| Data mining can extract implied in it, people do not know in advance, but it ispotentially useful information and knowledge of the process, from a large number, incomplete,noisy, fuzzy and random data. The progress of Data’s generation and collection technology topromote commercial and scientific research have a lot of data sets, people accumulate moreand more data. Many important information hide behind vast amounts of data, people crave toa higher level analysis to known information or data, in order to make better use of these data.So the data mining technology will play a more important role in the development oftechnology in the future. In this paper, using the data mining technology, mining the pricechange rule behind in huge amounts of data from the securities industry, the main researchcontents are as follows:First of all, using association rules in data mining technology analyzes stock tradingdata, according to the characteristics of the transaction data put forward the corresponding ofdata mining model, mining the association rules which based APRIORI algorithm. Byconducting the preprocessing of data, structuring analysis indicators, and using the APRIORIalgorithm mine the correlation between the stock prices of listed companies. Through theanalysis of the results showed that: it is effective feasible for using the association rules toanalyzing the stock trading data. Provide meaningful reference value for the portfolio ofInvestors.Then, based on the principle of time series analysis, according to the characteristics ofthe stock data, use ARIMA model to analyze and forecast the history data of stock trading,they are concluded that the change rule of stock in the historical period, and predict the futureprice trend, It is successfully for the time series applied to the prediction of stock price trendand achieved certain results, analyze the price of the stock charts, mining the appropriate investment point in time. Provide a certain theoretical basis for investors. |
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