Firm Characteristics and Chinese Stocks |
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| Institution: | 1. School of Finance, Central University of Finance and Economics, Beijing 100081, China; jfuwei@gmail.com;2. College of Finance and Statistics, Hunan University, Changsha 410006, China;3. Olin Business School, Washington University in St. Louis, St. Louis, MO 63130, USA; zhou@wustl.edu;4. China Academy of Financial Research, Shanghai Advanced Institute of Finance, Shanghai 200000, China |
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| Abstract: | This paper presents 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 the “big-data” econometric methods: principal component analysis (PCA), partial least squares (PLS), and forecast combination to extract information from all the 75 firm characteristics. These characteristics are important return predictors, with statistical and economic significance. Furthermore, firm characteristics that are related to trading frictions, momentum, and profitability are the most effective predictors of future stock returns in the Chinese stock market. |
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| Keywords: | Partial least squares Machine learning Firm characteristics Chinese stock market Return predictability |
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