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Is the Long Memory Factor Important for Extending the Fama and French Five-Factor Model: Evidence from China

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  • Yicun Li
  • Yuanyang Teng
  • Wei Shi
  • Lin Sun

Abstract

This paper proposes a new factor model, which is built upon the marriage of the Fama and French five-factor model and a long memory factor based on the monthly data of the A-share market in the Chinese stock market from January 2010 to July 2020. We first examine the explanatory power of the Fama and French five-factor model. We find strong market factor return of market (RM), size factor small minus big (SMB), and value factor high minus low (HML) but weak factor robust minus weak (RMW) and investment factor conservative minus aggressive (CMA). Then, both the Hurst exponent and the momentum factors (MOM) are added to the model to test the improvement of the explanatory power of these two new factors. We find that both the momentum factor and the Hurst exponent factor can effectively improve the explanatory power of the model. The momentum factor captures the short-term trend, but it cannot completely replace the Hurst exponent, which reflects the long memory effect.

Suggested Citation

  • Yicun Li & Yuanyang Teng & Wei Shi & Lin Sun, 2021. "Is the Long Memory Factor Important for Extending the Fama and French Five-Factor Model: Evidence from China," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-7, June.
    • Handle: RePEc:hin:jnlmpe:2133255
    DOI: 10.1155/2021/2133255
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    Cited by:

    1. Yicun Li & Yuanyang Teng, 2023. "The Fama–French Five-Factor Model with Hurst Exponents Compared with Machine Learning Methods," Mathematics, MDPI, vol. 11(13), pages 1-19, July.

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