A Practical Solution to the Multiple-Testing Crisis in Financial Research (Presentation Slides)

30 Pages Posted: 18 May 2018 Last revised: 29 May 2018

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

Date Written: May 16, 2018

Abstract

Most discoveries in empirical finance are false, as a consequence of selection bias under multiple testing. This may explain why so many hedge funds fail to perform as advertised or as expected, particularly in the quantitative space. These false discoveries may have been prevented if academic journals and investors demanded that any reported investment performance incorporates the false positive probability, adjusted for selection bias under multiple testing.

In this presentation, we demonstrate how this adjusted false positive probability can be computed and reported for public consumption.

The full paper can be downloaded at http://ssrn.com/abstract=3177057

Keywords: Backtest overfitting, selection bias, multiple testing, quantitative investments, machine learning, financial fraud, smart beta, factor investing

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

Suggested Citation

López de Prado, Marcos and López de Prado, Marcos, A Practical Solution to the Multiple-Testing Crisis in Financial Research (Presentation Slides) (May 16, 2018). Available at SSRN: https://ssrn.com/abstract=3179826 or http://dx.doi.org/10.2139/ssrn.3179826

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

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