Network linkages to predict bank distress

Citation data:

Journal of Financial Stability, ISSN: 1572-3089, Vol: 35, Page: 226-241

Publication Year:
2018
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DOI:
10.1016/j.jfs.2016.10.011
Author(s):
Andreea Constantin; Tuomas A. Peltonen; Peter Sarlin
Publisher(s):
Elsevier BV
Tags:
Economics, Econometrics and Finance
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article description
Building on the literature on systemic risk and financial contagion, the paper introduces estimated network linkages into an early-warning model to predict bank distress among European banks. We use multivariate extreme value theory to estimate equity-based tail-dependence networks, whose links proxy for the markets’ view of bank interconnectedness in case of elevated financial stress. The paper finds that early warning models including estimated tail dependencies consistently outperform bank-specific benchmark models without networks. The results are robust to variation in model specification and also hold in relation to simpler benchmarks of contagion. Generally, this paper gives direct support for measures of interconnectedness in early-warning models, and moves toward a unified representation of cyclical and cross-sectional dimensions of systemic risk.