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논문검색

Valuing retail credit tranches with structural, double mixture models

초록

영어

This study considers the class of double mixtures to model a general dependence structure beyond the typical conditional independence assumption among the entities in a homogeneous credit portfolio. The two mixing components are i) the marginal distributions of the systemic and idiosyncratic factors and ii) the conditional probability measure that incorporates the further dependence structure among the idiosyncratic factors, given the systemic factor. For a large portfolio, the fair spread of a structured retail credit tranche is expressed in terms of the sums of single integrals, which can be easily computed numerically. We discuss the behaviors of tranche spreads under several double mixture models, and calibrate these models to market data.

목차

Abstract
 1 Introduction
 2 Model framework
 3 Double mixture models
 4 Retail credit tranche pricing
 5 Numerical examples
 6 Model calibration on real data
 7 Conclusions
 Appendix
 References

저자정보

  • Taehan Bae Assistant Professor, Department of Mathematics and Statistics, University of Regina, Regina, Saskatchewan, Canada.
  • Ian Iscoe Lead Mathematician, Risk Analytics, IBM Inc., Toronto, Ontario, Canada.
  • Changki Kim Assistant Professor, Korea University Business School, Seoul, Korea.

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