Reinforcement Learning for Automatic Financial Trading: Introduction and Some Applications

15 Pages Posted: 21 Dec 2012

See all articles by Francesco Bertoluzzo

Francesco Bertoluzzo

Ca Foscari University of Venice

Marco Corazza

Ca Foscari University of Venice - Dipartimento di Economia

Date Written: December 3, 2012

Abstract

The construction of automatic Financial Trading Systems (FTSs) is a subject of research of high interest for both academic environment and financial one due to the potential promises by self-learning methodologies and by the increasing power of actual computers. In this paper we consider Reinforcement Learning (RL) type algorithms, that is algorithms that optimize their behavior in relation to the responses they get from the environment in which they operate, without the need for a supervisor. In particular, first we introduce the essential aspects of RL which are of interest for our purposes, then we present some original automatic FTSs based on differently configured RL algorithms and apply such FTSs to artificial and real time series of daily financial asset prices.

Keywords: Financial Trading System, Reinforcement Learning, Stochastic control, Q-learning algorithm, Kernel-based Reinforcement Learning

JEL Classification: C61, C63, D83, G11

Suggested Citation

Bertoluzzo, Francesco and Corazza, Marco, Reinforcement Learning for Automatic Financial Trading: Introduction and Some Applications (December 3, 2012). University Ca' Foscari of Venice, Dept. of Economics Research Paper Series No. 33/WP/2012, Available at SSRN: https://ssrn.com/abstract=2192034 or http://dx.doi.org/10.2139/ssrn.2192034

Francesco Bertoluzzo

Ca Foscari University of Venice ( email )

Dorsoduro 3246
Veneto 30123

Marco Corazza (Contact Author)

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

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