Numerical Analysis of Rating Transition Matrix Depending on Latent Macro Factor via Nonlinear Particle Filter Method

Journal of Financial Engineering, Vol.1, Issue 3, 2014

27 Pages Posted: 26 Dec 2014

See all articles by Hidetoshi Nakagawa

Hidetoshi Nakagawa

Hitotsubashi University Business School

Hideyuki Takada

Toho University

Date Written: June 27, 2014

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

Suggested Citation

Nakagawa, Hidetoshi and Takada, Hideyuki, Numerical Analysis of Rating Transition Matrix Depending on Latent Macro Factor via Nonlinear Particle Filter Method (June 27, 2014). Journal of Financial Engineering, Vol.1, Issue 3, 2014, Available at SSRN: https://ssrn.com/abstract=2542692

Hidetoshi Nakagawa

Hitotsubashi University Business School ( email )

National Center for Sciences
2-1-2 Hitotsubashi,
Chiyoda-ku,, 1018439
Japan
342123104 (Phone)

Hideyuki Takada (Contact Author)

Toho University ( email )

Room 4421
Miyama 2-2-1
Funabashi, Chiba 274-8510
Japan
(+81)-47-472-1856 (Phone)

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