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

Yicun Li,Lin Sun,Yuanyang Teng,Wei Shi,Wen-Tsao Pan

doi:10.1155/2021/2133255

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.

Highlights

In the field of quantitative investment, factor models have always attracted much attention
robust minus weak (RMW) and small minus big (SMB) take a proportion about 50%, and the result is consistent with the five-factor model, which shows that the newly added momentum factor (MOM) and Hurst exponent have a certain degree of substitution to the five-factor model. e Hurst exponent has a certain effect, and it often appears in the model at the same time as MOM
Choosing the AIC criterion as the criterion for model selection, we get the average value of r square in the five-factor model, which is equal to 0.4002. e most efficient factor is the market factor, and conservative minus aggressive (CMA) performances are the weakest

Summary

Introduction

In the field of quantitative investment, factor models have always attracted much attention. Researchers study the differences of Hurst exponent estimation methods and incorporate the Hurst exponent’s long memory interpretation of time series into the factor model and compare it with the momentum factor. We will analyze the explanatory power of the Hurst exponent factor based on the Fama and French five-factor model and estimate Hurst exponent by two methods to test the results for robustness. En, we will fully compare the performance of Hurst exponent and momentum factor on model improvement and test the momentum effect and long memory of the time series in the Chinese capital market.

Five-Factor Model and Hurst Exponent

Empirical Application

Findings

Conclusions