Decomposing anomalies
Sabri Boubaker,
Bo Li,
Zhenya Liu and
Yifan Zhang
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Bo Li: Beijing International Studies University
Zhenya Liu: Renmin University of China = Université Renmin de Chine, CERGAM - Centre d'Études et de Recherche en Gestion d'Aix-Marseille - AMU - Aix Marseille Université - UTLN - Université de Toulon
Yifan Zhang: Renmin University of China = Université Renmin de Chine
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Abstract:
This paper introduces the functional principal component analysis approach for decomposing the panel returns of the anomaly-sorted portfolios. Using the US stock market data covering July 1963–July 2020, our findings indicate that the Fama–French (F–F) market factor can be captured by the first empirical functional principal component in the time-series. For the other F–F anomalies, market capitalization (Size), book-to-market ratio (B/M), profitability (OP), investment (Inv), and price momentum (Mom), the cross-sectional features remain in the monotonicity of the second principal component and in the curvature of the third principal component. Furthermore, a time-varying framework shows two neglected reversals of the F–F anomalies Inv and Size in the 1970s and the 1980s.
Keywords: Asset pricing; Anomaly variable; Factor model; Functional principal component analysis; Eigenfunction (search for similar items in EconPapers)
Date: 2021-05-01
Note: View the original document on HAL open archive server: https://hal.science/hal-03323669v1
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Citations: View citations in EconPapers (2)
Published in Economics Letters, 2021, 202, pp.109835. ⟨10.1016/j.econlet.2021.109835⟩
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03323669
DOI: 10.1016/j.econlet.2021.109835
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