Journal of Finance and Economics

Journal of Finance and Economics

ISSN: 2291-4951 (Print)    ISSN: 2291-496X (Online)

Volume 3 (2015), No. 1, Pages 15-30

DOI: 10.12735/jfe.v3i1p15

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Credit Portfolio Risk Evaluation based on the Pair Copula VaR Models

Luo Changqing1  Lu Yanlin1  Li Mengzhen1 

1Finance school, Hunan University of Commerce, China

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Aiming to solve the difficulty in describing the high dimensional dependency structure of credit assets, we construct pair copula VaR model to evaluate the credit portfolio risk. The empirical study which takes the publicly traded companies in Shanghai stock exchanges and Shenzhen stock exchanges shows that the Clayton copula with Canonical vine structure is the most appropriate function to describe the high dimensional low tail dependency structure. Meanwhile, the Monte Carlo simulation result proves that the pair copula VaR model can accurately measure the credit portfolio risk both in calm period and crisis period. Additionally, we acquired the optimal weights of the different credit assets in portfolio according to the simulation results of pair copula VaR models. Based on the research results, the commercial banks can dynamically adjust their credit asset allocation, so as to alleviate the credit portfolio risk and conduct more efficient credit risk management.

JEL Classifications: G21

Keywords: Pair Copula VaR; Low tail dependency; Credit portfolio risk; Canonical vine structure; D vine structure; Monte Carlo simulation

To Cite this Article: Luo, C.-Q., Lu, Y.-L., & Li, M.-Z. (2015). Credit portfolio risk evaluation based on the pair copula VaR models. Journal of Finance and Economics, 3(1), 15-30.

Copyright © Luo Changqing et al.

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This article is published under license to Science and Education Centre of North America. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License.

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Credit Portfolio Risk Evaluation based on the Pair Copula VaR Models