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

Artikel

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Financial Innovation ; ISSN: 2199-4730 ; Volume: 6 ; Year: 2020 ; Issue: 1 ; Pages: 1-19 ; Heidelberg: Springer

Klassifikation und Themen

• Klassifikation: Management ; Asset Pricing; Trading Volume; Bond Interest Rates ; Information and Market Efficiency; Event Studies; Insider Trading ; Financial Forecasting and Simulation
• Thema: Efficient market hypothesis ; Bombay stock exchange ; ARIMA ; KPSS ; S&P BSE Sensex ; Forecasting ; S&P BSE IT

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Challa, Madhavi Latha ; Malepati, Venkataramanaiah ; Kolusu, Siva Nageswara Rao
• Ereignis: Veröffentlichung
• (wer): Springer
• (wo): Heidelberg
• (wann): 2020

Weitere Informationen

• DOI: doi:10.1186/s40854-020-00201-5
• Handle: http://hdl.handle.net/10419/237226
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ