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


Ledoit, Olivier; Wolf, Michael; Zhao, Zhao (2019). Efficient sorting: a more powerful test for cross-sectional anomalies. Journal of Financial Econometrics, 17(4):645-686.

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, Ledoit, and Wolf (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, Ledoit, and Wolf (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:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Social Sciences & Humanities > Finance
Social Sciences & Humanities > Economics and Econometrics
Uncontrolled Keywords:Cross-section of returns, dynamic conditional correlations, GARCH, Markowitz port- folio selection, nonlinear shrinkage
Language:English
Date:2019
Deposited On:26 Feb 2019 12:16
Last Modified:15 Apr 2020 23:29
Publisher:Oxford University Press
ISSN:1479-8409
OA Status:Closed
Publisher DOI:https://doi.org/10.1093/jjfinec/nby015
Related URLs:https://www.zora.uzh.ch/id/eprint/128607/

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