scholarly journals Does volatility transmission between stock market returns of Central and Eastern European countries vary from normal to turbulent periods?

2020 ◽  
Vol 70 (3) ◽  
pp. 449-468
Author(s):  
Ngo Thai Hung
Keyword(s):  
Czech Republic ◽  
Stock Markets ◽  
Stock Price ◽  
Market Returns ◽  
Stock Market Returns ◽  
The Czech Republic ◽  
Crisis Period ◽  
Volatility Spillovers ◽  
Egarch Model ◽  
Eastern European Countries

AbstractThis study investigates the transmission mechanism of price and volatility spillovers across the Budapest, Warsaw, Prague, Bucharest, and Zagreb stock markets in the pre- and post-financial crisis periods under the framework of the multivariate Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model. By using daily closing prices, the results highlight certain interesting findings. I found evidence of price spillovers of the intraregional linkages among the stock price movements in five countries. This analysis shows the existence of bi-directional volatility spillovers between stock markets of the Czech Republic and Croatia in the pre-crisis period, and between Hungary and Romania in the post-crisis period. Also, there are significant volatility spillovers from Croatia to Poland and from Poland to the Czech Republic during two periods. The volatility is found to respond asymmetrically to innovations in other markets. The findings also indicate that the stock markets are more substantially integrated into crisis, as well as the persistence of volatility spillovers between the stock markets increases, and the financial stock markets become more integrated after the crisis period.

scholarly journals Givers or Recipients? Co-Movements between Stock Markets of CEE-3 and Developed Countries

2019 ◽  
Vol 11 (22) ◽  
pp. 6495 ◽  
Author(s):  
Grabowski
Keyword(s):  
Czech Republic ◽  
Euro Area ◽  
Stock Markets ◽  
Sovereign Debt ◽  
Debt Crisis ◽  
Developed Countries ◽  
Sovereign Debt Crisis ◽  
The Czech Republic ◽  
Volatility Spillovers ◽  
The Us

In this paper, time-varying co-movements between the stock markets of Poland, the Czech Republic, Hungary, and the capital markets of developed countries in stable and crisis periods are studied. The parameters of the VAR-AGDCC-GARCH (Vector Autoregressive- Asymmetric Generalized Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroscedasticity) model are estimated, and volatility spillovers are calculated. The evidence suggests that the level of correlation between stock return shocks of Central and Eastern European countries increased significantly in the period of financial turmoil and was high in the period of the US sub-prime crisis, as well as during the euro area sovereign debt crisis. After the announcement of the OMT (Outright Monetary Transactions) program, the evolution of the stock market indices in Central and Eastern Europe countries (CEECs) have followed different paths. An analysis of the volatility spillovers indicates that CEECs are the recipients of volatility. In the period of 2004–2019, they received much volatility—from Germany and the US, in particular. They also received much volatility from Spain during the euro area sovereign debt crisis. After 2012, volatility transmission to Poland, the Czech Republic, and Hungary dropped significantly.

A Mistrustful Society?

2020 ◽  
Vol 10 (2) ◽  
pp. 52-71
Author(s):  
Nicole Horáková
Keyword(s):  
Czech Republic ◽  
Empirical Data ◽  
European Countries ◽  
Eastern European ◽  
The Czech Republic ◽  
State Institutions ◽  
Government Institutions ◽  
European Values ◽  
European Values Study ◽  
Eastern European Countries

The level of trust in politicians also in government institutions is taken as an indicator of the state of society in general. Various studies have shown that the population of the Central Eastern European countries, and especially the citizens of the Czech Republic, lack trust in state institutions and democratic structures. The trust of the Czech population in government institutions is, compared to other (Western) European countries, at a relatively low level. This article aims to discuss different factors that are currently influencing this lack of trust: the historical, cultural, and institutional. The empirical data for this article is based on the European Values Study and Czech surveys of public opinion concerning trust in government institutions.

A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Returns ◽  
Stock Markets ◽  
Financial Integration ◽  
Ordinary Least Squares ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Impact

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.

scholarly journals Inclusive Growth in CEE Countries as a Determinant of Sustainable Development

2018 ◽  
Vol 10 (11) ◽  
pp. 3973 ◽  
Author(s):  
Ewa Cichowicz ◽  
Ewa Rollnik-Sadowska
Keyword(s):  
Sustainable Development ◽  
Multivariate Analysis ◽  
Czech Republic ◽  
Transition Economies ◽  
Eastern European ◽  
Inclusive Growth ◽  
Development Research ◽  
The Czech Republic ◽  
Components Analysis ◽  
Eastern European Countries

Pursuant to the concept of inclusive growth, the authors analyze the transition economies of Central and Eastern European countries, which have become EU members (Bulgaria, Croatia, the Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Romania, Slovakia, and Slovenia). CEE countries characterized by comparable historic and economic backgrounds now seem to reach diversified stages of development. The objective of the study is to identify the level of inclusive growth among CEE countries by taking into account indicators assigned to its seven pillars. The article’s thesis is that CEE countries represent social and economic heterogeneity as well as varied levels of sustainable development. Research methods included the application of the principal components analysis and the multivariate analysis. For a literature review, the bibliometric analysis was conducted with the visualization prepared by the VOSviewer software. The main findings suggest that Estonia, Slovenia, and the Czech Republic seem to exhibit the highest level of inclusive growth while Bulgaria and Romania represent the lowest level of indicators measured.

scholarly journals Inclusive Growth of the CEE Countries as a Determinant of Sustainable Development

2018 ◽  
Author(s):  
Ewa Cichowicz ◽  
Ewa Rollnik-Sadowska
Keyword(s):  
Sustainable Development ◽  
Czech Republic ◽  
Transition Economies ◽  
Eastern European ◽  
Inclusive Growth ◽  
The Czech Republic ◽  
Economic Background ◽  
Components Analysis ◽  
Eastern European Countries ◽  
Different Levels

Referring to the concept of inclusive growth, the authors analyse the transition economies of the Central and Eastern European countries, which are the current EU members (Bulgaria, Croatia, the Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Romania, Slovakia and Slovenia). That region was selected as the CEE countries characterized by comparable historic and economic background but now they seem to reach diversified stages of development. The objective of the study is to identify the level of inclusive growth among the CEE countries, taking into account indicators assigned to its seven pillars. The thesis is that the CEE countries represent socio and economic heterogeneity as well as different levels of sustainable development. The research methods involved the application of the principal components analysis and the multivariate analysis. For literature review, the bibliometric analysis was conducted with the visualization prepared by the VOSviewer software. The main findings suggest that Estonia, Slovenia and the Czech Republic seem to be the ones with the highest inclusive growth. On the other hand, Bulgaria and Romania represent the lowest level of inclusive growth indicators.

scholarly journals Financial contagion and 2016 oil crisis: a factor analysis

2020 ◽  
Author(s):  
Turki Maya
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Principal Component ◽  
Financial Contagion ◽  
Market Returns ◽  
Component Structure ◽  
Stock Market Returns ◽  
Oil Crisis ◽  
Market Indexes ◽  
Variance Explained

<p>The paper tries to answer the following question: could the 2016 oil price crisis generate financial contagion among stock markets? </p> <p>The study period is composed of two sub-periods; a quiet one from 3/01/2012 to 01/08/2014 and turbulent one from 04/08/2014 to 25/05/2016. Raw data consists of daily international stock market indexes prices. The co-movements of the stock market returns are analyzed through a principal component analysis (PCA).</p> <p>The results revealed that the <em>KMO</em> index (Kaiser-Mayer-Olkin) is higher during the turbulent period than during the quiet one and that the proportion of variance explained by the first component during the turbulent period reached 35% while during the quiet one it represented only 26,7%.Regarding the component structure, for the turbulent period, three factors are able to explain the stock markets indexes movements while for the quiet period four factors are required. </p> <p>The findings give more credit to the thesis supporting the linkage between cross correlation and financial contagion and classify the 2016 oil crisis, as just a coupling episode and not an extreme one.</p>

A GARCH Modelling of Volatility and M-GARCH Approach of Stock Market Linkages of North America

2018 ◽  
Vol 19 (6) ◽  
pp. 1538-1553 ◽  
Author(s):  
Ajaya Kumar Panda ◽  
Swagatika Nanda
Keyword(s):  
North America ◽  
Stock Market ◽  
Stock Markets ◽  
Market Integration ◽  
Return Volatility ◽  
Sample Period ◽  
Market Returns ◽  
Stock Market Returns ◽  
Current Period ◽  
Highly Sensitive

The present study attempts to capture the return volatility and the extent of dynamic conditional correlation between the stock markets of North America region. The data contain weekly stock market returns spanning from the second week of 1995 to the fourth week of June 2016. Using univariate ARCH and GARCH approaches, the study finds evidence of return volatility and its persistence within the region. Mexican stock market neither reacts intensely to immediate market fluctuations nor the part of the realized past volatility spill over to the current period, whereas the stock markets of Canada and USA experience high persistence of return volatility and Bermuda stock market returns are highly sensitive to the immediate market fluctuations. Using MGARCH-DCC, this article finds that emerging markets are less linked to the developed market in terms of return and that there also exists a weak co-movement between the stock markets. There is no evidence of market integration throughout the sample period. Correlations tend to spread out equally throughout the sample period, but the co-variances were found to be more volatile during 2008–2010. This article reveals that changes in co-movement are not due to a change in the correlations between markets but is simply due to volatility.

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