Investigating the effects of the COVID-19 pandemic on stock volatility in Sub-Saharan Africa:

dc.contributor.authorNcube, Mbongeseni
dc.contributor.authorSibanda, Mabutho
dc.contributor.authorMatenda, Frank, R.
dc.date.accessioned2026-07-07T07:55:48Z
dc.date.issued2024
dc.description.abstractThis study examines the impact of the COVID-19 pandemic on sector volatility in subSaharanAfricabydrawingevidencefromtwolargeandtwosmallstockexchangesintheregion. The analysisincludedstock-specificdata,COVID-19metrics,andmacroeconomicindicatorsfromJanuary 2019 to July 2022. This study employs generalized autoregressive conditional heteroskedasticity (GARCH) models to estimate volatility and Explainable Artificial Intelligence (XAI) in the form of Shapley Additive explanations (SHAP) to identify significant factors driving stock volatility during the pandemic. The findings reveal significant volatility increases at the onset of the pandemic, with government stringency measures leading to increased volatility in larger exchanges, while the introduction of vaccination programs helped to reduce volatility. Weaker macroeconomic fundamentals impact volatility in smaller exchanges. The healthcare sector has emerged as the most resilient, while non-essential sectors, such as consumer discretionary, materials, and real estate, face greater vulnerability, especially in smaller exchanges. The research findings reveal that the heightened stock market volatility observed was mainly a result of the government’s actions to combat the spread of the pandemic, rather than it's outbreak. Were commend that governments introduce sound policies to balance public health measures and economic stability, and that investors diversify their investments to reduce the impact of pandemics.
dc.identifier.citationNcube, M., Sibanda, M. and Matenda, F.R. (2024) 'Investigating the effects of the COVID-19 pandemic on stock volatility in Sub-Saharan Africa: Analysis using Explainable Artificial intelligence,' Economies, 12(5), p. 112. https://doi.org/10.3390/economies12050112.
dc.identifier.urihttps://doi.org/10.3390/ economies12050112
dc.identifier.urihttps://ir.lsu.ac.zw/handle/123456789/290
dc.language.isoen
dc.subjectCOVID-19 pandemic
dc.subjectsub-Saharan Africa
dc.subjectstock market volatility
dc.subjectGARCH models
dc.subjectExplainable Artificial Intelligence
dc.titleInvestigating the effects of the COVID-19 pandemic on stock volatility in Sub-Saharan Africa:
dc.title.alternativeanalysis using explainable artificial intelligence /
dc.typeArticle

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