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S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA

2020; Springer Nature; Volume: 6; Issue: 1 Linguagem: Inglês

10.1186/s40854-020-00201-5

2199-4730

Challa Madhavi Latha, Venkataramanaiah Malepati, Siva Nageswara Rao Kolusu,

Forecasting Techniques and Applications

Abstract This study forecasts the return and volatility dynamics of S&P BSE Sensex and S&P BSE IT indices of the Bombay Stock Exchange. To achieve the objectives, the study uses descriptive statistics; tests including variance ratio, Augmented Dickey-Fuller, Phillips-Perron, and Kwiatkowski Phillips Schmidt and Shin; and Autoregressive Integrated Moving Average (ARIMA). The analysis forecasts daily stock returns for the S&P BSE Sensex and S&P BSE IT time series, using the ARIMA model. The results reveal that the mean returns of both indices are positive but near zero. This is indicative of a regressive tendency in the long-term. The forecasted values of S&P BSE Sensex and S&P BSE IT are almost equal to their actual values, with few deviations. Hence, the ARIMA model is capable of predicting medium- or long-term horizons using historical values of S&P BSE Sensex and S&P BSE IT.