# Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information

arXiv: https://arxiv.org/abs/2407.21138 · HTML: https://mlsanity.com/paper/2407.21138/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 72 references that are in the map.
- First posted on arXiv 30 Jul 2024.

## Builds on (most cited first, 10 of 10)

- [Deep Hedging](https://mlsanity.com/paper/1802.03042/) (2018)
- [Deep Hedging of Derivatives Using Reinforcement Learning](https://mlsanity.com/paper/2103.16409/) (2021)
- [Quantum Deep Hedging](https://mlsanity.com/paper/2303.16585/) (2023)
- [An empirical analysis of dropout in piecewise linear networks](https://mlsanity.com/paper/1312.6197/) (2013)
- [Probabilistic Forecasting of Sensory Data with Generative Adversarial Networks - ForGAN](https://mlsanity.com/paper/1903.12549/) (2019)
- [Gamma and Vega Hedging Using Deep Distributional Reinforcement Learning](https://mlsanity.com/paper/2205.05614/) (2022)
- [Deep Hedging under Rough Volatility](https://mlsanity.com/paper/2102.01962/) (2021)
- [Robust Risk-Aware Option Hedging](https://mlsanity.com/paper/2303.15216/) (2023)
- [The QLBS Q-Learner Goes NuQLear: Fitted Q Iteration, Inverse RL, and Option Portfolios](https://mlsanity.com/paper/1801.06077/) (2018)
- [Deep Hedging with Market Impact](https://mlsanity.com/paper/2402.13326/) (2024)

## Built on by (most cited first, 2 of 2)

- [Application of Deep Reinforcement Learning to At-the-Money S&P 500 Options Hedging](https://mlsanity.com/paper/2510.09247/) (2025)
- [Learning to Hedge Swaptions](https://mlsanity.com/paper/2512.06639/) (2025)

## Abstract (arXiv)

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.