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01426nam a2200217Ia 4500 |
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10.3724-SP.J.1383.304014 |
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220706s2018 CNT 000 0 und d |
| 020 |
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|a 20962320 (ISSN)
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| 245 |
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|a Firm Characteristics and Chinese Stocks
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| 260 |
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|b KeAi Communications Co.
|c 2018
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| 856 |
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|z View Fulltext in Publisher
|u https://doi.org/10.3724/SP.J.1383.304014
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|a 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. © 2019 Elsevier B.V.
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|a Chinese stock market
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|a Firm characteristics
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|a Machine learning
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| 650 |
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|a Partial least squares
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| 650 |
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|a Return predictability
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| 700 |
1 |
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|a Jiang, F.
|e author
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1 |
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|a Tang, G.
|e author
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| 700 |
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|a Zhou, G.
|e author
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| 773 |
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|t Journal of Management Science and Engineering
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