A Fast Algorithm for Computing Expected Loan Portfolio Tranche Loss in the Gaussian Factor Model
نویسنده
چکیده
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 [1]. 1 The Gaussian Factor Model Let us consider a portfolio of N loans. Let the notional of loan i be equal to the fraction fi of the notional of the whole portfolio. This means that if loan i defaults and the entire notional of the loan is lost the portfolio loses fraction fi or 100fi% of its value. In practice when a loan i defaults a fraction ri of ∗This work was supported by the Director, Office of Science, Office of Advanced Scientific Computing Research, of the U.S. Department of Energy under Contract No. DEAC03-76SF00098.
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