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Efficient weighting: a more powerful test for cross-sectional anomalies


Ledoit, Olivier; Wolf, Michael; Zhao, Zhao (2018). Efficient weighting: a more powerful test for cross-sectional anomalies. Working paper series / Department of Economics 238, University of Zurich.

Abstract

Many researchers seek factors that predict the cross-section of stock returns. The standard methodology sorts stocks according to their factor scores into quantiles and forms a corresponding long-short portfolio. Such a course of action ignores any information on the covariance matrix of stock returns. Historically, it has been difficult to estimate the covariance matrix for a large universe of stocks. We demonstrate that using the recent DCC-NL estimator of Engle et al. (2017) substantially enhances the power of tests for cross-sectional anomalies: On average, 'Student' t-statistics more than double.

Abstract

Many researchers seek factors that predict the cross-section of stock returns. The standard methodology sorts stocks according to their factor scores into quantiles and forms a corresponding long-short portfolio. Such a course of action ignores any information on the covariance matrix of stock returns. Historically, it has been difficult to estimate the covariance matrix for a large universe of stocks. We demonstrate that using the recent DCC-NL estimator of Engle et al. (2017) substantially enhances the power of tests for cross-sectional anomalies: On average, 'Student' t-statistics more than double.

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Additional indexing

Item Type:Working Paper
Communities & Collections:03 Faculty of Economics > Department of Economics
Working Paper Series > Department of Economics
Dewey Decimal Classification:330 Economics
JEL Classification:C13, C58, G11
Uncontrolled Keywords:Cross-section of returns, dynamic conditional correlations, GARCH, Markowitz portfolio selection, nonlinear shrinkage
Language:English
Date:February 2018
Deposited On:06 Dec 2016 15:20
Last Modified:20 Feb 2018 08:52
Series Name:Working paper series / Department of Economics
Number of Pages:50
ISSN:1664-7041
Additional Information:Revised version ; Former title: Beyond sorting: a more powerful test for cross-sectional anomalies
OA Status:Green
Official URL:http://www.econ.uzh.ch/static/wp/econwp238.pdf
Related URLs:http://www.econ.uzh.ch/static/workingpapers.php

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