Credit Risk in an Economy with New Firms Arrivals

Silvia Centanni (), Immacolata Oliva and Paola Tardelli ()
Additional contact information
Silvia Centanni: University of Verona
Paola Tardelli: University of L’Aquila

Methodology and Computing in Applied Probability, 2017, vol. 19, issue 3, 891-912

Abstract: Abstract We propose a dynamic model to analyze the credit quality of firms. In the market in which they operate, the firms are divided into a finite number of classes representing their credit status. The cardinality of the population can increase, since new firms can enter the market and the partition is supposed to change over time, due to defaults and changes in credit quality, following a class of Markov processes. Some conditional probabilities related to default times are investigated and the role of occupation numbers is highlighted in this context. In a partial information setting at discrete time, we present a particle filtering technique to numerically compute by simulation the conditional distribution of the number of firms in the credit classes, given the information up to time t.

Keywords: Heterogeneous populations; Particle filter; Default correlation; Credit risk; 92D25; 92D15; 93E11; 60G35; 62L20; 91G40 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s11009-016-9525-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metcap:v:19:y:2017:i:3:d:10.1007_s11009-016-9525-4

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-016-9525-4

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().