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Pricing Credit Risk for Mortgages: Credit Risk Spreads and Heterogeneity across Housing Markets

机译:定价抵押贷款的信用风险:在住房市场的信用风险传播和异质性

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摘要

We develop a Monte Carlo procedure to project MSA-level house-price paths from 2013 to 2023. These price paths are applied to a fixed portfolio of synthetic mortgages in order to estimate credit risk spreads (CRS) for each MSA. Like the well-known annual percentage rate (APR)-which converts an array of fees into an all-encompassing annual measure of costs to borrowers-the CRS is a holistic measure that encompasses both expected losses from default plus the cost of capital (or unexpected credit losses) needed to cover losses in a stress scenario. We find variation in the CRS across MSAs, with the range spanning 37 basis points. This range spans 86 basis points for those carrying first-loss positions, such as private mortgage insurers. We conclude that, in order to accurately price credit risk, it is necessary to monitor more than borrower characteristics, but also local economic conditions.
机译:我们开发了一个蒙特卡罗程序,将2013年至2023年提起MSA级房价路径。这些价格路径适用于固定的合成抵押贷款组合,以估计每个MSA的信用风险传播(CRS)。 就像众所周知的年度百分比率(APR) - 将一系列费用转换为借款人的全包成本,CRS是一个整体措施,包括从默认的损失加上资本成本(或 意外的信贷损失)需要在压力方案中涵盖损失。 我们在MSA的CRS中找到了变化,范围跨越37个基点。 该范围跨越携带第一亏损职位的人数为86个基点,例如私人抵押保险公司。 我们得出结论,为了准确地价格的信贷风险,有必要监测超过借款人特征,也有必要监测额外的借款人特征。

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  • 来源
    《Real Estate Economics》 |2021年第3期|997-1032|共36页
  • 作者单位

    Fed Housing Finance Agcy Constitut Ctr 400 7th St SW Washington DC 20219 USA;

    Univ Texas Dallas EPPS 800 W Campbell Rd GR31 Richardson TX 75080 USA;

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  • 正文语种 eng
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