Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling

8 Pages Posted: 27 Jul 2023

See all articles by Masanori Hirano

Masanori Hirano

Preferred Networks, Inc.

Kentaro Minami

Preferred Networks, Inc.

Kentaro Imajo

Preferred Networks, Inc.

Date Written: July 24, 2023

Abstract

Deep hedging is a deep-learning-based framework for derivative hedging in incomplete markets. The advantage of deep hedging lies in its ability to handle various realistic market conditions, such as market frictions, which are challenging to address within the traditional mathematical finance framework. Since deep hedging relies on market simulation, the underlying asset price process model is crucial. However, existing literature on deep hedging often relies on traditional mathematical finance models, e.g., Brownian motion and stochastic volatility models, and discovering effective underlying asset models for deep hedging learning has been a challenge. In this study, we propose a new framework called adversarial deep hedging, inspired by adversarial learning. In this framework, a hedger and a generator, which respectively model the underlying asset process and the underlying asset process, are trained in an adversarial manner. The proposed method enables to learn a robust hedger without explicitly modeling the underlying asset process. Through numerical experiments, we demonstrate that our proposed method achieves competitive performance to models that assume explicit underlying asset processes across various real market data.

Keywords: deep hedging, price process, adversarial learning, neural network, option, financial market

Suggested Citation

Hirano, Masanori and Minami, Kentaro and Imajo, Kentaro, Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling (July 24, 2023). Available at SSRN: https://ssrn.com/abstract=4520273 or http://dx.doi.org/10.2139/ssrn.4520273

Masanori Hirano (Contact Author)

Preferred Networks, Inc. ( email )

Otemachi Bldg., 1-6-1 Otemachi
Chiyoda-ku, Tokyo 1000004
Japan

Kentaro Minami

Preferred Networks, Inc. ( email )

Otemachi Bldg., 1-6-1 Otemachi
Chiyoda-ku, Tokyo 1000004
Japan

Kentaro Imajo

Preferred Networks, Inc.

Otemachi Bldg., 1-6-1 Otemachi
Chiyoda-ku, Tokyo 1000004
Japan

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