School of Mathematical and Statistical Sciences Faculty Publications and Presentations
Document Type
Article
Publication Date
9-30-2024
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.
Recommended Citation
Nortey, Ezekiel NN, Ruben Agbeli, Godwin Debrah, Theophilus Ansah-Narh, and Edmund Fosu Agyemang. "A GARCH-MIDAS approach to modelling stock returns." Communications for Statistical Applications and Methods 31, no. 5 (2024): 535-556. https://doi.org/10.29220/CSAM.2024.31.5.535
Publication Title
Communications for Statistical Applications and Methods
DOI
https://doi.org/10.29220/CSAM.2024.31.5.535
Comments
Student publication. © The Korean Statistical Society, and Korean International Statistical Society.
CSAM has the policy that allows authors of articles in CSAM to post their Accepted Manuscript or the publisher's final PDF version of the article, to the author's homepage or an open institutional repository.