The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
TENET: Tail-Event driven NETwork risk
Open accessAbstract
CoVaR is a measure for systemic risk of the networked financial system conditional on institutions being under distress. The analysis of systemic risk is the focus of recent econometric analyses and uses tail event and network based techniques. Here, in this paper we bring tail event and network dynamics together into one context. In order to pursue such joint efforts, 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 to 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, be sensitive to non-linear relationships between them. Network analysis, its behaviour and dynamics, allows us to characterize the role of each financial industry group in 2007–2012: the depositories received and transmitted more risk among other groups, the insurers were less affected by the financial crisis. The proposed TENET - Tail Event driven NETwork technique allows us to rank the Systemic Risk Receivers and Systemic Risk Emitters in the US financial market.
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Cites
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Econometric measures of connectedness and systemic risk in the finance and insurance sectors
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Financial Intermediation and Credit Policy in Business Cycle Analysis
Gertler, M., & Kiyotaki, N. (2010) · Handbook of Monetary Economics · doi:10.1016/b978-0-444-53238-1.00011-9 · Cited by 1,966
Systemic Risk in Financial Systems
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Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks
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Cited by
Sun, T. (2025) · Journal of Risk and Insurance · doi:10.1111/jori.70023 · Cited by 6
Metadata
- Authors
- Härdle, W. K., Wang, W., & Yu, L.
- Venue
- Journal of Econometrics
- Publisher
- Elsevier BV
- Published
- 2016-06
- Volume
- 192
- Issue
- 2
- Pages
- 499-513
- ISSN
- 0304-4076 (ISSN-L)
- OpenAlex
- W2123423040
- Cited by
- 470
- References
- 31
- FWCI
- 28.08
- Type
- journal article
- Language
- en
- Open access
- green
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