A TGARCH Quantification of the Average Effect of COVID-19 Cases on Share Prices by Sector: Comparing the US and the UK

Hussein Hassan (), Minko Markovski () and Alexander Mihailov ()
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Hussein Hassan: Department of Economics, University of Reading
Minko Markovski: Department of Economics, University of Reading

No em-dp2023-15, Economics Discussion Papers from Department of Economics, University of Reading

Abstract: This paper proposes an econometric algorithm that quantifies by a single number (in the interval from 0 to –1) the average negative effect of the daily news regarding COVID-19 cases on stock-market prices by business sector. We apply it to the US and the UK, which results in a data-driven, ‘objective’ ranking of the adverse overall impact of the huge and persistent COVID-19 shock to sectoral share prices in these two leading economies that account for some 45% of global equity market capitalisation. Our quantification is based on a sample covering the full duration of the pandemic (1 January 2020 – 20 October 2022) and on a TGARCH approach, which we justify as particularly appropriate for the task at hand. Consequently, we establish three ranges of such an average impact: weak, moderate and strong. We, then, compare the sectors in the two countries and uncover similarities as well as differences. The most affected sector in both countries is technology, while industry comes next when both countries are considered together. Yet, there are sectoral differences too, with the specificity that the share prices of financials and utilities in the UK were the least affected of all business sectors in both economies. Our empirical quantification and comparison by sector, thus, points not only to some common patterns but also to the importance in explaining the differences of country-specific production and trade structures as well as of institutions and policies when dealing with the pandemic and its influence on stock-market prices.

Keywords: COVID-19 cases; sectoral stock-market prices; TGARCH quantification; daily correlations; US; UK (search for similar items in EconPapers)
JEL-codes: E71 G18 G41 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2023-10-03
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