Download this Paper Open PDF in Browser

Classification-Based Financial Markets Prediction Using Deep Neural Networks

Algorithmic Finance, 2016.

20 Pages Posted: 30 Mar 2016 Last revised: 9 Dec 2016

Matthew Francis Dixon

Illinois Institute of Technology - Stuart School of Business, IIT

Diego Klabjan

Northwestern University

Jin Hoon Bang

Northwestern University

Date Written: July 18, 2016

Abstract

Deep neural networks (DNNs) are powerful types of artificial neural networks (ANNs) that use several hidden layers. They have recently gained considerable attention in the speech transcription and image recognition community for their superior predictive properties including robustness to over fitting. However their application to algorithmic trading has not been previously researched, partly because of their computational complexity. This paper describes the application of DNNs to predicting financial market movement directions. In particular we describe the configuration and training approach and then demonstrate their application to back testing a simple trading strategy over 43 different Commodity and FX future mid-prices at 5-minute intervals. All results in this paper are generated using a C implementation on the Intel Xeon Phi co-processor which is 11.4x faster than the serial version and a Python strategy back testing environment both of which are available as open source code written by the authors.

Keywords: Deep Neural Networks, Algorithmic Trading, Commodity Futures, FX Futures

JEL Classification: C45, G1

Suggested Citation

Dixon, Matthew Francis and Klabjan, Diego and Bang, Jin Hoon, Classification-Based Financial Markets Prediction Using Deep Neural Networks (July 18, 2016). Algorithmic Finance, 2016.. Available at SSRN: https://ssrn.com/abstract=2756331

Matthew Francis Dixon (Contact Author)

Illinois Institute of Technology - Stuart School of Business, IIT ( email )

10 West 35th Street, 18th Floor
Chicago, IL 60616
United States

Diego Klabjan

Northwestern University ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

Jin Hoon Bang

Northwestern University ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

Paper statistics

Downloads
5,270
Rank
1,048
Abstract Views
12,397