Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/239667 
Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 14 [Issue:] 6 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-20
Verlag: 
MDPI, Basel
Zusammenfassung: 
We investigate a systemic risk measure known as CoVaR that represents the value-at-risk (VaR) of a financial system conditional on an institution being under distress. For characterizing and estimating CoVaR, we use the copula approach and introduce the normal tempered stable (NTS) copula based on the Lévy process. We also propose a novel backtesting method for CoVaR by a joint distribution correction. We test the proposed NTS model on the daily S&P 500 index and Dow Jones index with in-sample and out-of-sample tests. The results show that the NTS copula outperforms traditional copulas in the accuracy of both tail dependence and marginal processes modeling.
Schlagwörter: 
backtesting
CoVaR
Lévy process
NTS copula
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