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Estimating Portfolio of Bonds Credit Risk Value-at-Risk Based on Copula Function

机译:基于Copula函数的债券信用风险风险组合估计

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摘要

Risk management has become one of the top priorities in financial industry. A huge effort is being invested in developing reliable risk measurement methods and sound risk management techniques by academics and practitioners alike. Credit Metrics developed by J.P. Morgan is a useful tool for measure portfolio credit risk under Value-at-Risk. However, there are some deficiencies in finding correlation matrix of assets in portfolio under this methodology. In this paper, to improve the precise of estimate the correlation matrix, Copula function is combined with Credit Metrics. A brief introduction about the concepts of Copula and Credit Metrics will be also provided here. An example is performed to estimating the portfolio of bonds credit risk Value-at-Risk, using this combined method, in which Valueat-Risk is 8.76 yuan with 1% confidence. Our results demonstrate that this methodology could be applied to the risk management.
机译:风险管理已成为金融业的重中之重。学术界和从业者都投入了巨大的精力来开发可靠的风险衡量方法和完善的风险管理技术。摩根大通(J.P. Morgan)开发的Credit Metrics是衡量风险价值下投资组合信用风险的有用工具。然而,在这种方法下寻找投资组合中资产的相关矩阵存在一些缺陷。为了提高估计相关矩阵的准确性,将Copula函数与Credit Metrics相结合。这里还将提供有关Copula和信用指标的概念的简要介绍。使用该组合方法进行了一个示例,以估算债券信用风险的风险价值组合,其中Valueat-Risk为8.76元,置信度为1%。我们的结果表明,该方法可以应用于风险管理。

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