An approximate multi-period Vasicek credit risk model
Rubén García-Céspedes and
Manuel Moreno
Journal of Banking & Finance, 2017, vol. 81, issue C, 105-113
Abstract:
Financial institutions and regulators usually measure credit risk only over a one-year time horizon. Hence, current statistical models can generate closed-form expressions for the one-year loss distribution. Losses over longer horizons are considered using scenario analysis or Monte Carlo simulation. This paper proposes a simple multi-period credit risk model and uses Taylor expansion approximations to estimate the multi-period loss distribution. In this paper we extend the currently available second-order Taylor expansion approximations to credit risk with a third-order term and we use this new approximation to obtain the loss distribution in the multi-period framework. Our results show that the approximation is more accurate under recessions or for portfolios with high probability of default. We also show that, in general, the effect of this third-order adjustment is quite small.
Keywords: Finance; Credit risk; Approximate methods; Multi-period models (search for similar items in EconPapers)
JEL-codes: C15 C63 G21 (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378426617301048
Full text for ScienceDirect subscribers only
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:eee:jbfina:v:81:y:2017:i:c:p:105-113
DOI: 10.1016/j.jbankfin.2017.05.002
Access Statistics for this article
Journal of Banking & Finance is currently edited by Ike Mathur
More articles in Journal of Banking & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().