Future predictions in Indian stock market through linguistic-temporal approach

Stock market is an ever changing chaotic business area where prediction plays a major role. Prediction provides knowledgeable information regarding the current status of the stock price movement. Thus this can be utilised in decision making for customers in finalizing whether to buy or sell the particular shares of a given stock. Temporal data mining has been emerged as an interesting field in providing technologies for stock forecasting. As the data of the stock market is temporal in nature effective techniques can be applied to enhance prediction analysis. Many researchers have focused on this prediction research area, but still the results are not very accurate. The paper proposes a new approach of analysing the stock market and predicting in a hybrid form of linguistic-a priori concept. It provides accurate results in stock prediction which has a great impact in decision making with respect to the clients and knowledge discovery of various useful patterns for brokers. This approach provides the clients with the ease of getting information status of any stock price movement immediately.