Generalized Hypothesis Testing and Maximizing the Success Probability in Financial Markets

8 Pages Posted: 12 Jul 2013

See all articles by Tim Leung

Tim Leung

University of Washington - Department of Applied Math

Qingshuo Song

City University of Hong Kong (CityU)

Jie Yang

University of Illinois at Chicago

Date Written: October 11, 2011

Abstract

We study the generalized composite pure and randomized hypothesis testing problems. In addition to characterizing the optimal tests, we examine the conditions under which these two hypothesis testing problems are equivalent, and provide counterexamples when they are not. This analysis is useful for portfolio optimization to maximize some success probability given a fixed initial capital. The corresponding dual is related to a pure hypothesis testing problem which may or may not coincide with the randomized hypothesis testing problem. Our framework is applicable to both complete and incomplete market settings.

Keywords: hypothesis testing

JEL Classification: G10

Suggested Citation

Leung, Tim and Song, Qingshuo and Yang, Jie, Generalized Hypothesis Testing and Maximizing the Success Probability in Financial Markets (October 11, 2011). Available at SSRN: https://ssrn.com/abstract=2292771 or http://dx.doi.org/10.2139/ssrn.2292771

Tim Leung

University of Washington - Department of Applied Math ( email )

Lewis Hall 217
Department of Applied Math
Seattle, WA 98195
United States

HOME PAGE: http://faculty.washington.edu/timleung/

Qingshuo Song (Contact Author)

City University of Hong Kong (CityU) ( email )

Kowloon Tong
Hong Kong

Jie Yang

University of Illinois at Chicago ( email )

1200 W Harrison St
60607

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