Assistant Professor, Alliance University-Bangalore
Online published on 11 April, 2016.
In a common parlance, analysing or evaluating a company‘s stock and stock prices is most erratic and unpredictable. The reason for difficulty in predicting stock prices are its correlation with many macroeconomic variables like economic growth, Inflation, exchange rate, political stability etc… It may be difficulty in terms of above said exogenous methods but endogenous method has certain relevancy in predicting stock prices. This study uses most relevant endogenous method called data mining technique to evaluate its effectiveness in predicting stock prices. Data mining is well founded on the theory that the historic data holds the essential memory for predicting the future direction. Data mining technology helps everyone in knowing the hidden patterns in the data of the stocks and thus helps them in their investment decisions. Thus the prediction of stock marketing has always been challenging. In this connection, this study uses Moving Average, Typical Price, Chaikin Money Flow Indicator, Bollinger Bands and Relative Strength Index to analyse the stock market.
Stock Market, Data Mining, Investment strategies, Forecasting Stock prices, Data mining Techniques, Data Classification