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S&P - Public Finance Criteria (2007). - The Global Clearinghouse

S&P - Public Finance Criteria (2007). - The Global Clearinghouse

S&P - Public Finance Criteria (2007). - The Global Clearinghouse

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Cross Sector <strong>Criteria</strong>folio increases, especially when one allows for correlationamong participants.Modeling Loss RatesMore incremental analyses of pools became possibleas computers became faster, and the value ofiterative statistical methods was better understood.While often the actual default probability distributionof a specific pool may not be determined theoretically,it can be approximated and observedthrough repeated random trials, just as the repeatedflipping of a coin will reveal the true probability ofheads to be 50%. Standard & Poor’s quantitativegroup within structured finance has developed softwarethat uses a Monte Carlo methodology, featuringsuch an iterative process to estimate the defaultrate probability distribution for any pool entered.<strong>The</strong> software has now been adapted to allow forthe analysis of municipal pools as well. From thisdistribution is derived a set of stressed default rateswhich vary according to the pool rating desired.This methodology fully captures the effects ofobligor concentration, correlation, and obligorcredit quality in a simultaneous manner, thus permittingmore insight into incremental changes inpool credit quality as pool composition evolves.To derive the portfolio default probability distribution,a default matrix is used to assign a specificdefault probability to each participant obligationbased on the nature of the participant, its creditquality, and the obligation’s maturity.Model InputsTo run the simulation, the model requires each participant’sasset type, par amount, rating, and maturities.For most governmental entities, the asset typewill be the postal abbreviation for the state inwhich the participant is located. For non-profitorganizations and certain other sectors, a sectorspecificcode should be used (see table 1). <strong>The</strong> assettype designation helps determine the correlationbetween participants. Model inputs, or assets, areat the maturity level, so a pool of 20 participantswith amortizing loans, each with 20 years remainingon their obligations under the pool would have20 x 20 or 400 assets. Alternatively, each loan maybe entered as a single asset, using the final maturityor the weighted average maturity. Maturities arerequired as the model uses the participant’s rating,security, and length of maturity to arrive at participantdefault probabilities. <strong>The</strong> model then runs aseries of trials from which the default probabilitydistribution and resulting stressed default rates aregenerated. While Standard & Poor’s will distributeversions of the model so that pool programs mayuse and become familiar with the software, we willalso require that participants provide the necessarydata so that we may run the default analysis inhousebefore issuing a rating.Cash Flow AnalysisOnce default stress levels have been established, theissuing agency will be asked to prepare cash flowsincorporating the default assumptions. Because themodel produces aggregate portfolio default rates,default rates should be applied against aggregaterepayments available to service debt each year thatdefaults are recognized. To translate the percent ofasset or loan portfolio defaults into amounts neededto absorb these defaults, recovery rates must alsobe considered. Recovery rates will vary based onthe nature of pool participants and the securitybeing pledged (see table 1). For state revolvingfunds (SRFs) and other government or quasi-governmentpublic purpose pools backed by water andsewer utility pledges or GOs, the assumption thatobligors remain in default for four years and thenbegin paying principal, interest, and other requiredpayments in full (at 100%) will continue. Poolsconsisting of other types of obligations or that lackgovernment motive and oversight will have recoveryrates less than 100% after the four-year defaultperiod. <strong>The</strong> methodology employed by the programadministrators in granting loans to participatingentities and monitoring the ongoing financial andoperating status of the borrowers may also influenceduration assumptions.While the Monte Carlo model reveals how muchof the pool should be expected to default, it revealsnothing about the expected timing of defaults.Standard & Poor’s will assume that all defaultsbegin to occur over a four-year period, with 25%occurring each year over the period. <strong>The</strong> end resultis that default scenarios will show some level ofdefault over a seven-year period (rather than a fouryearperiod), but 100% of the assumed defaults willoccur in only one year (rather than four years). Putanother way, if the assumed default rate for a givenportfolio at a given rating is 40%, then 25% x40%, or 10% of aggregate debt service should bedefaulted in the first year of defaults, 50% x 40%,or 20% in the second year, 75% x 40%, or 30% inthe third year, and 100% x 40% in the fourth year.Finally, recovery levels should be factored in toarrive at net defaulting amounts in each year. Inyear five of the previous example, if we assume90% recovery, then of the 10% of defaults thatbegan in year one, 10% x 90%, or 9% wouldbegin paying again, resulting in a net default rate of40%-9%, or 31% (see table 2).A pool’s vulnerability to participant defaults mayvary over the life of the rated bonds, so cash flowruns should also demonstrate that the pool canwithstand the stressed default rate at any point in44 Standard & Poor’s <strong>Public</strong> <strong>Finance</strong> <strong>Criteria</strong> <strong>2007</strong>

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