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

Abstract

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.