A study of cross-industry return predictability in the Chinese stock market

Michael Ellington, Michalis P. Stamatogiannis and Yawen Zheng

International Review of Financial Analysis, 2022, vol. 83, issue C

Abstract: We investigate cross-industry return predictability for the Shanghai and Shenzhen stock exchanges, by constructing 6- and 26- industry portfolios. The dominance of retail investors in these markets, in conjunction with the gradual diffusion of information hypothesis provide the theoretical background that allows us to employ machine learning methods to test for cross-industry predictability. We find that Oil, Telecommunications and Finance industry portfolio returns are significant predictors of other industries. Our out-of-sample forecasting exercise shows that the OLS post-LASSO estimation outperforms a variety of benchmarks and a long–short trading strategy generates an average annual excess return of 13%.

Keywords: Return predictability; Shrinkage; LASSO; Model selection; Industry portfolio (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 C55 G14 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:83:y:2022:i:c:s1057521922002071

DOI: 10.1016/j.irfa.2022.102249

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