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Contagion between selected European indexes during the Covid-19 pandemic

Gurgul Henryk, Syrek Robert

Operations Research and Decisions

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2023

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Vol. 33, No. 1

47--59

EN

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.

2

Contagion effects on capital and forex markets around GFC and COVID-19 crises : a comparative study

Brania Krzysztof, Gurgul Henryk

Operations Research and Decisions

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2021

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Vol. 31, No. 2

59--92

EN

The spread of crises across the financial and capital markets of different countries has been studied. The standard method of contagion detection is based on the evolution of the correlation matrix for the example of exchange rates or returns, usually after removing univariate dynamics with the GARCH model. It is a common observation that crises that have occurred in one financial market are usually transmitted to other financial markets/countries simultaneously and that they are visible in different financial variables such as returns and volatility which determine probability distribution. The changes in distributions can be detected through changes in the descriptive statistics of, e.g., returns characterised by expected value, variance, skewness, kurtosis, and other statistics. They determine the shape of the distribution function of returns. These descriptive statistics display dynamics over time. Moreover, they can interreact within the given financial or capital market and among markets. We use the FX currency cluster represented by some of the major currencies and currencies of the Višegrad group. In analysing capital markets in terms of equity indexes, we chose developed markets, such as DAX 30, AEX 25, CAC 40, EURSTOXX 50, FTSE 100, ASX 200, SPX 500, NASDAQ 100, and RUSSEL 2000. We aim to check the changes in descriptive statistics, matrices of correlation concerning exchange rates, returns and volatility based on the data listed above, surrounding two crises: the global financial crisis (GFC) in 2007–2009 and Covid 2019.

3

The dependencies of subindexes of Stoxx 600 during the Covid-19 pandemic

Gurgul Henryk, Syrek Robert

Managerial Economics

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2021

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Vol. 22, no. 2

73--94

EN

In this index study, the relationships between Stoxx Europe 600 and sector indices are analyzed. This research uses DCoVar and MES as analytical tools developed as a measure of systemic risk and applied to financial institutions, to sectoral subindexes. For the sake of systemic risk assessment we calculate the dynamic correlation model with bivariate t copula distribution. We focus on the impact of sectors on the market. Despite the similarity between the time series plots of both measures, with maximum values on similar days, the compatibility of daily rankings, measured as a percentage of concordant pairs, is equal to about 50%. The rankings of the most and least risky sectors are different and depend on the choice of measure, but in the case of both we observe poor stability. When sectors are ranked in terms of the highest and lowest mean values at specific intervals (designated by the structural break estimation method, which surpisingly detects very similar dates of structural changes) we draw the same conclusions. For both measures we note huge percentage changes in mean values of risk, especially in the period from February 24, 2020 till August 20, 2020 with respect to the previous period. The percentage changes for both intervals indicate the same most risky sectors, but the indications of both measures are not consistent.

4

Testing for the economic and environmental impacts of EU Emissions Trading System: A panel GMM approach

Gretszel Piotr, Gurgul Henryk, Lach Łukasz, Schleicher Stefan

Managerial Economics

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2020

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Vol. 21, no. 2

99--125

EN

The COVID-19 pandemic has had a great impact on the economies of the EU, also with regard to the future of EU climate policy. The plan to rebuild and support the EU economy seems to place less emphasis on environmental issues as the main focus has been shifted to a quick economic recovery. One of the issues discussed in this context is the continued operation of the EU ETS. From this perspective, empirical research devoted to a thorough analysis of the impact of the EU ETS is of particular importance. At the same time, the current economic literature lacks any econometric analyzes devoted to the issues in question that would use detailed and reliable databases on EU ETS like the one provided by the Wegener Center for Climate and Global Change. The aim of this paper is to make a preliminary assessment of the effectiveness of the EU ETS in terms of reducing the actual emissions while preserving the economic growth of EU member states. The extensive empirical analysis is focused on examining the issues in question for different phases of the EU ETS and various groups of EU economies that vary in terms of economic development and the overall air pollutant emission.