The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Machine learning in the Chinese stock market
Open accessAbstract
We add to the emerging literature on empirical asset pricing in the Chinese stock market by building and analyzing a comprehensive set of return prediction factors using various machine learning algorithms. Contrasting previous studies for the US market, liquidity emerges as the most important predictor, leading us to closely examine the impact of transaction costs. The retail investors’ dominating presence positively affects short-term predictability, particularly for small stocks. Another feature that distinguishes the Chinese market from the US market is the high predictability of large stocks and state-owned enterprises over longer horizons. The out-of-sample performance remains economically significant after transaction costs.
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Law, finance, and economic growth in China
ALLEN, F., QIAN, J., & QIAN, M. (2005) · Journal of Financial Economics · doi:10.1016/j.jfineco.2004.06.010 · Cited by 4,446
Empirical Asset Pricing via Machine Learning
Gu, S., Kelly, B., & Xiu, D. (2020) · The Review of Financial Studies · doi:10.1093/rfs/hhaa009 · Cited by 2,545
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Maxing out: Stocks as lotteries and the cross-section of expected returns
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A Test for Superior Predictive Ability
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Organization Capital and the Cross‐Section of Expected Returns
EISFELDT, A. L., & PAPANIKOLAOU, D. (2013) · The Journal of Finance · doi:10.1111/jofi.12034 · Cited by 996
Financial statement analysis and the prediction of stock returns
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Cited by
The More, the Better? Predicting Stock Returns with Local and Global Data
Cakici, N., & Zaremba, A. (2025) · doi:10.2139/ssrn.5181449 · Cited by 2
Metadata
- Authors
- Leippold, M., Wang, Q., & Zhou, W.
- Venue
- Journal of Financial Economics
- Publisher
- Elsevier BV
- Published
- 2022-08
- Volume
- 145
- Issue
- 2
- Pages
- 64-82
- ISSN
- 0304-405X (ISSN-L)
- OpenAlex
- W3196503391
- Cited by
- 584
- References
- 35
- FWCI
- 59.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
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