Balakrishna, B S (2010): Levy Subordinator Model: A Two Parameter Model of Default Dependency.
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Abstract
Subordinators are Levy processes with nondecreasing sample paths. They are natural processes to model default dependency. They help ensure that the loss process is nondecreasing leading to a promising class of dynamic models. The simplest subordinator is the Levy subordinator, a maximally skewed stable process with index of stability 1/2. Interestingly, this simplest subordinator turns out to be the appropriate choice as the basic process in modeling default dependency. It involves just two parameters to assess dependency risk, a measure of correlation and that of the likelihood of a catastrophe. Its attractive feature is that it admits a closed form expression for its distribution function. This helps in automatic calibration to individual hazard rate curves and efficient pricing with Fast Fourier Transform techniques. It is structured similar to the onefactor Gaussian copula model and can easily be implemented within the framework of the existing computational infrastructure. As it turns out, the Gaussian copula model can itself be recast into this framework highlighting its limitations. The model can also be investigated numerically with a Monte Carlo simulation algorithm. As is now well appreciated, random recovery is helpful in better pricing of the senior tranches and the model admits a tractable framework of random recovery. The model is investigated numerically and the implied base correlations are presented over a wide range of its parameters. The investigation also demonstrates its ability to generate reasonable hedge ratios.
Item Type:  MPRA Paper 

Original Title:  Levy Subordinator Model: A Two Parameter Model of Default Dependency 
Language:  English 
Keywords:  default risk; correlation smile; CDO; Levy process; subordinator; semianalytical; FFT; copula; catastrophe 
Subjects:  G  Financial Economics > G1  General Financial Markets > G13  Contingent Pricing ; Futures Pricing 
Item ID:  26274 
Depositing User:  S Balakrishna 
Date Deposited:  31. Oct 2010 17:09 
Last Modified:  23. Feb 2013 20:24 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/26274 
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