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Numerical analysis of rating transition matrix depending on latent macro factor via nonlinear particle filter method

Author

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  • Hidetoshi Nakagawa

    (Graduate School of International Corporate Strategy, Hitotsubashi University, Hitotsubashi 2-1-2, Chiyoda-ku, Tokyo 101-8439, Japan)

  • Hideyuki Takada

    (Department of Information Science, Toho University, Miyama 2-2-1, Funabashi, Chiba 274-8510, Japan)

Abstract

We propose a new nonlinear filtering model for a better estimation of credit rating transition matrix consistent with the hypothesis that rating transition intensities as well as dynamics of financial asset prices depend on some unobservable macroeconomic factor. We attempt a branching particle filter method to numerically obtain the conditional distribution of the latent factor. For an illustration, we analyze a rating transition history of Japanese enterprises. As a result, we realize that our model can capture some contagion effect of credit events and an interpolative role of financial market information on the rating transition intensities.

Suggested Citation

  • Hidetoshi Nakagawa & Hideyuki Takada, 2014. "Numerical analysis of rating transition matrix depending on latent macro factor via nonlinear particle filter method," Journal of Financial Engineering (JFE), World Scientific Publishing Co. Pte. Ltd., vol. 1(03), pages 1-31.
    • Handle: RePEc:wsi:jfexxx:v:01:y:2014:i:03:n:s2345768614500263
    DOI: 10.1142/S2345768614500263
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    References listed on IDEAS

    as
    1. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
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