An Effective Time Series Analysis for Stock Trend Prediction Using ARIMA Model for Nifty Midcap-50

The data mining and its tool has played a vital role in exploring the data from different ware houses. Using data mining tools and analytical technologies we do a quantifiable amount of research to explore new approach for the investment decisions .The market with huge volume of investor with good enough knowledge and have a prediction as well as control over their investments. The stock market some time fails to attract new investor. The reason states that non-aware and also people don’t want to come forward to fall in to the risk. An approach with adequate expertise is designed to help investors to ascertain veiled patterns from the historic data that have feasible predictive ability in their investment decisions. In this paper the NSE – Nifty Midcap50 companies among them top 4 companies having max Midcap value has been selected for analysis. The historical data has a significant role in, helping the investing people to get an overview about the market behavior during the past decade. The stock data for the past five years has been collected and trained using ARIMA model with different parameters. The test criterions like Akaike Information Criterion Bayesian Information Criterion (AICBIC) are applied to predict the accuracy of the model. The performance of the trained model is analyzed and it also tested to find the trend and the market behavior for future forecast.