Research on the components of CSI300: Perspective from quantitive finance
DOI:
https://doi.org/10.54691/bcpbm.v30i.2504Keywords:
single factor analysis; Fama-Macbeth regression analysis; quantitative investment analysis; turnover rate; change ratio; capital debt ratio.Abstract
This paper takes Shanghai and Shenzhen 300 component stocks as the research object. Specifically, this paper selects stock market data, risk data and corporate financial data from March 2020 to March 2022 for quantitative investment research, in order to obtain effective influencing factors to explain excess returns and obtain timeliness and positive investment returns. The empirical process is summarized as follows. Firstly, the factor data obtained from CSMAR are analyzed by time series single factor combination analysis to obtain three effective influencing factors: turnover rate, fluctuation and capital debt ratio. Then, Fama-MacBeth regression is carried out to verify the independent influencing factors and whether there is interaction. The regression results show that the intercept and coefficient are relatively obvious, these three factors have a good explanation effect on the stock excess return.
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