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A study of data-driven momentum and disposition effects in the Chinese stock market by functional data analysis

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  • Ruanmin Cao

    (CITIC Securities Co., Ltd.)

  • Lajos Horváth

    (University of Utah)

  • Zhenya Liu

    (Renmin University of China
    Aix-Marseille University)

  • Yuqian Zhao

    (University of Waterloo)

Abstract

We apply a functional data analysis approach to decompose the cross-sectional Fama–French three-factor model residuals in the Chinese stock market. Our results indicate that other than Fama–French three factors, there are two orthonormal asset pricing factors describing the behavioral biases in their historical performances: between winner and loser stocks, and extreme and mediocre-performing stocks, respectively. We explain these two factors through investors’ overreaction, overconfidence and the lead-lag effect. These findings empirically show the existence of momentum and disposition effects in the Chinese stock market. A buy-and-hold mean-variance optimized portfolio incorporating these two market anomalies boosts the Sharpe ratio to 1.27 .

Suggested Citation

  • Ruanmin Cao & Lajos Horváth & Zhenya Liu & Yuqian Zhao, 2020. "A study of data-driven momentum and disposition effects in the Chinese stock market by functional data analysis," Review of Quantitative Finance and Accounting, Springer, vol. 54(1), pages 335-358, January.
  • Handle: RePEc:kap:rqfnac:v:54:y:2020:i:1:d:10.1007_s11156-019-00791-x
    DOI: 10.1007/s11156-019-00791-x
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    3. Zhao, Yuqian, 2021. "Validating intra-day risk premium in cross-sectional return curves," Finance Research Letters, Elsevier, vol. 43(C).
    4. Mohamed S. Ahmed & John A. Doukas, 2021. "Revisiting disposition effect and momentum: a quantile regression perspective," Review of Quantitative Finance and Accounting, Springer, vol. 56(3), pages 1087-1128, April.

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    More about this item

    Keywords

    Momentum effect; Disposition effect; Functional principal component analysis; Portfolio selection; Chinese stock market;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G40 - Financial Economics - - Behavioral Finance - - - General

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