An Overview of Factor Modeling for CDO Pricing

Laurent, Jean‐Paul; Cousin, Areski

doi:10.1002/9781118266915.ch7

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…Note that the above procedure for MGB2 distribution is still applicable for any other one-factor model, in which θ is replaced by the common factor. The probability mass function of N (t) is given by matching the coefficient of the polynomial terms of the same order in (8) and (9).…”

Section: Distributions Of Number Of Default and Time Of Mth Defaultmentioning

confidence: 99%

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Pricing synthetic CDO with MGB2 distribution

Cui

2014

Statistics and Its Interface

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In this paper we apply MGB2 distribution to price synthetic CDO. MGB2 distribution has flexible dependence structure and it is suitable to model extreme risk. The monotonicity of the spread of equity tranche with respect to some parameter is shown. We compare our model with the onefactor Gaussian, Clayton and double t models. Although our proposed MGB2 model is not flexible enough to produce the implied compound correlation smile, it is much more flexible to produce the patterns of base correlation curve than the others. Besides, concerning base correlation, MGB2 and double t model match the market data better than the Gaussian and Clayton copula models.

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Section: Distributions Of Number Of Default and Time Of Mth Defaultmentioning

confidence: 99%

“…A modeler is then left to choose the number of the factors and specify the distributions of them so that the model can fit the market prices well. For more details about factor model for multi-name credit derivatives pricing, we refer the readers to [9,10].…”

Section: Introductionmentioning

confidence: 99%

Pricing synthetic CDO with MGB2 distribution

Cui

2014

Statistics and Its Interface

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Valuation of portfolio loss derivatives in an infectious model

Cousin

Dorobantu

Rullière

2012

Mathematical and Statistical Methods for Actuarial Sciences and Finance

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Dependent defaults and losses with factor copula models

Ackerer¹,

Vatter

2017

Dependence Modeling

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Abstract:We present a class of exible and tractable static factor models for the term structure of joint default probabilities, the factor copula models. These high-dimensional models remain parsimonious with paircopula constructions, and nest many standard models as special cases. The loss distribution of a portfolio of contingent claims can be exactly and e ciently computed when individual losses are discretely supported on a nite grid. Numerical examples study the key features a ecting the loss distribution and multi-name credit derivatives prices. An empirical exercise illustrates the exibility of our approach by tting credit index tranche prices.

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An Overview of Factor Modeling for CDO Pricing

Cited by 5 publications

References 44 publications

Pricing synthetic CDO with MGB2 distribution

Pricing synthetic CDO with MGB2 distribution

Valuation of portfolio loss derivatives in an infectious model

Dependent defaults and losses with factor copula models

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