Predicting the Stock Market Index Using Stochastic Time Series Arima Modelling: The Sample of BSE and NSE

24 Pages Posted: 19 Sep 2019

Date Written: August 1, 2019

Abstract

Stock market is basically volatile and the prediction of its movement will be more useful to the stock traders to design their trading strategies. An intelligent forecasting will certainly abet to yield significant profits. Many important models have been proposed in the economics and finance literature for improving the prediction accuracy and this task has been carried out through the modelling based on time series analysis. The main aim of this paper is to check the stationarity in time series data and predicting the direction of change in stock market index using the stochastic time series ARIMA modelling. The best fit ARIMA (0,1,0) model was chosen for forecasting the values of time series, viz., BSE_CLOSE and NSE_CLOSE by considering the smallest values of AIC, BIC, RMSE, MAE, MAPE, Standard Error of Regression, and the relatively high Adjusted R2 values. Using this best fitted model, the predictions were made for the period ranging from 7th January, 2018 to 3rd June, 2018 (22 expected values) using the weekly data ranging from 6th January, 2014 to 31st December, 2017 (187 observed values). The results obtained from the study confirmed the prospective of ARIMA model to forecast the future time series in short-run and would assist the investing community in making the profitable investment decisions.

Keywords: BSE_CLOSE, NSE_CLOSE, ARIMA model, Forecasting, AIC, BIC, MAPE

JEL Classification: G170, C53, C58, E37

Suggested Citation

C, Viswanatha Reedy, Predicting the Stock Market Index Using Stochastic Time Series Arima Modelling: The Sample of BSE and NSE (August 1, 2019). Available at SSRN: https://ssrn.com/abstract=3451677 or http://dx.doi.org/10.2139/ssrn.3451677

Viswanatha Reedy C (Contact Author)

Dept. of Business Management. ( email )

Rayalaseema University
Kurnool
Kurnool, Andhra Pradesh 518002
India
9848263463 (Phone)

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