Experiments of Deep Hedging using Artificial Market Simulation

Abstract

Deep Hedging is now a key technology that uses deep learning to hedge derivatives. Various models for the underlier price process have been used for it, and it is known that the model is important for hedging performances. In this study, we conducted Deep Hedging experiments using artificial market simulations for its underlier simulator. As an artificial market simulation model, we employed simple models based on fundamental, chat, and noise factors. As a result, we confirmed that even the simple artificial market simulation could be used for an underlier simulator for Deep Hedging, and its performance is almost equivalent to the conventional Deep Hedging models under certain conditions.