## Links to all tutorial articles (same as those on the Exam pages)## Credit Portfolio View- Written by Mukul Pareek
- Created on Monday, 27 December 2010 22:13
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This is the second of five articles that discuss the various approaches to measuring credit risk in a portfolio. This article covers CreditPortfolio view. CreditPortfolio View is conceptually not too dissimilar from the Credit Metrics model described earlier, ie it relies upon a knowledge of the transition matrices between the different credit ratings. The only difference is that the transition matrix itself has an adjustment applied to it for the business cycle. But once this adjusted transition matrix has been obtained, the rest of the process works in the same way as for the Credit Metrics model.
is the Conditional transition matrix. How do we derive the ‘factor’? M x Factor The factor is just the conditional probability of default in period divided by the unconditional (or historical) probability of default in the same period. This is expressed as follows:tWhere is the unconditional transition matrix, and M is the conditional probability of default in period t, and P_{j,t} is the unconditional probability of default in period t. (Consider the entire expression to be one variable, not a product of ϕP_{j,t} and ϕ.).P_{j,t}
Now Here, is an index value derived using a multi-factor regression model that considers a number of macro economic factors, Y_{j,t} representing the industry and t the time period. jvaries between 0 and 1, and represents the probability of default for speculative grade issuers.P_{j,t} Using simulation, one can generate values of over a multi-period horizon, apply it to the historical transition matrix from the rating agencies, and simulate the value of the credit portfolio to calculate the bottom 5th or 1st percentile.P_{j,t} The exact mathematics and mechanics of the above are beyond the scope of the handbook – understanding the above conceptually should suffice. |