Modern Perspectives on Reinforcement Learning in Finance

The Journal of Machine Learning in Finance, Vol. 1, No. 1, 2020.

28 Pages Posted: 16 Sep 2019 Last revised: 16 Mar 2021

See all articles by Petter N. Kolm

Petter N. Kolm

New York University (NYU) - Courant Institute of Mathematical Sciences

Gordon Ritter

New York University (NYU) - Courant Institute of Mathematical Sciences; City University of New York (CUNY) - Weissman School of Arts and Sciences; Rutgers, The State University of New Jersey - Financial Statistics & Risk Management; New York University (NYU) - NYU Tandon School of Engineering

Date Written: September 6, 2019

Abstract

We give an overview and outlook of the field of reinforcement learning as it applies to solving financial applications of intertemporal choice. In finance, common problems of this kind include pricing and hedging of contingent claims, investment and portfolio allocation, buying and selling a portfolio of securities subject to transaction costs, market making, asset liability management and optimization of tax consequences, to name a few. Reinforcement learning allows us to solve these dynamic optimization problems in an almost model-free way, relaxing the assumptions often needed for classical approaches.

A main contribution of this article is the elucidation of the link between these dynamic optimization problem and reinforcement learning, concretely addressing how to formulate expected intertemporal utility maximization problems using modern machine learning techniques.

Keywords: Dynamic programming, Finance, Hedging, Intertemporal choice; Investment analysis, Machine learning, Optimal control, Options, Portfolio optimization, Reinforcement learning

JEL Classification: G11, C61

Suggested Citation

Kolm, Petter N. and Ritter, Gordon, Modern Perspectives on Reinforcement Learning in Finance (September 6, 2019). The Journal of Machine Learning in Finance, Vol. 1, No. 1, 2020. , Available at SSRN: https://ssrn.com/abstract=3449401 or http://dx.doi.org/10.2139/ssrn.3449401

Petter N. Kolm (Contact Author)

New York University (NYU) - Courant Institute of Mathematical Sciences ( email )

251 Mercer Street
New York, NY 10012
United States

Gordon Ritter

New York University (NYU) - Courant Institute of Mathematical Sciences ( email )

New York University
251 Mercer Street
New York, NY 10012
United States

City University of New York (CUNY) - Weissman School of Arts and Sciences ( email )

One Bernard Baruch Way
New York, NY 10010
United States

Rutgers, The State University of New Jersey - Financial Statistics & Risk Management ( email )

110 Frelinghuysen Road
479 Hill Center, Busch Campus
Piscataway, NJ 08854
United States

New York University (NYU) - NYU Tandon School of Engineering ( email )

6 MetroTech Center
Brooklyn, NY 11201
United States

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