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Credit default prediction and parabolic potential theory

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  • Bedini, Matteo L.
  • Hinz, Michael

Abstract

We consider an approach to credit risk in which the information about the time of bankruptcy is modelled using a Brownian bridge that starts at zero and is conditioned to equal zero when the default occurs. This raises the question whether the default can be foreseen by observing the evolution of the bridge process. Unlike in most standard models for credit risk, we allow the distribution of the default time to be singular. Using a well known fact from parabolic potential theory, we provide a sufficient condition for its predictability.

Suggested Citation

  • Bedini, Matteo L. & Hinz, Michael, 2017. "Credit default prediction and parabolic potential theory," Statistics & Probability Letters, Elsevier, vol. 124(C), pages 121-125.
    • Handle: RePEc:eee:stapro:v:124:y:2017:i:c:p:121-125
    DOI: 10.1016/j.spl.2017.01.009
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    References listed on IDEAS

    as
    1. Matteo Ludovico Bedini & Rainer Buckdahn & Hans-Jurgen Engelbert, 2016. "Unexpected Default in an Information Based Model," Papers 1611.02952, arXiv.org.
    2. Giesecke, Kay, 2006. "Default and information," Journal of Economic Dynamics and Control, Elsevier, vol. 30(11), pages 2281-2303, November.
    3. Matteo Ludovico Bedini & Rainer Buckdahn & Hans-Jurgen Engelbert, 2016. "Brownian Bridges on Random Intervals," Papers 1601.01811, arXiv.org.
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    Cited by:

    1. Mohammed Louriki, 2019. "Brownian bridge with random length and pinning point for modelling of financial information," Papers 1907.08047, arXiv.org, revised Dec 2021.

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