Time Series Models for Credit Default Swap Premiums

24 Pages Posted: 16 Jun 2016

See all articles by Márton Eifert

Márton Eifert

Technische Universität München (TUM)

Date Written: August 14, 2015

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 moving average 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.

Keywords: continuous-time ARMA processes, CARMAprocesses, credit default swaps, intensitybased models, normal inverse Gaussian process;,Ornstein–Uhlenbeck process.

Suggested Citation

Eifert, Márton, Time Series Models for Credit Default Swap Premiums (August 14, 2015). Journal of Credit Risk, Vol. 11, No. 3, 2015. Available at SSRN: https://ssrn.com/abstract=2795525

Márton Eifert (Contact Author)

Technische Universität München (TUM) ( email )

Arcisstrasse 21
Munich, 80333
Germany

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