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Type | Working Paper |
Scope | Discipline-based scholarship |
Title | Efficient sorting: a more powerful test for cross-sectional anomalies |
Organization Unit | |
Authors |
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Language |
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Institution | University of Zurich |
Series Name | Working paper series / Department of Economics |
Number | 238 |
ISSN | 1664-7041 |
Number of Pages | 51 |
Date | 2018 |
Abstract Text | 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. |
Official URL | http://www.econ.uzh.ch/static/wp/econwp238.pdf |
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PDF File | Download from ZORA |
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Keywords | Cross-section of returns, dynamic conditional correlations, GARCH, Markowitz portfolio selection, nonlinear shrinkage, Portfoliomanagement, Aktienrendite, Matrizenrechnung, Schätzung, Prognosemodell, Kovarianzmatrix, Portfolio Selection, t-Test |
Additional Information | Revised version ; Former titles: Beyond sorting: a more powerful test for cross-sectional anomalies ; Efficient weighting: a more powerful test for cross-sectional anomalies |