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Random LGD adjustments in the Vasicek credit risk model

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  • Rubén García-Céspedes
  • Manuel Moreno

Abstract

This paper proposes an approximate formula to measure the credit risk of portfolios under random recoveries. This formula is based on a Taylor expansion and enables having recoveries that are correlated with the default rates over the business cycle. We show how to calibrate the corresponding models and the accuracy of the approximation using defaulted corporate bonds data for the period 1982–2014. Our results show that the proposed formula can be used to approximate the loss distribution of a portfolio under random correlated recoveries in a very satisfactory way. Moreover, this kind of recovery models could be easily implemented under the Basel capital requirements regulation to improve the credit risk measurement.

Suggested Citation

  • Rubén García-Céspedes & Manuel Moreno, 2020. "Random LGD adjustments in the Vasicek credit risk model," The European Journal of Finance, Taylor & Francis Journals, vol. 26(18), pages 1856-1875, December.
    • Handle: RePEc:taf:eurjfi:v:26:y:2020:i:18:p:1856-1875
    DOI: 10.1080/1351847X.2020.1789685
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    References listed on IDEAS

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    1. García-Céspedes, Rubén & Moreno, Manuel, 2017. "An approximate multi-period Vasicek credit risk model," Journal of Banking & Finance, Elsevier, vol. 81(C), pages 105-113.
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    Cited by:

    1. Barbagli, Matteo & Vrins, Frédéric, 2023. "Accounting for PD-LGD dependency: A tractable extension to the Basel ASRF framework," Economic Modelling, Elsevier, vol. 125(C).

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