Ambiguity Aversion and Portfolio Efficiency Tests

40 Pages Posted: 18 Apr 2019

See all articles by Valery Polkovnichenko

Valery Polkovnichenko

Board of Governors of the Federal Reserve System

Hui Wang

Bentley University - Department of Finance

Date Written: June 2018

Abstract

Testing portfolio alpha against a linear factor model can be interpreted as a mean-variance efficiency test of the optimal portfolio of factors. For ambiguity neutral investor, adding active portfolio with statistically significant alpha always implies efficiency gain relative to the optimal portfolio of factors. In contrast, for ambiguity averse investor, the efficiency gain must be above a threshold which depends on the uncertainty about the factors' and active portfolio's expected returns. Building on the theoretical framework developed in Garlappi, Uppal and Wang (2007), we propose a new method to test portfolio efficiency relative to a factor model by using asset exclusion conditions from the optimal portfolio of the ambiguity averse investor. The asset exclusion threshold is an F-statistic that is non-redundant with significance of alpha under the ambiguity-neutral test. Active portfolios with statistically significant alpha but weak efficiency gain may be excluded from the optimal portfolio. We apply this criterion empirically to screen active portfolios ("anomalies'') and find that some anomalies do not pass our exclusion test under statistically reasonable ambiguity about their expected return.

Keywords: ambiguity, portfolio efficiency test

JEL Classification: G11

Suggested Citation

Polkovnichenko, Valery and Wang, Hui, Ambiguity Aversion and Portfolio Efficiency Tests (June 2018). Available at SSRN: https://ssrn.com/abstract=3357088 or http://dx.doi.org/10.2139/ssrn.3357088

Valery Polkovnichenko (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

Hui Wang

Bentley University - Department of Finance ( email )

175 Forest St
Waltham, MA 02452
United States

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