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

机译:长记忆因子对扩展法玛和法国五因素模型重要吗:来自中国的证据

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摘要

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.
机译:本文基于2010年1月至2020年7月中国股市A股市场的月度数据,在Fama和法国五因素模型和长记忆因子的结合基础上,提出了一种新的因子模型。我们首先考察了Fama和法国五因素模型的解释力。我们发现市场因子回报率(RM)强劲,规模因子小减大(SMB),价值因子高减低(HML),但弱因子稳健减弱(RMW),投资因子保守减进(CMA)。然后,将Hurst指数和动量因子(MOM)加入模型中,以检验这两个新因子的解释力的提高。我们发现动量因子和Hurst指数因子都能有效提高模型的解释力。动量因子捕捉了短期趋势,但不能完全取代赫斯特指数,这反映了长期记忆效应。

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