Bayesian Switching Volatility Models for Analysing Stock Returns in Ghana
-
Edward Akurugu
and
Abdul Ghaniyyu Abubakari
Abstract
The goal of this research was to use Bayesian switching volatility models to model the stock returns of the GCB, bank in Ghana. Monthly stock prices of GCB bank for the period of 138 months were used for the study. The two-state Markov-Switching GARCH models were used in the study to determine the best model for modelling and forecasting the stock returns. The Deviance Information Criteria was considered when selecting the best model. Based on the Deviance Information Criteria, E-GARCH variance specification with skewed student-t innovation was shown to be appropriate for modelling the stock returns. The estimates of the best model showed the first regime to exhibit the features of “turbulent market conditions” while the second regime exhibits “tranquil market conditions”. The risk analysis finds the best model to generally perform better in estimating both Value-at-Risk and Expected Shortfall at 1% rather than 5%. The study advises investors to invest in GCB bank because of the high returns connected with the stock and the fact that when “turbulent market conditions” arise, the recovery rate for these stocks is faster.
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Articles in the same Issue
- Frontmatter
- Politically Viable U.S. Electoral College Reform
- Voting for Eurosceptic Parties and Societal Polarization in the Aftermath of the European Sovereign Debt Crisis
- Improving the Explanation of Electoral Behavior Through a Combination of Historical and Local Context – The Case of the AfD’s Results at the Federal Election in Germany in 2017
- The Politics of Income Inequality: Redistribution, Turnout and Responsiveness
- Economy, Commerce, and Energy: How Do the Factors Influence Carbon Dioxide Emissions in Japan? An Application of ARDL Model
- Bayesian Switching Volatility Models for Analysing Stock Returns in Ghana
