Discrimination of China´s stock price manipulation based on primary component analysis

The behaviors of Price manipulation in stock markets have largely distorted stock prices, undermining the interests of small and medium investors. It is of great importance to the future development of stock markets that such activities be discriminated and prevented. After analyzing the characteristics of stock price manipulations, this paper establishes a logistic regression model for the discrimination of stock price manipulations by selecting Shanghai and Shenzhen stock markets as examples and by using significant indicators of stock price manipulation based on Primary Component Analysis. This model has a higher level of significance and a higher success rate of prediction than previous models.