Measuring systemic risk in the financial institution via dynamic conditional correlation and delta conditional value at risk mode and bank rating

Systematic risk (in economics often called aggregate risk or undiversifiable risk) is vulnerability to events which affect aggregate outcomes such as broad market returns, total economy-wide resource holdings, or aggregate income. In many contexts, events like earthquakes and major weather catastrophes pose aggregate risks they affect not only the distribution but also the total amount of resources. In this paper we study systemic risks in the Iranian banking sector by using two famous systemic risk measures theMES (marginal expected shortfall) and CoVaR. To compute both measures we employ Engle's dynamic conditional correlation model. Our empirical analysis shows, first, that although these two systemic risk measures differ in defining the contributions to systemic risk, both are qualitatively very similar in explaining the cross-sectional differences in systemic risk contributions across banks. Last, using a threshold VAR model, we suggest an overall systemic risk measure – the aggregateMES – and its associated threshold value for use as an early warning indicator. The paper is innovative in terms of the use of statistical models (dynamic conditional correlation model) and available data Looking for the rating of commercial banks using by approaches MES and COVAR.