Reinforcement Learning for Credit Index Option Hedging

Francesco Mandelli, Marco Pinciroli, Michele Trapletti and 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.

Date: 2023-07
New Economics Papers: this item is included in nep-cmp, nep-fmk and nep-rmg
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Citations: View citations in EconPapers (2)

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