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Arima model in forecasting share prices

Abstract

The fluctuation in share price of a particular company is of great concern for investors who want to invest in that particular company. These fluctuations are analysed in detail using various statistical techniques. Analysts make use of historical data to predict the trends, patterns in the data, or forecast the process behaviour either within the range or outside the range of the observed data so that investors can have an idea about the market behaviour. Amongst the various techniques used for forecasting, a time series forecasting tool called ARIMA (Auto Regressive Integrated Moving Average) method has been used from time to time. For this, R programming software is used which is useful for visualization, statistical computing, scientific inference, and graphical interface. R Studio is a free and powerful integrated development environment for R language which allows the user to implement ARIMA Model.The data of the share prices for the past two years of Star Cement Ltd. has been collected and trained using ARIMA model with different parameters. The test criterion like Akaike Information Criterion is applied to analyse the accuracy of the model. The one with the least AIC is chosen. The model is then used to forecast the performance of the stock for the next ten data points.

Stock Market Forecasting MethodsForecasting Techniques and ApplicationsAutoregressive integrated moving averageComputer scienceEconometricsTime seriesRange (aeronautics)Akaike information criterionStatistical inferenceData miningOperations researchIndustrial engineering
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