Financial Time Series Based On Fuzzy Clustering Strength Of The Reaction Of The Public Information

In the nature, many things are in development and change. If these changes are recorded according to the order of time, so we can get all kinds of time sequence. In securities market, many data are produces everyday. These data are recorded as financial time series. Through analyzing the time sequence. we can get some inspiration, which have important signification for the financial markets.Fuzzy clustering has rapidly flourished based in the fuzzy set theory. It made a lot of typical fuzzy clustering algorithm, but fuzzy C means clustering algorithm is the most typical and popular. Fuzzy C means clustering (FCM) algorithm is a classical fuzzy clustering analysis, the algorithm has been effectively used in data mining, pattern recognition, computer vision and decision support. It is important in theoretical and practical. Fuzzy clustering express the intermediary class and it can objectively reflect the real world. Fuzzy clustering analysis has become the mainstream of clustering technology.Public information is very important; the impact of public information on the stock market has become very important. Macroeconomic policy is typical public information, and is closely related with the stock market. It is very important on macroeconomic indicators, economic policy and analysis of the quantitative relationship. It can get the accurate information interaction between macroeconomic and stock market. The responses for stock price information are very important. At the same time, the prices of securities to the public information response characteristics should be analysis.The efficient markets hypothesis (EMH) maintains that market prices fully reflect all available information such as public or private information. Therefore, the study of analyzing the reaction of stock price to the information has attracted more and more attention. Here we proposed an effective measuring method using fuzzy c-means (FCM) for describing the reaction to public information, and further analyzing and quantify the intensity. Taking the deposit reserve rate, a kind of typical public information, as an example, the clustering results show that there are there prominent characters of reaction in Shanghai A-share market. Furthermore, the empirical results indicate that the clustering technique has a good effect in classifying the intensity of reaction of stock market to public information.