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Building Diversified Portfolios That Outperform Out-of-Sample (Presentation Slides)

33 Pages Posted: 11 Jan 2016 Last revised: 14 Aug 2016

Marcos Lopez de Prado

Lawrence Berkeley National Laboratory; Guggenheim Partners; Harvard University

Date Written: January 10, 2016

Abstract

Mean-Variance portfolios are optimal in-sample, however they tend to perform poorly out-of-sample (even worse than the 1/N naïve portfolio!) We introduce a new portfolio construction method that substantially improves the Out-Of-Sample performance of diversified portfolios.

The full paper is available at: http://ssrn.com/abstract=2708678.

Keywords: Risk parity, tree graph, cluster, dendogram, linkage, metric space

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

Suggested Citation

Lopez de Prado, Marcos, Building Diversified Portfolios That Outperform Out-of-Sample (Presentation Slides) (January 10, 2016). Available at SSRN: https://ssrn.com/abstract=2713516 or http://dx.doi.org/10.2139/ssrn.2713516

Marcos Lopez de Prado (Contact Author)

Lawrence Berkeley National Laboratory ( email )

1 Cyclotron Road
Berkeley, CA 94720
United States

HOME PAGE: http://www.lbl.gov

Guggenheim Partners ( email )

330 Madison Avenue
New York, NY 10017
United States

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

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

HOME PAGE: http://www.rcc.harvard.edu

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