Sophisticated vs. Simple Systemic Risk Measures

Abstract

This paper evaluates whether sophisticated or simple systemic risk measures are more suitable in identifying which institutions contribute to systemic risk. In this investigation, CoVaR, Marginal Expected Shortfall (MES), SRISK and Granger-Causality Networks are considered as sophisticated systemic risk measures. Market capitalization, total debt, leverage, the stock market returns of an institution, and the correlation between the stock market returns of an institution and the market, are considered as simple systemic risk measures. Systemic relevance is approximated by the receipt of financial support during the financial crisis and the classification, as a systemically important institution, by national or international regulators. The analyses are performed for all companies included in the S&P 500 composite index. The findings suggest that simple systemic risk measures have more explanatory power than sophisticated risk measures. In particular, total debt is found to be the most suitable indicator to detect institutions which contribute to systemic risk, according to the explanatory power and model fit. The most suitable sophisticated risk measure seems to be SRISK.

CAMELS Model With a Proposed ‘S’ for the Bank Credit Risk Rating

“…Several studies (Pankoke, 2014;Drehmann & Tarashev, 2011a, 2011bPais & Stork, 2013;…) confirmed that the size measures the systemic importance of a banking institution and represents a main determinant confirming the usual argument of "Too Big To Fail "TBTF"". However, Haldane and Madouros (2012) have shown that there is no solid evidence to indicate that major banks are less risky investments, except for the fact that they are too big to be allowed to fail.…”