{"title":"Modelling the volatility of African capital markets in the presence of the Covid-19\n pandemic: evidence from five emerging economies in Africa","authors":"Nureni Olawale Adeboye, Sakinat Oluwabukonla Folorunso, O. Abimbola, Rasaki Yinka Akinbo","doi":"10.59170/stattrans-2023-018","DOIUrl":null,"url":null,"abstract":"The growing concern over the global effects of the COVID-19 pandemic on every\n aspect of human endeavour has necessitated a continuous modelling of its impact on\n socio-economic phenomena, allowing the formulation of policies aimed at sustaining\n future economic growth and mitigating the looming recession. The study employed\n Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH)\n procedures to develop stock volatility models for the pre- and COVID-19 era. The\n Fixed-Effects Two Stage Least Square (TSLS) technique was utilised to establish an\n empirical relationship between capital market volatility and the COVID-19 occurrence\n based on equity market indices and COVID-19 reported cases of five emerging African\n economies: Nigeria, Egypt, South Africa, Gabon and Tanzania. The stock series was made\n stationary at the first order differencing and the model results indicated that the\n stock volatility of all the countries responded sharply to the outbreak of COVID-19 with\n the average stock returns of Nigeria and Gabon suffering the most shocks. The forecast\n values indicated a constant trend of volatility shocks for all the countries in the\n continuous presence of the COVID-19 pandemic. Additionally, the confirmed and death\n cases of COVID-19 were found to increase stock prices while recovered cases bring about\n a reduction in the stock prices in the studied periods.","PeriodicalId":37985,"journal":{"name":"Statistics in Transition","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics in Transition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59170/stattrans-2023-018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
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.
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.