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Spatial contagion between stock markets in Central Europe

100%
Czapkiewicz A., Wójtowicz T.
Managerial Economics
|
2017
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vol. 18
|
issue 1
23-46
EN
In this paper, we investigate contagion between three European stock markets: those in Frankfurt, Vienna, and Warsaw. Two of them are developed markets, while the last is an emerging market. Additionally, the stock exchanges in Vienna and Warsaw are competing markets in the CEE region. On the basis of daily and intraday returns, we analyze and compare the dependence between the major indices of these markets during calm and turbulent periods. A comparison of the dependence in the tail and in the central part of the joint distribution of returns (via a spatial contagion measure) indicates strong contagion among the analyzed markets. Additionally, the application of a conditional contagion measure indicates the importance of taking into account the situation on other markets when contagion between two markets is considered.
2
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Copula-based Stochastic Frontier Model with Autocorrelated Inefficiency

100%
Das A.
Central European Journal of Economic Modelling and Econometrics
|
2015
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issue 2
3
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A Bivariate Copula-based Model for a Mixed Binary-Continuous Distribution: A Time Series Approach

100%
Bień-Barkowska K.
Central European Journal of Economic Modelling and Econometrics
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2012
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issue 2
4
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On Testing Significance of the Multivariate Rank Correlation Coefficient

58%
Kończak G.
|
2018
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vol. 3
|
issue 335
21-34
PL
Współczynnik korelacji rang Spearmana pozwala na badanie siły zależności między dwiema zmiennymi, dla których dokonano pomiaru na skali porządkowej. W literaturze są prezentowane rozszerzenia tego współczynnika na przypadek wielowymiarowy. W tych konstrukcjach wykorzystywane są zwykle funkcje łączące (kopule). W artykule przedstawiono propozycję testowania istotności zależności wielowymiarowej dla danych mierzonych na skali rangowej. Przedstawiony test dla istotności wielowymiarowego współczynnika korelacji rang wykorzystuje metodę permutacyjną. Własności proponowanego testu scharakteryzowano z wykorzystaniem symulacji komputerowych.  
EN
The Spearman’s rho is a measure of the strength of the association between two variables. There are some extensions of this coefficient for the multivariate case. Measures of the multivariate association which are the generalisation of the bivariate Spearman’s rho are considered in the literature. These measures are based on copula functions. This article presents a proposal of the testing for the multivariate Spearman’s rank correlation coefficient. The proposed test is based on the permutation method. The test statistic used in the permutation test is based on the empirical copula function. The properties of the proposed method have been described using computer simulations.  
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