Abstract
This contribution presents the application of Dempster-Shafer theory to the prediction of China’s stock market. To be specific, we predicted the most promising industry in the next month every trading day. This prediction can help investors to select stocks, but is rarely seen in previous literatures. Instead of predicting the fluctuation of the stock market from scratch all by ourselves, we fused ratings of 44 industries from China’s securities companies using Shafer’s evidence theory. Our preliminary experiment is a daily prediction since 2012-05-02 with ratings published 10 days before that day. Our predicted industries have an average rank of 19.85 in earnings, 11.8% better than random guessing (average rank is 22.5). The average rise rate of predicted industries in a month is 0.59%, 0.86% higher than overall (which is -0.274%), and nearly 0.7% higher than simple voting (which is -0.097%). Our predictions are posted on Weibo every day since 2014-04-28.
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Xu, Y., Wu, L., Wu, X., Xu, Z. (2014). Belief Fusion of Predictions of Industries in China’s Stock Market. In: Cuzzolin, F. (eds) Belief Functions: Theory and Applications. BELIEF 2014. Lecture Notes in Computer Science(), vol 8764. Springer, Cham. https://doi.org/10.1007/978-3-319-11191-9_38
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DOI: https://doi.org/10.1007/978-3-319-11191-9_38
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