Abstract/Summary

This thesis comprises three empirical chapters that examine the impact of COVID-19 on financial markets, with a specific emphasis on sectoral stock price responses, market volatility, and spillover effects across various countries and time periods. The first chapter is the first to empirically uncover, via a recent GARCH-based estimation technique addressing the problem of dimensionality, volatility correlations and Granger causality between the daily COVID-19 cases and the share price indexes in all 11 sectors of the Global Industry Classification Standard across 11 major world economies accounting for 83.1% of the global stock market capitalization for the two full years of the global pandemic, January 2020 - December 2021. We document a shift of density mass from dominantly negative correlations by sector from the first and second halves of 2020, with no vaccines to reassure human fear, to dominantly positive correlations in the first and second halves of 2021, with the population vaccinated two or three times and recovering its optimism. Granger causality tests reveal almost immediate news transmission, of a day or two, from the COVID-19 cases to sectoral price indexes, with some common patterns but also some heterogeneity by sector and country. We interpret the documented main trends and findings by the usual story of how societies learn: faced with an unexperienced danger and no cure for the virus, people panicked all over the world in 2020, influencing share prices dominantly in a negative direction; by contrast, once equipped with vaccines and feeling reassured for the longer run, optimism recovered in 2021, and stock prices, including by sector, too. The second chapter 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 capitalization. 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 estimate the ranges of such an average impact: weaker, moderate and strong. We, then, compare the ranges in the two countries and explore similarities as well as differences. The most affected sector in both countries is technology, while industry comes next. When both countries are considered together, there are sectoral differences too, specifically 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 public and business policies when dealing with the pandemic and its influence on stock-market prices. The last chapter investigates how stock-market volatility in major economies (Namely, the United States, Germany, China, and Japan) spills over into the returns of United Kingdom’s stock market between 2000 and 2023. Using daily data and advanced econometric models from the GARCH family combined with a VAR-X framework, it quantifies the magnitude, persistence, and direction of volatility transmissions across periods marked by the global financial crises, Brexit, COVID-19, and the Ukraine war. The findings reveal that returns of the UK stock market exhibit strong and immediate volatility responses to shocks from the US and German stock indices reflecting deep financial integration. While responses to shocks from Chinese and Japanese stock indices are weaker or delayed, translating structural and regulatory differences. The study confirms the robustness of its results through impulse-response and stability tests concluding that understanding these interconnected dynamics are crucial for policymakers and investors seeking to manage risk and maintain stability in an increasingly globalised financial system.