Reinforcement Learning for Credit Index Option Hedging

2023/07/19 by Francesco Mandelli, Marco Pinciroli, Mandelli, Francesco +5
Economics, Econometrics and Finance · #Computational Finance (q-fin.CP) #FOS: Computer and information sciences #FOS: Economics and business #Machine Learning (cs.LG) #Risk Management (q-fin.RM) #Stochastic processes and financial applications #Trading and Market Microstructure (q-fin.TR)

paper · pdf · doi:10.48550/arxiv.2307.09844

openalex publication_date 2023/07/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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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