Portfolio Efficiency Tests with Conditioning Information - Comparing GMM and GEL Estimators

35 Pages Posted: 29 Sep 2020

See all articles by Caio Vigo Pereira

Caio Vigo Pereira

University of Kansas - Department of Economics

Márcio Laurini

University of São Paulo (USP) - Faculty of Economics, Administration and Accounting of Ribeirão Preto (FEARP)

Date Written: July 17, 2019

Abstract

We evaluate the use of Generalized Empirical Likelihood (GEL) estimators in portfolio efficiency tests for asset pricing models in the presence of conditional information. Estimators from GEL family present some optimal statistical properties, such as robustness to misspecification and better properties in finite samples. Unlike GMM, the bias for GEL estimators do not increase with the number of moment conditions included, which is expected in conditional efficiency analysis. By means of Monte Carlo experiments, we show that GEL estimators have better performance in the presence of data contaminations, especially under heavy tails and outliers. An extensive empirical analysis shows the properties of the estimators for different sample sizes and portfolios types for two asset pricing models.

Keywords: Portfolio Efficiency, Conditional Information, Efficiency Tests, GEL, GMM

JEL Classification: C12, C13, C58, G11, G12

Suggested Citation

Vigo Pereira, Caio and Laurini, Márcio, Portfolio Efficiency Tests with Conditioning Information - Comparing GMM and GEL Estimators (July 17, 2019). Available at SSRN: https://ssrn.com/abstract=3421775 or http://dx.doi.org/10.2139/ssrn.3421775

Caio Vigo Pereira (Contact Author)

University of Kansas - Department of Economics ( email )

1300 Sunnyside Drive
Lawrence, KS 66045-7585
United States

Márcio Laurini

University of São Paulo (USP) - Faculty of Economics, Administration and Accounting of Ribeirão Preto (FEARP) ( email )

Av. Bandeirantes 3900 - Monte Alegre
Ribeião Preto, 14040-900
Brazil

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