Deep Reinforcement Learning (DRL) for Portfolio Allocation

ECML PKDD Demo track 2020

5 Pages Posted: 2 Jul 2021

See all articles by Eric Benhamou

Eric Benhamou

Université Paris Dauphine; EB AI Advisory; AI For Alpha

David Saltiel

A.I. Square Connect; AI For Alpha

Jean-Jacques Ohana

Université Paris Dauphine

Jamal Atif

Université Paris Dauphine

Rida Laraki

Université Paris-Dauphine, PSL Research University

Date Written: 2020

Abstract

Deep reinforcement learning (DRL) has reached an unprecedent level on complex tasks like game solving (Go or StarCraft II), and autonomous driving. However, applications to real financial assets are still largely unexplored and it remains an open question whether DRL can reach super human level. In this ECML PKKDD demo, we showcase state-of-the-art DRL methods for selecting portfolios according to financial environment, with a final network concatenating three individual networks using layers of convolutions to reduce network's complexity.

The multi entries of our network enables capturing dependencies from common financial indicators features like risk aversion, citigroup index surprise, portfolio specific features and previous portfolio allocations. Results on test set show this approach can overperform traditional portfolio optimization methods.

Keywords: Deep Reinforcement Learning, Portfolio Selection

JEL Classification: G11

Suggested Citation

Benhamou, Eric and Saltiel, David and Ohana, Jean-Jacques and Atif, Jamal and Laraki, Rida, Deep Reinforcement Learning (DRL) for Portfolio Allocation (2020). ECML PKDD Demo track 2020, Available at SSRN: https://ssrn.com/abstract=3871071 or http://dx.doi.org/10.2139/ssrn.3871071

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

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

Jean-Jacques Ohana

Université Paris Dauphine ( email )

Place du Maréchal de Tassigny
Paris, Cedex 16 75775
France

Jamal Atif

Université Paris Dauphine ( email )

Place du Maréchal de Tassigny
Paris, Cedex 16 75775
France

Rida Laraki

Université Paris-Dauphine, PSL Research University ( email )

Place du Maréchal de Lattre de Tassigny
Paris, 75016
France

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