An Discrimination Research on Insider Trading and Market Manipulation in Chinese Security Market based on Probabilistic Neural Network
The discrimination and supervision of insider trading and market manipulation is very bard 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.
insider trading market manipulation probabilistic neural network discrimination analysis
MA Zheng-xin ZHANG Wei
School of Management Tianjin University Tianjin, China Shool of Management Tianjin University Tianjin, China
国际会议
成都
英文
116-119
2010-07-09(万方平台首次上网日期,不代表论文的发表时间)