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In the field of quantitative finance, volatility models, such as ARCH, GARCH,FIGARCH, SV, EWMA, play the key role in risk and portfolio management.Meanwhile, factor investing is more and more famous since mid of 20 century.CAPM, Fama French three factor model, Fama French five-factor model, MSCI Barrafactor model are mentioned and developed during this period. In this paper, wewill show why we need adjust group of factors by our MAXFLAT low-passvolatility model. All of our experiments are under China's CSI 300 and CSI 500universe which represent China's large cap stocks and mid-small cap stocks. Ourresult shows adjust factors by MAXFLAT volatility model have better performancein both large cap and small cap universe than original factors or other riskadjust factors in China A share. Also the portfolio constructed by MAXFLAT riskadjust factors have continuous excess return and lower beta compare withbenchmark index.

Adjust factor with volatility model using MAXFLAT low-pass filter and construct portfolio in China A share market