Knowing When to Stop

When you think about bad CRE loans, most people picture homes being demolished in Victorville, unsold high rise condos in Miami, or vacant office buildings in Orange County. But how about Minnesota? From a Minneapolis Star Tribune story (hat tip Calculated Risk):

Minnesota ranks fifth nationally, with 50, or 12 percent, of its banks carrying particularly high levels of dead real estate loans, according to an analysis done for the Star Tribune by Foresight Analytics, a financial research firm in Oakland, Calif. Only Florida, Georgia, Illinois and California have more banks at such levels.

A key quote:

Bank consultant Robert Viering, principal of River Point Group Inc. in Monticello, had that lesson drilled into him when he was a regional credit officer at the former Norwest Bank. A credit manual, circa 1990, warned him and his colleagues: "The pivotal issue in CRE lending is knowing when to stop. Restraint must be initiated by bankers because historically borrowers have been unable to recognize the warning signs. Commercial real estate lending should not be viewed as the cornerstone of a loan portfolio."

Stopping, of course, involves saying no before the problem is evident. This is something people are very bad at doing (for more on that, see my post Rising Markets Create Lender Losses).

Complexity, Predictability, and Cascade Effects

Duncan Watts has a great piece in the The Boston Globe titled, “Too Complex to Exist.” I love the illustration:

Some excerpts:

ON AUG. 10, 1996, a single power line in western Oregon brushed a tree and shorted out, triggering a massive cascade of power outages that spread across the western United States. Frantic engineers watched helplessly as the crisis unfolded, leaving nearly 10 million people without electricity. Even after power was restored, they were unable to explain adequately why it had happened, or how they could prevent a similar cascade from happening again - which it did, in the Northeast on Aug. 14, 2003…

Traditionally, banks and other financial institutions have succeeded by managing risk, not avoiding it. But as the world has become increasingly connected, their task has become exponentially more difficult. To see why, it's helpful to think about power grids again: engineers can reliably assess the risk that any single power line or generator will fail under some given set of conditions; but once a cascade starts, it's difficult to know what those conditions will be - because they can change suddenly and dramatically depending on what else happens in the system. Correspondingly, in financial systems, risk managers are able to assess their own institutions' exposure, but only on the assumption that the rest of the world obeys certain conditions. In a crisis it is precisely these conditions that change in unpredictable ways.

In the article Watts proposes some regulatory steps to limit the complexity of financial systems. I am not optimistic; it is very hard to restrict activities until a problem is obvious (see my post “Rising Markets Create Lender Losses” for more on this). I think a more pragmatic route is for institutions to create firewalls within the organization so that the failure of one business line doesn’t take the whole institution down (e.g., AIG’s CDS operation pulling down the insurance business).

Rising Markets Create Lender Losses

People anticipate the future will be like the past. From a DNA article, “Why Economists Can’t See a Recession Coming”:

Robert J Barbera, chief economist, Investment Technology Group, in his book The Cost of Capitalism -- Understanding Market Mayhem and Stabilizing our Economic Future, writes: "Since the economy is not in a recession 80% of the time, the safe strategy is to predict recessions only when they have already arrived! That means you're right 80% of the time. Simply put, forecasting the recent past is the way to go and it is the dominant strategy employed by professional forecasters…Most of the time, tomorrow bears a close resemblance to yesterday. After all, both industry and economic trends tend to last for years, not for days. Once we acknowledge that we confront a world of pervasive uncertainty, it is quite reasonable to decide until circumstances change, we will plan as if present circumstances are likely to persist."

This approach to forecasting guarantees lenders will take losses. If you don’t say no when markets are rising, you are certain to have significant exposure at the top of the market which will create losses when the market softens. This time around, although everyone knew at an intellectual level that home prices could go down, the long term trend of rising house prices made it easy to justify rating models and lending decisions which didn’t adequately weight this possibility.

Does Tim Geitner Read My Blog? Are Regulators to Blame for the Housing Crisis?

From a Washington Post interview over the weekend, via Calculated Risk:

Geithner: "For something this big and damaging to happen it takes a lot of mistakes over time. And it is that combination of things. Interest rate here and around the world were kept too low for too long. Investors made - took a bunch of risks without understanding the risks. They were betting on the expectation that house prices would continue to go up - to go up forever. Rating agencies failed to rate these products adequately. Supervisors failed to underwrite loans with sufficiently conservative standards. So those basic checks and balances failed. And people borrowed too much. It took all those things for it to happen."

From my March 21, 2009 post, “Whose Error Was the Housing Crisis?”:

Here are some errors which had to align to get to where we are today:

1) Borrowers took out loans they couldn’t afford

2) Lenders made loans to borrowers which the borrowers couldn’t afford

3) Ratings agencies rated securities comprised of these loans as safe

4) Security purchasers relied on the erroneous ratings and bought the securities

Any of these parties could have averted the crisis had they avoided their respective error.

Calculated Risk takes Geitner to task for not mentioning two other factors:

Although there were many factors in the housing and credit bubble, the two keys were: 1) rapid innovation in the mortgage industry (securitization, automated underwriting, rapidly expanded wholesale lending, etc), and 2) a complete lack of oversight by regulators. As the late William Seidman wrote in his memoir (published in 1993): "Instruct regulators to look for the newest fad in the industry and examine it with great care. The next mistake will be a new way to make a loan that will not be repaid."
Geithner failed to mention the rapid changes in lending and the failure of government oversight as the two critical causes of the bubble. Either Geithner misspoke or he still doesn't understand what happened - and that is deeply troubling.

Although “innovation” and the regulators were factors, they were by no means the key factors. I think the innovations CR refers to should be viewed more as tools than culprits (an NRA bumper sticker for bankers - “Automated Underwriting doesn’t Kill Lenders, Lenders Kill Lenders”). More on this topic at “Why Did WAMU Abandon Underwriting Standards?”

The role of regulators is more complex. Certainly if disclosures were improved or some practices were prohibited, some bad loans might not have been made or bought. However, the errors listed above are so basic and so self-destructive I question the ability of outside intervention to control the behavior.

“Legacy” CMBS?

What is a “Legacy”? From Merriam Webster:

Main Entry: ¹leg·a·cy 1 : a gift by will especially of money or other personal property : bequest 2 : something transmitted by or received from an ancestor or predecessor or from the past <the legacy of the ancient philosophers>

Usually a legacy is good, but sometimes you inherit something really screwed up. When WAMU tanked 18 days after Alan Fishman took the CEO job, no one blamed Fishman (although some thought the $7.5M he was paid for the 18 days was a little excessive). The key point here is that it’s only a legacy if you inherited it. It’s not a legacy if the problem was created on your watch.

So, when the Federal Reserve says “Legacy CMBS” is now eligible collateral for the TALF program, I think they’re misapplying the word. These securities would be legacy securities if the management responsible for buying and/or originating them had been replaced, and new management was cleaning up the mess. But, in most cases that management change hadn’t occurred. Perhaps in their own minds management has changed (“That was the old me – the new me would never do those deals”), but I don’t think that counts.

Granted, calling the securities what they are - “wish we were never involved with these CMBS” – is clumsy. We need something short and catchy to describe them. I propose “Whoops CMBS”, in honor of the WPPSS bond default back in 1982. Of course, that was just a $2.25B default; maybe we should call them “Big Whoops CMBS”. Or maybe we could call them “Do-over CMBS.”

Although the misuse of the word ”legacy” in this financial crisis has been irritating me for a while, the impetus for this post actually came from a non-real estate story (yes, I do have other interests). Ian Media Networks filed bankruptcy yesterday, and this quote caught my eye:

“We are pleased with the support from our first lien senior debt holders to resolve the company’s legacy debt issues and fund our television growth plans,” said Brandon Burgess, Ion’s chairman and chief executive officer, in a statement.

Out of curiosity I took a look at Mr. Burgess’s bio, and it turns out he joined ION in November, 2005. Even if the “legacy debt issues” were the result of debt taken on before then, the debt and equity markets were available on pretty favorable terms until last year. Instead of “legacy debt issues”, I think this is more like “didn’t deal with it when I should have debt issues.”

Recommended reading for more on the way people distance themselves from their mistakes: Carol Tavris and Elliot Aronson, Mistakes Were Made (But Not by Me).

Seeing Patterns Where There Are None: Geography

Humans are wired to detect patterns, but sometimes there isn’t one. For example, what distinguishes the best and worst performing submarkets in Orange County?

You might focus on geography first; the real estate mantra is location, location, location. Are the best and worst performing submarkets concentrated in a particular area?

Here’s a map, with the five best performing markets (as measured by combined occupancy and rent change) highlighted in green, and the worst ones in red:

Looking at this, you would have to conclude there’s not a pattern; the best performing and the worst performing markets are pretty will mixed up.

The data is for the first quarter 2009 from RealFacts, as reported by Lansner on Real Estate.  Here’s the chart accompanying the story; can you find a pattern in the occupancy and rent changes?

Roads Before Roofs, Roofs Before Retail

The stories and video of new houses being demolished in Victorville are continuing to pop up in blogs and other news sources (see Calculated Risk, the LA Times, and the Wall Street Journal, for example). It’s a compelling story, but the way it’s being presented almost everywhere is misleading.

First, here’s the video if you haven’t already seen it:

The video, and every story I’ve seen referencing it except one, gives the clear impression the bank thinks it makes economic sense to demolish completed and virtually completed but unsold houses because the market is so bad. However, the original source of the story (see this post) interviewed an officer at the bank, who makes clear the real issue is the homes were built before the roads and other site improvements were completed. Completed homes could have been sold at some price, but if there’s no road to the home you can’t sell it.

This is obviously bad construction lending practice; you should complete site improvements first (or make sure you’ve held back enough money to do so). Hence the headline, roads before roofs. This seems obvious, but it happens more often than you might think. When I was at Capmark a few years ago one of our workout deals was a project where we funded the equity portion of a purchase of a multifamily land parcel, and then discovered the access road we needed couldn’t be built because it would cross a stream which was the home of an endangered fish species. That investment was a total loss.

It’s also obvious it takes more than a few mistakes to bring down a lender, but when you have a major due diligence breakdown like this, you have to wonder if it’s not the tip of an iceberg of bad decisions. From the WSJ story linked above:

Guaranty Bank has significant exposure to construction loans to home builders. Last month, its parent company, Guaranty Financial Group, was issued a "cease and desist" order by the federal Office of Thrift Supervision, citing the firm's "unsafe and unsound banking practices."

I’ve previously posted about Capmark’s problems here. Since then, they reported a $1B loss in the first quarter.

The second part of the headline is roofs before retail. Before you develop a retail project, you want to make sure there are enough people living in the market area to support it. Because subdivisions were being developed at such a rapid rate, this rule was frequently violated, and when the music stopped on the residential side many retail projects were left without a customer base. Between the two retail sites indicated below, which do you think is doing better?

The lesson is, it’s important to develop in the right order; infrastructure, then residential, then retail.

Why Doesn’t CRE Loan Underwriting Ever Get Any Better?

Via Zero Hedge, S&P reports lax loan underwriting is responsible for the upcoming losses on CMBS loans:

The rationale for the variation in results among the 2005-2007 vintages is that the underwriting standards, already looser than for past vintages, became progressively worse as the property cash flows and valuations rose quickly during those years. For example, most of the large pro-forma loans were underwritten during 2006 and especially 2007, and 2007 deals also claimed the highest average Standard & Poor's LTVs and lowest average Standard & Poor's DSCs (followed by 2006, then 2005). Thus, when commercial real estate prices and cash flows peaked in 2007, the most recent origination was by far the most vulnerable to cash flow declines…

This is the same explanation used to explain losses during the 1990-1994 real estate recession, the S&L debacle of the 1980’s, and probably every other major real estate downside since lending began. Why don’t we get any better at this?

An obvious explanation is that underwriters knew of the risks, but were ignored by management seeking profits and market share (I’ve posted on the pressures on credit officers here, and on the market share issue here). These are real issues, but I think there is a more fundamental problem; I think most underwriters, and many credit approvers, don’t know how to tell a good loan from a bad loan.

If you take the S&P approach outlined above, you don’t need to get into the details – at the top of the cycle, just tighten your LTV and DSC requirements. Of course, this advice is about as helpful as telling an investor to buy low and sell high. And, anyone who has been in a credit approval position knows how difficult it is to pull back in a strong market. Given that you are going to have to do business during market peaks, how can you select the deals most likely to succeed?

The way people become experts is through thoughtful practice. In his book, How We Decide, Jonah Lehrer profiles Herb Stein, a television director who has shot more than 50,000 scenes and won eight Emmies over a twenty five year career. After shooting an episode, Stein says:

I watch the whole thing, and I just take notes. I’m looking really hard for my mistakes. I pretty much always want to find thirty mistakes, thirty things that I could have done better. If I can’t find thirty, then I’m not looking hard enough.

Bill Robertie, a world class chess master and poker and backgammon player (backgammon World Champion twice), is also profiled:

Robertie didn’t become a world champion just by playing a lot of backgammon. “It’s not the quantity of practice, it’s the quality,” he says. According to Rpbertie, the most effective way to get better is to focus on your mistakes… After Robertie plays a chess match, or a poker hand, or a backgammon game, he painstakingly reviews what happened. Every decision is critiqued and analyzed. Should he have sent out his queen sooner? Tried to bluff with a pair of sevens? What if he had consolidated his backgammon blots? Even when Robertie wins – and he almost always wins – he insists on searching for his errors, dissecting those decisions that could have been a little better. He knows that self-criticism is the key to self-improvement; negative feedback is the best kind.

Underwriters don’t have the opportunity to do this kind of analysis, for three reasons. The first is that lenders do very little meaningful analysis of existing loan performance. Asset management monitors debt service coverage, occupancy, property condition, and that’s about it, which is like trying to diagnose an illness from the patient’s weight, blood pressure, and temperature. These performance metrics are monitored because they’re easy, but they’re just not that revealing. I don’t know of any lenders who systematically analyze underperforming deals to understand why they are underperforming (see my posts, “Why What You Know About Income Property Performance is Probably Wrong”, and “The Slippery Slope to Default” for more on what lenders should be paying attention to).

The second problem is that there is rarely a feedback loop to the underwriters giving them even the minimal performance data collected. The back-end asset management group and front-end underwriting are not connected, and the lessons to be learned at the back from actual performance are rarely conveyed to the front in a useful form.

These two problems are correctable, but the third problem is more difficult. Stein has daily rough cuts to review for mistakes. Robertie has many games each day he can review and analyze. But, CRE underwriting mistakes are generally only revealed when markets are under economic stress, and such events may happen only four or five times in an underwriter’s entire career. The consequences are twofold. First, bad deals are never revealed because they never are stressed by a downturn -almost every CRE loan made from 1995 to 2007 has performed to date, because it was never stressed. Secondly, good deals are overwhelmed by economic events – there were good loans made in 2006-07, but it is very likely many of those loans will default given the severe distress of this market. Stein and Robertie have an opportunity to excel because they have frequent, clear feedback. Even under the best of circumstances, CRE underwriters get infrequent, unclear feedback. I’ve written more on feedback issues in my post “Why Do Lenders Take Excessive Risks? Certainty and Feedback Issues.”

To summarize, underwriting does not get better because the opportunities to learn are infrequent, little effort is made by lenders to learn even when the opportunity presents itself, analysis is confined to superficial symptoms, and the little that is learned is not conveyed to the people who need the information. The only good thing I can say is there is plenty of opportunity for improvement.

Why Do Bankers Take Excessive Risks?

There are plenty of economic explanations being offered  to explain bankers’ risky behavior (e.g., poorly designed incentive plans, inadequate risk modeling). On a more basic level, the old standbys ignorance, hubris, and greed are called on. I’m sure some people were ignorant of the risks, and some people were in it for the money. But how do you explain the participation of very intelligent people who were aware of the risks, had every reason to protect their good reputations, and had no economic reason to jeopardize their already very lucrative positions? And it’s not just bankers – why do successful real estate investors continue to leverage their portfolios to the max and take on high risk deals, when they could secure their positions and be able to ride out any storm?

Maybe it’s their brain chemistry; human brains get high on challenges. From Gregory Berns’ book, Satisfaction: The Science of Finding True Fulfillment:

Any stressor, especially a physical one, results in the release of cortisol. The biochemical interaction of cortisol and dopamine in the striatum suggests that these two chemicals are involved in the achievement of satisfaction, perhaps even transcendence. Alone, neither compound can provide a state resembling satisfaction. Dopamine may be associated with transient euphoria, but you need cortisol to get that satisfying feeling. And because cortisol is released most effectively by stressful situations, the road to satisfying experiences must necessarily pass through the terrain of discomfort.

At the most basic level, people take risks because the biochemical results make them feel good. Understanding this goes a long way towards explaining obviously self-destructive risky behavior.

How Did the Losses Get So Big?

Many people still believe that this crisis was created by lenders making bad loans to subprime borrowers, and many people have trouble understanding how the losses to financial institutions can exceed the amount lost on the bad loans themselves. Matt Taibbi (via Rortybomb) makes it all clear:

Do you actually think that it was a few tiny homeowner defaults that sank gigantic companies like AIG and Lehman and Bear Stearns? …What we’re talking about here is the difference between one homeowner defaulting and forty, four hundred, four thousand traders betting back and forth on the viability of his loan. Which do you think has a bigger effect on the economy?

As I posted here, this crisis is a result of an alignment of errors on the part of borrowers, lenders, rating agencies, and securities investors. After reading Taibbi, we should add to that list the failure of the government to properly regulate the CDS market and internal risk controls at companies like AIG.

Extremely Improbable Events Happen All the Time

Risk managers assert in their defense that the current economic crisis was an unforeseeable, low probability event. From Andrew Haldane’s paper, Why Banks Failed the Stress Test:

Risk managers are of course known for their pessimistic streak. Back in August 2007, the Chief Financial Officer of Goldman Sachs, David Viniar, commented to the Financial Times:

“We are seeing things that were 25-standard deviation moves, several days in a row”

To provide some context, assuming a normal distribution, a 7.26-sigma daily loss would be expected to occur once every 13.7 billion or so years. That is roughly the estimated age of the universe. A 25-sigma event would be expected to occur once every 6 x 10124 lives of the universe. That is quite a lot of human histories.

How is it possible that extremely low probability events occur? The answer is that, while many events are highly probable over a short period of time, over longer periods events are extremely improbable. It is highly probable that when you go to bed tonight, you will get up in the morning from the same bed. But, think back to where you went to bed twenty years ago, and the events in your life that brought you to where you go to sleep now. How likely was it that you ended up where you are? That you have the job you have? That you have the spouse and kids you do?

From Carl Bialik’s The Numbers Guy blog:

We tend to fixate on those events that are memorable, after they happen. Peter H. Westfall, a statistician at Texas Tech University, notes that any given order of a shuffled 52-card deck has about a one in 10 to the 68th power probability of happening, including the sequence in which all 52 cards appear in order. “Everything we see has about a zero probability,” Westfall said. “Calculating these probabilities after the fact is kind of meaningless.”

The present we’re living has impossibly low odds of occurring.

Bank risk managers acted as though every tomorrow would be similar to the short term past, and didn’t account for less probable but still very possible outcomes (like house prices declining) which could rapidly create a much different environment in just a year or two (like the one we’re living in now).

Whose Error was the Housing Crisis?

Who is responsible for the housing crisis? Some candidates are borrowers, lenders, rating agencies, and securities investors.  Attempts to blame one party or another fail, because the crisis is the result of a combination of errors by different parties which all aligned. Think of a wedge of Swiss cheese; to see through it, all the holes must line up. This approach is explained in James Reason’s Human Error, and illustrated in a diagram from that book:

In the housing crisis, here are some errors which had to align to get to where we are today:

1) Borrowers took out loans they couldn’t afford

2) Lenders made loans to borrowers which the borrowers couldn’t afford

3) Ratings agencies rated securities comprised of these loans as safe

4) Security purchasers relied on the erroneous ratings and bought the securities

Any of these parties could have averted the crisis had they avoided their respective error.

I am not saying that every member of each class made their error; plenty of potential borrowers didn’t borrow, not every lender made bad loans, not every rating was bad, and not every investor bought bad securities. But, enough of each class made these mistakes to trigger the events leading to the current situation.

Also, I am not saying that individual actors didn’t benefit from their actions at the time – there were certainly some winners. And, looking at each individual decision made, it’s not clear that any of them were irrational at the time. These were errors in the sense that, in hindsight, collectively we would have been better off if people had acted differently.

In any complex system, it’s often more likely that a major breakdown is the result of an alignment of errors, rather than the failure of a single component.

Loan Underwriting, Financial Cycles, and Ponzi Financing

Loan underwriting of all types (consumer, residential mortgage, CRE) follows cycles. From Edward Leamer’s “Housing and the Business Cycle” paper:

Why do lenders “forget all about risk”? I’ve previously argued it has to do with certainty of outcomes and slow feedback loops (see here).

The Inevitability of Errors

Errors are inevitable – no matter what the stakes, no matter how much you practice, things are going to go wrong a certain percentage of the time in any complex task or decision. The New York Times has an article with an excellent example: basketball free throws.

There is nothing in sports as straightforward as a free throw; the equipment is always the same, the geometry is constant, and there is no defense interfering. The only variables are the player’s concentration and control over his or her body. And yet, at the highest level of the game, it goes wrong 25% of the time, year after year after year:

In the National Basketball Association, the average has been roughly 75 percent for more than 50 years. Players in college women’s basketball and the W.N.B.A. reached similar plateaus — about equal to the men — and stuck there.

The general expectation in sports is that performance improves over time. Future athletes will surely be faster, throw farther, jump higher. But free-throw shooting represents a stubbornly peculiar athletic endeavor. As a group, players have not gotten better. Nor have they become worse.

“It’s unbelievable,” Larry Wright, an adjunct professor of statistics at Columbia, said as he studied the year-by-year averages. “There’s almost no difference. Fifty years. This is mind-boggling.”

And it’s not like the stakes aren’t high:

Last season, Memphis was 38-2 despite making only 61 percent of its free throws, missing an average of nearly 10 a game. The Tigers lost the national championship game after missing 4 of 5 free throws in the final 72 seconds against Kansas, which had made a late 3-point shot to tie the game and won in overtime…About two-thirds of a winning team’s points in the final minute typically come from the free-throw line…

Obviously, we need to work to eliminate mistakes and design systems to minimize the chance of them occurring. But, a certain percentage of the time errors will happen. Learn what you can from them and move on.