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

Madhavi Latha Challa (), Venkataramanaiah Malepati () and Siva Nageswara Rao Kolusu ()
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Madhavi Latha Challa: CMR College of Engineering & Technology
Venkataramanaiah Malepati: SG Govt. Degree & PG College
Siva Nageswara Rao Kolusu: Department of Management Studies, Vignan Foundation for Science, Technology & Research

Financial Innovation, 2020, vol. 6, issue 1, 1-19

Abstract: 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.

Keywords: Efficient market hypothesis; Bombay stock exchange; ARIMA; KPSS; S&P BSE Sensex; Forecasting; S&P BSE IT; G12; G14; G17 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1186/s40854-020-00201-5

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