A study of cross-industry return predictability in the Chinese stock market
研究上海和深圳股市的跨行业收益可预测性，发现石油、电信和金融行业收益能预测其他行业，基于LASSO的OLS估计在样本外预测中表现最佳，多空策略年均超额收益13%。
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%.