# Fast Computation of the Expected Tranche Loss of CDO Credit Portfolio (Scripts) 1.0

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• Last update: 5 years ago
• Price: Free |
• Operating system: Linux, Mac OS X, Win All, BSD, Solaris
• Publisher: Pavel Okunev (1 other programs)
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## Fast Computation of the Expected Tranche Loss of CDO Credit Portfolio (Scripts) Publisher's description

### The code is explained in the article P. Okunev, "A Fast Algorithm for Computing Expected Loan Portfolio Tranche Loss in the Gaussian Factor Model", LBNL-57676, 2005

The code is explained in the article P. Okunev, "A Fast Algorithm for Computing Expected Loan Portfolio Tranche Loss in the Gaussian Factor Model", LBNL-57676, 2005.

http://www-library.lbl.gov/docs/LBNL/576/7.../LBNL-57676.pdf

Futher refinments of this algorithm are descibed in Okunev, Pavel, "Using Hermite Expansions for Fast and Arbitrarily Accurate Computation of the Expected Loss of a Loan Portfolio Tranche in the Gaussian Factor Model" .

http://ssrn.com/abstract=748625

This is a MATLAB code. It's relatively easy to adapt it for VBA.

ATTENTION: This code was tested and works well for portfolios of size 125. The accuracy will decrease for smaller portfolios. Higher accuracy can be achieved using the methos described in Okunev, Pavel, "Using Hermite Expansions for Fast and Arbitrarily Accurate Computation of the Expected Loss of a Loan Portfolio Tranche in the Gaussian Factor Model" .

http://ssrn.com/abstract=748625

This implements one factor Gaussian model.

[loss]=gsloss(L,w,p,a,d,N)
L = exposures,as fraction of total
portfolio, taking into account the recovery rate
Example: loan 1 is 0.01 fraction of the total portfolio, recovery rate is
40% then L(1)=0.01*(1-0.4)
p = default probabilities
a = attachement point
d = detachment point
N = number of names in the portfolio
loss = expected tranche loss as percentage of the portfolio nominal
expressed in basis points

#### System Requirements:

MATLAB 7 (R14)
Program Release Status: Major Update
Program Install Support: Install and Uninstall

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