Reinforcement Learning for Credit Index Option Hedging

Francesco Mandelli; Marco Pinciroli; Michele Trapletti; Edoardo Vittori

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arXiv · 2307.09844

Reinforcement Learning for Credit Index Option Hedging

Francesco Mandelli·Marco Pinciroli·Michele Trapletti·Edoardo Vittori

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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.

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BibTeX RIS

Francesco Mandelli, Marco Pinciroli, Michele Trapletti, Edoardo Vittori. 2023-07-19. Reinforcement Learning for Credit Index Option Hedging. https://arxiv.org/abs/2307.09844

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