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    Title: Investment Styles and the Multiple Testing of Cross-Sectional Stock Return Predictability
    Authors: 羅秉政
    KendroVincent
    Hsu, Yu-Chin;Lin, Hsiou-Wei
    Contributors: 金融系
    Keywords: Anomalies;Cross-section of stock returns;Data-snooping bias;Multiple testing;Selective inference
    Date: 2021-11
    Issue Date: 2022-07-05 16:34:53 (UTC+8)
    Abstract: The scheme of simultaneously testing many profitable strategies may conceal the hazard of data-snooping bias. However, certain portfolio returns are also more likely to exhibit codependency because of their same investment styles. Aiming at the phenomena of stock return anomalies, we consider two multiple testing approaches: one ignores the classification of portfolios and the other utilizes such information. The results based on grouped multiple testing suggest that the implied adjusted critical values for t-statistics may vary across investment styles, and several statistically significant portfolios may be unidentified under the pooled setup.
    Relation: Journal of Financial Markets, Vol.56, pp.1-24
    Data Type: article
    DOI link: https://doi.org/10.1016/j.finmar.2020.100598
    DOI: 10.1016/j.finmar.2020.100598
    Appears in Collections:[Department of Money and Banking] Periodical Articles

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