基于Copula-AL法的VaR和CVaR的度量与分配

摘要/Abstract

摘要： 金融资产收益率的实际分布具有明显尖峰肥尾和不对称等特征,本文采用非对称拉普拉斯分布来刻画这些特征,结合Copula函数技术来描述资产间的相关性结构,研究了市场组合VaR和CVaR的度量和分配。选取上证指数和深圳成指的组合为例,计算了组合风险及其分配。结果表明,基于t-Copula-AL模型的VaR、CVaR法计算简单准确,且能方便地进行风险分配。

关键词: VaR, CVaR, Copula, 非对称拉普拉斯分布

Abstract: The actual distributions of asset returns are always characterized by steep peaks, heavy tails and asymmetry.In this paper,asymmetric Laplace distribution is used to describe these features, study the VaR and CVaR of market portfolio and their allocation by combining with Copula function technique in describing the relationship between assets.The portfolio risk and their allocation with portfolio of Shanghai Composite Index and Shenzhen Component Index are also calculated. The results show that VaR and CVaR based on t-Copula-AL model are more simple and precise, and could be easily used to calculate risk allocation.

Key words: value at risk, conditional value at risk, Copula, asymmetric laplace distribution

中图分类号:

F830.9

杜红军, 王宗军. 基于Copula-AL法的VaR和CVaR的度量与分配 [J]. 中国管理科学, 2012, (3): 1-9.

DU Hong-jun, WANG Zong-jun. Measuring and Allocating VaR and CVaR Based on Copula-AL Method[J]. Chinese Journal of Management Science, 2012, (3): 1-9.

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