S&P revised their proposed criteria, most notably by applying strict leverage limits to only the AAA rating category. The limit imposes a 75:1 maximum ration to all credits, while original proposition included a dichotomy between structured finance at 20:1 and municipal credits at the now-adopted 75:1. While this uniformity concedes that a hard cap should consider the most-credit worthy insured portfolio (as The Dragon advised), the level of the limit is debatable.
The nature of the risk premium shows that the leverage ratio for bond insurers should be substantially higher than banks of equivalent creditworthiness as pointed out here and exemplified here. The exact level is admittedly part art, making an outright condemnation of S&P's limit difficult. However within the realm of what S&P had been considering, the rating agency certainly took the right path.
The wording of some of the modifiers and tests such as the capital adequacy model suggests S&P opened the criteria to more discretion of its analysts, another point for which we argued. The overall construction of the model still resembles a Rube Goldberg project, but less rickety. This is worse news for the future accuracy of S&P's model than for the guarantors. Having a rigid model allows the guarantors to game the system. For starts, lower credits and and stop-loss structures just became more attractive, especially for guarantor's seeking a AAA rating and on large and structured finance credits where expected recoveries are lower.
For all intensive purposes, this is really only immediately applicable to Assured Guaranty.
That explains why Assured made some convincing points regarding the recovery strength unique to guarantors which S&P applied. Given recent events in put-back litigation, its shocking that similar adjustments aren't made on the structured finance side. To S&P's credit, neither The Dragon nor Assured called for such adjustments. Then again, there were greater concerns.
There are other disappointments. For example:
-Investing in self-insured obligations considered a negative after low hurdle is met despite no additional credit risk taken on.
-Applying higher that expected stress losses to largest obligors test that contemplates "benign" environment.
-Largest obligors test measured across ratings categories and not sub-sector.
Nonetheless, this model is a drastic improvement and we applaud S&P for addressing areas of concern. Assured made a non-committal press release after the model was announced (and their stock shot up over 10%). While we are not going to rebuild the capital adequacy model, Assured's business risk profile is likely to be the top score given the industry score (of 2, second best) and the guarantor's being the best positioned in the industry. The business risk profile is determined by a matrix of industry score and competitive position.
Furthermore, the company's operating performance, management, financial flexibility, and liquidity scores should be the best in the industry. Even if Assured scored the worst possible - a 6 - on capital adequacy, it could reach the top half of scores with modifications from those other modifying scores. Given a top business risk profile, Assured would have to score in the bottom half of the financial risk profile score to fall out of the AA category. That should not be the case and - without actually applying many of the metrics - we'll bet it will not be the case.
Showing posts with label In Defense of Bond Insurance. Show all posts
Showing posts with label In Defense of Bond Insurance. Show all posts
Saturday, August 27, 2011
Friday, April 29, 2011
Actual Leverage Ratios and Risk Premiums
The Dragon has previusly commented on misguided interpretations of leverage. Being exceptionally skilled at absent-minded meandering, some data presented itself exactly where we did not look. Specifically, in a paper examining another recent spectacular blow up entitled "Leveraged Municipal Bond Arbitrage, What Went Wrong?" (Deng et al., 2009). They offer the following calculations on a portfolio of long AAA municipal bonds with spreads to after-tax (@ a 35% rate) treasuries of the same maturity:
That leaves 9.6 basis points to credit risk. So in relation to a financial institution (such as a bank) that is investing in these securities, a guarantor is baring 6.5% of the risk increment of the security above and beyond treasuries. Notably, that percentage gives no consideration to interest rate risk as priced in term premiums. Furthermore, the insurer receives a benefit from the optionality and possible early retirment of its risk rather than the opportunity cost risked by an investor.
All of this naively assumes that risk is accurately priced. Risk itself assures that we essentially always pay too much or too little for an exposure. However even with an exceptional marign of error, the magnitude shown in this example is striking.
Of course, spreads widen with lower grade bonds but that is due not only to increased credit risk but also to increased liquidity risk as those bonds tend to be issued by smaller, less frequent issuers. This is especially true in the municipal market. Lower credits are also less liquid because investors generally require more due diligence to cozy up to a credit. Wide bid-ask spreads and historical default rates suggest that attributing even 25% of AAA-A spread to credit risk is too much, but we will use that number in the example that follows.
For reference, here are the historical default rates published in the Municipal Bond Fairness Act (HR 6308) (here) (which led to Moody's and Fitch recalibrating) and found on Wikipedia as of April 2011 here.
Lets take the numbers from Deng et al and combine them with current environment spreads to account for interest rate risk and spreads between AAA and A rated munis. As of 4/19/11, the AAA 20-1 year term spread is about 400 basis points. To the benefit of our detractors, we will normalize that to 250. Also as of 4/19/11, the 20 year A - AAA muni spread is 93 basis points, which we will trust to approximate normal
Please visit this link to see the model:
https://spreadsheets.google.com/ccc?key=0AlFMaAd3v9o0dE9obFlmZWdwaTdlRFh1V1pncU8xaGc&hl=en_GB
The output indicates that 6.7% of the total risk is attributable to credit (note that the earlier 6.5% AAA number did not include term risk in the total risk denominator.) As such, the equivalent of a 10x bank leverage ratio would be a 149x FG leverage ratio. This indicates that threshold leverage ratios suggested by S&P and Fitch are too low for their intended uses.
While not nearly thorough, we contend this example has been balanced and conservative. The rating agencies ought to publish something that very much outdoes this summary investigation before instituting proposed leverage ratios.
Our average estimated liquidity risk premium for January 2005 through April 30, 2007 is 74.7 basis points. From January 2005 to April 2007 option costs and average liquidity risk explain 138 basis points of the 147.6 basis points the brokerage firms marketed as an arbitrage opportunity.
That leaves 9.6 basis points to credit risk. So in relation to a financial institution (such as a bank) that is investing in these securities, a guarantor is baring 6.5% of the risk increment of the security above and beyond treasuries. Notably, that percentage gives no consideration to interest rate risk as priced in term premiums. Furthermore, the insurer receives a benefit from the optionality and possible early retirment of its risk rather than the opportunity cost risked by an investor.
All of this naively assumes that risk is accurately priced. Risk itself assures that we essentially always pay too much or too little for an exposure. However even with an exceptional marign of error, the magnitude shown in this example is striking.
Of course, spreads widen with lower grade bonds but that is due not only to increased credit risk but also to increased liquidity risk as those bonds tend to be issued by smaller, less frequent issuers. This is especially true in the municipal market. Lower credits are also less liquid because investors generally require more due diligence to cozy up to a credit. Wide bid-ask spreads and historical default rates suggest that attributing even 25% of AAA-A spread to credit risk is too much, but we will use that number in the example that follows.
For reference, here are the historical default rates published in the Municipal Bond Fairness Act (HR 6308) (here) (which led to Moody's and Fitch recalibrating) and found on Wikipedia as of April 2011 here.
Cumulative historic default rates (in percent)
------------------------------------------------------------------------
Moody's S&P
Rating categories ---------------------------------------
Muni Corp Muni Corp
------------------------------------------------------------------------
Aaa/AAA......................... 0.00 0.52 0.00 0.60
Aa/AA........................... 0.06 0.52 0.00 1.50
A/A............................. 0.03 1.29 0.23 2.91
Baa/BBB......................... 0.13 4.64 0.32 10.29
Ba/BB........................... 2.65 19.12 1.74 29.93
B/B............................. 11.86 43.34 8.48 53.72
Caa-C/CCC-C..................... 16.58 69.18 44.81 69.19
Investment grade................ 0.07 2.09 0.20 4.14
Non-invest grade................ 4.29 31.37 7.37 42.35
All............................. 0.10 9.70 0.29 12.98
------------------------------------------------------------------------Lets take the numbers from Deng et al and combine them with current environment spreads to account for interest rate risk and spreads between AAA and A rated munis. As of 4/19/11, the AAA 20-1 year term spread is about 400 basis points. To the benefit of our detractors, we will normalize that to 250. Also as of 4/19/11, the 20 year A - AAA muni spread is 93 basis points, which we will trust to approximate normal
Please visit this link to see the model:
https://spreadsheets.google.com/ccc?key=0AlFMaAd3v9o0dE9obFlmZWdwaTdlRFh1V1pncU8xaGc&hl=en_GB
The output indicates that 6.7% of the total risk is attributable to credit (note that the earlier 6.5% AAA number did not include term risk in the total risk denominator.) As such, the equivalent of a 10x bank leverage ratio would be a 149x FG leverage ratio. This indicates that threshold leverage ratios suggested by S&P and Fitch are too low for their intended uses.
While not nearly thorough, we contend this example has been balanced and conservative. The rating agencies ought to publish something that very much outdoes this summary investigation before instituting proposed leverage ratios.
Sunday, January 30, 2011
Of Banks and Bond Insurers - Leverage
Upon the release of S&P's recent request for comment on proposed criteria for rating bond insurers, an astonished Mark Tapley looked to the available formal compositions for reference on the matter. He found very little and resolved to think it out himself. So sit back, relax and let The Blue Dragon cure your insomnia... or skip to the end to read the summary.
---
This post attempts to shed light on leverage as it relates to bond insurance. The discussion focuses on components of the risk premium by way of comparison with banking as that is a more widely understood and accepted practice. An obvious mathematical relationship unveils itself to relate capital ratios between banks and bond insurers. Extrapolating upon that relationship reveals basic, common sense rules for evaluating bond insurers.
----
Some market participants have observed that bond insurance is an uneconomical business. The usual claim identifies the leverage in the business as unsustainable. As an introduction and to the end of better understanding the historical precedence in which entire sectors of finance are misunderstood, we start with a little history and a definition from Merriam-Webster: "Usury - 1. archaic: interest."
This term once applied to charging any interest at all. Interest has been considered criminal at many different times across a wide range of nations and religions including Islam, Judaism and Christianity. Today, a claim of usury in the Western world would refer to the charging of exorbitant interest rates. The development of this word has followed the development of finance. The modern banking system takes it for granted that interest rates provide a just and proper incentive for entities to lend by compensating for the risks inherent in lending.
That it has not always been so should give pause to those that would dismiss the idea of bond insurance as nonviable. A similar effect should be caused by the history of insurance. Almost 4,000 years ago, ancient Babylonians developed a system as part of the Code of Hammurabi that smacks of debt insurance. In the system, a borrower could pay a premium to a lender for the lender's guarantee that it would forgive the loan under certain circumstances (i.e. the borrowers goods are stolen.) This is the reverse of modern bond insurance. A simple understanding of markets informs us that the premium and risk in such circumstances could be forwarded by the lender to another party. The role of that hypothesized third party is the role bond insurers play today; the present and the ancient display two sides of the same coin.
But history is good for so much preambling. The economics are what count.
The economics of credit risk are a large determinant of the economics of the bond insurance business. The economics of the entire risk premium are a large determinant of the economics of banking. One may observe that the risk premium of a bond can be sliced and diced various ways but there exist three basic components: interest rate risk, liquidity risk and credit risk. These three risks have been separately priced in actual markets. For example, municipal entities have issued bonds in which an issuer bears interest rate risk, banks bear liquidity risk via stand-by purchase agreements and bond insurers bear the credit risk through financial guarantee contracts. The isolation of these three components of the risk premium are not merely theoretical.
A traditional bank exposes itself to all of these risks when lending without credit enhancement, so an examination of that institution behooves an understanding of these risks. A bank funds long-term loans with short term liabilities. The potential for swift withdrawals exposes a bank to liquidity risk above and beyond the contingent demands on liquidity experienced by other market participants. This funding risk is normally benign but spikes during panics, depressions and recessions. The Federal Reserve Bank System was in large part created as a lender of last resort (a role previously played by John Pierpont Morgan, Sr.), to help alleviate the vicious cycles of runs on banks.
On the other hand, a financial guaranty insurance company (an FGI) with a typical capital structure has negligible funding risk. The collateral calls that destroyed AIG Financial Products were an example of funding risk that must be considered when assessing the risks of an FGI. Exposure to mark-to-market settlement and its implication for potential ballooning and acceleration of insurance liabilities should also be considered in the risk profile of a particular FGI. With properly written insurance contracts an FGI faces neither interest rate nor liquidity risk in its portfolio of insured exposures. A well structured FGI then will only face interest rate and liquidity risk in its investment portfolio which is of a size many times smaller than its insured exposure. Importantly, the FGI is not in the business of mismatching assets and liabilities; rather, the FGI optimizes its investment portfolio through some process that balances contingent liability immunization and return on investment maximization.
If we consider all risk to be accurately priced then it is possible to mathematically relate bank capital ratios with those of bond insurers. Specifically, a bank's loan portfolio requires a certain amount of capital to achieve a certain overall risk profile. An FGI exposed to the exact same loan portfolio but through insurance will require a smaller capital ratio to obtain a risk profile equivalent to the bank. The exact relationship between those ratios is mathematically determined by a simple and eloquent formula.
If,
(BC) x (CDS) / (RP) = (FC)
and therefore,
(FC) / (CDS) x (RP) = (BC)
then,
Brisk = FGrisk
where,
BC = the bank's capital ratio
CDS = cost of the credit insurance with negligible counter party risk
RP = the entire risk premium
FC = the financial guarantor's capital ratio equivalent
Brisk = bank's risk profile
FGrisk = the financial guarantor's risk profile
The greatest insights will be garnered from this equivalence when normalized (cycle-neutral) numbers are used. Analysts must be careful in applying the necessary assumptions to obtain such normalization. The formula can be applied to garner information across industries or to particular insurers. In evaluating particular bond insurers, the weighted average components of the risk premium of the particular insurer should be applied.
The sensitivity of the model to the CDS component highlights the sensitivity of appropriate capital ratios for a given risk profile. Intuitively, if the loan portfolio has less credit risk, the FC:BC ratio will be higher at a given risk profile. This can be extrapolated across FGIs that maintain equivalent risks other than the credits in the insured portfolio. (Assuming such equivalent risk maintenance is unrealistic but allows for the following insight. Also, embedded within such assumption is the equivalence of debt service outstanding distribution and present value on the insured portfolio.) With all else equal, consider a low risk FGI taking on one half the credit risk per unit of debt-service insured compared to a base case FGI. The low risk FGI will have an equivalent risk profile to the base case FGI when the low risk FGI insures twice the debt-service as the base case FGI.
The same logic that proves that an FGI will have a higher capital leverage ratio than a bank of equivalent risk, also proves that an FGI insuring better credits than another FGI must insure more credits to reach an equivalent risk profile. Both aspects of this conclusion are intuitively pleasing. They also highlight the importance of the credits being insured.
Summary
This has been a very preliminary look at the nature of bond insurance and the credit leverage inherent to the business. Traces of bond insurance are found in ancient history, indicating that the economic benefits of insurance have long applied to credit. However, the actual economics of the business determine its viability and the best methods for assessing the industry. In assessing the risks inherent to the business, certain prescriptions for capital structure and policy writing present themselves. As applied to total capital leverage, appropriate levels can be surmised by a simple mathematical extrapolation from better established capital ratios in the banking sector. Those formulas and that logic can be used to assess capital leverage of particular FGIs and draw conclusions about the FGIs risk profile. Capital leverage ratios are only one component of the risk profile of an FGI. Further consideration regarding the distribution of debt-service insured, credit diversification, capital structure and economic catastrophe is warranted and will be discussed at a later time.
---
This post attempts to shed light on leverage as it relates to bond insurance. The discussion focuses on components of the risk premium by way of comparison with banking as that is a more widely understood and accepted practice. An obvious mathematical relationship unveils itself to relate capital ratios between banks and bond insurers. Extrapolating upon that relationship reveals basic, common sense rules for evaluating bond insurers.
----
Some market participants have observed that bond insurance is an uneconomical business. The usual claim identifies the leverage in the business as unsustainable. As an introduction and to the end of better understanding the historical precedence in which entire sectors of finance are misunderstood, we start with a little history and a definition from Merriam-Webster: "Usury - 1. archaic: interest."
This term once applied to charging any interest at all. Interest has been considered criminal at many different times across a wide range of nations and religions including Islam, Judaism and Christianity. Today, a claim of usury in the Western world would refer to the charging of exorbitant interest rates. The development of this word has followed the development of finance. The modern banking system takes it for granted that interest rates provide a just and proper incentive for entities to lend by compensating for the risks inherent in lending.
That it has not always been so should give pause to those that would dismiss the idea of bond insurance as nonviable. A similar effect should be caused by the history of insurance. Almost 4,000 years ago, ancient Babylonians developed a system as part of the Code of Hammurabi that smacks of debt insurance. In the system, a borrower could pay a premium to a lender for the lender's guarantee that it would forgive the loan under certain circumstances (i.e. the borrowers goods are stolen.) This is the reverse of modern bond insurance. A simple understanding of markets informs us that the premium and risk in such circumstances could be forwarded by the lender to another party. The role of that hypothesized third party is the role bond insurers play today; the present and the ancient display two sides of the same coin.
But history is good for so much preambling. The economics are what count.
The economics of credit risk are a large determinant of the economics of the bond insurance business. The economics of the entire risk premium are a large determinant of the economics of banking. One may observe that the risk premium of a bond can be sliced and diced various ways but there exist three basic components: interest rate risk, liquidity risk and credit risk. These three risks have been separately priced in actual markets. For example, municipal entities have issued bonds in which an issuer bears interest rate risk, banks bear liquidity risk via stand-by purchase agreements and bond insurers bear the credit risk through financial guarantee contracts. The isolation of these three components of the risk premium are not merely theoretical.
A traditional bank exposes itself to all of these risks when lending without credit enhancement, so an examination of that institution behooves an understanding of these risks. A bank funds long-term loans with short term liabilities. The potential for swift withdrawals exposes a bank to liquidity risk above and beyond the contingent demands on liquidity experienced by other market participants. This funding risk is normally benign but spikes during panics, depressions and recessions. The Federal Reserve Bank System was in large part created as a lender of last resort (a role previously played by John Pierpont Morgan, Sr.), to help alleviate the vicious cycles of runs on banks.
On the other hand, a financial guaranty insurance company (an FGI) with a typical capital structure has negligible funding risk. The collateral calls that destroyed AIG Financial Products were an example of funding risk that must be considered when assessing the risks of an FGI. Exposure to mark-to-market settlement and its implication for potential ballooning and acceleration of insurance liabilities should also be considered in the risk profile of a particular FGI. With properly written insurance contracts an FGI faces neither interest rate nor liquidity risk in its portfolio of insured exposures. A well structured FGI then will only face interest rate and liquidity risk in its investment portfolio which is of a size many times smaller than its insured exposure. Importantly, the FGI is not in the business of mismatching assets and liabilities; rather, the FGI optimizes its investment portfolio through some process that balances contingent liability immunization and return on investment maximization.
If we consider all risk to be accurately priced then it is possible to mathematically relate bank capital ratios with those of bond insurers. Specifically, a bank's loan portfolio requires a certain amount of capital to achieve a certain overall risk profile. An FGI exposed to the exact same loan portfolio but through insurance will require a smaller capital ratio to obtain a risk profile equivalent to the bank. The exact relationship between those ratios is mathematically determined by a simple and eloquent formula.
If,
(BC) x (CDS) / (RP) = (FC)
and therefore,
(FC) / (CDS) x (RP) = (BC)
then,
Brisk = FGrisk
where,
BC = the bank's capital ratio
CDS = cost of the credit insurance with negligible counter party risk
RP = the entire risk premium
FC = the financial guarantor's capital ratio equivalent
Brisk = bank's risk profile
FGrisk = the financial guarantor's risk profile
The greatest insights will be garnered from this equivalence when normalized (cycle-neutral) numbers are used. Analysts must be careful in applying the necessary assumptions to obtain such normalization. The formula can be applied to garner information across industries or to particular insurers. In evaluating particular bond insurers, the weighted average components of the risk premium of the particular insurer should be applied.
The sensitivity of the model to the CDS component highlights the sensitivity of appropriate capital ratios for a given risk profile. Intuitively, if the loan portfolio has less credit risk, the FC:BC ratio will be higher at a given risk profile. This can be extrapolated across FGIs that maintain equivalent risks other than the credits in the insured portfolio. (Assuming such equivalent risk maintenance is unrealistic but allows for the following insight. Also, embedded within such assumption is the equivalence of debt service outstanding distribution and present value on the insured portfolio.) With all else equal, consider a low risk FGI taking on one half the credit risk per unit of debt-service insured compared to a base case FGI. The low risk FGI will have an equivalent risk profile to the base case FGI when the low risk FGI insures twice the debt-service as the base case FGI.
The same logic that proves that an FGI will have a higher capital leverage ratio than a bank of equivalent risk, also proves that an FGI insuring better credits than another FGI must insure more credits to reach an equivalent risk profile. Both aspects of this conclusion are intuitively pleasing. They also highlight the importance of the credits being insured.
Summary
This has been a very preliminary look at the nature of bond insurance and the credit leverage inherent to the business. Traces of bond insurance are found in ancient history, indicating that the economic benefits of insurance have long applied to credit. However, the actual economics of the business determine its viability and the best methods for assessing the industry. In assessing the risks inherent to the business, certain prescriptions for capital structure and policy writing present themselves. As applied to total capital leverage, appropriate levels can be surmised by a simple mathematical extrapolation from better established capital ratios in the banking sector. Those formulas and that logic can be used to assess capital leverage of particular FGIs and draw conclusions about the FGIs risk profile. Capital leverage ratios are only one component of the risk profile of an FGI. Further consideration regarding the distribution of debt-service insured, credit diversification, capital structure and economic catastrophe is warranted and will be discussed at a later time.
Wednesday, January 26, 2011
Response to S&P Proposals
26 January 2011
Regarding Aspects of Fundamental Analysis and Rules in S&P’s Proposed Bond Insurance Criteria.
To: Standard and Poor’s
Various measures have been developed in the course of time to assist the financial analyst in her quest for valuable insight. Five years ago, S&P was using quantitative determinants for ratings in structured finance. However, the run-up to the financial crisis saw these parameters supplant fundamental analysis.
Your proposal for bond insurer rating criteria includes large swaths of fundamental analysis. I commend you for including stressed scenario analysis (32-35 and 50-56) and related analysis to answer the questions: “What are the chances of default? What would recoveries likely be?” But I encourage you to consider making your models more flexible. In January 2008, would it have been appropriate to model 3 or 4 years of growth in NPO before a stress period as the measure of capital adequacy? A crisis does not come with a four year warning, please allow your analysts to look at the most appropriate horizons as dictated by changing circumstances. I also encourage your analysts to focus on liquidity bottlenecks, or peaks in large amounts of concentrated (or correlated) lower quality insured debt service. I understand this is a more labor intensive method that may be called for only in extenuating circumstances. In short, enable and encourage S&P analysts to think like a chief risk officer; do not relegate them to administration of data and rigid parameters.
Such rigid parameters are witnessed in S&P’s newly proposed leverage limits (29-31). These static limits would account for a mezzanine tranche and a super-senior tranche of the same deal equally. As stated, exposure size would also rate zero-coupon and premium bonds equally. Given the impartial treatment of par outstanding and considering that these are absolute limits, S&P should believe there is no feasible institution that could be both AAA and in violation of these limits. However three months ago, S&P considered such an institution to exist in Assured Guaranty at multiples of the proposed limits. This will result in lower ratings for the only insurance company that was able to write business throughout the recent experience. If such inflexible limits are applied, they should be a high-limit safety net and not a low-limit Maginot Line.
I have found your S&P grading systems helpful when considering specific facets of a credit. Your proposed grading scales (22-28) will be no exception. However, it offends logic to think the inflexible relationships between these scores will not greatly benefit from common sense fundamental analysis.
Frustrated athletes often revert to bad habits, S&P must remember that rigid models have been gamed and train-wrecked before. A kaleidoscope of numbers easily produces an illusion of precision. But such a structured illusion will only offer an opportunity for your analyst to defer to a Rube Goldberg project of scores connecting to matrices to limits. This class of machine appears to do much but in the end only fries an egg; and normally the egg is burnt. Your good cooks can do better!
The remaining leaders of the bond insurance industry have asked for a more stable ratings regime. They may not agree with my rejection of overwhelming reliance on inflexible models and limits. As an analyst, investor and observer, I suggest S&P look within; reexamine the sectors in which S&P has the best and worst ratings track records. Municipal bond ratings have been stable, predictive and founded on key tenants of ability and willingness to pay. Then look at RMBS.
Regards,
Mark Tapley
The Blue Dragon
http://tapleysbluedragon.
tapleysbluedragon@gmail.com
--
Connect with me on LinkedIn: http://uk.linkedin.com/pub/
Regarding Aspects of Fundamental Analysis and Rules in S&P’s Proposed Bond Insurance Criteria.
To: Standard and Poor’s
Various measures have been developed in the course of time to assist the financial analyst in her quest for valuable insight. Five years ago, S&P was using quantitative determinants for ratings in structured finance. However, the run-up to the financial crisis saw these parameters supplant fundamental analysis.
Your proposal for bond insurer rating criteria includes large swaths of fundamental analysis. I commend you for including stressed scenario analysis (32-35 and 50-56) and related analysis to answer the questions: “What are the chances of default? What would recoveries likely be?” But I encourage you to consider making your models more flexible. In January 2008, would it have been appropriate to model 3 or 4 years of growth in NPO before a stress period as the measure of capital adequacy? A crisis does not come with a four year warning, please allow your analysts to look at the most appropriate horizons as dictated by changing circumstances. I also encourage your analysts to focus on liquidity bottlenecks, or peaks in large amounts of concentrated (or correlated) lower quality insured debt service. I understand this is a more labor intensive method that may be called for only in extenuating circumstances. In short, enable and encourage S&P analysts to think like a chief risk officer; do not relegate them to administration of data and rigid parameters.
Such rigid parameters are witnessed in S&P’s newly proposed leverage limits (29-31). These static limits would account for a mezzanine tranche and a super-senior tranche of the same deal equally. As stated, exposure size would also rate zero-coupon and premium bonds equally. Given the impartial treatment of par outstanding and considering that these are absolute limits, S&P should believe there is no feasible institution that could be both AAA and in violation of these limits. However three months ago, S&P considered such an institution to exist in Assured Guaranty at multiples of the proposed limits. This will result in lower ratings for the only insurance company that was able to write business throughout the recent experience. If such inflexible limits are applied, they should be a high-limit safety net and not a low-limit Maginot Line.
I have found your S&P grading systems helpful when considering specific facets of a credit. Your proposed grading scales (22-28) will be no exception. However, it offends logic to think the inflexible relationships between these scores will not greatly benefit from common sense fundamental analysis.
Frustrated athletes often revert to bad habits, S&P must remember that rigid models have been gamed and train-wrecked before. A kaleidoscope of numbers easily produces an illusion of precision. But such a structured illusion will only offer an opportunity for your analyst to defer to a Rube Goldberg project of scores connecting to matrices to limits. This class of machine appears to do much but in the end only fries an egg; and normally the egg is burnt. Your good cooks can do better!
The remaining leaders of the bond insurance industry have asked for a more stable ratings regime. They may not agree with my rejection of overwhelming reliance on inflexible models and limits. As an analyst, investor and observer, I suggest S&P look within; reexamine the sectors in which S&P has the best and worst ratings track records. Municipal bond ratings have been stable, predictive and founded on key tenants of ability and willingness to pay. Then look at RMBS.
Regards,
Mark Tapley
The Blue Dragon
http://tapleysbluedragon.
tapleysbluedragon@gmail.com
--
Connect with me on LinkedIn: http://uk.linkedin.com/pub/
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