Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information
- URL: http://arxiv.org/abs/2407.21138v2
- Date: Tue, 12 Aug 2025 19:34:19 GMT
- Title: Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information
- Authors: Pascal François, Geneviève Gauthier, Frédéric Godin, Carlos Octavio Pérez Mendoza,
- Abstract summary: We present a dynamic hedging scheme for S&P 500 options, where rebalancing decisions are enhanced by integrating information about the implied volatility surface dynamics.<n>The optimal hedging strategy is obtained through a deep policy gradient-type reinforcement learning algorithm.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We present a dynamic hedging scheme for S&P 500 options, where rebalancing decisions are enhanced by integrating information about the implied volatility surface dynamics. The optimal hedging strategy is obtained through a deep policy gradient-type reinforcement learning algorithm. The favorable inclusion of forward-looking information embedded in the volatility surface allows our procedure to outperform several conventional benchmarks such as practitioner and smiled-implied delta hedging procedures, both in simulation and backtesting experiments. The outperformance is more pronounced in the presence of transaction costs.
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