Detection of False Investment Strategies Using Unsupervised Learning Methods

25 Pages Posted: 23 Apr 2018 Last revised: 7 May 2019

See all articles by Marcos Lopez de Prado

Marcos Lopez de Prado

Cornell University - Operations Research & Industrial Engineering; Abu Dhabi Investment Authority; True Positive Technologies

Michael J. Lewis

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

Date Written: August 18, 2018

Abstract

Most investment strategies uncovered by practitioners and academics are false. This partially explains the high rate of failure, especially among quantitative hedge funds (smart beta, factor investing, stat-arb, CTAs, etc.) In this paper we examine why false positives are so prevalent in finance, why researchers fail (in many cases purposely) to detect them, and why firms are able to monetize their scheme. Beyond merely pointing to this industrywide problem, we offer a practical solution. We hope that the machine learning tools presented in this paper will help financial academic journals filter out false positives, and bring up the retraction rate to reasonable levels. The SEC, FINRA and other regulatory agencies worldwide could use these tools to take a more active role in curving this rampant financial fraud. A presentation based on this paper can be found at
https://ssrn.com/abstract=3173146.

Keywords: Backtest overfitting, selection bias, multiple testing, quantitative investments, machine learning, financial fraud

JEL Classification: G0, G1, G2, G15, G24, E44

Suggested Citation

López de Prado, Marcos and López de Prado, Marcos and Lewis, Michael J., Detection of False Investment Strategies Using Unsupervised Learning Methods (August 18, 2018). Available at SSRN: https://ssrn.com/abstract=3167017 or http://dx.doi.org/10.2139/ssrn.3167017

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

Abu Dhabi Investment Authority ( email )

211 Corniche Road
Abu Dhabi, Abu Dhabi PO Box3600
United Arab Emirates

HOME PAGE: http://www.adia.ae

True Positive Technologies ( email )

NY
United States

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

Michael J. Lewis

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

New York University
New York, NY 10012
United States

Bank of America ( email )

United States

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