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Analysis of contagion from the dynamic conditional correlation model with Markov Regime switching

机译：基于马尔可夫政权切换的动态条件相关模型的传染性分析

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Over the last decades, the transmissions of international financial events have been the subject of many academic studies focused on multivariate volatility models. This study evaluates the financial contagion between stock market returns. The econometric model employed, regime switching dynamic correlation (RSDC). A modification was made in the original RSDC model, the introduction of the GJR-GARCH-N and also GJR-GARCH-t models, on the equation of conditional univariate variances, thus allowing us to capture the asymmetric effects in volatility and also heavy tails. A database was built using series of indices in the United States (S&P500), the United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) from 1 February 2003 to 20 September 2012. Throughout this study the methodology is compared with those frequently found in literature, and the model RSDC with two regimes was defined as the most appropriate for the selected sample with t-Student distribution in the disturbances. The adapted RSDC model used in this article can be used to detect contagion - considering the definition of financial contagion from the World Bank called very restrictive - with the help of the empirical exercise.
机译：在过去的几十年中，国际金融事件的传递一直是许多关注多元波动率模型的学术研究的主题。这项研究评估了股票市场收益之间的金融传染。使用计量经济学模型，政权切换动态相关性（RSDC）。对原始RSDC模型进行了修改，引入了GJR-GARCH-N模型以及GJR-GARCH-t模型，以条件单变量方差方程为基础，从而使我们能够捕获波动率的不对称影响以及严重的尾部。从2003年2月1日至2012年9月20日，使用美国（S＆P500），英国（FTSE100），巴西（IBOVESPA）和韩国（KOSPI）的一系列指数建立了数据库。在整个研究过程中，该方法与那些在文献中经常发现的模型，具有两种状态的RSDC模型被定义为最适合于在扰动中具有t型学生分布的选定样本。考虑到世界银行对金融危机的定义非常严格，本文通过实证研究可以使用本文中使用的经过修改的RSDC模型来检测危机的蔓延。

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