Firm Characteristics and Chinese Stocks
41 Pages Posted: 19 Jul 2018
Date Written: May 30, 2018
This paper conducts a comprehensive study on predicting the cross section of Chinese stock market returns with a large panel of 75 individual firm characteristics. We use not only the traditional Fama-MacBeth regression, but also “big-data” econometric methods: principal component analysis (PCA), the partial least squares (PLS) and forecast combination to extract information from all of the 75 firm characteristics. We find the firm characteristics are important predictors, significant both statistically and economically. In addition, the recent developed PLS performs the best. Our empirical results further indicate that those firm characteristics that are related to trading frictions, momentum, and profitability are the most effective predictors for future stock returns in the Chinese stock market.
Keywords: Partial Least Square, Firm Characteristics, Systematic Factor, Chinese Stock Market
JEL Classification: G12, G14
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