TY - JOUR
T1 - Three regime bivariate normal distribution
T2 - a new estimation method for co-value-at-risk, CoVaR
AU - Choi, Ji Eun
AU - Shin, Dong Wan
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea [2019R1A2C1004679].
Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/12/12
Y1 - 2019/12/12
N2 - 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.
AB - 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.
KW - Asymmetric correlation
KW - contagion
KW - CoVaR
KW - delta-CoVaR
KW - quasi maximum likelihood
KW - systemic risk
UR - http://www.scopus.com/inward/record.url?scp=85073585118&partnerID=8YFLogxK
U2 - 10.1080/1351847X.2019.1639208
DO - 10.1080/1351847X.2019.1639208
M3 - Article
AN - SCOPUS:85073585118
SN - 1351-847X
VL - 25
SP - 1817
EP - 1833
JO - European Journal of Finance
JF - European Journal of Finance
IS - 18
ER -