违约概率的期限结构

Oliver Blümke
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引用次数: 0

摘要

会计准则要求金融机构必须根据金融工具的完全到期日来衡量违约风险。这需要预测未来的违约概率。对未来违约概率的预测涉及两个方面:预测宏观经济情景和预测未来平均(相对于宏观经济)违约概率。本文讨论了未来平均违约概率的建模问题。由于默认值和观测值的数量较少,这在企业领域提出了一个难题,并且需要一个简洁的模型来处理稀疏的数据情况。随着时间的推移,企业的违约概率会以不同的模式发生变化,而这种模式取决于初始评级等级,这加大了难度。对于初始投资级评级,违约风险增加,而对于评级等级底部的评级,违约概率降低。为了模拟这些不同的模式,本文提出扩展现有的离散时间生存模型,并在危险函数中加入一个额外的时间和协变量相关的形状参数。使用Standard &Poor的论文表明,形状参数能够再现不同的图案。将该模型与不使用形状参数的模型进行了基准测试,结果表明形状参数改善了样本内和样本外的预测。
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The Term Structure of Default Probabilities
Accounting standards require that financial institutions must measure default risk with respect to the full maturity of a financial instrument. This requires forecasting of future default probabilities. The forecast of future default probabilities concerns two aspects: forecasting macroeconomic scenarios and future average (with respect to the macro-economy) default probabilities. The present paper addresses the modelling of future average default probabilities. Due to the small number of defaults and observations this poses a difficult problem in the corporate area and requires a parsimonious model to deal with the sparse data situation. The degree of difficulty is made greater by the fact that default probabilities change for corporations via different patterns over time, with the pattern being depend on the initial rating grade. For initial investment-grade ratings the risk of a default increases, while for the bottom of the rating scale default probabilities decrease. To model these different patterns the paper proposes to extend the existing discrete-time survival model and to incorporate an additional time- and co-variate-dependent shape parameter into the hazard function. Using data from Standard & Poor's the paper shows that the shape parameter is able to reproduce the different patterns. The proposed model is bench-marked against a model which does not employ a shape parameter and the results show that the shape parameter improves in-sample and out-of-sample prediction.
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