Journal of Credit Risk
ISSN:
1744-6619 (print)
1755-9723 (online)
Editor-in-chief: Linda Allen and Jens Hilscher
Time series models for credit default swap premiums
Márton Eifert
Need to know
- Introduction to Lévy-driven continuous-time ARMA processes (CARMA)
- Implementation of a method for the recovery of the driving Lévy process
- Application to a large set of observed CDS premia time series
- Estimation of the distribution law yields Normal Inverse Gaussian Lévy increments
Abstract
ABSTRACT
We present statistical models for the continuous-time dynamics of credit default swap (CDS) premiums within an intensity-based credit risk modeling framework. Based on historical daily CDS premiums for a large set of different corporate reference entities from several developed countries, we fit continuous-time autoregressive movingaverage processes of an appropriate order driven by a Lévy process. We recover the driving noise process, which only shows a stochastic volatility effect for particular branches. On a distributional level, the increments of the noise process are, as a rule, best modeled by a normal inverse Gaussian distribution.
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