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Monte Carlo based collateralized loan obligation (CLO) valuation under

Sundin, Karl LU (2010) NEKA31 20092
Department of Economics
Abstract (Swedish)
In this thesis a model for valuing an arbitrary collateralized loan obligation (CLO) is implemented. A CLO is a structured credit product whose performance relies on a pool of corporate loans. Valuation
in the context of this thesis is the price on a CLO security and the distribution for the price. The major driver behind the performance of the loan pool is the default distribution among obligors. Along with
individual default probabilities the default dependence structure is the main factor influencing the default distribution. The dependence structure is hard to observe in the market, it is therefore of
interest to see how various dependence structures affect the CLO valuation and thus how much effort should be put into finding the... (More)
In this thesis a model for valuing an arbitrary collateralized loan obligation (CLO) is implemented. A CLO is a structured credit product whose performance relies on a pool of corporate loans. Valuation
in the context of this thesis is the price on a CLO security and the distribution for the price. The major driver behind the performance of the loan pool is the default distribution among obligors. Along with
individual default probabilities the default dependence structure is the main factor influencing the default distribution. The dependence structure is hard to observe in the market, it is therefore of
interest to see how various dependence structures affect the CLO valuation and thus how much effort should be put into finding the most suitable dependence model. The dependence structure for the defaults in the pool is modeled using three different copulas namely; Gaussian, Student t and Clayton. The computation is done using Monte Carlo simulations. I my results I find that the dependence structure affects the valuation of different CLO securities differently. My conclusion is
that the impact is not great enough to justify time consuming efforts to find the right dependence structure since there are a lot of other potentially larger error sources in the valuation. (Less)
Please use this url to cite or link to this publication:
author
Sundin, Karl LU
supervisor
organization
course
NEKA31 20092
year
type
M2 - Bachelor Degree
subject
keywords
Monte Carlo, collateralized loan obligation, CLO, copula
language
English
id
1614891
date added to LUP
2010-06-14 13:47:34
date last changed
2010-06-14 13:47:34
@misc{1614891,
  abstract     = {{In this thesis a model for valuing an arbitrary collateralized loan obligation (CLO) is implemented. A CLO is a structured credit product whose performance relies on a pool of corporate loans. Valuation
in the context of this thesis is the price on a CLO security and the distribution for the price. The major driver behind the performance of the loan pool is the default distribution among obligors. Along with
individual default probabilities the default dependence structure is the main factor influencing the default distribution. The dependence structure is hard to observe in the market, it is therefore of
interest to see how various dependence structures affect the CLO valuation and thus how much effort should be put into finding the most suitable dependence model. The dependence structure for the defaults in the pool is modeled using three different copulas namely; Gaussian, Student t and Clayton. The computation is done using Monte Carlo simulations. I my results I find that the dependence structure affects the valuation of different CLO securities differently. My conclusion is
that the impact is not great enough to justify time consuming efforts to find the right dependence structure since there are a lot of other potentially larger error sources in the valuation.}},
  author       = {{Sundin, Karl}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Monte Carlo based collateralized loan obligation (CLO) valuation under}},
  year         = {{2010}},
}