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A Fast Algorithm for Computing Expected Loan Portfolio Tranche Loss in the Gaussian Factor Model

Author

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  • Pavel Okunev

    (LBNL & UC Berkeley)

Abstract

We propose a fast algorithm for computing the expected tranche loss in the Gaussian factor model. We test it on a 125 name portfolio with a single factor Gaussian model and show that the algorithm gives accurate results. We choose a 125 name portfolio for our tests because this is the size of the standard DJCDX.NA.HY portfolio. The algorithm proposed here is intended as an alternative to the much slower Moody's FT method.

Suggested Citation

  • Pavel Okunev, 2005. "A Fast Algorithm for Computing Expected Loan Portfolio Tranche Loss in the Gaussian Factor Model," Risk and Insurance 0506002, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpri:0506002
    Note: Type of Document - pdf; pages: 6
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/ri/papers/0506/0506002.pdf
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    Cited by:

    1. Pavel Okunev, 2005. "Using Hermite Expansions for Fast and Arbitrarily Accurate Computation of the Expected Loss of a Loan Portfolio Tranche in the Gaussian Factor Model," Finance 0506015, University Library of Munich, Germany.
    2. Pavel Okunev, 2005. "Fast Computation of the Economic Capital, the Value at Risk and the Greeks of a Loan Portfolio in the Gaussian Factor Model," Risk and Insurance 0507004, University Library of Munich, Germany.

    More about this item

    Keywords

    Moody's Fourier Transform method; portfolio loss distribution; DJCDX; CDS portfolio; CDS; expected tranche loss;
    All these keywords.

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