PubFinCriteria_2006_part1_final1.qxp

exposure, or any noteworthy component scores.

The MPE measures how much a counterparty could

expect to lose on a transaction over the life of the

transaction if the other counterparty failed to per-

form its obligations on the swap. MPEs are typical-

ly two standard deviation value-at-risk calculations

using relatively standard techniques for projecting

potential paths of future interest rates. MPEs are

influenced by the swap’s notional amount, average

life, and the terms of the trade—fixed-to-floating

swap, floating-to-fixed, floating-to-floating—and

the optionality embedded in the swap. We will ask

the issuer to calculate a MPE for swaps that are in

danger of terminating early. If necessary, we will

use the MPE and measure it against the issuer’s liq-

uidity reserves to determine the credit impact of

swap termination.

Net variable rate exposure

We will calculate a net variable-rate interest expo-

sure ratio for all issuers of variable rate debt and/or

swaps for use in conjunction with any DDP score.

The net variable exposure measures the potential

risk to an issuer’s revenue stream and reserve levels

resulting from rising variable rates. Net variable

rate exposure ratio incorporates all current interest

rate derivatives, fixed and floating rate debt, and

any natural hedges (i.e., qualified investment assets

designed to offset interest rate risk). The exposure

ratio will also be calculated on a pro forma basis to

gauge prospective levels of variable exposure, given

either proposed derivatives structures or future

bond issuance. For example, some issuers have

entered into swaptions that may become effective in

the future, depending upon the level of interest

rates. If we are concerned that a counterparty may

have an incentive to terminate a fixed-to-floating

rate swaption on an issuer, we will assess the poten-

tial exposure of future variable interest rates for the

issuer through the net variable rate exposure calcu-

lation. Another example is an issuer that partially

hedges a 30-year variable rate issue for 10 years

with a floating-to-fixed rate swap. Through this

simulation, we are able to determine the impact of

rollover risk, or the risk that the issuer will not be

able to re-hedge its variable rate exposure upon

expiration of the swap.

Conclusion

In an effort to hedge risks, many entities are enter-

ing into derivative instruments that have a long,

successful history. Understanding the risks associat-

ed with these types of agreements is critical. With

our DDP, Standard & Poor’s adds an independent

evaluation of the risks associated with certain deriv-

atives and the potential impact on credit quality

and ratings.■

Long-Term Municipal Pools ..............................................................................................

http://www.standardandpoors.com 43

S

tandard & Poor’s Ratings Services criteria for rating

pools of municipal obligations reflects the fact that

the likelihood of default of bonds secured by a pool of

assets is a function of both the expected distribution of

defaults within the asset pool, and the level of over-col-

lateralization available to cure those defaults. The like-

lihood that an obligor will cause a bond pool to

default depends on the obligor’s credit quality and the

influence of that obligor on the total performance of

the pool (the pool’s relative concentration or diversity).

To the extent that additional funds (through reserves or

coverage) can provide protection against a certain level

of obligor defaults, then a rating commensurate with

the probability of exceeding that amount of loss may

be assigned to the pool bonds. Higher pool ratings

therefore require higher over-collateralization to protect

against higher cumulative default probabilities.

In the absence of any over-collateralization, step-

up obligations on the part of participants, or other

structural enhancements, pool ratings will typically

fall to a level at or near the rating of the lowest-

rated participant. Pool programs without step-up

provisions are not eligible for ratings above the rat-

ing of the weakest participant if the pool contains

fewer than 10 separate obligors.

While the theory behind the pool criteria would

appear straightforward, the application proves

more difficult. Determining the cumulative default

probability distribution for a pool of obligations

becomes extremely difficult as the size of the port-

Long-Term Municipal Pools