Phiri Andrew, Anyikwa Izunna, Moyo Clement
Department of Economics, Faculty of Business and Economic Studies, Nelson Mandela University, Port Elizabeth, 6031, South Africa.
Heliyon. 2023 Mar;9(3):e14195. doi: 10.1016/j.heliyon.2023.e14195. Epub 2023 Mar 7.
In our study, we employ DCC-GARCH and Wavelet coherence analysis to examine the co-movement between global covid-19 indicators (cases, recoveries and deaths) and stock returns of main equity markets in G20 countries using daily data spanning between February 2, 2020 and August 28, 2021. Our empirical results show that the co-movement between COVID-19 and G20 stock returns has been switching between negative and positive correlations across the entire time window. The wavelet coherence analysis further reveal that negative (positive) co-movements predominantly exist as lower (higher frequencies) for cases and deaths and are more mixed for recoveries. The findings also show that the short-frequency components correspond to periods around the initial announcement of the initial pandemic and also around the announced of subsequent variants of the COVID-19 virus. Policy and market implications from our study are also discussed.
在我们的研究中,我们运用动态条件相关广义自回归条件异方差模型(DCC-GARCH)和小波相干分析,使用2020年2月2日至2021年8月28日的日数据,来检验全球新冠疫情指标(病例、康复和死亡)与二十国集团(G20)国家主要股票市场的股票回报之间的共同变动情况。我们的实证结果表明,在整个时间窗口内,新冠疫情与G20股票回报之间的共同变动一直在正负相关之间切换。小波相干分析进一步揭示,病例和死亡的负(正)共同变动主要存在于较低(较高)频率,而康复情况则更为复杂。研究结果还表明,短频率成分对应于疫情最初宣布前后以及新冠病毒后续变种宣布前后的时期。我们还讨论了该研究的政策和市场影响。