# Gamma and Vega Hedging Using Deep Distributional Reinforcement Learning

arXiv: https://arxiv.org/abs/2205.05614 · HTML: https://mlsanity.com/paper/2205.05614/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 May 2022.

## Built on by (most cited first, 15 of 15)

- [Deep Hedging with Market Impact](https://mlsanity.com/paper/2402.13326/) (2024)
- [A Robust Quantile Huber Loss With Interpretable Parameter Adjustment In Distributional Reinforcement Learning](https://mlsanity.com/paper/2401.02325/) (2024)
- [Catastrophic-risk-aware reinforcement learning with extreme-value-theory-based policy gradients](https://mlsanity.com/paper/2406.15612/) (2024)
- [Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information](https://mlsanity.com/paper/2407.21138/) (2024)
- [Jump Diffusion-Informed Neural Networks with Transfer Learning for Accurate American Option Pricing under Data Scarcity](https://mlsanity.com/paper/2409.18168/) (2024)
- [Deep Reinforcement Learning Algorithms for Option Hedging](https://mlsanity.com/paper/2504.05521/) (2025)
- [Applying Reinforcement Learning to Option Pricing and Hedging](https://mlsanity.com/paper/2310.04336/) (2023)
- [Hedging American Put Options with Deep Reinforcement Learning](https://mlsanity.com/paper/2405.06774/) (2024)
- [Hedging and Pricing Structured Products Featuring Multiple Underlying Assets](https://mlsanity.com/paper/2411.01121/) (2024)
- [EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement Learning](https://mlsanity.com/paper/2408.12446/) (2024)
- [Risk-averse policies for natural gas futures trading using distributional reinforcement learning](https://mlsanity.com/paper/2501.04421/) (2025)
- [Adaptive Nesterov Accelerated Distributional Deep Hedging for Efficient Volatility Risk Management](https://mlsanity.com/paper/2502.17777/) (2025)
- [Distributional Reinforcement Learning on Path-dependent Options](https://mlsanity.com/paper/2507.12657/) (2025)
- [Autonomous AI Agents for Option Hedging: Enhancing Financial Stability through Shortfall Aware Reinforcement Learning](https://mlsanity.com/paper/2603.06587/) (2026)
- [Robust Control under Stationary Ambiguity](https://mlsanity.com/paper/2608.04832/) (2026)

## Abstract (arXiv)

We show how D4PG can be used in conjunction with quantile regression to develop a hedging strategy for a trader responsible for derivatives that arrive stochastically and depend on a single underlying asset. We assume that the trader makes the portfolio delta neutral at the end of each day by taking a position in the underlying asset. We focus on how trades in the options can be used to manage gamma and vega. The option trades are subject to transaction costs. We consider three different objective functions. We reach conclusions on how the optimal hedging strategy depends on the trader's objective function, the level of transaction costs, and the maturity of the options used for hedging. We also investigate the robustness of the hedging strategy to the process assumed for the underlying asset.