Time your hedge with Deep Reinforcement Learning (ICAPS 2020 Presentation Slides)

38 Pages Posted: 20 Sep 2021

See all articles by Eric Benhamou

Eric Benhamou

Université Paris Dauphine; EB AI Advisory; AI For Alpha

David Saltiel

Université Paris Dauphine; A.I. Square Connect; AI For Alpha

Sandrine Ungari

Societe Generale

Abhishek Mukhopadhyay

SGCIB

Date Written: September 18, 2021

Abstract

Can an asset manager plan the optimal timing for her/his hedging strategies given market conditions?
The standard approach based on Markowitz or other more or less sophisticated financial rules aims to find the best portfolio allocation thanks to forecasted expected returns and risk but fails to fully relate market conditions to hedging strategies decision. In contrast, Deep Reinforcement Learning (DRL) can tackle this challenge by creating a dynamic dependency between market information and hedging strategies allocation decisions. In this paper, we present a realistic and augmented DRL framework that: (i) uses additional contextual information to decide an action, (ii) has a one period lag between observations and actions to account for one day lag turnover of common asset managers to rebalance their hedge, (iii) is fully tested in terms of stability and robustness thanks to a repetitive train test method called anchored walk forward training, similar in spirit to k fold cross validation for time series and (iv) allows managing leverage of our hedging strategy. Our experiment for an augmented asset manager interested in sizing and timing his hedges shows that our approach achieves superior returns and lower risk.

Keywords: Deep Reinforcement Learning, Portfolio selection, Hedge

JEL Classification: G12, G13

Suggested Citation

Benhamou, Eric and Saltiel, David and Ungari, Sandrine and Mukhopadhyay, Abhishek, Time your hedge with Deep Reinforcement Learning (ICAPS 2020 Presentation Slides) (September 18, 2021). Available at SSRN: https://ssrn.com/abstract=3926216 or http://dx.doi.org/10.2139/ssrn.3926216

Eric Benhamou (Contact Author)

Université Paris Dauphine ( email )

Place du Maréchal de Tassigny
Paris, Cedex 16 75775
France

EB AI Advisory ( email )

35 Boulevard d'Inkermann
Neuilly sur Seine, 92200
France

AI For Alpha ( email )

35 boulevard d'Inkermann
Neuilly sur Seine, 92200
France

David Saltiel

Université Paris Dauphine ( email )

Place du Maréchal de Tassigny
Paris, Cedex 16 75775
France

A.I. Square Connect ( email )

35 Boulevard d'Inkermann
Neuilly sur Seine, 92200
France

AI For Alpha ( email )

35 boulevard d'Inkermann
Neuilly sur Seine, 92200
France

Sandrine Ungari

Societe Generale ( email )

52 Place de l'Ellipse
La Défense, 92000
France

Abhishek Mukhopadhyay

SGCIB ( email )

52 Place de l'Ellipse
La Défense, 92000
France

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