Abstract: Data mining and predictive technologies developed using computer automated programs do a fair amount of trade in the market. Historic data holds the essential memory for predicting the future direction, is a well-founded theory about data mining. One way of predicting if future stocks prices will increase or decrease is Data Analysis. This technology is designed to help investors discover hidden patterns from the historic data that have probable predictive capability in their investment decisions. A challenging task of financial time series prediction is the prediction of the pricess of financial stock markets. Five methods of analyzing stocks were combined to predict if the day’s closing price would increase or decrease. These methods were Typical Price (TP), Bollinger Bands, Relative Strength Index (RSI), CMI and Moving Average (MA). This paper discussed various techniques which are able to predict with future closing stock price will increase or decrease better than level of significance. Also, it investigated various global events and their issues predicting on stock markets. It supports numerically and graphically.
Keywords: Data mining, Data analysis, TP, RSI, CMI, MA.