TY - JOUR
T1 - A limit distribution of credit portfolio losses with low default probabilities
AU - Shi, Xiaojun
AU - Tang, Qihe
AU - Yuan, Zhongyi
N1 - Funding Information:
This research was supported by the National Science Foundation of the United States (NSF: CMMI-1435864), the National Natural Science Foundation of China (NSFC: 71172014, 71628104, and 71673281), and a Centers of Actuarial Excellence (CAE) Research Grant (2013–2016) from the Society of Actuaries (SOA).
Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2017/3/1
Y1 - 2017/3/1
N2 - This paper employs a multivariate extreme value theory (EVT) approach to study the limit distribution of the loss of a general credit portfolio with low default probabilities. A latent variable model is employed to quantify the credit portfolio loss, where both heavy tails and tail dependence of the latent variables are realized via a multivariate regular variation (MRV) structure. An approximation formula to implement our main result numerically is obtained. Intensive simulation experiments are conducted, showing that this approximation formula is accurate for relatively small default probabilities, and that our approach is superior to a copula-based approach in reducing model risk.
AB - This paper employs a multivariate extreme value theory (EVT) approach to study the limit distribution of the loss of a general credit portfolio with low default probabilities. A latent variable model is employed to quantify the credit portfolio loss, where both heavy tails and tail dependence of the latent variables are realized via a multivariate regular variation (MRV) structure. An approximation formula to implement our main result numerically is obtained. Intensive simulation experiments are conducted, showing that this approximation formula is accurate for relatively small default probabilities, and that our approach is superior to a copula-based approach in reducing model risk.
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U2 - 10.1016/j.insmatheco.2017.02.003
DO - 10.1016/j.insmatheco.2017.02.003
M3 - Article
AN - SCOPUS:85014348539
SN - 0167-6687
VL - 73
SP - 156
EP - 167
JO - Insurance: Mathematics and Economics
JF - Insurance: Mathematics and Economics
ER -