Contagion effects on capital and forex markets around GFC and COVID-19 crises: A comparative study

IF 1.1 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Krzysztof Brania, H. Gurgul
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引用次数: 3

Abstract

This paper studies the spread of crises across the financial and capital markets of different countries. The standard method of contagion detection is based on the evolution of the correlation matrix for the example of exchange rates or returns, usually after removing univariate dynamics with the GARCH model. It is a common observation that crises that have occurred in one financial market are usually transmitted to other financial markets/countries simultaneously, and that they are visible in different financial variables, such as returns and volatility which determine probability distribution. The changes in distributions can be detected through changes in the descriptive statistics of, e.g., returns characterised by expected value, variance, skewness, kurtosis, and other statistics. They determine the shape of the distribution function of returns. These descriptive statistics display dynamics over time. Moreover, they can interreact within the given financial or capital market and among markets. In this article, we use the FX currency cluster represented by some of the major currencies and currencies of the Višegrad group, namely EUR/USD, EUR/CHF, USD/CHF, EUR/HUF, EUR/PLN, EUR/CZK, USD/CZK, USD/HUF, USD/PLN, CHF/PLN, CHF/PLN, CHF/CZK, CHF/HUF, PLN/CZK, and PLN/HUF. In analysing capital markets in terms of equity indexes, we chose developed markets, such as DAX 30, AEX 25, CAC 40, EURSTOXX 50, FTSE 100, ASX 200, SPX 500, NASDAQ 100, and RUSSEL 2000. Our aim is to check the changes in descriptive statistics, matrices of correlation with respect to exchange rates, returns and volatility on the basis of the data listed above, surrounding two crises: the global financial crisis (GFC) in 2007-2009 and Covid 2019.
全球金融危机和COVID-19危机对资本和外汇市场的传染效应:比较研究
本文研究了危机在不同国家的金融和资本市场的传播。传染检测的标准方法是以汇率或收益为例的相关矩阵的演化为基础的,通常是在用GARCH模型去除单变量动态之后。一个常见的观察是,在一个金融市场发生的危机通常同时传播到其他金融市场/国家,并且它们在不同的金融变量中可见,例如决定概率分布的回报和波动性。分布的变化可以通过描述性统计的变化来检测,例如,以期望值、方差、偏度、峰度和其他统计为特征的回报。它们决定了收益分布函数的形状。这些描述性统计数据显示了随时间变化的动态。此外,它们可以在给定的金融或资本市场内以及市场之间相互作用。在本文中,我们使用了由Višegrad组中的一些主要货币和货币代表的外汇货币集群,即欧元/美元、欧元/瑞郎、美元/瑞郎、欧元/瑞郎、欧元/捷克克朗、美元/捷克克朗、美元/瑞郎、瑞郎/瑞郎、瑞郎/瑞郎、瑞郎/瑞郎、瑞郎/捷克克朗、瑞郎/瑞郎、瑞郎/瑞郎、瑞郎/瑞郎、瑞郎/瑞郎、瑞郎/瑞郎、瑞郎/捷克克朗、瑞郎/瑞郎、瑞郎/瑞郎、瑞郎/瑞郎、瑞郎/瑞郎、瑞郎/捷克克朗和瑞郎/瑞郎/瑞郎。在根据股票指数分析资本市场时,我们选择了发达市场,如DAX 30、AEX 25、CAC 40、EURSTOXX 50、FTSE 100、ASX 200、SPX 500、NASDAQ 100和RUSSEL 2000。我们的目标是在上述数据的基础上,围绕2007-2009年全球金融危机和2019年新冠疫情这两场危机,检查描述性统计数据、汇率、回报和波动性相关矩阵的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Operations Research and Decisions
Operations Research and Decisions OPERATIONS RESEARCH & MANAGEMENT SCIENCE-
CiteScore
1.00
自引率
25.00%
发文量
16
审稿时长
15 weeks
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