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Efficient Sorting: A More Powerful Test for Cross-Sectional Anomalies

Author

Listed:
  • Olivier Ledoit
  • Michael Wolf
  • Zhao Zhao

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.

Suggested Citation

  • Olivier Ledoit & Michael Wolf & Zhao Zhao, 2019. "Efficient Sorting: A More Powerful Test for Cross-Sectional Anomalies," Journal of Financial Econometrics, Oxford University Press, vol. 17(4), pages 645-686.
    • Handle: RePEc:oup:jfinec:v:17:y:2019:i:4:p:645-686.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nby015
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    Citations

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    Cited by:

    1. Ahmed, Shamim & Bu, Ziwen & Symeonidis, Lazaros & Tsvetanov, Daniel, 2023. "Which factor model? A systematic return covariation perspective," Journal of International Money and Finance, Elsevier, vol. 136(C).
    2. Christis Katsouris, 2021. "Optimal Portfolio Choice and Stock Centrality for Tail Risk Events," Papers 2112.12031, arXiv.org.
    3. De Nard, Gianluca & Zhao, Zhao, 2022. "A large-dimensional test for cross-sectional anomalies:Efficient sorting revisited," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 654-676.
    4. Gianluca De Nard & Simon Hediger & Markus Leippold, 2022. "Subsampled factor models for asset pricing: The rise of Vasa," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1217-1247, September.
    5. De Nard, Gianluca & Zhao, Zhao, 2023. "Using, taming or avoiding the factor zoo? A double-shrinkage estimator for covariance matrices," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 23-35.

    More about this item

    Keywords

    cross-section of returns; dynamic conditional correlations; GARCH; Markowitz portfolio selection; nonlinear shrinkage;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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