Too Connected to Fail? Inferring Network Ties from Price Co-movements
Jakob Bosma, Michael Koetter, Michael Wedow
Journal of Business and Economic Statistics,
Nr. 1,
2019
Abstract
We use extreme value theory methods to infer conventionally unobservable connections between financial institutions from joint extreme movements in credit default swap spreads and equity returns. Estimated pairwise co-crash probabilities identify significant connections among up to 186 financial institutions prior to the crisis of 2007/2008. Financial institutions that were very central prior to the crisis were more likely to be bailed out during the crisis or receive the status of systemically important institutions. This result remains intact also after controlling for indicators of too-big-to-fail concerns, systemic, systematic, and idiosyncratic risks. Both credit default swap (CDS)-based and equity-based connections are significant predictors of bailouts. Supplementary materials for this article are available online.
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09.08.2017 • 29/2017
Vernetzt und aufgefangen
Während der Finanzkrise flossen Milliarden, um Banken zu retten, die ihren Regierungen zufolge zu groß waren als dass man sie hätte untergehen lassen dürfen. Doch eine Studie von Michael Koetter vom Leibniz-Institut für Wirtschaftsforschung Halle (IWH) und Ko-Autoren zeigt: Nicht nur die Größe der Bankhäuser war für eine Rettung entscheidend. Wesentlich war auch, wie zentral ein Institut im globalen Finanznetzwerk war.
Michael Koetter
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Extreme Dependence with Asymmetric Thresholds: Evidence for the European Monetary Union
Stefan Eichler, R. Herrera
Journal of Banking and Finance,
Nr. 11,
2011
Abstract
Existing papers on extreme dependence use symmetrical thresholds to define simultaneous stock market booms or crashes such as the joint occurrence of the upper or lower one percent return quantile in both stock markets. We show that the probability of the joint occurrence of extreme stock returns may be higher for asymmetric thresholds than for symmetric thresholds. We propose a non-parametric measure of extreme dependence which allows capturing extreme events for different thresholds and can be used to compute different types of extreme dependence. We find that extreme dependence among the stock markets of ten initial EMU member countries, the United Kingdom, and the United States is largely asymmetrical in the pre-EMU period (1989–1998) and largely symmetrical in the EMU period (1999–2010). Our findings suggest that ignoring the possibility of asymmetric extreme dependence may lead to an underestimation of the probability of co-booms and co-crashes.
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