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A Comparative Study of Different Statistical Techniques Applied to Predict Share Value of State Bank of India (SBI)

Author(s): Hota H.S | Sahu Pushpanjali

Journal: International Journal of Soft Computing & Engineering
ISSN 2231-2307

Volume: 2;
Issue: 1;
Start page: 283;
Date: 2012;
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Keywords: Expert modeler | Exponential Smoothing | Auto Regressive Integrated Moving Average (ARIMA).

Prediction of share value is one of the critical job and is necessary for the current financial scenario, due to the high uncertainty prediction system can not predict the share value with high accuracy. In this piece of research work an attempt is made to analyze the prediction based on statistical techniques with special reference to the share value of State Bank of India (SBI). The data that is downloaded consists share value for open, close, volume, high, and low in equal interval of time from Jan-2003 to May-2011. Two different techniques ARIMA and Exponential Smoothing is used to compare the accuracy. Statistical measure are carried out and it is found that expert modeler is working well for the prediction of share value of SBI. The future value for the next 5 months from May-2011 from both the models are also evaluated

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