hedge.

Suggested Citation

  • Francesco Mandelli & Marco Pinciroli & Michele Trapletti & Edoardo Vittori, 2023. "Reinforcement Learning for Credit Index Option Hedging," Papers 2307.09844, arXiv.org.
    • Handle: RePEc:arx:papers:2307.09844
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    References listed on IDEAS

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    1. Olivier Guéant & Jiang Pu, 2017. "Option Pricing And Hedging With Execution Costs And Market Impact," Mathematical Finance, Wiley Blackwell, vol. 27(3), pages 803-831, July.
    2. Leland, Hayne E, 1985. "Option Pricing and Replication with Transactions Costs," Journal of Finance, American Finance Association, vol. 40(5), pages 1283-1301, December.
    3. Robert A. Jarrow & Stuart M. Turnbull, 2008. "Pricing Derivatives on Financial Securities Subject to Credit Risk," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 17, pages 377-409, World Scientific Publishing Co. Pte. Ltd..
    4. Igor Halperin, 2019. "The QLBS Q-Learner goes NuQLear: fitted Q iteration, inverse RL, and option portfolios," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1543-1553, September.
    5. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    6. Edoardo Vittori & Michele Trapletti & Marcello Restelli, 2020. "Option Hedging with Risk Averse Reinforcement Learning," Papers 2010.12245, arXiv.org.
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    Cited by:

    1. Reilly Pickard & Yuri Lawryshyn, 2023. "Deep Reinforcement Learning for Dynamic Stock Option Hedging: A Review," Mathematics, MDPI, vol. 11(24), pages 1-19, December.
    2. Roberto Daluiso & Marco Pinciroli & Michele Trapletti & Edoardo Vittori, 2023. "CVA Hedging by Risk-Averse Stochastic-Horizon Reinforcement Learning," Papers 2312.14044, arXiv.org.

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