Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information
<|reference_start|>Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information: 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, with a novel hybrid neural network architecture improving the training performance. 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.<|reference_end|>
@article{françois2024enhancing,
    title={Enhancing Deep Hedging of Options with Implied Volatility Surface
  Feedback Information},
    author={Pascal Franc{c}ois, Genevi`eve Gauthier, Fr'ed'eric Godin, Carlos
  Octavio P'erez Mendoza},
    journal={arXiv preprint arXiv:2407.21138},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.21138},
    primaryClass={q-fin.RM cs.LG q-fin.CP}
}