TY - JOUR
T1 - Which COVID-19 information really impacts stock markets?
AU - Jakub Szczygielski, Jan
AU - Charteris, Ailie
AU - Rutendo Bwanya, Princess
AU - Brzeszczyński, Janusz
PY - 2023/4/1
Y1 - 2023/4/1
N2 - Information about COVID-19 abounds, but which COVID-19 data actually impacts stock prices? We investigate which measures of COVID-19 matter most by applying elastic net regression for measure selection using a sample of the 35 largest stock markets. Out of 24 measures, COVID-19 related Google search trends, the stringency of government responses and media hype prevail. These measures proxy for COVID-19 related uncertainty, the economic impact of lockdowns and panic-driven media attention respectively, summarizing key aspects of COVID-19 that move stock markets. Moreover, geographical proximity to the virus’s outbreak and a country’s development level also matter in terms of impact.
AB - Information about COVID-19 abounds, but which COVID-19 data actually impacts stock prices? We investigate which measures of COVID-19 matter most by applying elastic net regression for measure selection using a sample of the 35 largest stock markets. Out of 24 measures, COVID-19 related Google search trends, the stringency of government responses and media hype prevail. These measures proxy for COVID-19 related uncertainty, the economic impact of lockdowns and panic-driven media attention respectively, summarizing key aspects of COVID-19 that move stock markets. Moreover, geographical proximity to the virus’s outbreak and a country’s development level also matter in terms of impact.
KW - COVID-19
KW - pandemic
KW - returns
KW - global stock markets
KW - elastic net regression
KW - machine learning
U2 - 10.1016/j.intfin.2022.101592
DO - 10.1016/j.intfin.2022.101592
M3 - Article
VL - 84
JO - Journal of International Financial Markets, Institutions and Money
JF - Journal of International Financial Markets, Institutions and Money
SN - 1042-4431
M1 - 101592
ER -