An Discrimination Research on Insider Trading and Market Manipulation inChinese Security Market based on Probabilistic Neural Network

摘要

The discrimination and supervision of insider trading and market manipulation is very hard because of the cover-up used and the large trading data. So this paper firstly analyses the impact of insider trading and market manipulation on the security market. Based on it, we set up the discrimination model with probabilistic neural network, and use it to discriminate the insider trading and market manipulation in Chinese security market. The result shows that the model set up in this paper performs quite well. Compared with Logistic model, it is easier to design and practice. And its discrimination accuracy is apparently higher than other models.