10 мая 2022 г. · 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 ...

We show how reinforcement learning can be used in conjunction with quantile regression to develop a hedging strategy for a trader responsible for derivatives. Abstract · Introduction · The RL model · Results

22 февр. 2023 г. · Our objective is to illustrate how RL can be used to develop a strategy for managing gamma and vega risk. The same reinforcement approach can be ...

It shows how RL can be used to develop a strategy for using options to manage gamma and vega risk with three different objective functions. These objective ...

These authors consider how reinforcement learning can be used to hedge a single call or put option using a position in the underlying asset. The key measure of ...

This study investigates the use of deep reinforcement learning algorithms to hedge convexity and volatility (gamma and vega) in a system that includes ...

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 ...

This is the companion code for the paper Gamma and Vega Hedging Using Deep Distributional Reinforcement Learning.

In this paper, we propose the Quantile Option Architecture (QUOTA) for exploration based on recent advances in distributional reinforcement learning (RL).

We use deep distributional reinforcement learning (RL) to develop hedging strategies for a trader responsible for derivatives dependent on a particular ...