信用违约掉期定价与交易对手风险的简化模型与共同跳跃过程

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL Probability in the Engineering and Informational Sciences Pub Date : 2022-02-22 DOI:10.1017/S0269964822000018
Yu Chen, Yu Xing
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引用次数: 1

摘要

摘要本文研究了考虑交易对手风险的信用违约互换(CDS)定价问题。假设参考公司和交易对手的默认跳跃强度分别遵循具有独立跳跃和共同跳跃的均值回归CIR过程。利用PDE方法可以得到联合生存概率密度和第一次违约概率密度的近似闭型解。在此基础上,利用概率密度表达式,得到了带有交易对手风险的普通跳变CDS价格的简化公式。在数值分析部分,我们发现引入共跳过程后,参考资产违约对CDS价格的影响大于交易对手违约对CDS价格的影响。
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Credit default swap pricing with counterparty risk in a reduced form model with a common jump process
Abstract In this paper, we study the credit default swap (CDS) pricing with counterparty risk in a reduced form model. The default jump intensities of the reference firm and counterparty are both assumed to follow the mean-reverting CIR processes with independent jumps respectively and a common jump. The approximate closed-form solutions of the joint survival probability density and the probability density of the first default can be obtained by using the PDE method. Then with the expressions of the probability densities, we can get the formula for the CDS price with counterparty risk in a reduced form model with a common jump. In the numerical analysis part, we find that the default of the reference asset has a greater impact on the CDS price than that of the default of counterparty after introducing the common jump process.
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来源期刊
CiteScore
2.20
自引率
18.20%
发文量
45
审稿时长
>12 weeks
期刊介绍: The primary focus of the journal is on stochastic modelling in the physical and engineering sciences, with particular emphasis on queueing theory, reliability theory, inventory theory, simulation, mathematical finance and probabilistic networks and graphs. Papers on analytic properties and related disciplines are also considered, as well as more general papers on applied and computational probability, if appropriate. Readers include academics working in statistics, operations research, computer science, engineering, management science and physical sciences as well as industrial practitioners engaged in telecommunications, computer science, financial engineering, operations research and management science.
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