Estimation in the continuous time mover‐stayer model with an application to bond ratings migration
- 1 April 2004
- journal article
- research article
- Published by Wiley in Applied Stochastic Models in Business and Industry
- Vol. 20 (2) , 155-170
- https://doi.org/10.1002/asmb.531
Abstract
The usual tool for modelling bond ratings migration is a discrete, time‐homogeneous Markov chain. Such model assumes that all bonds are homogeneous with respect to their movement behaviour among rating categories and that the movement behaviour does not change over time. However, among recognized sources of heterogeneity in ratings migration is age of a bond (time elapsed since issuance). It has been observed that young bonds have a lower propensity to change ratings, and thus to default, than more seasoned bonds.The aim of this paper is to introduce a continuous, time‐non‐homogeneous model for bond ratings migration, which also incorporates a simple form of population heterogeneity. The specific form of heterogeneity postulated by the proposed model appears to be suitable for modelling the effect of age of a bond on its propensity to change ratings. This model, called a mover–stayer model, is an extension of a Markov chain.This paper derives the maximum likelihood estimators for the parameters of a continuous time mover–stayer model based on a sample of independent continuously monitored histories of the process, and develops the likelihood ratio statistic for discriminating between the Markov chain and the mover–stayer model. The methods are illustrated using a sample of rating histories of young corporate issuers. For these issuers the default probabilities predicted by the Markov chain and mover–stayer models are different. In particular for 1–4 years old bonds the mover–stayer model estimates substantially lower default probabilities from rating C than a Markov chain. Copyright © 2004 John Wiley & Sons, Ltd.Keywords
This publication has 18 references indexed in Scilit:
- Bayesian inference for the mover–stayer model in continuous time with an application to labour market transition dataJournal of Applied Econometrics, 2003
- Analyzing rating transitions and rating drift with continuous observationsJournal of Banking & Finance, 2002
- The importance and subtlety of credit rating migrationJournal of Banking & Finance, 1998
- A mover-stayer mixture of Markov chain models for the assessment of dedifferentiation and tumour progression in breast cancerJournal of Applied Statistics, 1997
- Markov ChainsPublished by Cambridge University Press (CUP) ,1997
- An extended mover—stayer model for diagnosing the dynamics of trial and repeat for a new brandApplied Stochastic Models and Data Analysis, 1996
- On maximum likelihood estimation in the moverstayer modelCommunications in Statistics - Theory and Methods, 1996
- Statistical Models Based on Counting ProcessesPublished by Springer Nature ,1993
- A Markov Chain Model for Unskilled Workers and the Highly MobileJournal of the American Statistical Association, 1990
- Maximum Likelihood Estimation in the Mover-Stayer ModelJournal of the American Statistical Association, 1984