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The objective of this article is to investigate the dependencies between selected European subindices before and during the COVID-19 pandemic. Research Design & Methods: The main analysis was quantitative. We used copula entropy and Pearson’s correlation. We considered the closing prices of sectoral indices from France (CAC sectors), Germany (DAX sectors), the UK (FTSE sectors), and the US (SP sectors), along with the main indices from these countries, that is CAC40, DAX, SP500, and FTSE100 (we collected the data from the database investing.com for the period from 4 January 2017 to 30 March 2023). We performed all analyses using R along with supplementary packages. Findings: When it comes to indications of the strength of dependence before and after the event (the outbreak of the COVID-19 pandemic) in relation to mutual information (delta) and linear correlation, we saw the biggest differences for the German market. For the DAX sectors, linear correlation underestimates post-event dependencies. The dependencies for other countries were similar on average. For half of the sectors (all markets), we recorded an increase in dependence after the event. A sector where we recorded growth in all countries was the TECH sector. Implications & Recommendations: The dependence measurement using mutual information expressed in terms of copulas has many advantages. It is not limited to measuring linear correlations. It can also capture a nonlinear correlation. Furthermore, it not only measures the dependence degree, but also considers the dependence structure, which is more than a correlation. Moreover, there was no assumption about the ellipticity of marginal and joint distribution. This dependence measure even allows for the modelling of the dependence of variables with different cumulative distribution functions. Contribution & Value Added: The novelty of this article is that it compares the results of dependence measurements by linear correlations and mutual information expressed in terms of copula entropy. Considering the indices and subindices of the main European stock markets, when both measures of dependence were used, we obtained significantly different results in both subperiods under investigation (i.e. before and after March 11, 2020). [ABSTRACT FROM AUTHOR]

The main aim of this study is to examine dynamic dependence and proof of contagion during the Covid-2019 pandemic. The empirical data are daily prices from six European indexes. The FTSE, DAX and CAC indexes represent the largest and most developed stock markets in Europe, while the Austrian ATX index represents small developed markets. The WIG and BUX indexes represent emerging European markets. This empirical study, based on the Dynamic Conditional Correlation model, which is applied to different pairs of indexes, aims to convince the reader of the increase in the correlation between the time of the pandemic (after 30 December 2019) and the period before the beginning of the pandemic. For all pairs, the mean value of the conditional correlations in the pre-Covid period was statistically below the values in the Covid period. The results indicate contagion in Europe after the outbreak of the Covid-2019 pandemic. [ABSTRACT FROM AUTHOR]

The main aim of this study is to examine dynamic dependence and proof of contagion during the Covid-2019 pandemic. The empirical data are daily prices from six European indexes. The FTSE, DAX and CAC indexes represent the largest and most developed stock markets in Europe, while the Austrian ATX index represents small developed markets. The WIG and BUX indexes represent emerging European markets. This empirical study, based on the Dynamic Conditional Correlation model, which is applied to different pairs of indexes, aims to convince the reader of the increase in the correlation between the time of the pandemic (after 30 December 2019) and the period before the beginning of the pandemic. For all pairs, the mean value of the conditional correlations in the pre-Covid period was statistically below the values in the Covid period. The results indicate contagion in Europe after the outbreak of the Covid-2019 pandemic. [ABSTRACT FROM AUTHOR]

The main aim of this study is to examine dynamic dependence and proof of contagion during the Covid-2019 pandemic. The empirical data are daily prices from six European indexes. The FTSE, DAX and CAC indexes represent the largest and most developed stock markets in Europe, while the Austrian ATX index represents small developed markets. The WIG and BUX indexes represent emerging European markets. This empirical study, based on the Dynamic Conditional Correlation model, which is applied to different pairs of indexes, aims to convince the reader of the increase in the correlation between the time of the pandemic (after 30 December 2019) and the period before the beginning of the pandemic. For all pairs, the mean value of the conditional correlations in the pre-Covid period was statistically below the values in the Covid period. The results indicate contagion in Europe after the outbreak of the Covid-2019 pandemic. [ABSTRACT FROM AUTHOR]