Insider trading in stock market is the trading of a corporation's stock or other securities by individuals with potential access to non-public information about the company. It exists in almost all of the stock markets around the world and is recognized as an illegal action because it may cause the unstable development of the stock market, which is denoted by the serious deviation of stocks' true value and market value. Most of the countries in the world detected insider trading mainly through great fluctuations of the stock price. However, this is very difficult to operate because of the uncertainty of noise trading. Noise trading refers to a stock trader makes his or she investing decisions only by hearsay or rumor, and it has active and reactive effect on stock price. Therefore, the price of a stock, which is involved in insider trading, is determined not only by insider traders but also noise traders. Of course, we neglect the effect of other environment. Under their effect, the stock price may rise, fall or not change. Thus, in order to understand how they affect the stock price together and support the detection work of insider trading better, ontology based framework, for investigating the relationships between insider trading, noise trading and stock price fluctuation is proposed. Until now, there are no researches using ontology to explore how insider trading and noise trading affect a stock price, and this paper supports a new angle to recognize insider trading. Besides the parts of introduction and related work, this paper mainly contains three parts.
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