Market Microstructure in the Age of Machine Learning

48 Pages Posted: 11 Jun 2018

See all articles by Marcos Lopez de Prado

Marcos Lopez de Prado

Cornell University - Operations Research & Industrial Engineering; True Positive Technologies

Date Written: June 10, 2018

Abstract

In this presentation, we analyze the explanatory (in-sample) and predictive (out-of-sample) importance of some of the best known market microstructural features. Our conclusions are drawn over the entire universe of the 87 most liquid futures worldwide, covering all asset classes, going back through 10 years of tick-data history.

Keywords: Market microstructure, machine learning, feature importance, prediction, out-of-sample

JEL Classification: C02, D52, D53, G14

Suggested Citation

López de Prado, Marcos, Market Microstructure in the Age of Machine Learning (June 10, 2018). Available at SSRN: https://ssrn.com/abstract=3193702 or http://dx.doi.org/10.2139/ssrn.3193702

Marcos López de Prado (Contact Author)

Cornell University - Operations Research & Industrial Engineering ( email )

237 Rhodes Hall
Ithaca, NY 14853
United States

HOME PAGE: http://www.orie.cornell.edu

True Positive Technologies ( email )

NY
United States

HOME PAGE: http://www.truepositive.com

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