Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information

Pascal François, Geneviève Gauthier, Frédéric Godin, Carlos Octavio Pérez Mendoza
7/30/2024
q-fin.RMcs.LGq-fin.CP

No official code found. Best implementation: cpmendoza/DeepHedging_JIVR (6 stars, MIT, last commit 2024-07-06).

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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Code Implementations(1)

cpmendoza/DeepHedging_JIVRCommunity100%
MIT
64Python, Jupyter NotebookApr 12, 20242 years agoMIT

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Cite this paper

@article{franois2024enhancing,
  title  = {Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information},
  author = {Pascal François and Geneviève Gauthier and Frédéric Godin and Carlos Octavio Pérez Mendoza},
  year   = {2024},
  eprint = {2407.21138},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.21138v2}
}

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