SFB649DP2014 066
TENET: Tail-Event driven NETwork risk
Wolfgang Karl Härdle
Weining Wang
Lining Yu
Abstract:
A system of risk factors necessarily involves systemic risk. The analysis of systemic
risk is in the focus of recent econometric analysis and uses tail event and
network based techniques. Here we bring tail event and network dynamics together
into one context. In order to pursue such joint effects, we propose a semiparametric
measure to estimate systemic interconnectedness across financial institutions based
on tail-driven spillover effects in a high dimensional framework. The systemically
important institutions are identified conditional on their interconnectedness structure.
Methodologically, a variable selection technique in a time series setting is
applied in the context of a single-index model for a generalized quantile regression
framework. We could thus include more financial institutions into the analysis to
measure their tail event interdependencies and, at the same time, being sensitive to
non-linear relationships between them. Network analysis, its behaviour and dynamics,
allows us to characterize the role of each industry group in the U. S. financial
market 2007 - 2012. The proposed TENET - Tail Event driven NETwork technique
allows us to rank the systemic risk contributions of publicly traded U.S. financial
institutions.
Keywords:
Systemic Risk, Systemic Risk Network, Generalized Quantile, Quantile Single-Index
Regression, Value at Risk, CoVaR, Lasso
JEL Classification:
G01, G18, G32, G38, C21, C51, C63