抵押贷款:估计违约相关性和预测违约风险

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引用次数: 1

摘要

违约相关性是信用风险的一个关键驱动因素。在巴塞尔监管框架中,它是通过资产价值相关参数来衡量的。尽管过去的研究表明,抵押贷款(通常是银行资产负债表上最大的资产类别)的参数校准过度,但它们没有考虑到小样本或非高斯风险因素造成的偏差。使用非高斯非线性状态空间模型来调整这些偏差,我发现巴塞尔标准适用于英国和美国的抵押贷款。该模型还能准确而简洁地预测抵押贷款违约率。该模型生成未来抵押贷款违约率的风险价值估计,可用于为压力测试和宏观审慎政策提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mortgages: Estimating Default Correlation and Forecasting Default Risk
Default correlation is a key driver of credit risk. In the Basel regulatory framework it is measured by the asset value correlation parameter. Though past studies suggest that the parameter is over-calibrated for mortgages — generally the largest asset class on banks’ balance sheets — they do not take into account bias arising from small samples or non-Gaussian risk factors. Adjusting for these biases using a non-Gaussian, non-linear state space model I find that the Basel calibration is appropriate for UK and US mortgages. This model also forecasts mortgage default rates accurately and parsimoniously. The model generates value-at-risk estimates for future mortgage default rates, which can be used to inform stress-testing and macroprudential policy.
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