Networks in risk spillovers: A multivariate GARCH perspective

IF 2 Q2 ECONOMICS Econometrics and Statistics Pub Date : 2023-10-01 DOI:10.1016/j.ecosta.2020.12.003
Monica Billio , Massimiliano Caporin , Lorenzo Frattarolo , Loriana Pelizzon
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Abstract

A spatiotemporal approach is proposed for modeling risk spillovers using time-varying proximity matrices based on observable financial networks and a new bilateral Multivariate GARCH specification is introduced. The covariance stationarity and identification of the model is studied, developing the quasi-maximum-likelihood estimator and analysing its consistency and asymptotic normality. Further, it is shown how to isolate risk channels and it is discussed how to compute target exposure in order to reduce the system variance. An empirical analysis on Euro-area sovereign credit default swap data indicates that Italy and Ireland are key players in spreading risk, France and Portugal are major risk receivers, and Spain’s non-trivial role as a risk middleman is uncovered.

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风险溢出中的网络:多元GARCH视角
基于可观察金融网络,提出了一种利用时变邻近矩阵建模风险溢出的时空方法,并引入了一种新的双边多变量GARCH规范。研究了模型的协方差平稳性和辨识性,建立了拟极大似然估计量,分析了其一致性和渐近正态性。此外,还展示了如何隔离风险渠道,并讨论了如何计算目标暴露以减少系统方差。对欧元区主权信用违约掉期数据的实证分析表明,意大利和爱尔兰是分散风险的关键参与者,法国和葡萄牙是主要的风险接受者,西班牙作为风险中间人的重要作用被揭示。
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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
84
期刊介绍: Econometrics and Statistics is the official journal of the networks Computational and Financial Econometrics and Computational and Methodological Statistics. It publishes research papers in all aspects of econometrics and statistics and comprises of the two sections Part A: Econometrics and Part B: Statistics.
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