Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/48698
Authors: 
Weißbach, Rafael
Mollenhauer, Thomas
Year of Publication: 
2011
Series/Report no.: 
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2011: Die Ordnung der Weltwirtschaft: Lektionen aus der Krise - Session: Interest Rates A16-V2
Abstract: 
The time-continuous discrete-state Markov process is a model for rating transitions. One parameter, namely the intensity to migrate to an adjacent rating state, implies an ordinal rating to have an intuitive metric. State-specific intensities generalize the state-stationarity. Observing Markov processes from a multiplicative intensity model, the maximum likelihood parameter estimators for both models can be written as a martingale transform of the processes that count transitions between the rating states. A Taylor expansion reveals consistency and asymptotic normality of the parameter estimates, resulting in a chi-square-distributed likelihood ratio of state-stationarity and the state-specific model. This extents to time-stationarity. Simulations contrast the asymptotic results with finite samples. An application to a sufficiently large set of credit rating histories shows that the one-parameter model can be a good starting point.
Subjects: 
Rating
Metricality
Multiple Markov process
Counting process
Likelihood ratio
JEL: 
C33
C41
G33
Document Type: 
Conference Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.