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Incorporating multi-dimensional tail dependencies in the valuation of credit derivatives.
- Source :
-
Quantitative Finance . Dec2011, Vol. 11 Issue 12, p1803-1814. 12p. 3 Diagrams, 2 Charts, 4 Graphs. - Publication Year :
- 2011
-
Abstract
- The need for an accurate representation of tail risk has become increasingly acute in the wake of the credit crisis. We introduce a hyper-cuboid normal mixture copula that permits the representation of complex tail-dependence structures in a multi-dimensional setting. We outline an efficient pattern-recognition calibration methodology that can identify tail dependencies independent of the number of risk factors considered. This model is used to develop a new framework for pricing credit derivative instruments, and we derive semi-analytical and analytical pricing formulae for a first-to-default swap and illustrate with an example valuation. Model assumptions are validated against iTraxx Series 5 equity data over an 8-year period. Identification and representation of tail dependencies is crucial to further the study of contagion dynamics, and our model provides a basis for future research in this area. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14697688
- Volume :
- 11
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Quantitative Finance
- Publication Type :
- Academic Journal
- Accession number :
- 67098389
- Full Text :
- https://doi.org/10.1080/14697688.2010.544324