Szczygielski Jan Jakub, Bwanya Princess Rutendo, Charteris Ailie, Brzeszczyński Janusz
Department of Accounting and Financial Management, Newcastle Business School (NBS), Northumbria University, Newcastle upon Tyne, NE1 8ST, United Kingdom.
Department of Finance, Kozminski University, ul. Jagiellońska 57, 03-301, Warsaw, Poland.
Financ Res Lett. 2021 Nov;43:101945. doi: 10.1016/j.frl.2021.101945. Epub 2021 Jan 26.
Uncertainty surrounding COVID-19 is widespread. We investigate the timing and quantify the impact of COVID-19 related uncertainty on returns and volatility for regional market aggregates using ARCH/GARCH models. Drawing upon economic psychology, COVID-19 related uncertainty is measured by searches for information as reflected by Google search trends. Asian markets are more resilient than others. Latin American markets are most impacted in terms of returns and volatility. For most regions, there is evidence of an increasing impact of COVID-19 related uncertainty which dissipates as the crisis evolves. We confirm that Google search trends capture uncertainty by comparing this measure against alternative uncertainty measures.
围绕新冠疫情的不确定性广泛存在。我们利用自回归条件异方差/广义自回归条件异方差（ARCH/GARCH）模型，研究新冠疫情相关不确定性对区域市场总量回报及波动性产生影响的时间，并对其影响进行量化。借鉴经济心理学，新冠疫情相关不确定性通过谷歌搜索趋势所反映的信息搜索量来衡量。亚洲市场比其他市场更具韧性。拉丁美洲市场在回报和波动性方面受影响最大。对于大多数地区，有证据表明新冠疫情相关不确定性的影响在增加，而随着危机的演变这种影响会消散。通过将这一衡量指标与其他不确定性衡量指标进行比较，我们证实谷歌搜索趋势能够捕捉不确定性。
