Detection of False Investment Strategies through FWER and FDR (Seminar Slides)

30 Pages Posted: 1 Apr 2021 Last revised: 9 May 2022

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: March 8, 2021

Abstract

Financial systems rarely allow experimentation. For example, we cannot reproduce the flash crash of 2010 while controlling for environmental conditions. As a result, much financial research relies on the statistical analysis of finite (historical) datasets, where: (a) Time series datasets are limited, and (b) The investment universe is limited.

The implication is that a large number of hypotheses are tested on the same observations. In the context of asset management, this situation leads to false investment strategies and losses, particularly among quantitative funds.

This seminar explains how to detect false investment strategies by controlling for the familywise error rate (FWER) and the false discovery rate (FDR) of an organization. It is part of Cornell University's ORIE 5256 course.

Keywords: Multiple testing, p-values, p-hacking, selection bias, familywise error rate, false discovery rate

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

Suggested Citation

López de Prado, Marcos and López de Prado, Marcos, Detection of False Investment Strategies through FWER and FDR (Seminar Slides) (March 8, 2021). Available at SSRN: https://ssrn.com/abstract=3799803 or http://dx.doi.org/10.2139/ssrn.3799803

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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