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A GARCH-MIDAS approach to modelling stock returns
Communications for Statistical Applications and Methods 2024;31:535-556
Published online September 30, 2024
© 2024 Korean Statistical Society.

Ezekiel NN Norteya, Ruben Agbelia, Godwin Debraha, Theophilus Ansah-Narhb, Edmund Fosu Agyemang1,c

aDepartment of Statistics and Actuarial Science, University of Ghana, Ghana;
bGhana Atomic Energy Commission, Kwabenya, Ghana;
cSchool of Mathematical and Statistical Science, College of Sciences, University of Texas Rio Grande Valley, USA
Correspondence to: 1 School of Mathematical and Statistical Science, College of Sciences, University of Texas Rio Grande Valley, USA. E-mail: edmundfosu6@gmail.com
Received February 21, 2024; Revised May 19, 2024; Accepted May 20, 2024.
 Abstract
Measuring stock market volatility and its determinants is critical for stock market participants, as volatility spillover effects affect corporate performance. This study adopted a novel approach to analysing and implementing GARCH-MIDAS modelling methods. The classical GARCH as a benchmark and the univariate GARCH-MIDAS framework are the GARCH family models whose forecasting outcomes are examined. The outcome of GARCH-MIDAS analyses suggests that inflation, interest rate, exchange rate, and oil price are significant determinants of the volatility of the Johannesburg Stock Market All Share Index. While for Nigeria, the volatility reacts significantly to the exchange rate and oil price. Furthermore, inflation, exchange rate, interest rate, and oil price significantly influence Ghanaian equity volatility, especially for the long-term volatility component. The significant shock of the oil price and exchange rate to volatility is present in all three markets using the generalized autoregressive conditional heteroscedastic-mixed data sampling (GARCH-MIDAS) framework. The GARCH-MIDAS, with a powerful fusion of the GARCH model’s volatility-capturing capabilities and the MIDAS approach’s ability to handle mixed-frequency data, predicts the volatility for all variables better than the traditional GARCH framework. Incorporating these two techniques provides an innovative and comprehensive approach to modelling stock returns, making it an extremely useful tool for researchers, financial analysts, and investors.
Keywords : GARCH-MIDAS, Johannesburg stock market, all share index, Nigeria stock exchange market, Ghana stock exchange