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A limit distribution of credit portfolio losses with low default probabilities
Institution:1. China Financial Policy Research Center, School of Finance, Renmin University of China, No. 59 Zhongguancun Street, Haidian District, Beijing 100872, PR China;2. Department of Statistics and Actuarial Science, University of Iowa, 241 Schaeffer Hall, Iowa City, IA 52242, USA;3. Department of Risk Management, The Pennsylvania State University, 362 Business Building, University Park, PA 16802, USA;1. Département de Mathématiques et d’informatique, Université du Québec à Trois-Rivières, Trois-Rivières (Québec), Canada G9A 5H7;2. Institut de Statistique, Biostatistique et Sciences Actuarielles (ISBA), Université Catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium;1. Tianjin University of Commerce, Tianjin, China;2. Tianjin University of Finance and Economics, Tianjin, China;1. Department of Economics and CREIP, Universitat Rovira i Virgili, Avinguda de la Universitat 1, 43204 Reus, Spain;2. Department of Econometrics, Riskcenter-IREA, University of Barcelona, Avinguda Diagonal, 690, E-08034 Barcelona, Spain
Abstract: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.
Keywords:Credit portfolio loss  Extreme risk  Limit distribution  Loss given default  Model risk  Multivariate regular variation  Tail dependence
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