Numerical analysis of rating transition matrix depending on latent macro factor via nonlinear particle filter method
Numerical analysis of rating transition matrix depending on latent macro factor via nonlinear particle filter method
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通过非线性粒子滤波方法对取决于潜在宏观因素的评级转移矩阵进行数值分析
DOI：
10.1142/s2345768614500263
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Hideyuki Takada
中科院分区：
文献类型：
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作者：
Hidetoshi Nakagawa;Hideyuki Takada
我们提出了一个新的非线性滤波模型，以更好地估计信用评级转换矩阵一致的假设，评级转换强度以及金融资产价格的动态依赖于一些不可观察的宏观经济因素。我们尝试了一种分支粒子滤波方法，数值计算得到的条件分布的潜在因素。作为例证，我们分析了日本企业的评级转变历史。结果表明，我们的模型可以捕捉到信用事件的传染效应和金融市场信息对评级转换强度的插值作用。
We propose a new nonlinear filtering model for a better estimation of credit rating transition matrix consistent with the hypothesis that rating transition intensities as well as dynamics of financial asset prices depend on some unobservable macroeconomic factor. We attempt a branching particle filter method to numerically obtain the conditional distribution of the latent factor. For an illustration, we analyze a rating transition history of Japanese enterprises. As a result, we realize that our model can capture some contagion effect of credit events and an interpolative role of financial market information on the rating transition intensities.