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Contagion between selected European indexes during the Covid-19 pandemic

Gurgul Henryk, Syrek Robert

Operations Research and Decisions

2023

Vol. 33, No. 1

47--59

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.

Analysis of stock market linkages: evidence from the selected CEE markets

Chocholatá M.

Journal of Theoretical and Applied Computer Science

2013

Vol. 7, nr 4

56--69

This paper analyses the stock market linkages of the selected Central and Eastern European (CEE) markets (Czech Republic – PX, Hungary – BUX and Poland – WIG20) with the Western European stock market represented by the German DAX and studies also the comovement between the individual CEE countries’ stock markets. The dynamic conditional correlation (DCC) models were used to model the co-movements and thereafter in some cases the smooth transition analysis was carried out in order to capture how these correlations evolve over time. The analysis was based on weekly data over the sample period January 3rd, 1997 – November 29th, 2013 (883 observations). In the first step the asymmetric univariate autoregressive conditional heteroscedasticity model of Glosten, Jagannathan and Runkle (GJR) was estimated for individual stock return series. The results of the DCCGJR models estimated in the next step show almost in all analysed cases the increasing level of conditional correlations. In four cases (BUX_DAX, WIG20_DAX, BUX_PX and PX_WIG20) the DCC series were identified to be nonstationary – I(1) and nonlinear logistic smooth transition regression (LSTR) model was used to capture the gradual transition towards greater co-movements and to find out if the increasing level of DCC could be attributed to the accession of these countries into the European Union (EU) in May 2004.