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Three regime bivariate normal distribution: a new estimation method for co-value-at-risk, CoVaR

Title
Three regime bivariate normal distribution: a new estimation method for co-value-at-risk, CoVaR
Authors
Choi, Ji-EunShin, Dong Wan
Ewha Authors
신동완
SCOPUS Author ID
신동완scopus
Issue Date
2019
Journal Title
EUROPEAN JOURNAL OF FINANCE
ISSN
1351-847XJCR Link

1466-4364JCR Link
Citation
EUROPEAN JOURNAL OF FINANCE vol. 25, no. 18, pp. 1817 - 1833
Keywords
Asymmetric correlationCoVaRdelta-CoVaRquasi maximum likelihoodsystemic riskcontagion
Publisher
ROUTLEDGE JOURNALS, TAYLOR &

FRANCIS LTD
Indexed
SSCI; SCOPUS WOS scopus
Document Type
Article
Abstract
We propose a new distribution for estimation of co-value-at-risk, CoVaR, a financial system risk measure conditional on an institution in a financial distress: a three regime bivariate normal (3RN) distribution which is composed of three bivariate normal distributions with asymmetric variance matrices for the right-tail, left-tail and mid-part corresponding to the return of an institution. The distribution captures explicitly the asymmetric correlation of system return and institution return: usually stronger for bad times than for good times. The 3RN distribution allows simple evaluations of the CoVaR taking full advantage of asymmetric correlation. An implementation for the quasi maximum likelihood estimator (QMLE) is provided. The proposed estimation method is applied to stock price data sets consisting of one financial system and four financial institutions: the US S&P 500 index, Bank of America Corporation, JP Morgan Chase & Co., Goldman Sachs Group, Inc. and Citigroup Inc. The data analysis shows that the proposed method has better in-sample and out-of-sample violation performance than existing methods and some other possible candidates.
DOI
10.1080/1351847X.2019.1639208
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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