Modelling systemically important banks vis-à-vis the Basel Prudential Guidelines

Our paper investigates Indonesia’s systemically important banks (SIBs) using theoretical approaches—CoVaR, marginal expected shortfall (MES), and SRISK—to compare with the Basel guidelines as benchmark. We use Indonesian banks’ market and supervisory data over the 2008–2019 period. The research aims to seek intertheoretical model interaction and SIB ranking in concordance with the Basel guidelines as applied by a bank supervisor. The findings show that SRISK produced a more consistent ranking compared with CoVaR and MES. CoVaR and MES had higher intermodel correlation converted to 59% similarity in rankings. Further, all theoretical models are in line with the Basel guidelines, where the closest approximation is at 47%. The results indicate that policy makers could use scholarly models as validation tools and help improve supervision decision to identify systemically important institutions

Macroeconomics of systemic risk : transmission channels and technical integration

The avenue to find a balanced assessment of systemic financial institutions needs the integration of macro and micro granular datasets. This paper investigates how macroeconomic shocks affect systemic risk through several transmission channels. Employing Indonesia datasets over 2008–2019, we regressed three market models: CoVaR, MES, and SRISK using fixed effect, random effect, GARCH(1,1), and finite mixture models. The findings show that stock beta, market index, and exchange rate volatility amplify the systemic risk while the liquidity spread outcome varies due to different of model variables and the deepness of the country’s financial market. We propose a practical systemic risk assessment framework and samples of technical integration to capture the overall risk endogenously and externally expose the systemically important financial institutions