# Fast Computation of the Expected Tranche Loss 1.0

OS : Windows / Linux / Mac OS / BSD / Solaris

Script Licensing : Free for non-commercial purposes.

Created : Aug 14, 2007

Downloads : 2

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## The code is explained in the article P. Okunev, "A ...

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

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" .

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

ATTENTION: This code was tested and works well for portfolio 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".

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)

w = loading factors

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

Copyright by Pavel Okunev 2005

E-mail: pokunev@math. lbl. gov

This code is provided as is. The author provides no warranty and assumes no responsibility for any losses due to the use of this code.

You are granted permission to use this code for personal use and for academic research.

This code may not be used for commercial purposes without explicit permission by the author.

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" .

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

ATTENTION: This code was tested and works well for portfolio 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".

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)

w = loading factors

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

Copyright by Pavel Okunev 2005

E-mail: pokunev@math. lbl. gov

This code is provided as is. The author provides no warranty and assumes no responsibility for any losses due to the use of this code.

You are granted permission to use this code for personal use and for academic research.

This code may not be used for commercial purposes without explicit permission by the author.

**• MATLAB Release: R14**

**Demands:****Fast Computation of the Expected Tranche Loss 1.0 scripting tags:**cdo credit port, factor, pavel, loss, expected, gaussian, tranche, earth sciences, okunev, code, portfolio, expected tranche loss.

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