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

Hidetoshi Nakagawa () and Hideyuki Takada ()
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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

Journal of Financial Engineering (JFE), 2014, vol. 01, issue 03, 1-31

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.

Keywords: Credit risk; credit rating transition; nonlinear filtering; branching particle filter (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1142/S2345768614500263

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