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Dynamic correlation analysis of financial contagion: Evidence from the Central and Eastern European markets☆

TLDR
This article applied the Dynamic Conditional Correlation (DCC) multivariate GARCH model to examine the time-varying conditional correlations to the weekly index returns of seven emerging stock markets of Central and Eastern Europe.
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This article is published in International Review of Economics & Finance.The article was published on 2011-10-01. It has received 353 citations till now. The article focuses on the topics: Financial contagion & Eastern european.

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Financial Contagion in Latin America

TL;DR: In this paper, the authors used a Dynamic Conditional Correlation multivariate GARCH approach for testing for contagion among Latin American financial markets to shocks originated in the United States and Europe.
Journal ArticleDOI

Segment Stock Market, Foreign Investors, and Cross-Correlation: Evidence from MF-DCCA and Spillover Index

TL;DR: Empirical results show that among the selected markets, the three markets with the strongest spillover effects with AHA and AHH are Taiwan, South Korea, and Singapore, respectively, and the weakest one is Australia during the sample scenarios.
Journal ArticleDOI

Financial Contagion in EFA Markets in Crisis Periods: A Multivariate GARCH Dynamic Conditional Correlation Framework

TL;DR: Forbes and Rigobon as mentioned in this paper defined contagion as an increase in cross-market linkages resulting from the shocks to a country or group of countries, which is the most commonly used definition of financial contagion.
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Another Look at Large-Cap Stock Return Comovement: A Semi-Markov-Switching Approach

TL;DR: In this paper, the authors revisited the question of how stock return comovement varies with volatility and market returns and proposed an eigenvalue-based measure of comovements implied by the state-dependent correlation matrix estimated using a novel multivariate semi-Markov-switching approach.
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Modelling interactions among the housing market and key US sectors

TL;DR: In this paper, the authors evaluate the dynamic interactions among the housing market and ten key US sectors including: consumer discretionary, consumer staples, energy, financials, industrial, technology, health care, materials, utility and telecommunications.
References
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Journal ArticleDOI

Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models

TL;DR: In this article, a new class of multivariate models called dynamic conditional correlation models is proposed, which have the flexibility of univariate generalized autoregressive conditional heteroskedasticity (GARCH) models coupled with parsimonious parametric models for the correlations.
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No Contagion, Only Interdependence: Measuring Stock Market Comovements

TL;DR: The authors showed that correlation coefficients are conditional on market volatility, and that there was virtually no increase in unconditional correlation coefficients (i.e., no contagion) during the 1997 Asian crisis, 1994 Mexican devaluation, and 1987 U.S. market crash.
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No Contagion, Only Interdependence: Measuring Stock Market Co-Movements

TL;DR: In this article, the authors examined stock market co-movements and applied these concepts to test for stock market contagion during the 1997 East Asian crises, the 1994 Mexican peso collapse, and the 1987 U.S. stock market crash.
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Extreme Correlation of International Equity Markets

TL;DR: This article showed that correlation is not related to market volatility per se but to the market trend and that correlation increases in bear markets, but not in bull markets, and they also showed that the distribution of extreme correlation for a wide class of return distributions can be derived using extreme value theory.
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Is the correlation in international equity returns constant: 1960–1990?

TL;DR: In this article, the authors studied the correlation of monthly excess returns for seven major countries over the period 1960-90 and found that the international covariance and correlation matrices are unstable over time.
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