Skip navigation

Tag Archives: RMBS

Here is the March 16th 20011 CREPIG podcast interview with JW Najarian & Robert Schecter. It has been described as ‘educational’.

This interview covers many topics, the economy, residential mortgages, commercial properties, distressed property industry, and especially methodology errors.

This interview is also available at the QuantumRisk website, http://www.QuantumRisk.com/.

I hope you find this interview informative and an enabler to executing better investment decisions.

___________________________________________________________________
Advertisements

Guan Jianzhong, Chairman of Dagong Global Credit Rating Co. Ltd

Bloomberg reports that China’s Dagong Global Credit Rating Co. reduced its credit rating for the U.S. to A+ from AA citing a deteriorating intent and ability to repay debt obligations.

Having worked on both sides of the world, I have come to associate such statements with shortsightedness. My past experience as a senior research analyst for a brokerage firm in Asia-Pacific would suggest that we are going to see problems in China by 2012.

In this blog post we take a look at how consumers could cope with the Mortgage Mess. Yes, we need strong banks otherwise the Dagong rating will be fulfilled, but this economy is 70% consumer driven. We therefore need stronger consumers, as strong consumers underpin the health of the banks, and not the other way around. Using China as an example, as China’s income per capita rises its banks and financial services companies become more confident of themselves, therefore the Dagong ratings comment above. 

I want to inform our readers that QuantumRisk’s CMBS Property Risk Analytics promotion ended September 10, 2010 per an earlier newsletter. The new pricing, valid until March 2011, is available here.

Home Prices Sag in August 2010

The State of the Housing Market
In my August 2009 blog post Have we hit the Housing Bottom? I had suggested that the house prices will bottom in 1Q 2010. Given the graph, I must say that this was a pretty good estimate of timing. 

The second question I had attempted to answer then, was home price recovery sustainable? My answer at that time was that it was more likely not.

The economic analysis presented by HiddenLevers (see picture) suggests that house prices are struggling to maintain an upward momentum. 

Why? There are two reasons. First the glut in foreclosed homes (1 in 4 for sale are foreclosed) will keep supply substantially greater than demand. Second, 1 in 6 homes in foreclosure translates into 1 in 6 homeowners who will not be able to participate in homeownership for at least 7 years or a 15% reduction in demand.

The graph shows that house prices are now hovering in the 68% to 71% range of their 2006 peak values.  From an economic cycle perspective, the housing industry collapsed before the commercial property industry. Given a 15% reduction in residential ownership capacity, it is very likely that commercial property sector will recover before the residential sector does. That is, the trough in the residential sector will be longer than that of commercials.

What is not reported in the news is the residential vacancy rates. A friend of mine who works for a utility company told me a few weeks ago, this utility is seeing 1 in 7 homes vacant. This is 50% more than reported by US Census Bureau for 2Q. That means rental incomes will not increase in the medium term. It also means that utility revenues will fall by 14%.

Some other bank just increased the difficulty of Chief Executive Officer Brian T. Moynihan 'hand to hand combat' over mortgage disputes.

The Next Big Wave: Legal Risk
Most of us are focused on market, credit & operational risks, but the next big wave will be legal risk.

I recently found out that banks are selling the second mortgage on foreclosed homes to debt collectors. Sure this maybe legally possible but lets weigh the pros & cons. The pros. Maybe banks think they can get back they principal in the second mortgage by selling the second mortgage to a debt collector. Sounds great, high fives to the managers who thought up this one. And at worst you don’t even have to write it off your balance sheet just yet. Kudos.

But wait. Does anyone really think they can get their money back from homeowners who could not even pay their first mortgage? Especially if they are unemployed? It also raises another question, what was the function and scope of collateralization?

Now the cons. What this action has done is to clarify that in the event of a foreclosure / repossession, the bank recognizes that collateralized debt survives ownership and can be put back to owner / originators. (Check with legal counsel for an informed opinion.) In the United States one cannot have one set of laws for one group of people and another set for another group of people.

Therefore, investors who bought RMBS bonds can now recognize that their securitized bonds survive any asset ownership issues, and banks are now liable for securitized bonds because they survive ownership.

I found out about a bank’s access to your personal funds some years ago. When I contacted the FDIC about it they said they could not do anything about it. Some mortgage contracts include a single sheet document that states that the bank has the right to move your funds around to keep your mortgage current. This I believe is antithetical to the securities law because securities law does not allow financial services companies to move funds around for a client for the benefit of the company.

The problem here is given such a ‘contract’ will or does the bank have the right to reach out to your 401(k) or similar funds?

Prime fixed rate foreclosures jump

How Consumers Can Protect Themselves
There are several ways consumers can protect themselves from future messy mortgage problems:

 1. House Pricing: The graph above (picture in State of the Housing Market, above) suggests that with today’s market conditions a home buyer should consider as an upper limit a purchase price of about 70% of the 2006 appraisal. If the housing situation deteriorates, this 70% number will drop. Looking at CMBS for guidance, this number can get to be as low as 54%.

 2. Appraiser Selection: Before purchasing, get an appraisal of the property by an appraiser who does not have links to banks as this minimizes banker bias.

 3. Mortgage Origination: If you are purchasing a foreclosed property, it is not recommended that you get your mortgage from the same bank that foreclosed the property. Why? At least in theory, in the event that there are ownership issues, you have a different bank behind you. 

 4. Safeguards: Given the state of the housing market, it would be prudent for the home buyer not rush into a purchase as the housing market is not likely to recover anytime soon. If you do so, you would need to have staying power. Therefore, before making a purchase, here are some points you should consider:

 4.1 Title Insurance: Don’t sign an S&P if you cannot get title insurance.

4.2 Deposit: Make your deposit conditional upon getting a clean title.

4.3 Indemnification: Require that the seller and/or the mortgage provider accepts liability for any future ownership claims in the event of the failure of the title insurance company. The lesson of 2008 was that many securitized bond credit enhancements (credit insurance) turned out to be worthless when the economy as a whole turned south.

4.4 Survival: Require that in the event of a foreclosure/repossession that all collateralized claims (1st, 2nd & 3rd liens) cannot survive the ownership.

4.5 Delinquency: Require that the mortgage provider cannot start foreclosure proceedings until the mortgage is at least 90 days past due. In the state of Colorado there are no laws to prevent a lender from foreclosing on day 2. Yes, even I was surprised by this, and know of at least one recent case where the foreclosure proceeding was started on day 50. 

4.6 Miscellaneous Contracts: Do not allow the mortgage lender have access to your other funds. Remove all such ‘subcontracts’ from your S&P agreement.

 5. Walk Away: If there are any doubts about the price, property or claims on the property, walk away. This market in not going to recover any time soon, and there will be plenty of second chances.

 There are many really good managers in banks, but as a general rule banks rotate their managers. So the great manager you see today could be replaced by a rogue manager tomorrow. Therefore do not feel ‘uncomfortable’ including these conditions in your S&P. You may even have to hire your own legal counsel to protect yourself. Remember it is wiser to walk away then to be burdened by a debt for a property you no longer own.

Summary
The real sad story is that we will eventually see 1 in 6 families homeless. To put things into perspective, James Fry, founder of Mean Street Ministry, reports that when he started this ministry about 10 years ago, there were 2 suicides per year, today there are 2 a week. We as a family have known James Fry, his family & his ministry for many years. Let us in Thanksgiving help someone in return.

___________________________________________________________________ 

Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational / educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position. Nor is this blog post to be construed as investment advice. 

Contact: Ben Solomon, Managing Principal, QuantumRisk
___________________________________________________________________

Real Problem versus Many Perspectives 
The perspectives reported on the Mortgage Mess varies very widely. From the political right is the Wall Street editorial “We’re not aware of a single case so far of a substantive error” to the political left Congressman Alan Grayson’s “the easiest way to make a buck is to steal it”. This one really shocked me, financial institutions and their mortgage servicing departments hired hair stylists, Walmart floor workers and people who had worked on assembly lines and installed them in “foreclosure expert” jobs with no formal training.

In my opinion these are details that subtract from the big picture. Without understanding the big picture we would not have a context in which to address this Mortgage Mess.

What is the big picture? It is, is our fiduciary responsibility to our shareholders or is our fiduciary responsibility to our customers? Correct picture but wrong perspective.

Our fiduciary responsibility is to our shareholders and that this fiduciary responsibility is derived from our fiduciary responsibility to our customers. We’ll discuss each perspective below.

Residential Mortgage Industry is Shrinking
First some context to this discussion. From the Wall Street reported data I estimate that 15.4% or about 1 in every 6 US homes are in foreclosure, and this does not include recent past foreclosures. That is a huge amount and bank troubles pale in comparison to this number. What does this number tell us?

It says that the mortgage market size will shrink by 15% as foreclosures are executed because foreclosed home owners will be barred for at least 7 years from participating in this market. The lowest estimate I was able to find was 10%. Therefore to remain profitable banks will have to lay off at least 15% of their residential mortgage staff.

Further, as reported in the New York Times, if title companies shy away from insuring foreclosed properties because they think those properties are vulnerable to claims, this will further depress the market, as investors too will shy away. 

Looking at the CMBS industry for clues, even though the reported commercial property appraisals are hovering in the 55% range, the anecdotal prices I have heard suggest purchase prices averaging between 10 to 20 cents on the dollar, and there are no reported foreclosure problems. Therefore, we can infer that the residential mortgage industry will experience similar appraisal versus selling price discrepancies and is therefore not out of the woods, yet.

Good News for Banks?
The Florida attorney general’s office says it doesn’t have the power to investigate banks but it has started an investigation into the law practices. To complicate matters, one needs to be aware that there is a difference between industry practice and actual mortgage regulation. There are also enormous variations from state to state with respect to foreclosure procedures. I found that in one state banks can start foreclosures on day 2 (1 day delinquent). This means that even though the 50 State Attorney General’s offices have launched investigations into the mortgage industry, in my opinion the banks don’t have to worry about them as these offices have no teeth. But some how this does not sound like good news, right?

First Fiduciary Responsibility
This Bloomberg article very nicely summarizes the current Mortgage Mess. That there are two fronts, “against U.S. homeowners challenging the right to foreclose and mortgage-bond investors demanding refunds that could approach $200 billion”. Of course this is an evolving situation and it is very likely many more fronts will open up.

The first fiduciary responsibility is to your customer. This is very clear in the many securities regulations since 1933. Of course banks are governed by banking regulations and in many instances are exempt from securities regulations as these exemptions are covered in the banking regulations.  Therefore I wonder if the banking regulations are any where nearly as concerned about protecting bank customers as the securities regulations require of investment advisors and broker-dealers?

Though the individual contracts appear to be in favor of the banks, investors are using every means possible to force banks to buy back bad mortgages. The final outcome, however, may play out in terms of power of buyers versus power of sellers, and not through legal means. That is investors in the future will seek assets from players who are amenable to buy backs than from those who are not.

This may be a good thing for the economy as insufficient principal protection may cause investors to seek alternative investments such as manufacturing, R&D driven technology licensing, and new materials, to name a few. Why? Because residential mortgages are no more safer than R&D.

Therefore, why did the residential mortgage market develop to the size it did? I can only conjecture that the existence of GSEs led to the mistaken belief that residential mortgages were one of the safest forms of investments.

Second Fiduciary Responsibility

The second fiduciary responsibility is to shareholders as this is a derivative of the fiduciary responsibility to customers. It is in this context that one would ask the question, how did this Mortgage Mess come to be?

In this context, given the Wall St. crash of 2008 and in the light of the Goldman Sachs hearings, the Wall Street editorial opinion that “We’re not aware of a single case so far of a substantive error” is difficult to justify as this would raise other questions.

As a general rule organizational seniority and salaries increase with fiduciary responsibility to shareholders. Therefore the questions, why did we did not have in place the systems and procedures to detect “substantive error”? Why were we paying managers so much if they did not know what was happening? What were these managers thinking?

Quite obviously operational risk and credit risk methodologies were insufficient. And may be they were ignored? A rethink of these methodologies and how risk committees are staffed and to whom they report to is in order.

Some Likely Future Outcomes

In the context of the First Fiduciary Requirement we can infer some future outcomes. 

Firstly, if there genuinely were mistakes in the foreclosure process, the second lien holder should now have a claim to the funds recovered from the sale of the property as the first lien holder did not conduct his fiduciary responsibility correctly. (Check this with your attorney as he may disagree.)

Second, title insurance fees may increase. Title insurers have two options either do not insure the title or substantially increase the fact checking required. The latter will increase title insurance fees. Assuming that Congressman Alan Grayson’s findings are correct, I believe that title insurance firms will choose not to insure as it would be more expedient to not insure than to dig up bad documents. Therefore, don’t expect title insurance for foreclosed homes unless the bank owns the title insurance firm, but this should raise questions of bias. My guess is that the title insurance problem is only going to get more complicated.

Third, future bank purchases will be structured more like an asset sale than an acquisition or merger. Why? First you don’t absorb the bad management team. Second by insisting only on asset purchases you put into place a screening process that substantially ensures that you are not purchasing a barrel of bad apples. Sure its a lot of work but that comes back to the banks’ fiduciary responsibility to its shareholders. An asset sale would allow the purchaser to include a clause that any future claims due to fraud, misstatement or omissions are the liability of the seller’s management team. Therefore one can infer that Bank of America’s purchase of Countrywide as a single company was not a good strategy, and that any subsequent M&A activity in the banking sector would require a rethink.

Fourth, further changes to securities regulation. Dodd-Frank indeed may turnout to be insufficient or in the worst case irrelevant as private action against mortgage industry participants further tighten regulation. For example if we assume that the alleged wrong doings were conducted by a handful of employees and not an issue of management culture, checks and controls, then we can expect changes to portions of the securities and banking regulations that would provide investors more time to seek recourse. For example Securities Act of 1934, Section 10(b), investors have two years from discovery of the fraud or five years from when it occurred to file their claim, while Sections 11 and 12(a)(2) claims against misstatements or omissions must be brought within one year of discovery and three years of the securities filing. These timing could be changed to 10 years or simply no statue of limitations for any fraud, misstatements or omissions.

Fifth, we would expect bond investors require,
1) A buy back clause in any future securitization, and that buy back clause is automatically transferrable to any and all future bond holders. At the very least in the event of the failure of the insurance provider.

2) That any third party providing a fee based opinion about a or soon to be securitized deal state that they have fully examined the collateral backing the deal.

Summary
This downside risk assessment of the residential mortgage industry suggest that an end to the industry turmoil is not in sight. Further, we can expect substantial private sector initiated changes to investment contracts that will provide both investors and home owners with better uniform protection.

___________________________________________________________________ 

Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational / educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position. Nor is this blog post to be construed as investment advice. 

Contact: Ben Solomon, Managing Principal, QuantumRisk
___________________________________________________________________

Here are two interesting articles from the Wall Street Journal describing events in both the RMBS and CMBS industries, that give us an idea of what is happenning at to opposite ends of the investment spectrum. Mortgage Funds Brace for Major Shift and Small Investors Lost It All in Memphis.

In the first article there are 2 points worth noting:
1.1) Mortgages that are underwater. 
The Markit index of subprime securities issued in the second half of 2006 recovered from below 60 (March 2009) to around 80. This points to the need for staying power to recover losses if one is already in the market or the discounts to look for if one is getting into the market.

1.2) Prepayment & loss assumptions.
My belief is that many mortgage deals (CMO, CMBS etc) were based on ‘optimistic’ (or ‘pessimistic’ depending on your point of view) prepayment assumptions which no longer hold. Low rates would suggest an increase in prepayments, but this will not the case because banks are essentially not lending. That is, bond structures based on 100 to 350 PSAs are probably seeing prepayment rates at 0 PSA. That means one has to rethink the support & subordinate bonds.

The second factor, losses, is a very severe factor and in my opinion, not adequately built into deal portfolios. An early estimate is that CMBS asset defaults are now around 6.4% – 6.8%. A huge increase from a previous 1.8%. However, given the two recent big defaults Crescent Real Estate Equities and Stuyvesant Town and Peter Cooper Village, one should expect the dollar defaults to be greater because of the dollar skew further to the right. The only way to handle losses is to factor transactions at deep discount. This articles shows that some fund managers are doing that.

.

In the second article, we note
2.1) CMBS delinquencies.
CMBS delinquencies climbed to 6.5%. This is in line with our first pass default estimates of 6.4% to 6.8%.

2.2) Banks are having difficulties providing credit.
40 banks turned down the opportunity to refinance the Cherry Road property. Without a healthy functioning securitization industry, banks are unable to provide credit, and therefore hampering this economic recovery.

2.3) Duration Matching.
My guess given the wisdom of hindsight, properties like Cherry Road should have be financed with a longer term debt, 10 years instead of 5.

.

When juxtaposed these two stories tell us:
3.1) Shift Focus.
The need to shift the focus of cash flow securitization analytics from prepayment modeling to loss modeling.

3.2) Preserve Capital.
Investors’ primary concern should be the preservation of their capital and therefore a realistic strategy for the preservation of capital is the high LTV capital structure.

3.3) Liquid Assets.
TIC are really illiquid and all things being equal, CMBS AAA bonds might have been a better investment, in that one would probably not have lost $7 million. Google results on TICs.

3.4) Optimism Can Be Misplaced.
With hindsight, the use of TICs with low LTVs would suggest investors with an optimistic perspective on the economy and that there was probably insufficient downside risk assessment. But then we never really know until things are too late, right?

3.5) Sophisticated Investors.
The concept that investors are ‘sophisticated’ based on their net worth needs some rethinking.

___________________________________________________________________

Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position. Nor is this blog post to be construed as investment advice.

Contact: Ben Solomon, Managing Principal, QuantumRisk

___________________________________________________________________

Many unintended consequences in business & finance occur because upside (profitability) and downside (loss) risk have very different characteristics.

Background
In 2007 I sifted through 330,000 RMBS (Residential Mortgage Backed Securities) assets or loans with the purpose of developing a default & loss econometric model that would enable my then employer differentiate between good and bad RMBS bonds.

I had to do a lot of data structuring and clean up to standardize incoming data from about 20 different servicers. I should say data structuring and data scrubbing. And after that sift through this asset data set to filter out the bad data. So you can imagine the amount of work that went into this.

My strategy to identify the loss quality of a bond was to use the origination and close data to forecast future losses. Why? Because once you have purchased the bond you are stuck with whatever losses that unfold.  If this was possible we could very quickly eliminate the poor quality bonds, and use cash flow methodologies (more on this in a later blog) to evaluate the better quality bonds. We did not want to expend effort valuing poor quality bonds.

Dichotomy of Metrics
Well, at least that was the theory. What went wrong? In residential mortgages FICO scores are a major component, if not the primary driver for assessing future default behavior. I found that for residential mortgage FICO scores at origination were poor predictors of future defaults. How? Build two probability distributions of FICO scores. The first is a distribution of FICO scores of the borrowers at origination for all assets. The second is the distribution of the FICO scores at origination for defaulted assets only. You could not tell the difference between the two distributions!

Bewildering. Was there an analogy in other areas of finance? Yes. Company pro forma profitability analysis are good predictors of future profitability, but they are poor predictors of severe losses or bankruptcy risk. To get a handle on future company bankruptcy risk one requires a tool like Altman’s Z-Scores.

Here we observe a dichotomy in forecasting characteristics. On the one hand pro forma informs us of future profitability and on the other hand Altman’s Z-Scores informs on bankruptcy risk. We concluded that FICO scores behave like pro forma profitability, that they are good predictors of success but poor predictors of defaults.

I must add that unlike investment bankers and fund managers who are focused on upside risk or profitability, my career in financial services has been focused on downside risk. Therefore I did not test if FICO scores are good predictors of success.

When we recognized this dichotomy we abandoned RMBS bonds as a viable investment vehicle. But this story does not end here. I have an extensive business reengineering background and investigated how FICO scores are generated.

How Credit Cards Drive FICO Scores
From a business process perspective recent FICO scores are generated by your credit card issuer. Really. You the card holder use your card to transact purchases. In so doing you create debt. How much of this debt you pay down, how quickly, etc., is reported to the rating agencies. This reporting provides an insight into your debt payment characteristics which the rating agencies convert into FICO scores. FICO scores appear to predict defaults because they are adjusted downwards as your credit card payments deteriorate. That is, in my opinion, FICO scores have a limited window of about 90-days within which they work, but by then it is too late for the card issuer. Or no credit card visibility no FICO adjustments.

Here is the weak link in this whole business process. Without your credit card spending and payments reported by your card issuer, the rating agencies would not have a clue what your recent credit rating should be.

Take 2 people John & Jay. John has house and car payments and uses his credit card for all his purchasing transactions. Jay also has house and car payments, but he only uses cash for his purchasing transactions.

Now both have suffered a partial loss of income. They both continue to make house and car payments. Therefore the ratings agencies cannot tell from these payment that there has been a partial loss of income. Both reduce their spending to manage within their new realities. But John has now slowed his credit card payments. The rating agencies see this and are able to adjust John’s FICO scores accordingly but not Jay’s.

The use or not of credit cards provides asymmetric information to rating agencies. Now guess what happens as credit card companies ramp up interest rates, consumers pay down their card debt and stop using their cards.

Unintended Consequences
All manner of unintended consequences occur.

1. The banking industry loses it recent FICO information for a much larger proportion of the population.

2. Consumers do get penalized with lower FICO scores for not having recent payment histories.

3. First time home buyers will face higher rates because they don’t have sufficient recent history.

4. FICO scores are no longer as “effective” as they were “supposed” to be.

5. Because of this additional “FICO risk” for the same “risk” bonds with credit card debt should trade at a discount to bonds with residential mortgages which in turn should trade at a discount to CMBS bonds.

6. As I had stated in my Feb/02/09 post Risk-Reward is Non-Linear, increased rates will increase defaults. The unintended consequence of this is that banks that have rushed to increase rates to 30% before the new laws come into effect, will have locked themselves into a population demographics that experiences a higher default rate. Therefore we can expect to see an increase in credit card losses.

Summary
I’m sure there are a lot of very smart people in the credit card and rating industries, but… This situation is not dissimilar to what I observed as a management consultant reengineering manufacturing companies – one may have the best, the brightest and the most experienced managers but surprisingly when they come together at their management meetings they do strange things.

There needs to be a better way to address bank losses on credit cards and a better way to treat customers. Remember your customers are not your enemies.

___________________________________________________________________

Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.
___________________________________________________________________

The Opportunity:
What would you pay to know the Black Swan of your CMBS deal risk?

Reverse that question!

What would a deal manager pay you to know the Black Swan of his CMBS deal?

The Need:
Inspite the bad publicity surrounding CDOs and structured finance the tranche strucutre is one of the most efficient methods of creating differentiated classes of assets, as The Committee on the Global Financial System explains:

A key goal of the tranching process is to create at least one class of securities whose rating is higher than the average rating of the underlying collateral pool or to create rated securities from a pool of unrated assets. This is accomplished through the use of credit support (enhancement), such as prioritisation of payments to the different tranches.

However, what really caused the market to substatially undervalue these assets was that the default rate and the severity of the loss was much greater than even the complex rating processes had estimated them to be.  Have you noticed that some (many?) of the AAA tranches had losses?

The Solution:
The answer is an econometric assessment of the default and loss distributions of CMBS assets. Note, not a single point value but the whole distribution. This distribution will provide the CMBS Deal’s 95% or 98% VaR and CVaR loss estimates.

From this distribution we can then recalculate the loss estimates for each tranche, and be pretty certain what the loss characteristics of these tranches are independently of the ratings assigned to the tranches. A backup second opinion, if you would.

Why would this provide better answers?
1. We know the assigned ratings did not cut it.
2. We know the vintage or triangular matrix method provided incorrect default and loss curves. I was the first & only person to correctly identify that a major tool, vinatges/triangular matrix method, used in the mortgage idustry was providing incorrect results. The link provides access to an Excel worksheet that allows you to confirm this for yourself. To understand the magnitude of this finding one only need to look at the vast array of mortgage analyses, from the Esaki-Snyder reports to the Wachovia 2008 CMBS Loss Study, that use this tool.
3. The DSCR loss model used in the CMBS industry does not match the historical data. I discovered this weakness in the method through extensive testing against the historical data. Do you know of anyone who has personally tested these tool against the historical data?

What would the solution look like?

The graph below is a simulated long term VaR & CVaR loss outcome for a simulated CMBS deal.

CMBSPartnership

This graph is based on a set of CMBS loss & default distributions, and provides a second method to evaluating bond pricing. After all at the end of the day, isn’t cashflow analysis and DSCR’s about bond pricing? Notice how VaR (green dash) consistently underestimates CVaR (purple dash). We can add in Black Swans into this report. Note that my initial assessement was that CMBS Black Swans are on the order of 20% to 80%.

Partnership:
I am seeking partnerships with banks/investment funds/ratings companies to fund the development of this econometric CMBS business, which I expect to be transferrable to the RMBS sub-industry.

Call me 303-618-2800 or email me at benjamin . t . solomon AT QuantumRisk . com if you are interested in this business.

___________________________________________________________________
Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.
___________________________________________________________________

This series of blogs is derived from my discussions on the LinkedIn Quant Finance: What is the best approach to handling CMBS &/or RMBS Credit Risk analysis? discussion forum. Russel explained that “projected defaults” are foreclosures + delinquents, and all his observed FICO scores were above 670.

 I saw FICO scores between 520 and 820, and almost always once a loan became delinquent it would foreclose.

The main reason I did not consider delinquencies was because I had to be sure it did foreclose and the loan age when it foreclosed, and this data was not available for delinquents.

This agrees with your conclusion about delinquencies but our subsequent handling of the data is different.

Your last comment sums it the best, the underwriting standards varied and deteriorated so much that FICO scores were no longer reliable measures of foreclosures. (eg 820 in sub-prime??)

Another possible scenario is that underwritten FICO scores are based on ‘good’ financial standing in a ‘good’ economic environment. But once a person experiences financial stress, FICO scores are lagged indicators with a range of or even an indeterminate set of lag times. Then given the financial stress all individuals irrespective of their original FICO scores, respond similarly to this financial stress.

That is under financial stress the underlying statistical behavior of the financially stressed population is different from the underlying statistical behavior of the population in good financial standing.

So FICO score may actually be good predictors of success, but poor predictors of failure. This is similar to company profitability versus Altman’s Z-scores. This first predicts success, the second failure.

___________________________________________________________________
Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.
___________________________________________________________________

This series of blogs is derived from my discussions on the LinkedIn Quant Finance: What is the best approach to handling CMBS &/or RMBS Credit Risk analysis? discussion forum.

Here is the problem with vintage per the triangular matrix method. (I gave it that term because nobody else I talked to knew what it was named.) If you look at the Esaki-Snyder report or the Wachovia CMBS 2008 Loss Study, there is this averaging method, that looks like a triangular matrix, to determine the average over vintages by loan age.

It gives one an incorrect shape of loss or defaults over the life of an asset. There is a simple test to prove this. Assume that all defaults (or losses) are constant over the life of the loan say 2% every year. The age-default profile should be a horizontal line. Now say that as the economy improves the defaults decrease by 0.2% per vintage, ie yr 2000=2%, yr 2001 = 1.8%, yr 2002 =1.6%, … but remains constant per vintage through the life of the asset.

You can do the same with increasing rates.

The method is biased because the averaged defaults (or loss) is no longer a horizontal line (the original correct input), and tends towards the value of the oldest vintage.

To make it easier for the reader I have provided the link to the Triangular Matrix Method Test Excel 2003 Spreadsheet. (Note: you may have some problems with IE8, try saving to disc.)

 

 Discalimer: This blog is purely for informational/educational purposes and is not intended to either negate or advocate any product, service, political position or persons.
Creative Commons License
QuantumRisk Blog Posts by Benjamin T Solomon is licensed under a Creative Commons Attribution-Noncommercial 3.0 United States License.
Based on a work at quantumrisk.wordpress.com.

This series of blogs is derived from my discussions on the LinkedIn Quant Finance: What is the best approach to handling CMBS &/or RMBS Credit Risk analysis? discussion forum.

In a previous comment I had found that FICO socres were not useful, Russell, however, found that FICO scores were extremely good predictors of defaults. Here I clarifying what & how I did my analysis:

If I’m correct all the data I used was non-agency, 2005, 2006 and some 2007. More than 100 ‘tapes’ from service providers and banks themselves. There were in total about 330,000 residential mortgages assets. And I think they were all subprime – thats why the incomplete data problem.

The probability distribution of the universe of underwritten FICO scores was identical to the probability distribution of the foreclosed (no deliquents) underwritten FICO scores. I did not look at vintage because firstly FICO scores should have been enough information, and secondly there is another problem with vintage.

I think the difference in our analyses is that I used FICOs at underwriting and Russell used FICOs at default. We will know in a future comment, and I’m not sure what Russell meant by “projected defaults”.

I would definitely like to hear from other analysts on how they handled RMBS defaults versus FICO scores so that all of have a very clear idea on how to use FICO scores in the most beneficial manner for the industry.

 

Discalimer: This blog is purely for informational/educational purposes and is not intended to either negate or advocate any product, service, political position or persons.
Creative Commons License
QuantumRisk Blog Posts by Benjamin T Solomon is licensed under a Creative Commons Attribution-Noncommercial 3.0 United States License.
Based on a work at quantumrisk.wordpress.com.

This series of blogs is derived form my discussions on the LinkedIn Quant Finance: What is the best approach to handling CMBS &/or RMBS Credit Risk analysis? discussion forum.

I agree with prepayments in RMBS space but I was looking for more than the usual accepted, standard knowledge. Sort of industry wisdom versus textbook stuff. Argyn had suggested other loss models and Russell had explained how migrating FICO scores affect RMBS portfolios. The discussion continues:

For example if Argyn had not mentioned bond pricing models that would not have jogged my memory about the negative correlations between RMBS and CMBS. This negative correlation is something anybody can test for themselves. I don’t have the data or the models so it is from memory. I would suggest testing residential losses against commercial losses by MSAs. There are some economic lag effects but never got to complete this study.

This negative correlation could be interpreted as consumer spending lags job loss or growth. Therefore, if the recession is long enough we can expect an increase in commercial property losses even as residential properties begin to recover. If the recession is short you won’t notice this lag because most consumers and property owners have some staying power. If the recession is too long then both are negatively affected.

OK let me step out of the ‘conventional space’ to make this discussion more interesting and hope that others would join in.

My thinking was once you have bought a deal, it is yours good, bad and ugly. So accounting for prepayments (the bad) in RMBS is a poor strategy. As a tactic you need to do it but as a strategy it is poor. And you are always stuck with the economy, and whatever it does.

My strategy for both RMBS & CMBS was to determine the CVaR (the ugly) that an investor was willing to tolerate within some investment horizon, say 5 years from the underwritten parameters.

To do this you need to know how a deal would perform over this investment horizon, from the underwritten parameters. That means prepayments are (1) of little value as they are driven by future changing economic fundamentals, and (2) they are management tools to deal with the bad.

The question I then had to answer was how do we minimize the ugly (CVaR) given only underwritten parameters?

Before I ran into the RMBS incomplete data problem and abandoned RMBS, I tested FICO scores. Could we use underwritten FICO scores to predict future losses in RMBS space? Once you have bought the deal you can watch credit scores deteriorate, but we want to avoid that as much as we can.

One of the things I did was to analyze the distribution of FICO scores in the ‘universe’ against the distribution in the defaulted assets. And to my surprise there was no difference. Underwritten FICO scores are unable to predict future deterioration of individual credit worthiness. That is one of the main reasons we abandoned RMBS because with incomplete data everything hinges on FICO scores. Again you can test this yourself.

I believe that from a forecasting perspective, FICO scores are a proxy for either disposal or discretionary income, that the two are highly correlated – I haven’t done this study, it is a guess having looked at tons of data.

In CMBS one can build a model to forecast future losses at a deal or portfolio level, and then determine from the CVaR-tolerance and investment-horizon, which portfolio you would invest in.

Anyone else seen these types of problems with FICOs?

Anybody tried the investment strategy I’ve outlined above?

 

Discalimer: This blog is purely for informational/educational purposes and is not intended to either negate or advocate any product, service, political position or persons.
Creative Commons License
QuantumRisk Blog Posts by Benjamin T Solomon is licensed under a Creative Commons Attribution-Noncommercial 3.0 United States License.
Based on a work at quantumrisk.wordpress.com.