September 05, 2007
Was 1991 a Real Credit Crunch or a Head Fake?
In this week's issue of The Institutional Risk Analyst, we take a look at some of the public data Basel II factors for the top-five US money center banks and ask a basic question: what if the "maxi" credit correction of the early 1990s, when the lead unit of Citigroup, Citibank NA, reported a peak of 360bp of defaults, was not really an outlier compared to the credit correction now underway?
That is, if you use 1991 as a worst case scenario in your VaR analysis, will you under shoot or over shoot the credit default wave that is hitting the US economy as you ponder these words?
Comments? Questions?
Posted by whalenc at 10:25 PM
June 19, 2007
Black Swan Hunting: Equity Markets and Random Events
This week we published a comment on Nassim Taleb's book, The Black Swan, which you may read by clicking the link below:
The Institutional Risk Analyst
The point of the comment was to reflect on how we often don't see the forest for the trees in life, as illustrated by the efforts to eradicate cholera in 19th Century England and the market reaction to the change in rules for stock buybacks by the US Internal Revenue Service.
A couple of PRMIA members responded by saying that they were less impressed with The Black Swan than with Taleb's first book, Fooled by Randomness.
One senior manager of equity operations at a bulge bracket shop reflected that life is not so complex or random as Taleb supposes.
Another PRMIA member in the audit sector reflects on the tax rules change:
"The failure to predict and model potential changes in tax regimes is only failure in as much as those held captive by models fail to consider behavioral implications. There is and has been a tendency to seek to limit those who 'cheat' the system. The options backdating scandals are a great example, as is the IRS regulatory change. In New Zealand this is known as the 'Tall Poppy Syndrome' Any poppy that grows too tall gets its top hacked off.
The options backdating scandal was completely predictable from a behavioral perspective, but not from a financial modeling perspective. As it became clear that backdating of options was transferring wealth from one group (the shareholders) to another (specific executives), it was only a matter of time before such behavior would either become authorized in accounting rules, and therefore model able, or that shareholders would rebel, using the SEC as their poppy hacker."
"The fundamental lesson is not that the IRS regulatory response, or the SEC’s response to options backdating, were “Black Swans”, but that our risk management models do not adequately consider the behavioral implications of economic activity. But then, that might have been your whole point here…"
Another reader opined:
"I am mid-way thru Black swan, and recommend taleb's first book "fooled by random." Just back from europe and could NOT PUT DOWN Richard Bookstarter's a Demon of our own Design. takes taleb's stuff to real world-boostarter was the Head Risk Officer at sollie and morgan stanley. it will scare the sh.. out of you. The real risk, in my opinion, is in public companies where the quants have audited certified numbers and can leverage them up 5 times greater(with derivatives) than the private ones where there are limited numbers much less audited ones."
Posted by whalenc at 07:28 AM
May 15, 2007
Pillar III Validation: Will Basel II Finally Discredit VAR?
Below is the latest issue of our news and comment, The Institutional Risk Analyst, which was inspired by a comment from a PRMIA member. I very much appreciate your input and encourage one and all to send reports, term sheets, apocryphal tales and other feedback care of this thread. If you see a deal or transaction that strikes you as remarkable, let us know -- Chris Whalen
The Institutional Risk Analyst
May 14, 2007
"Risk management is a serious business. Accordingly, the production of a risk 'measure' must be subjected to the question 'how do you know what you claim to know' – in other words, epistemology."
Nassim Taleb
Last month, a reader at the University of Michigan asked about our March 27, 2007 comment, "Countrywide Financial: It's All About Liquidity," where we asserted that "the use of risk pricing tools such as Value at Risk or 'VAR' models and other types of statistical routines arguably amplified the effect of excess liquidity, boosting the throughput of the Wall Street mortgage origination machine, generating big fees, and vastly expanding the pool of risk for end-users."
Asked the reader: "I would like to know how VAR can cause banks to take more risk than what is acceptable. Doesn't the Fed with its extremely loose monetary policy deserve more blame?"
Good question. The Fed's "easy money" monetary policy in the early part of the decade, what we've coined as the "Greenspan Effect," clearly contributed to "exuberant" behavior by investors, pushing risk spreads below the economic cost for many assets. The spectacle last year of CDS for subprime trading at annual spreads less than a quarter of the expected default rate on such portfolios or corporate CDS trading through the yields on the underlying bonds are two cases in point.
But no matter how pernicious the Greenspan Effect, in our view, the use of risk measures such as VAR contribute far more significantly to the problem. Determining "what is acceptable" is the key issue for risk managers, both in terms of setting the minimum expected loss in a given scenario and then how to benchmark these forward-looking estimates.
To review, VAR models summarize the expected maximum loss (or worst loss) over a target horizon within a given confidence interval. To us, this is an elegant way of saying "I don't know." Or to quote the author of Fooled by Randomness, Nassim Taleb: "There is an internal contradiction between measuring risk (i.e. standard deviation) and using a tool with a higher standard error than that of the measure itself."
If you have not done so, read Taleb's excellent LSE paper, "Epistemology and Risk Management."
The trouble with VAR models is that the methodology says nothing about specific risks regarding specific transactions, yet provides risk practitioners with the false impression that the particular risk has been measured. So widespread is the delusion that VAR is effective to measure risks of particular exposures that federal regulators are about to adopt it as the central method for measuring bank capital adequacy under Basel II (see our comments to the FDIC on the Basel II proposal by clicking here.)
By providing a technical framework for estimating market risk that, on the surface at least, has credibility, the Sell Side and the major rating agencies have evolved VAR into a powerful mechanism for increasing both transaction throughput and leverage. Simply stated, if the overall risk calculated in the VAR model appears to be low, then additional risk may be taken.
Since the Greenspan Effect pushed actual default rates on loans and bonds to near zero, particularly for mortgage collateral, VAR models became the Sell Side's best friend. By relying on assumptions of normality in the distribution of possible future events and using recent historical data, VAR models effectively minimize the true financial risk taken and thus are a key enabler of the vast expansion of leverage on Wall Street.
An interesting possibility comes into prospect, however, with the implementation of Pillar III of Basel II, the requirement for market discipline, where banks will be compelled to publicly disclose and benchmark the efficacy of VAR models against their actual results, including public "mark-to-actuals" results for VAR, Defaults, Loss Given Default and Exposure at Default, etc. Will Pillar III ultimately be the undoing of VAR?
For example, if a large bank publishes a VAR of say 1% of total investments in a given period, but then takes a loss of 3% on those same investments in the subsequent period, investors (not to mention auditors and regulators) will discern pretty quickly that the bank's management is flying blind.
As former Fed Vice Chairman Roger Fergusson told Congress in 2003: "Pillar III--disclosure--will highlight any significant differences across banks, in the expectation that counterparties will penalize inconsistent risk measures."
In the event, regulators will be forced to recommend higher capital levels for those banks which are not good at predicting future losses, one reason why the Economic Capital simulation in the IRA Bank Monitor includes such prudent assumptions about future expected loss.
A number of organizations try to address the inadequacies of VAR by including obligor-specific factors in their risk models. Citigroup (NYSE:C), for example, explicitly combines VAR methodology with factors that track the specific issuer risk in debt and equity securities. But far too many organizations simply accept the basic VAR result as good enough.
If as, as we suspect, the cost of risk is rising back to the mean after almost a decade of below-average experience, then the Federal Reserve Board unwittingly may be creating the circumstances for finally discrediting the use of VAR models for estimating specific financial risks. Consider the irony: Just as global regulators are enshrining VAR as the centerpiece of the Basel II regime, markets may demonstrate that this method of measuring risk is entirely useless -- at least when expected losses are not hovering around zero.
Over the past decade, we suspect that VAR models have appeared effective because there was so little risk to measure. But in an environment where risk events are large and "unusually" frequent, we suspect that financial institutions will quickly be forced to look for alternatives. Or in political terms, when the next unexpected event (or series of events) takes down a large financial institution, we expect to see trial lawyers and members of Congress quizzing the bankers, their familiars at the rating agencies and regulators on the efficacy of VAR for predicting specific financial mishaps.
During the inevitable process of recrimination and accusation that will occur following the next big systemic financial event, we hope that somebody asks members of the Federal Reserve Board and other federal regulators why they ever agreed to adopt into regulation VAR as a means of measuring bank capital adequacy. As we wrote in our comments on Basel II: "By relying upon the false assumption that financial market events tend to follow a random, normally distributed pattern, the FDIC and other regulators are about to adopt into [the Basel II] regulation one of the most specious, dangerous and widely held misconceptions in the financial world."
By the way, to our prediction made last year that the rating agencies face big legal liability from facilitating the Street's explosion in asset securitization over the past few years ("The Golden Triangle: Banks, Hedge Funds and Ratings"), see the event just held by the Hudson Institute on May 3, "Where Did All the Risk Go?".
As Josh Rosner and Joe Mason write: "...the big three ratings agencies are often confronted with an array of conflicting incentives, which can affect choices in subjective measurements of risk. Of even greater concern, however, is the fact that the process of creating MBS and CDOs requires the ratings agencies to arguably become part of the underwriting team, leading to legal risks and even more conflicts."
More on this issue in a future IRA.
Posted by whalenc at 12:08 PM
March 18, 2007
Citibank: Benchmarking Mortgage and Subprime Risk
Below is our latest comment, which you can also read on the IRA web site by clicking here. As a special feature for PRMIA members, you can see the profile from the subscription version of the IRA Bank Monitor used in this comment by clicking here.
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The Institutional Risk Analyst
March 19, 2007
Last year, we noted that Citigroup (NYSE:C) was in the process of reducing the number of bank subsidiaries in the group, part of a trend among the largest money centers to streamline and rationalize that has seen large bank holding company ("BHC") peers like JP Morgan Chase (NYSE:JPM) slim down to just three bank units.
One of the telltale indicators that a consolidation has been completed is that the legal domicile of the successor institution has changed. Thus in the case of C lead unit Citibank NA (FDIC# 7213), the bank's legal address has changed from 399 Park Avenue in New York at the end of 2005 to 3900 Paradise Road in beautiful Las Vegas, NV.
Citibank's assets have grown from $706 billion at the end of 2005 to $1.1 trillion due to the fact that five other bank units were rolled-up, including Citibank Delaware, Citicorp Trust NA, Citi (West) FSB, Citibank Texas NA and West NA.
As a result of these mergers, Citibank's individual risk profile has now expanded to include the real estate assets of several former members of the FDICs mortgage specialization peer group, particularly the $121 billion asset Citi (West) FSB. At the end of 2006, real estate loans comprised 43% of Citibank's lending book and 24% of the bank's total assets, this vs. 15% and 8.3%, respectively, the year before. There is no net change for C on a consolidated basis, but for analysts the task of tracking individual loan category performance and building peer groups becomes a bit more labor intensive.
Of interest, now that Citibank has subsumed the mortgage assets of Citi (West) FSB, the weighted average maturity or WAM of the consolidated, bank-only profile for C has increased from 1.6 years at the end of 2005 to 3.7 years at the end of 2006. This change reflects the fact that the Office of Thrift Supervision does not release portfolio or aggregate maturity data for thrifts to the FDIC, even though the data is public. We've been trying to discover why the OTS is so intransigent regarding this key data, but no answer is forthcoming. Perhaps under Basel II OTS will be forced to publicly disclose this data like all other federal regulators.
At 454bp in gross yield, as calculated by the IRA Bank Monitor, real estate is the third most profitable area of lending for Citibank after loans to depository institutions (714bp) and miscellaneous loans (1,410bp), which is usually a euphemism for subprime loans. Indeed, looking at the high gross loan yield for Citibank's miscellaneous loans, which comprise 3.8% of total assets, subprime consumer loans is a pretty good bet.
At 110bp of default in 2006, C has one of the highest bank default rates of any large BHC and just below the 112bp of HSBC Holdings (NYSE:HBC), which recently stumbled due to rising defaults and restatements related to subprime lending at its Household Finance unit. Here's the question of the week: Will C follow in HBC's unhappy footsteps and likewise be forced to restate past period results due to subprime loans?
Posted by whalenc at 04:15 PM
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December 18, 2006
Year-End Observations and 2007 Predictions
I extend holiday greetings to all PRMIA members and wish one and all a very safe, prosperous and happy New Year. Some thoughts on the past year and prognostications on the year ahead.
2007: Credit Risk & Rising Defaults
The combination of plentiful liquidity and a mounting shortage of quality assets equates to declining credit quality for the financial system as a whole, albeit one masked beneath the high tide of easy credit. One of my favorite publications, Daily Bankruptcy News, reported a prediction by vulture investor Wilbur Ross that 7% of junk bonds will be in default by this time next year. According to S&P, the world wide junk bond default rate in October was 0.98%. In the U.S., the default rate was 1.27%. Mr. Ross predicts that defaults will rise “even in the absence of an economic downturn."
It is interesting to compare the default rates in junk bonds with the banking sector. Through the third quarter of 2006, the gross default rate for Citibank NA, the lead unit of Citigroup (NYSE:C), was a mere 96.8bp or about 120bp annualized vs. about 40bp for the peer group (yes, defaults from Citibank's decidedly sub prime portfolio run 3x peer), according to the IRA Bank Monitor. The near-term peak in defaults for Citibank NA was 246.4bp in 2002 vs. 145.9bp for the peer group. You have to go back more than a decade, to 1991, to find a bank loan default rate higher than 2002, 332.6bp for Citibank NA vs. 251bp for the peers.
Looking at the excesses visible in the credit marketplace, I wonder: Are US banks set to revisit the peak in loan defaults illustrated by the data points above? However, recall that the junk bond default rate was 12% in 1991, thus the prediction made by Mr. Ross regarding junk defaults reaching just 7% next year is still relatively modest. Good news, even, given a slowing economy. Applying the same logic to the default rate of Citibank generates a 2007 default rate around 200bp, still below the near term peak in 2002 and nowhere near 1991. Is Mr. Ross being too optimistic?
2007: Interactive Data & Counterparty Risk Management
After returning from the XBRL conference in Philadelphia last week, my colleagues at IRA hosed me down in the decontamination showers and administered the antidote for electric Kool-Aid overdose. I'm doing fine now, thanks. In the New Year, IRA will focus some of our efforts on applying Interactive Data to enhancing the collection and management of counterparty credit risk. Notice that Interactive Data is spelled with an "I", not an "X."
As IRA CEO Dennis Santiago likes to remind our clients (as well as our own troops), it's about the business case, not the technology. Leave the acronyms at the door, please.
2007: Market & Liquidity Risk: The Next Regulatory Priorites
In a marketplace comprised of less liquid securities, market risk is greater. As noted in my previous comment, regulators are intent upon increasing the capital charge for market risk for precisely this reason. Look for market risk to supplant Economic Capital atop of the US regulatory agenda in 2007.
With decimalization and the advent of electronic trading on the major exchanges, investors and the dealers which serve them have migrated away from centralized markets and toward proprietary clearing networks and products. Private equity and OTC derivatives have several common features, such as less liquidity, wider bid-offer spreads and greater profits for the most agile players. Unfortunately, when end-users want or need to liquefy positions, the bid side is frequently far away from the theoretical "fair value" used to mark these positions to the notional market.
2006/2007: Basel II/Ia: Delay and More Delay
At the beginning of 2006, IRA suggested that the Basel II proposal was in trouble because of bad political management by the Federal Reserve Board and even less adept handling of the risk management methodology issues. We regret to say that very little has changed. With two contradictory proposals out for public comment -- Basel II and Basel Ia -- we are at a loss to predict just how this situation will be resolved. The fact that the Democrats now control both houses of the Congress makes the Basel II proposals and banking issues generally less of a priority in Washington than in 2006.
I continue to believe that the best path to Basel II adoption is for the US to emulate the processes in motion around the world and have all US banks adopt the standardized approach of Basel II, using the publicly available portfolio data from the FDIC -- the same data that we use for our Basel II by the Numbers survey. Fact is that the US is ahead of the rest of the world when it comes to the details of Basel II adoption. Why? Because of the structured, machine readable financial statement data gathered by the FDIC.
Neither the nations of Europe nor Asia have any standardized, portfolio level data, public or private, to use for Basel II benchmarking. The good news is that with the comment period on Basel II extended to coincide with the Basel Ia process, I have a few months more to press my firm's case for public data benchmarking.
Posted by whalenc at 01:11 PM
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November 02, 2006
Basel II & Neoclassical Idiocies: Mark to Model Lives Again!
On Monday of this week, the FT ran a very interesting article by an author named Philip Ball, "Baroque fantasies of a most peculiar science," which discusses the heavy reliance of the economics professional on quantitative methods. You can read the article on the FT web site.
Ball's provocative comments, which we defended on the FT letters page on Wednesday, caused us to comment on the degree to which the very same quantitative methods, what we call "derivative indicators," have infected the world of credit analysis. This is not to say that we believe that Merton models and VaR analysis have no place in a financial professional's armory, but they should not be the sole or even the primary means of assessing the credit quality of an obligor.
What really troubles us, however, is the spectacle of some of the largest US banks and risk tool vendors relying almost entirely on financial models to calculate Economic Capital requirements for Basel II. If the aggregate EC calculation for a bank is built upon a series of guestimates rather than actual analysis of the financial statements of specific obligors, then we believe that the bank's management has not done its job and the financial institution itself is left open to legal claims and even regulatory sanctions.
Today the regulators may smile and agree that quantitative models are sufficient, but in the event of an event, they will be the first to condemn such methods when the Congress holds the inevitable hearings to assign blame. Our comment from this week's issue of The Institutional Risk Analyst follows below:
Note: We have turned off the comments on this blog pending a solution to the really ugly SPAM we have been receiving. Please send your comments to chris@rcwhalen.com and we'll figure out how to post them.
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The Institutional Risk Analyst
Basel II & Neoclassical Idiocies: Mark to Model Lives Again!
November 1, 2006
Our comment regarding the lessons to be taken from the Amaranth hedge fund collapse drew some sharp criticisms from the risk modeling community (See The IRA, "Counterparty Credit Risk: Amaranth Aftermath"). In particular, our assertion that VaR models are useless for assessing market or credit risk seems to have struck a raw nerve among some members of the NY risk management community. Guess there's nothing to do but start the root canal.
First it needs to be stated that we have a bias. IRA exists in order to explore, develop and deliver fundamental analytical solutions. We started our firm in 2003 because we perceived that the Street had taken quantitative methods for assessing credit risk several bridges too far, resulting in a lengthening string of risk management failures such as Enron, Parmalat and WorldCom.
These corporate scandals, let us recall, were events where fundamental indicators were shinning bright red, but none of the derivative models used by quantitative credit analysts detected a problem - until well after the fact. Readers of The IRA will recall our report on the November 2004 meeting of the International Association of Financial Engineers when one of the founders of Moody's KMV admitted that quantitative models did not provide any advance warning of Enron and other corporate failures. Small wonder then that the IAFE subsequently implored us to remove our verbatim notes of that discussion from our web site.
Just as the economic profession has become dominated by neoclassical thought, which holds that all market participants are rational and fully informed, the risk community has embraced quantitative methods to such an extreme degree that the idea of performing a classical credit analysis on obligors is not even considered. Fascination with models and the mathematical tools borrowed from quantum physics has turned the economics profession - and, we suggest, their brethren in the risk analytics community -- into what Philip Ball, writing in the FT on Monday, calls purveyors of "neoclassical idiocies."
For example, in their IMF working paper (06/134) on "Risk Models of the Financial Sector Assessment Program," Avesani, Liu, Mirestean and Salvati state that "over the last ten years, we have witnessed major advances in the field of modeling credit risk. There are now three main approaches to quantitative credit risk modeling: the "Mertonstyle" approach, the purely empirical econometric approach, and the actuarial approach… Each of these approaches has, in turn, produced several models that are widely used by financial institutions around the world."
Notice that these respected researchers do not even mention the idea of using fundamental financial factors to track the behavior of a specific obligor. In the same paper, the authors then articulate "three main approaches to estimating the probabilities of default. One approach is to use historical frequencies of default events for different classes of obligors in order to infer the probability of default for each class. Alternatively, econometric models such as logit and probit could be used to estimate probabilities of default. Finally, when available, one could use probabilities implied by market rates and spreads."
Again, the concept of focusing attention on the behavior of a specific obligor is not even considered among the contemporary methods in use today by risk professionals. Instead, derivative indicators and models, using aggregate studies of past default experience and other data, are employed to estimate the possible future behavior of obligors. So hungry are the modelers for data to feed the great engine of statistical analysis that they even admit to using bond spreads as data inputs when equity market prices are unavailable!
Contemporary risk models, to paraphrase Ball, assume a degree of homogeneity and stability among subjects that simply does not exist. Most market professionals know this statement to be true, yet the risk vendors and the largest financial institutions have such an enormous investment in quantitative methods that they are unwilling to give them up.
The situation today reminds us of another era not too long ago, when the "whiz kids" of Wall Street made the mistake of relying upon "mark to model" methods for managing the risk in their bond portfolios -- and wound up damaging their trading desks and running from the law in shame. How quickly we forget the damage done by those SPARC 2 workstations in the hands of math geniuses. When the models and real life diverged, the trade tickets were found hidden in desk drawers as the guilty parties prayed that the real world would move back towards their risk position before anyone found out.
Why are such distinctions important to risk managers and regulators, especially those working to implement Basel II? Because unless and until a more balanced approach to credit risk methodology is adopted by US financial institutions, achieving full implementation of a true "risk weighted" approach to measuring bank capital adequacy will be impossible. "Marking to model" today does the same thing it did in the 1980's, it coils the risk spring with assumptions that are ever more distant from the fundamentals.
Recall, for example, that the original Basel II proposal was meant to encourage banks to calculate specific measures for the risks in each area of business, using consistent definitions for key terms such as Probability of Default ("P(D)"), Loss Given Default, Expected Loss and Exposure at Default. The idea of the original Basel II proposal was to track the P(D) of specific obligors and facilities, aggregate these individual ratings to measure the risks in a given portfolio and institution, and then assign a required capital weight to support these risks.
Banks around the world are spending billions of dollars to comply. From Bahrain to Beijing, they are increasing the safety and soundness of their banking systems by getting to know the fundamentals of their obligors. Unfortunately, the US banking industry, enamored as it is with derivative indicators, has never answered the obligor-specific challenge originally posed by Basel II.
With a few notable exceptions such as Citigroup (NYSE:C), the largest US banks have actually increased their reliance on quantitative methods for measuring credit risk, making it impossible for most large US banks to achieve the most advanced level of Basel II where each customer is internally rated by the bank. Whereas Basel II asks about the P(D) of a specific obligor, the best that most large banks and the vendors which support them are able to do in response is to talk about estimates of risk in a portfolio containing thousands of obligors.
The excessive reliance on quantitative methods to measure credit risk is a troubling development that should concern bank leadership. Why is it that so many of the brain trusts inside institutions are allowed to perpetuate the use of aggregate statistical models when the data and capability exists to build the best bottom up Basel II credit obligor modeling systems in the world? Had this process begun five years ago, when the new Basel Accord was in formulation, surely the dissonance between the models and the fundamentals would have narrowed to manageable margins by now. It's up to leadership of the major US banks and the regulatory agencies to begin to ask why this has not happened.
In the meantime, the modeling community shall continue to tack fudge factor on top of fudge factor to twist aggregate statistics to fit expected outcomes. In paper entitled "Convergence of Credit Capital Models" just published by the International Association of Credit Portfolio Managers and the International Swaps and Derivatives Association, the authors note that new regulatory capital requirements under Basel II have been promulgated that "allow firms following an advanced approach to submit their own estimates of key parameters as input into a single regulatory formula which does not depend on portfolio composition ." The authors also note that many of the largest US banks depend primarily on models provided by third party vendors to calculate credit risk and capital requirements.
Translated into plain terms, for the purpose of determining capital adequacy under Basel II, the largest US banks are proposing to substitute estimates of future expected and unexpected losses for actual analysis of specific obligors. This same derivative methodology will no doubt be proffered to satisfy the requirements of the revised survey for Shared National Credits, which like Basel II, asks banks to provide estimates of P(D) and other credit risk measures for specific obligors.
Regulators are responding to this pressure to aggregate. Some of the responses are innovative work saving solutions that prove to us that the United States remains at the vanguard of developing better techniques for managing large and complex economic infrastructures. For instance, we see the utility of implementing lending facility risk matrices as a way to bucket groupings of C&I obligors.
But we also note that nothing in this facility bin design relieves the institution of doing the fundamental work to document why each obligor went into a particular risk bin. Nor does it relieve the institution from its safety and soundness responsibilities to monitor and report, in Pillar III fashion, the bottom-up proof that each credit facility bin is free of "moral hazard" risks to both the regulatory examiners and their fully exposed auditors. Trust us when we say that, as you read these words, some of the leading US trial lawyers are focused on precisely this issue.
Viewed from the perspective of methodology choices, the fact that some of the largest US banks are now pressing regulators and the Congress for a simpler, "standardized" version of Basel II is no surprise given that so few institutions have demonstrated the willingness or ability to perform obligor specific analysis. Indeed, while many banks and their advocates in Washington blame the regulators for the lack of progress on Basel II, perhaps it is the neoclassical brain trusts inside many of the largest US banks which are to blame for the confusion and lack of focus in the US when it comes to measuring specific credit risk.
Questions? Comments? info@institutionalriskanalytics.com
Posted by whalenc at 06:48 AM
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October 03, 2006
First LTCM, then Sumitomo, now Amaranth. What next?
Last week, IRA published a comment entitled "The Golden Triangle: Banks, Hedge Funds and Ratings" regarding the marriage of convenience between the rating agencies, the dealer banks and the hedge funds in the OTC derivative market. The inspiration for this comment was the demise of the hedge fund Amaranth, but we've been pondering the operational risks being assumed by the rating agencies for some time.
Click here to read the September 26 edition of The Institutional Risk Analyst
We made some pretty strong comments about the process whereby rating agencies have become involved in rating (and pricing) Complex Structured Financial Instruments. We got more than a few comments on that missive as well.
But since last week, we have seen and heard a number of things that make us believe that Amaranth is only the first event in a chain of hedge fund failures that will test the stability of the financial markets.
The key thing to understand about Amaranth is that these "veteran" traders put on a spread trade in natural gas that any commodity specialist would have easily identified as reckless. It appears that Amaranth bought the global energy shortage story in 2005 and missed the time tested fundamentals of the physical energy markets.
Add the distorting effects of a global marketplace awash in liquidity and the risk magnification of OTC derivatives, and the result is a hedge fund that went from reporting double digit profits to liquidation in less than 180 days.
We heard at a meeting in NY last night that JPM was stuck with a credit loss as a result of margin calls on Amaranth, but other sources close to the matter say this in untrue and more, that the crippled hedge fund met all of its margin calls on the way down. JPM was Amaranth's clearing broker for energy futures.
Indeed, we hear that JPM showed up as a potential buyer of the Amaranth energy portfolio because it expects to profit handsomely from the trade. Call this one a near miss.
The key question is, are there more hedge funds out there getting ready to threaten investors and the major OTC derivatives dealers with large losses?
When you consider that many hedge funds utilize useless VaR models to understand transactions like the energy spread trade put on by Amaranth, it becomes clear to me, at least, that we are going to see a growing number of hedge funds forced to liquidate due to "unexpected" losses in the months ahead.
As Graham & Dodd wrote many years ago, the value of analysis declines in direct proportion to the speculative characteristics of any transaction.
Posted by whalenc at 09:42 PM
April 21, 2006
Basel II ANPR: Loss Given Default and Why Definitions Are Important
In the latest interagency notice of proposed rulemaking (NPR) that would implement Basel II risk-based capital requirements in the United States for large, internationally active banking organizations, the regulators define two loss metrics for default:
Expected Loss Given Default ("ELGD"), which is stated as a percentage and is an estimate of the economic loss rate if a default occurs; and Loss Given Default ("LGD"), which is stated as a percentage and is an estimate of the economic loss rate if a default occurs during economic downturn conditions.
Is it just me or does this definition of LGD seem a bit tortured? Indeed, a cynic might say that the Fed is "talking its book" by changing the definition of LGD from the original Basel II proposal and the 2005 ANPR.
To me, LGD is simply the maximum exposure of the institution to a given obligor as a % of the existing exposure. We use this methodology in our IRA Bank Monitor product, which in turn reflects the state of the art at several of the NY money centers.
Yet by defining LGD as applying to periods of economic stress, the Fed is muddying the water, in my view. Would it not be a better idea to leave the defintition of LGD as simple as possible, but then also include a "stressed" version of the same measure? The Fed might better call such a stressed LGD something like ELGD!
Whenever I see the world "economic" in a bank performance measure, my assumption is that we are leaving the real world and are headed to the astral plain of relativity and macro economic mumbo jumbo. If the economists at the Fed want to create a measure of LGD that reflects such guestimates, that's great, but how about we come up with a new name (LGD*?) and leave hard measures of credit loss like LGD alone!
Comments? Questions?
Posted by whalenc at 09:46 AM
March 16, 2006
Was QIS IV Wrong? Basel II by the Numbers 2005
This week, IRA released a report entitled "Basel II By the Numbers 2005," including economic capital measures and Basel II credit benchmarks for US bank and thrift holding companies with assets greater than $10 billion. This report presents a "fully stressed" view of the economic capital required to avoid default under an extreme loss scenario and then compares that level of capital requirement with the minimum Tier One Risk Based Capital Measure employed by regulators.
Some highlights from the "Basel II by the Numbers 2005" report:
In contrast to the fourth Quantitative Impact Study ("QIS") sponsored by US regulators, the fully-stressed economic capital measures presented in our report suggest that the largest US banks should be required to hold more capital under Basel II than under current minimum capital requirements. Activities such as trading, derivatives and investments appear to be the dominant factor supporting this view.
Conversely, medium and smaller financial institutions included in this analysis, which were not part of the QIS survey, appear to require levels of economic capital significantly below current minimum levels of regulatory risk based capital. This observation appears to be tied to the abnormally low levels of loan defaults observed throughout the banking industry over the past five years.
The summary metrics presented in "Basel II by the Numbers 2005" are based on "as filed" data from the FDIC's Research Information Service and aggregate all loan portfolios of the subsidiary banks, rolled-up to present a "bank only" view of the respective bank and thrift holding company. These public proxies serve as a point of departure for performing capital allocation, risk management and credit analysis tasks, such as generating internal probability of default ratings for the Advanced Internal Ratings Based approach of Basel II.
Why did we prepare this report? Very simply, in our view one of the major obstacles to adoption of Basel II, but by no means the only impediment, is the lack of a set of clear, publicly available measures by which policy makers, regulators, investors, risk managers and members of the public can measure and compare how different institutions will look under the new bank capital adequacy regime.
Despite the fact that the Basel II proposal places heavy emphasis on universal concepts such as transparency and validation, these basic prerequisites to successful alignment of global bank capital and risk measures depend upon the use of privileged, non-public analytical assumptions, data and ground rules. By preparing a matrix of bank metrics using only public data, we hope to demonstrate to our colleagues in the risk world that there is a transparent and easily validated way to attack the risk measurement tasks under Basel II.
Click here to register on the IRA web site and purchase the report.
Questions? Comments?
Posted by whalenc at 09:51 AM
February 27, 2006
Calculating Economic Capital With FDIC Data for Basel II Advanced IRB Tasks
This is the first of a series of posts concerning the "how do we get there from here" issue currently dogging Basel II adoption. It has been the view of my firm for some time that you cannot validate nor politically sell Basel II in Washington unless you start the process with public data and metrics.
Below is an announcement IRA put out last week regarding our use roll-ups of US bank holding companies to calculate EC, RAROC and related measures. We also calculate all of the major Basel II metrics -- current defaults, LGD, P(D), EAD and M, albeit using simple versions of the internal measures used by the Basel banks.
What this exercise yields is a public, transparent means of benchmarking all US banks and comparing them with one another based on both EC and the various Basel credit performance measures.
Of interest, whereas our colleagues in the banking and consulting worlds are content to grind EC figures using top level GAAP data from EDGAR, the FDIC figures allows you to calculate EC using discrete data for loans, trading, investments and other particular factors.
See below. Comments? Questions?
New Release of IRA Bank Monitor Includes Holding Company Profiles and Economic Capital Measures
February 23, 2006
Institutional Risk Analytics has released a new version of the IRA Bank Monitor, the first commercially available Basel II benchmarking system for US banks that employs "as filed," structured data and calculations from the Research Information Service ("RIS") of the Federal Deposit Insurance Corporation. The new version of the IRA Bank Monitor includes:
Bank Holding Company Profiles: Profiles for all US bank and thrift holding companies are synthesized using data from FDIC Call Reports and represent a "bank only" rollup view of the subject institution. Metrics displayed include performance measures such as Return on Assets, Return on Equity (nominal and tangible), and Risk Adjusted Return on Capital ("RAROC") and Basel II risk metrics such as Loss Given Default ("LGD"), Weighted Average Maturity and Exposure at Default ("EAD").
Economic Capital Calculations: In another IRA exclusive, measures for Economic Capital ("EC") are provided for each BHC as well as subsidiary units, using hard numbers from "as-filed" CALL/TFR reports to develop risk spread factors using IRA's proprietary statistical formulae. IRA benchmarks estimate EC for credit, trading and securities using consistent groundrules to maximize comparability.
Enhanced Display & Delivery: All of the new metrics in the IRA Bank Monitor are now available for inspection and analysis either via a Web display or an Excel download using Microsoft's SpreadsheetML standard.
The table below shows RAROC, Basel II Rating and LGD for the twelve largest financial holding companies in the FDIC RIS database using calculations from the IRA Bank Monitor:
If you want to see the table formatted correctly, go to the following link:
http://us1.institutionalriskanalytics.com/pub/IRANews.asp
The IRA Bank Monitor -- Q3 2005
HOLDING COMPANY
RAROC (%)
BASEL II RATING
LOSS GIVEN DEFAULT (%)
BANK OF AMERICA
20.1
BB
76.8
JPMORGAN CHASE & CO.
3.0
BB
74.5
CITIGROUP INC.
6.63
BB
69.9
WACHOVIA CORPORATION
16.26
BBB
54.6
WELLS FARGO & COMPANY
46.79
BBB
72.6
WASHINGTON MUTUAL
124.75
A
74.3
U.S. BANCORP
53.23
BBB
69.3
SUNTRUST BANKS, INC.
40.72
BBB
63.3
ROYAL BANK OF SCOTLAND
51.42
BBB
76.5
NATIONAL CITY CORPORATION
73.57
BBB
58.8
HSBC HOLDINGS PLC
5.29
BB
67.9
GOLDENWEST FINANCIAL
159.2
AAA
35.3
RAROC = Risk Adjusted Return On Capital. Also known as Return On Economic Capital. Basel II Rating = Actual loan portfolio default rate expressed as bond rating equivalent using industry break points. Loss Given Default ("LGD") = percent loss after default per dollar lent.
"These latest additions to the IRA Bank Monitor represent our continuing contribution to enable bank credit officers, executives and directors and regulators better define some of the most important measures of bank health and risk," comments IRA CEO Dennis Santiago." The US continues to be the most advanced banking system on earth despite the inability of risk professionals and regulators to communicate clearly and in a consistent fashion. Part of the reason that important initiatives such as Basel II remain moribund in the US is a lack of focus on defining universal, public data benchmarking measures that can be examined by policymakers and members of the financial community. These enhancements to the IRA Bank Monitor represent our latest contribution to this ongoing effort."
Subscriptions to the IRA Bank Monitor are available either via a Web interface or an on-site implementation. Separate license are available for FDIC CALL/TFR Bank Unit and FRB Y-9C Data, processed and converted to SQL, as well as the metrics and rules engine that powers the IRA Bank Monitor. IRA is available on a consulting basis to provide project management, implementation and operational maintenance tasks related to such implementations.
About IRA
IRA designs and builds customized risk analysis and valuation tools for credit officers, auditors, corporate lenders, regulators and other financial decision makers. Our transparent analytics systems utilize industry-standard relational databases and classical financial benchmarks to assess the performance of companies. By giving our clients full access to the analytics system and the underlying calculations, we help them to meet the internal risk ratings and compliance requirements of Sarbanes-Oxley and the New Basel Capital Accord.
Posted by whalenc at 04:22 PM
