An Immunity-based Method for Detecting Stock Market Index Anomaly
There are many uncertain factors affecting the normal trend of the stock market index. Among them, the influence caused by the uncertain national policy is relatively larger. Statistical methods have some limits when detecting the stock market index anomaly caused by these uncertain factors. The paper makes use of the thought in the artificial immune system with the clonal selection algorithm to put forward an intelligent method that is proposed to sense anomaly automatically and identify risk. And the main factors affecting stock market index fluctuation are quantitated and coded here. Then the model can detect abnormal features through self-adaptive learning and find out potential risk of stock market exactly and timely.
Stock market index anomaly Artificial Immune System Clonal selection
ZE-JUN WU HUI-HUI QIN YI-WEN LIANG
School of Computer, Wuhan University, Luojia Mountain., Wuhan 430072, China;College of Information, College of Information, Zhongnan University of Economics and Law, Nanhu Road No. 1, Wuhan 430073, Ch School of Computer, Wuhan University, Luojia Mountain., Wuhan 430072, China
国际会议
The 1st International Conference on Risk Analysis and Crisis Response(首届风险分析与危机反应国际学术研讨会)
上海
英文
462-467
2007-09-25（万方平台首次上网日期，不代表论文的发表时间）