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Systematic credit risk in securitised mortgage portfolios

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  • Lee, Yongwoong
  • Rösch, Daniel
  • Scheule, Harald

Abstract

This study analyses the level of systematic risk for US mortgage portfolio securitisations based on the variation of default rates which cannot be explained by observed deterministic factors. Systematic risk is decomposed into general systemic risk, rating-class-specific systematic risk and their covariance structure. General systematic risk sensitivities increase from lower rating classes to medium rating classes and decreases to higher rating classes. Rating-class-specific systematic risk shows an opposite pattern. The methodology provides for more accurate probability of default and Value-at-Risk forecasts.

Suggested Citation

  • Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2021. "Systematic credit risk in securitised mortgage portfolios," Journal of Banking & Finance, Elsevier, vol. 122(C).
    • Handle: RePEc:eee:jbfina:v:122:y:2021:i:c:s0378426620302582
    DOI: 10.1016/j.jbankfin.2020.105996
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    Cited by:

    1. Cho, Yongbok & Lee, Yongwoong, 2022. "Asymmetric asset correlation in credit portfolios," Finance Research Letters, Elsevier, vol. 49(C).
    2. Thi Mai Luong & Harald Scheule & Nitya Wanzare, 2023. "Impact of mortgage soft information in loan pricing on default prediction using machine learning," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 158-186, March.

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    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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