Measuring systemic risk with high-frequency data: A realized GARCH approach

被引：5
|
作者：
Chen, Qihao [1 ]
Huang, Zhuo [2 ]
Liang, Fang [3 ]
机构：
[1] Cent Univ Finance & Econ, China Econ & Management Acad, Beijing 100081, Peoples R China
[2] Peking Univ, China Ctr Econ Res, Natl Sch Dev, Beijing 100871, Peoples R China
[3] Sun Yat Sen Univ, Int Sch Business & Finance, Zhuhai 519082, Peoples R China
来源：
FINANCE RESEARCH LETTERS | 2023年 / 54卷
基金：
中国国家自然科学基金;
关键词：
Systemic risk; CoVaR; Multivariate realized GARCH; Multivariate skew-t distribution; CONDITIONAL HETEROSKEDASTICITY; MULTIVARIATE;
D O I：
10.1016/j.frl.2023.103753
中图分类号：
F8 [财政、金融];
学科分类号：
0202 ;
摘要：
This paper incorporates high-frequency information to measure systemic risk. Under the Multivariate Realized GARCH framework, we compute the CoVaR measure using a multivariate skew-t distribution. Using 5-minute data of 98 U.S. financial institutions from 2000 to 2022, we show the empirical improvement of the high-frequency measurement. We also investigate the relationship between institutions' systemic risk contributions and firm-level characteristics. Our empirical findings suggest that firm size and leverage are positively related to institutions' contributions to systemic risk.
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页数：9
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