Paper Title
Indian Stock Price Prediction using Diverse Approach of Rule based Algorithm and Fiscal News Articles

Abstract
Nowadays, the most significant challenges in the stock market is to predict the stock prices. In any country stock market is one of the most emerging sectors. Nowadays, many people are indirectly or directly related to this sector. Therefore, it becomes essential to know about market trends. This research examines and analyzes the use of artificial neural networks as a prediction tool. Specifically a neural network's ability to predict future trends of Stock Market Indices is tested. Accuracy is compared against a traditional forecasting method. While only briefly discussing neural network theory, this research determines the feasibility and practicality of using data mining as a predicting tool for the individual investor. Data mining algorithms have a great capability of finding hidden patterns and trends, if they are provided with a reasonable amount of input data and desired output. As the number of input values increases, the quality of prediction increases as well. Thus for a better indexes predictor, you would like to use more parameters than just the prime interest rate and indexes historical data. Prediction of stock market trends has been an area of great interest both to researchers attempting to uncover the information hidden in the stock market data and for those who wish to profit by trading stocks.The real issue lies in accurately predicting the future stock price/index movements, due to non-linear,non-parametric behavior of the stock marketsThus in this paper, we introduced to the fiscal predictor based upon data mining technique for BSE Sensex.The findings would help the investors, to make informed investment decisions to optimize the stock returns. Keywords - Stock Prediction, Fiscal News, Data Mining Rules, BSE SENSEX