A likelihood ratio test for stationarity of rating transitions
Abstract: "We study the time-stationarity of rating transitions, modelled by a time-continuous discrete-state Markov process and derive a likelihood ratio test. For multiple Markov processes from a multiplicative intensity model, maximum likelihood parameter estimates can be written as martingale transform of the processes, counting transitions between the rating states, so that the profile partial likelihood ratio is asymptotically χ2-distributed. An application to an internal rating data set reveals highly significant instationarity." [author's abstract]
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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Postprint
begutachtet (peer reviewed)
In: Journal of Econometrics ; 155 (2009) 2 ; 188-194
- DOI
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10.1016/j.jeconom.2009.10.016
- URN
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urn:nbn:de:0168-ssoar-268513
- Rights
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Open Access unbekannt; Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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25.03.2025, 1:54 PM CET
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Associated
Time of origin
- 2009
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Phase transitions, complexity, and stationarity in the production of polyrhythms
Obtaining reliable Likelihood Ratio tests from simulated likelihood functions
Likelihood Ratio Tests for Principal Components
Likelihood ratio tests for grouped observations
Testing Homogeneity of Time-Continuous Rating Transitions
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Modelling Rating Transitions
Phase transitions, complexity, and stationarity in the production of polyrhythms
Obtaining reliable Likelihood Ratio tests from simulated likelihood functions
Likelihood Ratio Tests for Principal Components
Likelihood ratio tests for grouped observations
Testing Homogeneity of Time-Continuous Rating Transitions
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Robust likelihood ratio tests for incomplete economic models