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.
Highlights
Theoretical and empirical studies have revealed that the relation between stock markets and economic growth is positive (Kim et al 2011; Guptha and Rao 2018; Mallikarjuna and Rao 2019)
Findings of the study The descriptive statistics of Standard and Poor (S&P) Bombay Stock Exchange (BSE) Sensex and S&P BSE Information Technology (IT) revealed that the mean returns were positive but nearly zero
An asymmetric tail indicates a high probability of earnings in returns with high risk, as the value of skewness is greater than the mean value of returns
Summary
Theoretical and empirical studies have revealed that the relation between stock markets and economic growth is positive (Kim et al 2011; Guptha and Rao 2018; Mallikarjuna and Rao 2019). Investment decision plays a significant role in attaining the desired returns through stock market forecasts. Considering the importance of forecasting stock prices and their returns, researchers have paid significant attention to enhancing the model accuracy in the prediction of stock price movements and returns. In this regard, the fundamental explanation is that investors, policymakers, and financial institutions must be dynamic and excel in their decision making in order to optimize the returns on their investments. Market efficiency has 3 forms: weak, semi-strong, and strong. The strong form states that the stock price movements have an impact on all open and inside information.
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