Systemic Importance Of Financial Institutions Research Articles

How Useful is The Marginal Expected Shortfall for the Measurement of Systemic Exposure: A Practical Assessment

We explore the practical relevance from a supervisor's viewpoint of a recent but already popular market-based indicator of the systemic importance of financial institutions, the marginal expected shortfall (MES). The MES of an institution can be defined as its expected equity loss when the market itself is in its left tail. We compute the dynamic MES developed by Brownlees and Engle (2010) for a panel of 65 large US banks over the last decade and a half. Running panel regressions of the MES on bank characteristics, we first find that the MES can be partly rationalized in terms of standard balance sheet indicators of bank health and systemic importance, but also that these relationships changed widely over time. We then ask whether the cross section of the MES can help to identify ex ante, i.e. before a crisis unfolds, which institutions are the more likely to suffer the most severe losses ex post, i.e. once it has unfolded. Unfortunately, using the recent crisis as a natural experiment, we find that standard balance-sheet metrics like the tier one solvency ratio are better able to predict equity losses conditional to a true crisis.

The Simple Econometrics of Tail Dependence

The aim of this paper is to show that measures on tail dependence can be estimated in a convenient way by regression analysis. This yields the same estimates as the non-parametric method within the multivariate Extreme Value Theory framework. The advantage of the regression approach is contained by its straightforward extension to the estimation of higher dimensional tail dependence. We provide an example on international stock markets. The regression approach to tail dependence can be applied to estimate several measures of systemic importance of financial institutions in the literature.

Are Banks Too Big To Fail? Measuring Systemic Importance of Financial Institutions

We consider three measures on the systemic importance of a financial institution within a interconnected financial system. Based on the measures, we study the relation between the size of a financial institution and its systemic importance. From both theoretical model and empirical analysis, we find that in analyzing the systemic risk posed by one financial institution to the system, size should not be considered as a proxy of systemic importance. In other words, the too big to fail argument is not always valid, and alternative measures on systemic importance should be considered. We provide the estimation methodology of systemic importance measures under the multivariate Extreme Value Theory (EVT) framework.