Stock Market Crisis Early Warning Model Based on Network Information Text Mining

Jian Li, Junfeng Guo · 2020

In order to improve the accuracy of stock market crisis warning model. This paper proposes a stock market crisis early warning model based on network information text mining. Firstly, the method introduces network information variables and uses principal component analysis to reduce dimension. Then, BP neural network based on particle swarm optimization is used to establish and optimize the stock market crisis warning model. Compared with the traditional method, the new method has higher warning effect.

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