A hidden Markov model of credit quality

被引：21

作者：

Korolkiewicz, Malgorzata W. ^{[1
]}

Elliott, Robert J. ^{[2
]}

机构：

[1] Univ S Australia, Sch Math & Stat, Adelaide, SA 5001, Australia

[2] Univ Calgary, Haskayne Sch Business, Calgary, AB T2N 1N4, Canada

来源：

JOURNAL OF ECONOMIC DYNAMICS & CONTROL | 2008年 / 32卷 / 12期

关键词：

Credit quality; Filtering; Hidden Markov models; EM algorithm;

D O I：

10.1016/j.jedc.2008.03.006

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper presents a hidden Markov model of credit quality dynamics, and highlights the use of filtering-based estimation methods for models of this kind. We suppose that the Markov chain governing the 'true' credit quality evolution is hidden in 'noisy' or incomplete observations represented by posted credit ratings. Parameters of the model, namely credit transition probabilities, are estimated using the EM algorithm. Filtering methods provide recursive updates of optimal estimates so the model is 'self-calibrating'. The estimation procedure is illustrated with an application to a data set of Standard & Poor's credit ratings. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：3807 / 3819

页数：13

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