International Journal of Mathematics Trends and Technology
Volume 51 | Number 4 | Year 2017 | Article Id. IJMTT-V51P535 | DOI : https://doi.org/10.14445/22315373/IJMTT-V51P535
The paper investigates the trend of four specific prices on the Bombay Stock Exchange. These are the shares of public sector Oil companies HPCL, IOCL, BPCL, and ONGC. An Autoregressive Moving Average model has been used for modelling purposes. BSE to a certain extent reflect the degree of inflection which has a great signification on national economic by time series model Autoregressive .This model is a simple and practical model in financial time series analysis which has relatively high for forecast accuracy. The paper utilizes monthly secondary data from web site www.bseindia.com through the statistical analysis of BSE from the year of, January 2, 2012 to October, 12, 2017. ADF unit root test of Autocorrelation function ACF diagram and partial autocorrelation function PACF diagram to the prediction of model. The prediction of the models showed that the ARIMA model is valid and forecast accuracy is relative high.
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A.V. Jadhav, K.B.Kamble, "Prediction of Stock prices in Oil Sectors using ARIMA Model," International Journal of Mathematics Trends and Technology (IJMTT), vol. 51, no. 4, pp. 266-270, 2017. Crossref, https://doi.org/10.14445/22315373/IJMTT-V51P535
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