2009
DOI: 10.1007/s11009-009-9142-6
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Initial and Final Backward and Forward Discrete Time Non-homogeneous Semi-Markov Credit Risk Models

Abstract: In this paper we show how it is possible to construct an efficient Migration models in the study of credit risk problems presented in Jarrow et al. (Rev Financ Stud 10:481-523, 1997) with Markov environment. Recently it was introduced the semi-Markov process in the migration models (D'Amico et al. Decis Econ Finan 28:79-93, 2005a). The introduction of semi-Markov processes permits to overtake some of the Markov constraints given by the dependence of transition probabilities on the duration into a rating catego… Show more

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Cited by 33 publications
(26 citation statements)
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“…This difference is explained only by the different starting time s. This means that really the non-homogeneity play an important role in the description of the rating dynamics. Additional results and indicators on the semi-Markov rating migration model can be applied as suggested in [8,10,11].…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…This difference is explained only by the different starting time s. This means that really the non-homogeneity play an important role in the description of the rating dynamics. Additional results and indicators on the semi-Markov rating migration model can be applied as suggested in [8,10,11].…”
Section: Resultsmentioning
confidence: 99%
“…Other improvements could be obtained by analysing duration dependent indicators which can be considered in the semi-Markov framework as showed in [10] and [11].…”
Section: Discussionmentioning
confidence: 99%
“…Markov chains are of interest in a wide range of applications, for example, telecommunication systems [1,2], remanufacturing and inventory systems [3], speech recognition [4], PageRank [5][6][7], microbial gene [8], and AIDS [9]. In recent years, the predictions of data sequences have become more and more useful in other applications such as sales demand prediction [10], DNA sequencing [11], credit risk [12], and stock prices [13].…”
Section: Introductionmentioning
confidence: 99%
“…The credit risk problem is widely discussed in the financial literature (D' Amico et al 2010). Risk assessment is accomplished by estimating the probability of occurrence and severity of risk impact (Zavadskas et al 2010).…”
Section: Introductionmentioning
confidence: 99%