Structural credit risk models with Lévy processes

the VG and NIG cases

Chiara Brambilla, Martin Gurny, Sergio Ortobelli Lozza

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We propose alternative structural credit risk models for determining probabilities of default (PDs) based on two well-known Lévy processes - the Variance Gamma (VG) process and the Normal Inverse Gaussian (NIG) process, respectively. In particular, using Lévy processes, we propose a methodology to overcome the distributional drawbacks of the classical Merton model. Therefore, we discuss an empirical comparison of estimated PDs obtained from the VG and the NIG models on a dataset of 24 companies with strong capitalization in the US market. The empirical evidence suggests that both the models are able to capture the situation of instability that affects each company in considered period and, in fact, are very sensitive to the periods of the financial crisis.

Original languageEnglish
Pages (from-to)101-119
Number of pages19
JournalFar East Journal of Mathematical Sciences
Volume97
Issue number1
DOIs
Publication statusPublished - 2015

Keywords

  • Credit risk
  • Default probabilities
  • Lévy processes
  • Structural models

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