Minimizing Shortfall

Quantitative Finance, Forthcoming

21 Pages Posted: 3 Feb 2011 Last revised: 22 Sep 2016

See all articles by Lisa R. Goldberg

Lisa R. Goldberg

University of California, Berkeley; Aperio Group

Michael Y. Hayes

MSCI Inc.

Ola Mahmoud

University of California, Berkeley; University of Zurich

Date Written: January 26, 2013

Abstract

This paper describes an empirical study of shortfall optimization with Barra Extreme Risk. We compare minimum shortfall to minimum variance portfolios in the US, UK, and Japanese equity markets using Barra Style Factors (Value, Growth, Momentum, etc.). We show that minimizing shortfall generally improves performance over minimizing variance, especially during down-markets, over the period 1985-2010. The outperformance of shortfall is due to intuitive tilts towards protective factors like Value, and away from aggressive factors like Growth and Momentum. The outperformance is largest for the shortfall that measures overall asymmetry rather than the extreme losses

Keywords: empirical study, shortfall, optimization, Barra, Extreme Risk minimum, shortfall minimum, variance portfolios, US, UK, Japanese equity markets, Barra, Style Factors, Value Growth Momentum measures overall asymmetry

Suggested Citation

Goldberg, Lisa R. and Hayes, Michael Y. and Mahmoud, Ola, Minimizing Shortfall (January 26, 2013). Quantitative Finance, Forthcoming. Available at SSRN: https://ssrn.com/abstract=1754021 or http://dx.doi.org/10.2139/ssrn.1754021

Lisa R. Goldberg (Contact Author)

University of California, Berkeley ( email )

Department of Statistics
367 Evans Hall
Berkeley, CA 94720-3860
United States

Aperio Group ( email )

3 Harbor Drive
Suite 315
Sausalito, CA 94965
United States

Michael Y. Hayes

MSCI Inc. ( email )

2100 Milvia St.
Berkeley, CA 94704
United States

Ola Mahmoud

University of California, Berkeley ( email )

Center for Risk Management Research
Evans Hall
Berkeley, CA 94720
United States

University of Zurich ( email )

Schönberggasse 1
Zürich, 8001
Switzerland

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