Since 2014, the Ghana Stock Exchange (GSE) main index has experienced turbulent stock market volatility and its overall performance continues to follow a downward trend. Consequently, this has awakened unprecedented interest in key stakeholders in order to halt the downward performance of the index. The call for further investigations and research into the stock market volatility put this study in the forefront. The first objective of this research was to analyse the statistical properties of GSE main index. The second objective was the determination of relation between stock price movement and volatility. Finally, the study also sought to find out the extent to which the prediction of volatility and returns of GSE main index could minimise the risk incurred by investors. The most empirically proven model called the Generalised Autoregressive Conditional Heteroskedasticity (GARCH), which takes care of all the statistical properties and stochastic dynamics of asset returns was used in capturing the stylish features of GSE main index: volatility clustering, excess kurtosis, leverage effects and unit ischolar_mains. The distribution innovations of the residuals term considered in the application of the GARCH model were normal, Student’t’ and Generalised Error Distribution (GED). The result from the study indicated that EGARCH (1, 1) model with GED was the best model fitted for the GSE main index series during the in-sample period estimation. It is also observed surprisingly that higher GARCH orders could not out-perform lower GARCH orders. The prediction of volatility and returns on assets of GSE main index was good. The results of the prediction were validated by tools like Root Mean Square Error, Theil Inequality coefficient and simple regression line. On the whole, investors can possibly rely on the findings of this study to make further financial decisions regarding stock market volatility.
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