Modelling the volatility of African capital markets in the presence of the Covid-19 pandemic: evidence from five emerging economies in Africa

Q4 Mathematics Statistics in Transition Pub Date : 2023-03-15 DOI:10.59170/stattrans-2023-018
Nureni Olawale Adeboye, Sakinat Oluwabukonla Folorunso, O. Abimbola, Rasaki Yinka Akinbo
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Abstract

The growing concern over the global effects of the COVID-19 pandemic on every aspect of human endeavour has necessitated a continuous modelling of its impact on socio-economic phenomena, allowing the formulation of policies aimed at sustaining future economic growth and mitigating the looming recession. The study employed Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) procedures to develop stock volatility models for the pre- and COVID-19 era. The Fixed-Effects Two Stage Least Square (TSLS) technique was utilised to establish an empirical relationship between capital market volatility and the COVID-19 occurrence based on equity market indices and COVID-19 reported cases of five emerging African economies: Nigeria, Egypt, South Africa, Gabon and Tanzania. The stock series was made stationary at the first order differencing and the model results indicated that the stock volatility of all the countries responded sharply to the outbreak of COVID-19 with the average stock returns of Nigeria and Gabon suffering the most shocks. The forecast values indicated a constant trend of volatility shocks for all the countries in the continuous presence of the COVID-19 pandemic. Additionally, the confirmed and death cases of COVID-19 were found to increase stock prices while recovered cases bring about a reduction in the stock prices in the studied periods.
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新冠肺炎疫情下非洲资本市场波动的建模:来自非洲五个新兴经济体的证据
人们越来越担心新冠肺炎疫情对人类努力各个方面的全球影响,因此有必要不断模拟其对社会经济现象的影响,以便制定旨在维持未来经济增长和缓解迫在眉睫的衰退的政策。该研究采用了指数广义自回归条件异方差(EGARCH)程序,开发了前新冠肺炎时代和后两个时期的股票波动率模型。基于股票市场指数和五个新兴非洲经济体(尼日利亚、埃及、南非、加蓬和坦桑尼亚)的新冠肺炎报告病例,利用固定效应两阶段最小二乘法(TSLS)技术建立资本市场波动与新冠肺炎发生之间的实证关系。股票序列在一阶差分时是平稳的,模型结果表明,所有国家的股票波动率对新冠肺炎疫情的爆发反应剧烈,尼日利亚和加蓬的平均股票回报率受到的冲击最大。预测值表明,在新冠肺炎疫情持续存在的情况下,所有国家的波动性冲击呈持续趋势。此外,新冠肺炎确诊和死亡病例被发现会提高股价,而康复病例会导致研究期间股价下跌。
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来源期刊
Statistics in Transition
Statistics in Transition Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.00
自引率
0.00%
发文量
0
审稿时长
9 weeks
期刊介绍: Statistics in Transition (SiT) is an international journal published jointly by the Polish Statistical Association (PTS) and the Central Statistical Office of Poland (CSO/GUS), which sponsors this publication. Launched in 1993, it was issued twice a year until 2006; since then it appears - under a slightly changed title, Statistics in Transition new series - three times a year; and after 2013 as a regular quarterly journal." The journal provides a forum for exchange of ideas and experience amongst members of international community of statisticians, data producers and users, including researchers, teachers, policy makers and the general public. Its initially dominating focus on statistical issues pertinent to transition from centrally planned to a market-oriented economy has gradually been extended to embracing statistical problems related to development and modernization of the system of public (official) statistics, in general.
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