Wednesday, December 30, 2009

Artisan Vodka



I am a cocktails man rather than a beer or wine-enthusiast, and my drink of choice has long been the Cape Cod (vodka and cranberry---particularly with a smooth vodka component such as Grey Goose or Ketel One). I was pleased to recently learn of the existence of a locally-made premium vodka called "Touch".

Touch Vodka is made using the ancient technology of the pot still. Mass-market spirits are produced in a fractionating column still (as is gasoline, basically), which is fast and economically scalable and produces a high-proof result, but the cost of the efficient separation is that flavors ("congeners") are burned out. Vodka is traditionally distilled to very high proofs (190-194) in a column still, producing what is basically pure alcohol (below 190 you have a whisky), and then filtered to make it consumable by human beings.

With a pot still, in contrast, you get incomplete separation, a much more variable and time-intensive process, and a need to go through multiple iterations of distillation. The process starts in a pumpkin-shaped pot, traditionally made of copper: because alcohol has a lower boiling point than water does, the alcohol steam rises from the fermented liquid in the pot and is funneled through a "worm". The worm cools the alcohol back to liquid form and it drips into a container. The first round is typically very weak, so the process is repeated until the desired end product is obtained. The incomplete separation and retention of the congeners allows for the creation of a particularly flavorful product. However, this requires a great deal of operator skill and judgment, hence the artisanal nature of the work. I believe that Ketel One was the first vodka producer to offer a pot still vodka in the US, and pot distillation is generally regarded by critics as the mark of a distinguished choice.

We'll get into more detail on a somewhat conceptually similar---albeit darker---process in a future post, when we discuss the gas centrifuge cascade used to create enriched (weapons-grade) uranium for nuclear bombs.

Touch Vodka is made from a champagne yeast infused with wildflower honey from Florida pine forests and the Everglades, and distilled (over in the old pirate haven of Tampa) in pots similar to those used by the bootleggers during Prohibition. Controls of the process allow it to be produced without recourse to filtering at the end; unfiltered vodkas are traditionally just blindness-inducing monstrosities because the pre-filtered proof state is so high, but Touch is pot distilled straight to 80 proof and does not require that "step-down transformer" step of terminal filtration. It is a very flavorful and elegant vodka, up there with other artisan spirits such as the Tito's Handmade Vodka created by an Austin geophysicist. The bottle is rather pretty, too, complete with hand-applied paper roses (in other words, it looks good as a gift).

The stuff is hard to get, though: locally, it is sold at a few hip restaurants, such as HUE in downtown Orlando, and there are some boutique fine-spirit shops around that carry it. If you like exotic vodka, it is worth the search.

Tuesday, December 29, 2009

Pulp Fiction

I am mostly a non-fiction type, but I thought it would be fun to mention a few novels that I have enjoyed in recent years. My tastes tend to run to techno-thrillers and fairly violent plots, so these will certainly not appease all literary appetites...

Sci-Fi/Fantasy

I think my favorite cyberpunk novel is Neal Stephenson's Cryptonomicon. Stephenson must be a great guy to have a beer with---his erudition is extraordinary.

In the swashbuckling, sword-and-sorcery fantasy department, a newcomer named Brent Weeks wrote a series called The Night Angel Trilogy that struck me as an impressive work. It chronicles the development of a street urchin into a magnificently lethal warrior-assassin. The villains in the story are so despicable that you cannot wait for them to pay.

Thrillers

The Spanish writer Arturo Perez-Reverte has a breadth of knowledge that rivals that of Neal Stephenson, although Perez-Reverte's particular interests are chess, art, fencing, rare books, and the occult. I have enjoyed all of his books, but my favorite is probably The Club Dumas. The Club Dumas was made into a Polanski film starring Johnny Depp and retitled The Ninth Gate.

My friend Marcus Wynne does great work combining very highly trained military special warfare characters and real-world equipment and tactics with a nuanced psychological study of the dark side of the job. I think No Other Option is my favorite one by Marcus.

The rather misogynistic and opinionated South African writer Wilbur Smith manages to combine very vivid descriptions of African wildlife with violent action, "Mary Sues" (i.e., unnaturally perfect, wish-fulfillment characters embodying traits that the author particularly desires), and backdoor political intrigues. My favorites by Smith are A Time To Die, about a physically godlike and ruthless Rhodesian commando veteran-turned-professional big-game hunter's problems when he crosses the wrong border pursuing a rogue elephant, and Hungry As The Sea, a more poetic story of a man's losses and redemption during a life spent in the hazardous profession of remote, high-risk ocean salvage operations.

Frederick Forsyth's The Dogs of War is worth a read or re-read, in my opinion. Classic mercenary stuff here.

A sophisticated financial thriller, David Schofield's The Pegasus Forum involves a psychotically bitter Nobel Prize laureate economist's master plot to destroy the Japanese economy, using tools that include a handpicked crew of former disciples that have been strategically placed in senior positions at the US Federal Reserve and the Bank of Japan, Wall Street and City of London investment banks, and a secretive Cayman Islands-based global macro hedge fund called "XFin Partnership." It is a fun book.

Manga

If you are into this art form, you might enjoy a series called Black Lagoon, about a small paramilitary team running a heavily modified WW II era PT boat ("Black Lagoon") around Southeast Asia and performing various illegal jobs, mostly as contractors for organized crime syndicates in the region.

Heavier Literature

Mark Helprin's Memoir from Antproof Case was very enjoyable for me, particularly as a coffee drinker. The protagonist has a background that includes Harvard, service as a fighter pilot in WW II, investment banking, and time in a Swiss mental institution. The book starts off as rollicking satire, but it becomes quite serious and poignant towards the end.

Non-Fiction Adventure

Frank Pope, who was a member of Oxford's MARE (Maritime Archaeology Research) Unit, wrote Dragon Sea about a dangerous and complex joint-archaeology/underwater commercial salvage operation in the waters off of Vietnam. Issues related to time and expense cause decision-makers to opt for a saturation diving approach, and Pope's discussion of the risks and characters that make up the sat-dive world are memorable and rich in insider's detail. He also gets into a discussion of the tensions between an academic archaeological project and the fine art auction market, since a percentage of the artifacts recovered from the shipwreck---a treasure trove of 15th century ceramic pieces---must be sold to offset the costs of the operation.

Laird Hamilton

Big-wave surfing icon Laird Hamilton...doing what he does best in the monster waves of "Jaws", Maui.



As a (*bit past his prime*) Florida surfer, I think surfing, particularly big-wave work like Laird does, is also a good metaphor for the type of trading strategy that we follow. Rather than trying to precisely value the market, predict the future, or figure out causality chains (probably impossible in a complex adaptive system like a market), we just try to identify and ride the "waves" of long-term price trends. To paraphrase John Henry, "We want to be long when a market is going up and short when a market is going down. Period." Actually doing this is fairly involved, of course, but there is a Zen simplicity that underlies both surfing and systematic trend-exploitation approaches.

Monday, December 28, 2009

The Permanent Portfolio

In the last entry, we discussed the fiscal discipline imparted by the four-part "Crashproof" structure of a limited-purpose checking account, untouchable savings account, discretionary slush fund, and investment clearinghouse account. In this post, we'll specifically look at the investment account and discuss a concept that the late author Harry Browne termed the "Permanent Portfolio".

Harry Browne was a very intriguing character. A free market/Austrian economics disciple and former Libertarian Party presidential candidate, Browne taught himself economics and finance and worked as an investment advisor, specializing in the Holy Trinity of alternative investment strategies (AIS), asset protection structures, and offshore banking, for about three decades. One of his books, How I Found Freedom in An Unfree World, is probably the coolest self-help guide I have ever read.

(Harry Browne)

The essence of Browne's Permanent Portfolio concept is to create a conservative, all-weather/all-terrain investment system that allows the owner to sleep at night, regardless of what is happening in the world. While part of an investment clearinghouse account can be deployed towards active management styles and strategies that attempt to time the market to some extent (which of course is what a hedge fund manager does), the Permanent Portfolio would represent the "passive" component of the overall program. He wanted it to combine three features: safety ("it should protect you against every possible economic future. You should profit during times of normal prosperity, but you should also be safe ((perhaps even profit)) during bad times"); stability ("even in the worst possible circumstances, the portfolio's value should drop no more than slightly---so that you won't panic and abandon it"); and simplicity (the portfolio should be easy to maintain).

Browne breaks the macroeconomic landscape down into four general scenarios: prosperity (bull markets), inflation (rising prices, probably due to loose monetary policies previously discussed on this blog), tight-money (Federal Reserve response to inflation), and deflation (prices decline, purchasing power of cash grows, can be associated with a depression if it occurs rapidly due to demand shocks). He makes no attempt at predicting which scenario is more likely from a probabilistic standpoint; he considers them equally probable for planning purposes.

Harry Browne: "To be protected in all circumstances, each economic environment must have at least one investment in the Permanent Portfolio that responds well to it."

Browne then splits his Permanent Portfolio into four asset classes: stocks, bonds, gold, and cash. Stocks would do very well during a prosperity scenario, bonds do pretty well during prosperity (as interest rates fall) and deflation (as interest rates are aggressively cut down by a desperate central bank), gold does very well in an inflationary environment (tends to do fairly poorly in the other three), and cash earns a premium during a tight money situation and in a deflation (cash is neutral during prosperity and a loser during inflation). I should note that Browne's scenario narratives generally do not involve an absolute, final economic catastrophe, like an actual sovereign default by the United States. This is probably reasonable, since the US government would resort to debt monetization in that situation, and try to inflate its way out of its debts through the printing press (some believe this exact scenario has become likely, and we'll devote a blog entry specifically to discussing it).

Browne's asset allocation system is to divide investments equally across the four classes: each gets 25%. This form of allocation is called "1/N" in investment literature because an allocation receives a funding level of 1 divided by the number of investment options (in this case 4). In contrast to 1/N, much of Modern Portfolio Theory rests on the notion that statistical information regarding asset performance, specifically expected return, standard deviation (used as a proxy for risk), and correlation can be fed into an optimization engine and an ideal portfolio mix for some target level of "risk" (i.e., standard deviation)---say, 59.6% allocated to stocks and 40.4% allocated to bonds---can be constructed and implemented.

Snobs will say that 1/N is remedial, almost vulgar in its simplicity. In real-world testing, however, 1/N has routinely outperformed the more quantitatively sophisticated mean-variance portfolio optimization, and this is true for two reasons: 1) financial market prices do not follow the Gaussian statistical distribution that would give terms like standard deviation meaning, and correlations are unstable and tend to increase when the economy is stressed; 2)in trading system design, optimization of this naive, fragile kind is called "overfitting to the curve" and is considered very foolish. In fact, it appears that even the founder of the mean-variance portfolio optimization revolution, Harry Markowitz, ultimately used 1/N when it came to making real decisions about his own investment portfolios, and the Black Swan himself, Nassim Taleb, likes it.

In terms of periodic rebalancing, Brown recommends looking at the net asset value of the portfolio and modifying it if any particular asset rises to over 35% of the total NAV, or if any has fallen to below 15%. An investor basically makes sure that each investment has an equal allocation. In his words, "To rebalance the portfolio to its original percentages, just sell enough of the leading investments to reduce each to 25% of the total value. Use the proceeds from those investments to buy more of the investments that have fallen below 25%."

The intuition might be that Permanent Portfolio would never make any money, since gains in one asset class would be offset by losses in another. In practice, the gains in the winners reliably tend to be larger than the losses in the losers, hence a positive return is achieved over time.

There are various ways to go about constructing a Permanent Portfolio, but the key elements in my humble opinion are: A) exposure to the US S&P 500 or Russell 3000 index with as little friction (fees, transaction costs) as possible, which means purchasing an index ETF; B) exposure to the US Treasury 10-year; C) deciding whether to invest in a gold fund, to physically hold gold bullion, or both (pros and cons of various methods of gold investment will be left for a future discussion, but for now I will say that buying gold mining company stocks is not the same as having true exposure to the commodity itself); and D) deciding whether the cash allocation should be in addition to the cash already held in a contingencies/savings account (the cash will probably be put in a Treasury Money Market Fund or Money Market Fund mixed with three-month T-bills).

Alternatively, there is a mutual fund family based on the Permanent Portolio (but with other allocations within it). One member, PRPFX, has achieved a 5-year return of 8.62%. If you followed Browne's recommended portfolio mix to the letter since 1972 (after the US left the gold standard so that the printing press could be more fully put to work), you would have achieved a compound annual growth rate of about 9.7%, which defeats a (much riskier) 100% US stock market allocation over the same period. The thing actually achieved a positive return (+2%) last year; I think the worst year was 1981, when it lost 4%.

For further reading: I have enjoyed all of Browne's books, particularly the aforementioned, philosophical "How I Found Freedom in An Unfree World", and managed to get a couple of them signed by the author before he died. The most concise discussion of the Permanent Portfolio is found in the quick, accessible "Fail-Safe Investing", although a Google search under "Browne Permanent Portfolio" will yield all kinds of interesting tidbits.

Sunday, December 27, 2009

Crashproofing

In the book "Crashproof Your Life", attorney Thomas Schweich lays out a simple framework for mitigating the risk of individual financial catastrophe. At the heart of his book is his "pyramid" structure, with each of the four corners representing a different bank account:

1) a limited-purpose checking account
2) a discretionary "slush fund"
3) an untouchable savings account
4) an investment clearinghouse account

Although he does not appear to be formally trained as an evolutionary psychologist or behavioral economist, Schweich does recognize that human beings are inherently susceptible to some maladaptive decision-making pressures and his purpose is to create a four-account, autonomous direct-deposit structure that forces fiscal discipline. For instance, the limited-purpose checking account is used only for recurring expenses (house, car, utilities, food). The slush fund is for shopping sprees, vacations, and so on. The savings account is essentially a doomsday fund and is never accessed under normal conditions. The investment clearinghouse account is used to fund investment programs (more on this later).

As Schweich puts it: "Under the pyramid plan, the first two accounts control your spending and the second two accounts grow your savings...the purpose of this legal structure is to change the way you think about money. The pyramid system places absolute structural limits on how and when you can spend your money. As you will see, each of the four categories has some flexibility, which is necessary for any structure to last; but if you are to crashproof your finances, you have to structure your mind as rigidly as you structure your accounts: the limited-purpose checking account pays for day-to-day expenses, the slush fund covers extraordinary expenses, the savings account accumulates cash available for true emergencies, and the investment account grows your wealth and builds your long-term security. You cannot use money in one account to cover a perceived shortfall in another. Use the clear legal structures to create clear mental structures that will prevent you from dissipating your wealth in the way the forces of disorder want you to do."

The author goes on to discuss his allocation principles, which go something like this: an individual or couple should take after-tax annual income and then divide by ten. The ten units are then allocated according to a fixed-percentage schema: he starts by committing 7 units (70% of after-tax income) to the bill-paying checking account, then 1 unit (10%) to each of the other three accounts. It is vitally important to Schweich that the allocations be made automatically via direct-deposit, and that ATM card use is somehow strictly controlled.

One person's recurring expenses will obviously be different from another person's: a woman who needs to dress very well as part of her job, for instance, may be perfectly reasonable in viewing the limited-purpose checking account as the funding source for her wardrobe. However, Schweich cautions against this practice and he has some fairly draconian rules regarding what constitutes a legitimate recurring expense and what should be rightfully considered a discretionary/slush fund-sourced expense. For example, he says, "To qualify as 'routine', the total amount you can spend on entertainment should not exceed about 5 percent of the sum that you put into the account. In the case of our extended family, that would be about $210 per month (5 percent of $4200)."

Allocation percentages do evolve over time: for instance, after seven or eight years (depending on prevailing interest rates), the savings account will hold the equivalent of about 100% of average after-tax income. At that point, the individual or couple has a year's worth of income saved in the apocalyptic "end of days" account and can probably cease making allocations to the account and rebalancing. Perhaps after rebalancing the checking account still receives 70% of free cash flows, but each of the two other active accounts (slush fund and investment clearing house account) now receives 15%.

The "average after-tax income" issue is very important: if the saver(s)also grow living expenses over the time horizon being discussed, then it may take longer than planned to save the target 1 year (more or less) of expenses that are meant to be covered by the doomsday savings account. This is because the amount held in savings after, say, seven years may not be sufficient to cover a year of living expenses if the living expenses are now at an all-time peak.

Schweich's policy for the slush fund is to first use it to pay off debts, usually by starting with the highest interest rate problems (credit cards) and then working down. In this regard, he joins Dave Ramsey and a host of other pop-personal finance writers who have strong anti-debt leanings. In theory, of course, leverage can be very attractive if the interest-rate differential between money going out on loans and money coming in from investments is favorable to the borrower, but few true risk-free arbitrage opportunities exist, time/interest rate coordination activities can be perilous, and many of these writers are inherently conservative regarding leverage for other, usually good reasons. Leverage is an amplifier of one's fortunes, good and bad. Virtually no investment opportunities will ever manage to consistently clear the annual rate charged by credit card companies, so few would argue that this is ever going to be an application of favorable leverage.

My own feeling on this is that the slush fund should be used to retire expensive consumer debt like credit cards, but not for mortgage prepayment efforts unless the individual is truly conservative and so is his significant other. My fear is that an obsessive focus on total elimination of debt may result in negative consequences for the relationship, as the couple forgoes vacations, gifts, and so on. I doubt that Schweich would be sympathetic to this complaint---in fact, he'd probably say that potential mates could use this as a selection filter to avoid being hitched to dangerously irresponsible "party" people and the like.

The social problems potentially created by a zealous commitment to crashproofing may be particularly acute for men. A single guy looking for or trying to keep a romantic partner and competing in a world of strutting, peacocking males promising their potential mates exotic vacations, frequently buying gifts, and so on may find himself penalized for being so conservative and accused of being miserly or inelegant, so my suspicion is that this approach works best for either established (post-courtship phase) couples who are operating as a true economic team, for hardcore independent lone-wolf types who are not interested in marketing themselves to potential mates on the axis of lifestyle enhancement/generosity, or perhaps for singles who are socially networked into groups that share certain conservative lifestyle qualities (Helen Fisher would call these types "Builders"---more on that in a future post). I think that, for virtually everyone else, the courtship phase of a relationship will prioritize fitness-signaling and chivalry and thus an aggressively conservative "Crashproof" economic strategy may not work well in the dating/mate-selection environment. It is a fine line, I know, and I really am not qualified to offer any insights into this aspect.

For long-term debt retirement, my modification to Schweich's pyramid would be to keep the slush fund for toys and fun after the credit cards are paid off, and to use future growth in the amount of money allocated to the limited-purpose checking account for the more conservative prepayment stuff. In other words, imagine that a couple currently earns $100,000 and thus places $70,000 (using the Schweich basic 70/10/10/10 allocation rule; this may not work for everyone) in the limited-purpose checking account. Let's say that living expenses can be kept within this $70,000 envelope, and that next year the couple does wonderfully well and earns $200,000. Our lucky lovers now have $140,000 (70% * $200k)available for the specialized checking account, but their actual expenses are still only $70,000. There are good arguments for this surplus being allocated to the investment account, but in keeping with the highly conservative, "crashproof" nature of the Schweich plan I would submit that the money could in fact be intelligently applied towards early retirement of long-term debt, most specifically the house note.

In terms of his discussions of the investment clearinghouse account, Schweich is not a money manager and thus his descriptions of options are not meant to be exhaustive. I believe that a separate concept, one created by the late libertarian author and investment strategist Harry Browne, is very useful in maintaining the goals of Schweich's crashproofing financial pyramid structure as we move into the more dangerous and uncertain waters of personal investmment planning. I'll describe Browne's "Permanent Portfolio" in my next blog entry.

For Further Reading: Thomas Schweich's book is titled "Crashproof Your Life: A Comprehensive Three-Part Plan for Protecting Yourself from Financial Disasters".

Saturday, December 26, 2009

Random Thoughts on Travel Tech




Portable flash drives, or "thumb drives", are well-established as a convenient way to carry around important data. I bought a couple of these "TAC Drive" thingies from TAD Gear (www.tadgear.com) and have been wearing one on its dog tag chain. The TAC Drive is billed by the manufacturer as a "rugged USB flash drive" and claims to be able to withstand saltwater immersion to 100 feet for 60 minutes, temperature extremes, and some shock/impact drop tests. The TAD version has that company's signature skull logo. I have a lot to say about TAD Gear, but for now I'll just state for those unfamiliar with the company that I think TAD is a great outfitter for what I will term "paramilitary global nomad chic".

TAC Drive is intended for use as a personal medical records system---in that regard, it would benefit from "positive externality network effect" economics (i.e., the more people that carry their health information on portable USB drives, the more valuable the approach becomes as the health care system becomes configured to take full advantage of the technology).

I use mine a bit differently. I downloaded a freeware product called "Portable Apps" (www.portableapps.com) to my TAC Drives. This application allows you to plug your thumb drive into a USB port on a host computer and then do some basic Internet work through the thumb drive, rather than directly through an application on the host computer. The idea here is that you are overseas at an Internet cafe or hotel business center computer or equivalent, wish to check your e-mails or surf for info, but do not trust the security of the computer you are working on. With an application like Portable Apps, you would do everything through the thumb drive and thus reduce your exposure to issues like identity theft. Portable Apps also gives you some relatively easy to use encryption capability for the information you store on your drive. Installed in a TAC Drive, it is a bit like wearing a small, rugged, external hard drive around your neck. In case this is important to some readers, I will note that I have worn a TAC Drive USB dog tag through airport metal detectors and it cleared them with no problem (your mileage may vary).

To be honest, I feel that my first line of defense against travel infosec problems is to just bring a netbook. I found that a normal laptop was just too much for me to lug around on field/expeditionary travel related trips, but I found myself at a bar with Junichi Ujiie, the chairman of Nomura, while attending a conference in Tokyo in October and became interested in the little Sony VAIO W netbook he carried in his briefcase. I picked one up a month or two ago and found that it is about the perfect size for what I need---the screen and keyboard are still quite user-friendly, but the overall footprint is about half the size of a traditional laptop. You do give up some features (for example, no DVD drive), but it may be worth it depending on the nature of your trip. Loaded with appropriate apps (Skype, Google Earth, Nikon Transfer and ViewNX, etc.), it's an agile, elegant solution.

As a reviewer for National Geographic Adventure recently put it: "...a lightweight, no-frills machine with a screen that is bigger than a smartphone's is a godsend. If you really crave computing power, limited memory is offset by free online storage devices...if I were planning an extended trip---a month of trekking, say---I'd pack a netbook, rely on Wi-Fi, and avoid Internet cafes altogether."



(...took this picture of the grounds of the Imperial Palace just hours before discovering the joys of the VAIO W netbook and shot glasses of ice-cold sake)

I also recently ordered a VAIO UX after seeing Christian Bale/John Connor using one in "Terminator: Salvation." It looks pretty cool, although I suspect I will use the W a lot more.

Another gadget that I just picked up is a Cinemin Swivel (www.wowwee.com/en/products/tech/projection/cinemin/swivel), a palm-sized DLP projector system for iPod or laptop. I have only watched a couple of downloaded music videos with it; the clarity is not the greatest unless you have a pitch-black room. You can project movies onto the side of a tent and do some other interesting things with the playful little device. I put it in a Maxpedition FR-1 pouch along with a couple of iPods, headphones, an external battery juicer, and stuff like that. I'll show my whole travel bag set-up in a future blog entry and explain what I like to carry and why (noting that this is a highly subjective area, of course).

(VAIO W netbook and Cinemin iPod projector shown with standard hardback book for scale)

Wednesday, December 23, 2009

Clouded Leopard

Nice footage here of this rare, hauntingly beautiful creature:

Tuesday, December 22, 2009

Game Theorist Buys A Car

The political scientist and applied game theorist Bruce Bueno de Mesquita has described a very intriguing approach for new car purchases. Mesquita, a master quantitative negotiator and strategist, is concerned with the signals that the would-be car buyer sends to the dealer when he shows up, finds a model that he likes, and begins the process of haggling over price and features. Salespeople know to draw out the initial courtship phase as long as possible, and many employ persuasion techniques straight out of Cialdini's seminal work in order to get the buyer to commit psychologically to the vehicle, particularly after a favorable test drive. The salesperson usually leaves the buyer in a waiting lounge area so that he can go "discuss the deal" with his sales manager. Once again, the wait may be extended, or perhaps the good cop salesman/bad cop faceless manager routine is iterated through several times in order to try to create a sort of Stockholm Syndrome effect, wherein the buyer sympathizes with the salesperson and thinks that the salesman is his friend, is looking out for him, is making reasonable concessions, is on his side against the tyranny of the sales manager...

As Bueno de Mesquita explains: "...But there you are subjecting yourself to the salesperson's pitch, standing before a car dealer in his or her place of business, feeling compelled to haggle over the price, probably to your embarrassment and certainly to your disadvantage. The whole time you're talking to the dealer you're revealing information that sets you up to pay too much.

"Being there is what game theorists call a costly signal. It's a costly signal because your expenditure of time and energy announces that you want to buy, that there's a good chance you'll buy from the dealership you're visiting rather than go elsewhere, and, especially if you have kids with you, that you want to get out of there as quickly as possible. That first step, then, your simply being there, translates into strengthening the salesperson's hand in getting a good price. They believe you're ready to buy, and you've done precious little to dissuade them. Score one for the dealer, none for you."

Bueno de Mesquita goes on to discuss the informational asymmetries that the dealership's salesman enjoys. For example, the buyer may have done online research and found the invoice price of the car, but the salesman has information about local market conditions---aspects such the popularity (or lack thereof) of a certain color and how that information can be used to pile on additional costs. The salesman may also ask for you to quote him a price, and you may feel compelled to give something that is at least credible. The salesman's game is to make you feel that your offer is absurdly low, but that he will attempt to "work with you" and go talk to his manager. Alternatively, the salesman may say that the dealership has a no-haggle sticker price policy, which will probably lead to an even worse, perhaps much worse, result for the buyer.

A game theoretic solution? The buyer starts by doing online research and determining exactly what he wants. When he has determined color, options, and so on, he finds every relevant dealer within a 20-50 mile radius of his home. Then he calls each dealership with a very precisely articulated proposal.

Bueno de Mesquita: "Here is my typical spiel: 'Hello, my name is Bruce Bueno de Mesquita. I plan to buy the following car (list the exact model and features) today at five PM. I am calling each of the dealerships within a 50 mile radius of my home and I am telling each of them what I am telling you. I will come in and buy the car today at five PM from the dealer who gives me the lowest price. I need to have the all-in price, including taxes, dealer prep (I ask them not to prep the car and not to charge me for it, since dealer prep is little more than giving you a washed car with plastic covers and paper floormats removed, usually for hundreds of dollars), everything, because I will make out the check to your dealership before I come and will not have another check with me.'

"If you are making your first call, be sure to tell the salesperson that you will tell the next dealer the price you've been quoted. After the first call, make sure the future salespeople know that you will be repeating whatever is the lowest price offered to you so far. That way, future dealers know what price they must beat, and the dealer you are currently talking to knows that if he wants to have a shot at selling you a car, he had better quote his lowest price."

Bruce Bueno de Mesquita states that he has purchased Hondas, Toyotas, and Volkwagens using this competition/auction-structuring price-discovery technique, and he has always managed to defeat even the Internet-quoted price with it. He has taught it to his students and many of them have also employed the method, with similarly excellent results.

Monday, December 21, 2009

Puppy Love

From anthropologist and author Helen Fisher:

"In her groundbreaking book, The Hidden Life of Dogs, Elizabeth Marshall Thomas maintained that dogs show deep romantic passion for one another. She arrived at this conclusion moments after she introduced Misha, a handsome Siberian husky, to her daughter's young and beautiful dog of the same breed, Maria. Thomas had agreed to house Misha while his owners were on an extended trip to Europe.

"The day arrived. Misha's owners delivered this vibrant male to the Thomas home. Misha pranced into the living room to look about, settling his gaze immediately on the gorgeous Maria. In an instant he bounded to her feet and skidded to a stop. At once, Thomas writes, 'Maria dropped to her elbows in an invitation to play. Chase me, her gesture said. And he did. Quickly, lightly, the two delighted creatures spun around the room. Misha and Maria were so taken with each other that they noticed nothing; they were entranced within their own bubble. Misha didn't even notice when his owners left.'

"The two joyous dogs were immediately inseparable. Together they ate and slept and roamed; together they bore four hearty pups; together they reared them---until the dark day when Misha's owners gave him away to people in the countryside. For weeks Maria sat in the window seat of the Thomas home in the very spot where she had watched her beloved Misha being forced into a car. Here she pined. Eventually she gave up waiting for him to return. But 'Maria never recovered from her loss,' Thomas writes. 'She lost her radiance...and showed no interest in forming a permanent bond with another male, even though, over the years, several eligible males joined our household.'"

.....

Is there a Misha for every Maria? Can they survive life's many trials?

Friday, December 18, 2009

"Price Gouging"

Apparently most of the states have laws on the books against the practice of "price gouging", which occurs when sellers raise prices, usually on critical goods like water, plywood, generators, gasoline, batteries, and ice, after a storm or some other disaster has caused serious lifestyle disruptions to a large segment of the local population. The wording of the laws seems to vary from place to place, but generally the rules state that a seller cannot raise normal prices beyond some amount---in some cases the amount specified is zero, in some cases it is 10%, in some it is "reasonable"---in response to a crisis. The idea is obviously to prevent unscrupulous and opportunistic merchants from taking advantage of desperate disaster victims.

While intentions may be good, this is yet another case of an economic scenario in which the right heart leads to the wrong results. Laws against price-gouging almost guarantee that there will be a shortage of critical goods if and when a disaster does strike a community. There are three reasons for this:

1. No incentive for merchants to carry excess inventory. Let's say that a local Home Depot sees that the demand for portable generators is normally at level 5, but in the wake of a major hurricane that demand goes to level 10 immediately. If Home Depot carries an inventory of generators that is appropriate for normal conditions, the generators will sell out quickly before or just after a storm and then there will be no generators available at any realistic price. In order to have enough to meet a level 10 demand, the store will have to order many more generators than it ever sells under normal conditions, which means dedicating inventory space and possibly working capital to products that may (with a high probability) just sit there on the shelves. Perhaps the hurricane never materializes and Home Depot just carries excess generator inventory indefinitely.

To carry the excess inventory of generators, Home Depot needs to be compensated for the risk that the economic justification for carrying this inventory---a sudden, upwards demand shock for generators created by mass power outages---never comes. The store manager needs to feel that the excess generators will fetch a premium in the event of a storm in order to cover the (possibly greater) probability that the store will just end up ordering more than it can sell. The concern is one of irreducible uncertainty.

The result of anti-price gouging legislation is that Home Depot won't maintain an excess inventory of generators, and thus the store will sell out of these products quickly when they are needed most, probably in the short period before a major storm arrives when it has become clear that the area in question is going to get hit. At the point that Home Depot and other stores sell out, the cost of a generator truly skyrockets---you have to start looking at more and more extreme measures being necessary to obtain one.

There is a cruel irony at work: dropping the anti-price gouging legislation would lead to many stores carrying the excess inventory in the hopes of making these special profits, but if many stores do this it would lead to prices coming down on the increase in supply. The paradox is that allowing merchants to charge as much as they can gives them the incentive to carry the inventories, which in turn brings generator prices down because of the creation of competitive pressures on the sell-side. The best way to guarantee the availability of cheap generators during a disaster is to allow competing sellers to try to price gouge.

2. Emergent entrepreneurs have no incentive to become involved. Continuing with our generator example, a private citizen in a neighboring-but-relatively-unaffected city or county could rent a large truck, purchase a bunch of generators and some supplies, bring his chainsaw (to cut his way through fallen trees) and rifle, and attempt to make his way into the disaster area in order to set up shop and sell generators. However, he would not be able to charge a premium over what he purchased the generators for (unless he was willing to break the law), and thus would be unable to cover his costs, let alone to achieve the kind of profit that would be necessary to motivate someone to drop everything and attempt a short-term, high-risk, capital-intensive project like this.

This is not to say that heroic Good Samaritan types will be dissuaded, because such people exist and will operate at heavy financial losses and personal risk to try to bring aid to the needy. However, these people are recognized as heroic for a good reason: they are rare. Once again, the best way to get generators into the area is to encourage a range of motivating emotions, most notably greed, in order to deploy resources and human creativity towards a social good.

3. There is no mechanism for differentiating between casual and serious needs. Charles may want a generator because he needs to keep his life support equipment going; Bob may want a generator because he wants to be able to continue to watch porn. Unless the people at Home Depot can read minds and determine what uses Bob and Charles have in mind, that last generator may go to Bob if he happens to get there a few minutes before poor Charles.

If the generator sells at a premium, however, Bob would be expected to decide against a purchase long before Charles would. We can certainly all construct hypothetical situations in which Bob would be prepared to pay more for a porn capability than Charles would be willing to pay for his physical health (Bob is a desperate porn-addict; Bob has vast wealth; Charles doesn't actually care about his physical well-being), but the market price discovery mechanism is not about trying to guarantee the optimal result in every single instance, no matter how unusual, eccentric, or insane.

We can also look at this from a labor perspective: if in the wake of the same storm you try to hire a contractor to build a gazebo in your backyard, you may find that virtually none are available. The few who are may give you a price quote for the job that is far in excess of what you would have normally expected to pay, so you put the project on hold. The reason for the lack of availability and high prices is because the contractors are busy doing major projects, like putting families' homes back together. If a contractor takes on your job, he may miss another, larger and more lucrative one, so he wants to be paid for his risk. Given the dire needs of some members of the community, your gazebo should in fact be put on hold, but the only way for this to happen is through the indirect transmission of the market price discovery system.

If contractor wages were artificially held down by government price controls, however, this mechanism would not be able to work. The attempt would no doubt be to prevent the wealthy from monopolizing resources at the expense of the poor, but the actual effect would be to give all projects the same priority and to cause distortions and poorly coordinated distributions of resources. If the free market system were permitted to work, a large piece of the problem could be solved efficiently and then government agencies, NGOs, charity organizations, churches, and the like could come in and try to identify those who had clear needs, but who lacked ability to pay.

Wage and price controls have historically managed to induce scarcities very effectively, and variations on our Home Depot/generator theme can be applied to many other industries, including health care. It is one of the great conceits of central planning enthusiasts that they believe they have access to more information than does the "distributed intelligence" of a free market, and that they can arbitrarily set the optimal clearing price without knowing the evolving dynamics of true supply and demand.

Wednesday, December 16, 2009

Chute Boxe



In the summer of 2006 I had the opportunity to spend some time training with the professional fight team of the Chute Boxe Academy of Curitiba, Brazil. At the time, Chute Boxe was arguably the most feared mixed-martial arts (MMA) camp in the world---it had produced a stable of elite MMA fighters and was seen as a premier source of combat athletes for the prestigious Japanese PRIDE FC fight promotion (PRIDE would frequently sell-out the Tokyo Dome and the Saitama Super Arena).

The adventurer John Falk, clearly a fellow fan, did a great article on his experience at Chute Boxe for National Geographic. I thought it captured the personality of the academy very well:

http://www.nationalgeographic.com/adventure/john-falk/brazil-fight-club.html


The training I received was truly world-class, and I was amazed at both the skill level and professionalism of the fighters and coaches. Chute Boxe was known for its ferocious, hybrid fighting style, a pragmatic mix of Muay Thai and Brazilian Jiu-Jitsu that emphasized sophisticated, relentless compound attacks both standing and on the ground. They were also known for an extremely grueling training routine, and I learned the truth behind this reputation first-hand. This video gives a sense of how it all worked:



I did not emerge from the training unscathed: I had my foot, ribs, and (as evidenced from the picture below) nose broken while at Chute Boxe.




The damage was all sustained in a single day of full-contact sparring---the foot was an accident, the ribs and nose were the result of knees delivered to my hapless body and face while I was caught by my opponent in the double neck-tie control position favored in Muay Thai (in the military, it would be said that I had received the "full benefits of the training"). The good news: A) I was considered competent enough to warrant such an exciting training opportunity with an elite fighter, and B) the bloody and painful lesson did impart a sense of urgency in me regarding drilling the various escapes from the Thai clinch. The bad news is that none of those escape and countering techniques ever worked well for me against guys like Wanderlei Silva and Mauricio "Shogun" Rua. Still, I suppose that I am in esteemed company in at least this regard.

Unfortunately, it looks like it will be impossible for me to ever recreate my great experience at the Chute Boxe Academy: not so long after I left, PRIDE went under financially and many of the Chute Boxe star athletes and coaches left the camp to start their own gyms. Besides, I'll be 40 before too long and need to give up on any attempts to keep up with hungry, training-obsessed 24-year-old professional athletes (some of them no doubt cycling Boldenone, EPO, and other performance-enhancing drugs) before I have to be carried out of the gym on a stretcher, if not in a casualty bag.

I did manage to take a hundred or so pictures while I was there, so maybe in the future I will post a few more to add a splash of local color to an otherwise fairly dry (dare I say tedious?) hedge fund blog. Combining a pit bull aggressiveness and shocking capacity for violence in the ring with a gentle, easygoing, Brazilian surfer mentality outside of it, the fighters and coaches at Chute Boxe were probably the coolest guys I have ever met.

Monday, December 14, 2009

The Crash

If you have been patient enough to follow the story this far, I hope that our simple car-crash schema is now fully developed and we have the four basic components we need in order to have our spectacular "accident":

1. The Engine. A fractional-reserve banking system that is inherently dangerous, but extremely efficient at providing liquidity and credit expansion. The main parties who stand to lose if and when the system fails---depositors---no longer care much about risk levels because of generous depositor insurance (which, thanks to clever ploys like CDARS, are effectively unlimited in terms of loss coverage), and bank owners have been compromised by concepts like the "Greenspan put".

2. The Fuel. The Federal Reserve pumped so much money into the banking system starting in 2002 that the Fed Funds Rate had turned negative in real terms, making saving a loser's game and borrowing the breakfast of champions. Serious departures from moderate monetary policy regimes, such as that described by the Taylor Rule, combined with the bank multiplier effect of the fractional-reserve system, led to a vast amount of credit being available.

3. The Steering Wheel. The vast amount of credit was directed towards the housing market. The US Government, through FHA, Fannie, Freddie, and the Community Reinvestment Act, has made affordable housing a priority for many years. Fannie and Freddie, who had incestuous relationships with key players in the House and Senate (mostly Democrats, but some Republicans were also involved), were particularly instrumental in creating an insatiable appetite for subprime mortgages, mortgages that the two GSEs purchased from the banks (freeing them to generate more), then securitized and initially sold into the market. At a certain point, Fannie and Freddie began acting like giant hedge funds and using their AAA credit rating (courtesy of government backstops) to borrow cheaply and repurchase mortgage-backed securities for their own balance sheets. Perhaps $1.5 trillion in toxic subprime material was being carried in this way, until Fannie and Freddie suffered catastrophic losses, failed, and were placed under government control.

4. The Gas Pedal. Sophisticated financial engineering contrivances such as CDOs and CDS allowed banks to remove mortgages from their own balance sheets and also created a tiered structure for new derivative securities that gave purchasers the ability to daintily select from a menu of offerings, with choices dependent on product credit quality and risk tolerance. The methods used by market operators and ratings agencies to assess default probabilities suffered from statistically optimistic assumptions regarding market behavior that have now been falsified. The result of this apparatus was a money machine that performed very well for years, and then generated huge losses in 2007 and 2008. Of the five major investment banks in the US, one failed outright, two were sold off (by heavy-handed government intervention and as-yet-undisclosed threats/promises)to other banks, and two converted to bank holding companies in time to avoid being taken under.

Basic Things That Went Wrong

In the 1980s, the economists Bob Van Order and Chet Foster were hired by Freddie Mac to further develop their earlier, option-based mortgage default model. The Foster-Van Order model essentially predicts that mortgage defaults will rise as the owners' equity in their homes becomes negative. The key inputs to the model involve A) the endogenous drivers of owner equity (the down-payment as a percentage of home price being the biggest for new mortgages) and B) the exogenous drivers of owner equity (i.e., home price appreciation).

The basic logic is this: if a home is currently worth $350,000 and the owners have $70,000 in equity (either by a 20% down payment or a combination of down payment and accumulated equity from having made payments over time), then the owners would rather sell the home for $350,000 if they suddenly were placed under financial distress than allow it to be foreclosed upon by the bank. A sale will still yield $70,000 for them. If, on the other hand, the house is now worth $350,000 but the outstanding mortgage is for $400,000, the owners are said to have negative equity in the home and selling it will not be sufficient to even pay off the mortgage, let alone realize any gains, hence the much higher probability of default.

Applications of the Foster-Van Order model thus involve specifying a probability distribution for the future path of home prices. To stress-test the model for harsh conditions, one would specify periods of house declines: Arnold Kling, formerly at Freddie Mac, has reported that one such stress test used during this time period involved four consecutive years of 10% declines in home prices (a very harsh test indeed).

Another key input in the model was the size of the down-payment, and here is why: if the assumption is that negative equity status creates an incentive for default, then a larger down-payment gives a natural buffer against home price depreciation. A very low down-payment---say, 0%---means that, for a new mortgage, equity is ENTIRELY dependent on home price appreciation for many years. There is no buffer---any downward shock to housing prices immediately puts these owners underwater and thus far more likely to default, and the strength of this relationship increases at an accelerating, non-linear pace as home prices continue to fall.

Note how different the Foster-Van Order approach is from the Gaussian copula approach, which used correlations between derivatives (credit default swaps) instead of explicitly conducting downside sensitivity tests for home prices themselves.

Unfortunately for everyone involved, there is an inescapable tension between the noble goal of increasing housing affordability and the need to protect securitization issuers/purchasers like Fannie Mae and Freddie Mac from the dire results predicted by the Foster-Van Order model should the unholy combination of falling house prices and very low down-payments be achieved. As we now know, the faction favoring housing affordability won out in the early 2000s and a grand social experiment took place after that.

It is possible that housing affordability, as a public policy goal, should in fact win out, despite the recent catastrophe, and that larger down-payments would disenfranchise a huge percentage of the population and create terrible social consequences down the road. This is impossible to state with certainty, of course, but perhaps we need to accept the risk of periodic market crashes as part of doing business, a basic operating cost that comes with attempts to link free market profit incentives for innovation and risk-taking with the moral hazard of socialized losses when things inevitably do go wrong.

My personal feeling is that the orientation towards lower down-payments also fits within the Keynesian war against savers (since higher down-payments will require that people save a far greater percentage of their incomes, this would represent a problem for the Keynesian utopia. Edward Bellamy, an early American socialist, perhaps best described the socialist disdain for personal savings in 1888: "No man has any care for the morrow, either for himself or his children,for the nation guarantees the nurture, education, and comfortable maintenance of every citizen from the cradle to the grave"). Any truly new policy regime that strives for internal coherence is going to involve an overhaul of basic assumptions regarding the proper roles of fiscal and monetary policy in shaping or distorting economic outcomes.

The Minsky Moment

The economist Hyman Minsky proposed that financial markets are inherently prone to bubbles and crashes, as periods of low volatility encourage excessive, debt-fueled risk-taking (his proposed solution thus was heavy on government intervention policies). He believed that booms and busts were the result of three different waves of financing methods that were employed by investors to take positions in financial assets: hedge, speculation, and Ponzi. In the hedge phase, cash receipts from investments easily covered interest and principal on debt. In the speculative phase, cash receipts from investments covered interest on debt, and there was a belief that future increases in cash receipts would allow for principal to be retired. In the final, Ponzi phase, cash receipts did not even cover interest payments on existing debt, so more debt had to be taken out to service the original.

Minsky believed that a normal yield curve would encourage a move towards speculative financing, since there would be profits to be made from borrowing at lower, short-term debt rates and loaning at the longer-term, higher rate. The danger was interest rate risk---needing to rollover short-term rates meant that the speculative financing position could be exposed should short rates exceed what was being earned on the long-term position. A Ponzi phase was simply unsustainable because the leverage would ultimately result in even a small shock bringing disaster. The catalytic event in which the Ponzi is finally exposed and the turmoil begins has been termed the "Minsky Moment".

I think there is something to be gained from Minsky's model, although I do not agree that the more dramatic swings are necessarily inherent features of the financial markets so much as they are an unfortunate consequence of a series of preventable problems, many of them stemming from distortions and moral hazards created by government intervention. I personally prefer the Austrian theory of the business cycle because it incorporates the role of monetary policy mistakes in creating a debt-friendly environment.

Regulations and Reforms

-Among the many regulatory initiatives that are being put forward is a return of the Glass-Steagall Act that formerly split commercial and investment banking functions. However, it was the revocation of Glass-Steagall that made the emergency, Treasury-pushed shotgun marriages of Bear Sterns and Merrill Lynch to JP Morgan Chase and Bank of America possible, and also allowed Goldman Sachs and Morgan Stanley to survive the crisis by converting to bank holding companies so that they could be recapitalized.

-Fannie Mae and Freddie Mac will almost certainly need to return to their old conforming-loans safety model, and to employ Foster-Van Order type risk modeling.

-Occasionally I hear or read the S&L crisis of the 1970s and early 80s being brought up as an example of another de-regulation-induced banking system disaster, but this is revisionist history. The Savings & Loans were limited by Regulation Q to paying depositors interest rates of 3% (eventually Congress raised this to 4%), in an environment of double-digit inflation. Money market funds were created to offer higher returns, and of course depositors fled the S&Ls. Congress first raised the allowable interest rate that the S&Ls could pay depositors, and then gave up and revoked Q when it was clear that the S&Ls were facing runs. This finally allowed the S&Ls to pay competitive rates and retain depositors. Unfortunately, these firms had also made long-term loans out at (low) fixed-rates, so they now found themselves underwater (i.e., paying a higher rate to short-term depositors than they received from mortgage payments). Advanced, creative stages of risk-taking were incentivized because of predictable principal-agent problems (managers knew that the firms were dead men walking, anyway, so they started taking wild bets) and some very bad loans were one result.

In other words, the S&Ls were really killed by inflation and the time/interest rate coordination problems that come with it, by monetary policy errors that started in the 1960s and culminated in Nixon taking the United States off of the gold standard so that the printing presses could be put to work.

Incidentally, mortgage securitization was developed by Fannie and Freddie because the S&Ls were prohibited from acting across state lines. Securitization allowed for mortgage originators in, say, California to access interested investor money in Illinois. If we wish to point the finger at CDOs and the like, we should also consider where mortgage-backed securities got their start.

-It is possible that FDIC insurance is too generous (currently at $250,000, but we already discussed how this is easily circumvented) and has removed depositor risk monitoring discipline from the banking system, but I do not believe that a reduction in FDIC coverage is politically feasible.

-Risk modeling approaches for CDOs and synthetic CDOs will be changed away from the Gaussian copula, probably by a third iteration of the Basel Accords. This would be very reasonable.

-CDS may be regulated as insurance contracts or placed on exchanges. My initial reaction to this is that it would be a sensible regulatory change, but I am wary of adverse unintended consequences, I am not a credit derivatives professional, and I have not studied the pros and cons to any degree.

In future posts we will discuss the investment climate that this crisis, and the government's response to it, have created and some future macroeconomic scenarios that may unfold as a result.

For Further Reading: Hyman Minsky's "Stabilizing an Unstable Economy" was a hard one for me because Minsky has a difficult style at times, but I think the book can be read with profit if the reader is sufficiently motivated. "The Austrian Theory of The Trade Cycle", a compilation of essays by many of the great economists of that (beloved) school, is an alternative that many readers will enjoy.

A 50-minute youtube lecture on the Austrian theory is available and I have posted a window below:


Sunday, December 13, 2009

Blood Upon The Risers



Was reminded of Airborne School today and had to put this one in!

Friday, December 11, 2009

The Gas Pedal: Rise of Structured Finance (Part 2)

The Gaussian Copula

Insurance actuaries have long been aware of a phenomenon called "Broken Heart Syndrome", in which the surviving partner in a romantic relationship tends to die sooner (statistically speaking) than normal after his or her companion dies. There are numerous causal explanations for this, from a rise in catecholamines, cortisol, and other physiological stress agents that would reduce immune system function, to a sheer psychological fatigue and loss of the spark, the will to live. These are all very important details for the medical and counseling professions to contend with.

For a life insurance actuary working with pure statistical data, however, the more pressing problem is how to determine the strengths of the co-dependencies: in the Broken Heart Syndrome context, the lives of two individuals in a romantic couple are not independent variables, but subject to an "if...then" clause that states that the chances of one dying in a given year are greater if his or her partner has died.

The statistical technique used to link two variables is called the "copula". In the late 1990s, a statistician named David Li (trained as an actuary and familiar with the Broken Hearts Syndrome modeling problem) came up with the idea that determination of the default probabilities for two mortgage derivatives could be approached from the same perspective that actuaries were using for BHS co-dependencies in human beings. Li did not, as has occasionally been reported, invent the Gaussian copula theorem; he was the first to use it in this particular financial application.

As a general rule, you should become very suspicious when you see the term "Gaussian" applied to anything in financial risk measurment. Gaussian means "normally distributed", and financial market prices feature far too many extreme events for us to state that they behave in accordance with this distribution. For example, the CFO of Goldman Sachs reported in 2008 that the bank had been hit with "25-sigma events several days in a row." Sigma indicates "standard deviation", the measure of dispersion used in the Gaussian/normal distribution. A single 25-sigma event should never occur in the history of the universe; the chances of rolling several in a row is inconceivable, beyond the laws of nature. If events like this are occurring (and large moves happen fairly frequently in the markets), then it indicates that the wrong statistical distribution is being used and the model is seriously underestimating the risks of extreme events.

Calculating the risk of a bond default could be done in one of two general ways: top-down or bottom-up. In a bottom-up approach, an analyst would go through the books of the company issuing the bonds and use various techniques, such as debt-coverage ratios and liquidity factors, to try to determine the chances that the company would default on its bond obligations. In a top-down approach, the analyst could look at many similarly rated companies and decide what the chances were of a default based on how many similar companies out there in the investable universe had defaulted in a given year.

In the case of a complex instrument like a CDO, however, an analyst is left with serious problems in the event that either approach is taken. Determining the probability of a particular individual homeowner defaulting by looking up that person's name and history is essentially impossible if one starts with a structured product that has bundled thousands of mortgages together and securitized them; in fact, the purpose of doing the bundling was to create an actuarial regularity that did not depend on the behaviors of any particular homeowners. On the other hand, a top-down approach could also be difficult because CDOs and credit default swaps are relatively new financial instruments, and thus there may not be enough data on actual defaults by issuers to try to statistically determine true investment risks under a variety of market conditions (the sample size would be too small to make statements that carried the necessary degrees of precision).

The solution was to look at the prices of the quasi-insurance contracts---the credit default swaps---that could be purchased to protect the owner of default by a particular issuer. The idea here was that the pricing of the insurance would indicate the risk of default (not an unreasonable assumption, really). The probability of default was backed out of the CDS prices and then fed into the Gaussian copula mechanism.

Remember the co-dependency issue that is described by the Broken Heart Syndrome. The probability of a mortgage default may be similarly connected to the probability of another mortgage defaulting; perhaps a general macro scenario, like a recession, could cause both default risks to increase at the same time (there is a bit of a jump in logic involved here: in the Broken Heart Syndrome case, the two lives have a co-dependence because the death of a spouse may indirectly cause the other spouse to die. In the case of a mortgage default, you have a third variable---recession, asteroid, Lex Luthor, whatever---that is creating the lack of independence).

The traditional statistical approach to examining this would be to look for the correlations between the credit default swap prices on the issuers of the mortgage-backed securities contained in a CDO. The problem with using so-called pair-wise correlations in this way is that you end up with a very complicated situation on your hand---the number of correlations increases exponentially as you add more issuers to a CDO, because you are examining how each issuer interacts with every other issuer. The mathematical expression is N(N-1)/2; if you had 100 issuers in a CDO, you'd have to calculate 4,950 different correlation relationships and then come up with a way to figure out your total default correlation risk. The model would become unwieldy very quickly. What the Gaussian copula allowed was for a single correlation input, perhaps the average correlation, to be used. In return, the copula would spit out a single correlation number from which you could determine the riskiness of the tranche.

Why was this so important? It was very important because the ratings agencies needed to ascertain the riskiness of these tranches in order to assign them credit ratings. The perceived riskiness was assessed by their default probabilities, which in turn were determined through the use of the Gaussian copula theorem.

There are all kinds on intricacies involved in how the Gaussian copula works and was used to assess the risk of CDO tranches, but the main point to drive home is that the GC, by making extensive use of the attractive, user-friendly properties of the normal distribution, is trading simplicity and ease-of-employment for a (known) tendency of this family of statistical distributions to seriously underestimate the risks of extreme events in the financial markets. Two related, additional problems: "non-stationarity", which means that the key statistical parameter used in these models---correlation---is not stable, but can change without notice; and "insufficiently time homogenous" data, which means that the data used to obtain the inputs for the model may come from a time period in which prices behaved differently than they can be depended on to behave in the future. The Economist: "There was no guarantee that the future would be like the past, if only because the American housing market had never before been buoyed up by a frenzy of CDOs."

I note that these are not problems that are unique to the Gaussian copula approach: much of modern finance, including Modern Portfolio Theory and the Black-Scholes Merton Option Pricing Model, is based on the assumption that markets live in a Gaussian world and that parameters are stable.

Many of the articles I have read have been very condescending in suggesting that there was something intrinsically stupid about using the Gaussian copula to determine the joint-default probabilities and arrive at a single scalar for determining risk. I don't agree---the mathematics involved may be straightforward once the particulars are encoded in a valuation algorithm, but getting to that point involved some subtleties that are the province of a small mathematical priesthood. A few serious quants---Paul Wilmott, Nassim Taleb---were pointing out that this was a dangerous practice, but the regulators certainly were not.

How This Helped to Cause Big Blow Ups

The financial instruments involved in these modeling efforts were extremely sensitive to changes in correlation assumptions. Imagine a line of 1,000 dominos, and think of correlation, simplistically but usefully for our purposes, measuring the inverse of the distance between them (i.e., a high correlation means two dominos are close together; a low correlation means a greater distance). When a domino is standing, it is is paying you money; when it falls, you lose money. You push the first domino; your losses depend on how many subsequently fall with it. If you get the *average* correlation even slightly wrong, you may find that you have far greater losses than you ever thought you would.

Many of the investors in CDOs had purchased them because they had been given an investment-grade rating; when default probabilities were shown to be higher than assumed, the ratings agencies had to mark them down. What you basically had here was a grand financial experiment taking place---no one was really sure how these things would behave

It may be surprising that some of the firms that took very serious losses on CDOs and synthetic CDOs lost money in the senior tranches that were supposed to be insulated from risk and very safe. The reason for this seeming anomaly is because those senior tranches were assumed to have lower correlations and were thus more sensitive to errors in the risk modeling process. Most people knew that the junk level "equity" stuff was pretty dangerous---primary customers were hedge funds who would engage in "long equity, short mezz" trades (buying the high-yield low tranche and shorting the middle, or mezzanine, tranche).

As mortgage-backed securities were purchased by CDOs, the leverage increased. A CDO's highly-rated, "safe" senior tranche could be comprised of risky, subprime mortgages if the modeling assumptions had given them a low joint default probability. When a correlation assumption was shown to be too low, however, the tranche could essentially be wiped out with a speed and violence that was completely unexpected, at least to the holder of a AAA-rated security.

In my opinion, the problem with applying things like the Gaussian copula to derivatives pricing is not that the attempts are congenitally deranged, it is that they create an aura of scientific respectability that lends itself to false precision. When a non-quant manager, probably an MBA and/or Oxbridge PPE type who is quite clever but lacks formal training in, say, things like Ito's lemma or Taylor series expansions, is fed an output number from a group of math or physics PhDs working in a bank's quantshop, that number may be used with a confidence that is inappropriate (business schools tend to push the Gaussian distribution and "frequentist" statistics, instead of the overarching Bayesian approach that I feel is more appropriate for decision-making under these conditions...much more on this in the future, as it is the real purpose for this whole blog).

There is always a tension between trading profit centers and risk management cells--if the risk managers allowed the firm to always scale to the worst-case scenario, no trades would ever be taken. The "just give me a number" mentality leads to problems even in non-leveraged, plain-vanilla financial models, because the single number that is selected is probably going to be the average of the range. Lets say that a firm is trying to decide on how much production capacity to buy, and that depends on what the annual sales forecast is. The management team takes the average sales forecast of 50,000 widgets and builds its production to meet this. Sounds reasonable, except that it almost guarantees disappointment: if widget sales fall below 50,000, which they will 50% of the time, the firm will have purchased excess production capacity. If widget sales are happily brisk and exceed 50,000, which they will the other 50% of the time, the firm will not be able to take advantage of this because it didn't buy enough production capacity.

Variations on this "flaw of averages" problem confound all kinds of business modeling attempts---they are present all over the place, although there are methods that can employed to try to mitigate their effects (Monte Carlo simulation, Real Options Analysis, game theory, etc.). But these all can have their own problems, too: for instance, Monte Carlo simulation requires that you have a good handle on the underlying statistical distribution. Financial markets present some pathological distributions; there is no clear agreement about how best to model them. Running thousands of iterations sampled from the wrong distribution would just give you the same problem of false precision that we have already described.

The methods that are least dependent on getting the assumptions about the distribution right are called "non-parametric." Our firm strongly believes in using non-parametric approaches wherever possible, and they do have the advantage of allowing for a Kalashnikov-like, battlefield-ready robustness. However, non-parametric methods still require that the past be at least somewhat indicative of the future, so you need to test against a very wide range of market conditions. If you have a situation in which past asset price behavior has been mild-mannered, even tame, non-parametric methods will not tell you how to deal with a future that is aggressively hostile and wild. Building a reserve for never-before-seen, catastrophic risks would have prevented these instruments from getting investment-grade quality ratings, which would have made them far less marketable, which would have made entities on all sides of these deals unhappy.

In the next section, we will put the fractional-reserve engine, monetary policy fuel, government affordable housing mandate steering wheel, and structural finance gas pedal together and finally have our spectacular crash.

For Further Reading: Pablo Triana's "Lecturing Birds on Flying" and Riccardo Rebonato's "Plight of The Fortune Tellers" are both excellent. A more accessible and conceptual discussion of the financial risks that come with false precision can be found in Nassim Taleb's "Fooled by Randomness" and "The Black Swan". Those who want to get into exploded detail regarding technical aspects of derivatives pricing will enjoy the forums at www.wilmott.com, which is the Oxford mathematician Paul Wilmott's site.

Wednesday, December 9, 2009

The Gas Pedal: Rise of Structured Finance (Part 1-Basics)

This section becomes unavoidably semi-technical, so perhaps the best way to approach it is to list the major characters up front and give a brief description of the roles that they play. There are four main three-letter terms that will be featured in today's tale: SPVs (special purpose vehicles); MBS (mortgage-backed securities); CDOs (collateralized debt obligations); and CDS (credit default swaps). There is also a mathematical theorem that plays a major role, and that is something called the "Gaussian copula."

An SPV is an accounting entity that purchases mortgages from a bank by going into the market and issuing bonds to pay for them. These bonds are called mortgage-backed securities (MBS). An SPV that purchases these securities instead of original mortgages is called a CDO; a CDO is just the next evolutionary step in the process after MBS bonds have been created. How does the CDO buy the mortgage-backed securities? It can issue bonds, of course, but frequently the CDO is funded by using short-term financing from the commercial-paper market. The CDO has now become a sort of bank---it borrows money in the market at short-term rates and then purchases longer-term MBS (often 20-30 year maturities) with them. Because of the timing mismatch, the CDO has to continually roll over its debt and take out new short-term loans again and again. The advantage is that the short-term financing is probably very cheap. The disadvantage is that the CDO has continuous financing needs and very bad things can happen if market liquidity suddenly dries up.

If a bondholder is concerned about the issuer defaulting on the bonds and not being able to pay him, he may purchase an insurance-like contract called a CDS to protect himself. Figuring out what the chances are of a bunch of individual mortgages defaulting at the same time is the job of the Gaussian copula theorem.

So let's start with a bank that wants to remove mortgages from its balance sheet. The bank creates a new entity to purchase these mortgages from the bank. The new entity, the SPV, finances the purchases by issuing bonds to third-party investors. Particularly in the wake of the Enron scandals, there are various FASB rules in place regarding the number of voting shares that a bank can legally hold in an SPV and still keep it distinctly separate from the bank's financial statements, so banks tend to have minimal control of the SPVs once they are up and running. In fact, ownership interest in the SPV will probably be dispersed among so many parties that the SPV will not show up on anyone's balance sheet; it will become part of the "shadow banking system". However, there are some circumstances that can force a bank to take an SPV back on its balance sheet, often at the worst possible time, and those circumstances were in fact met in 2008.

When an SPV is set up to purchase mortgages from the bank and issues bonds to pay for the mortgages, these bonds are now called "mortgage-backed securities". Because banks are required to set aside capital against mortgages they create, relieving the bank of these mortgages allows the bank to be "recharged" and to create more.

The cash flows that homeowners pay for their mortgages now pass through the SPV and become the coupons that the SPV's bondholders receive; the mortgages have been "securitized". The way it normally works is that (at least) three different flavors of bond---called "tranches"---are issued by the SPV, and investors can choose which one they would like based on their risk appetites. The safest bond is called the "senior tranche" because it is the first in line to receive cash flows from the mortgages. After the senior tranche gets paid, the "mezzanine" bondholders are second. The last claims on the mortgages go to the riskiest, third-level bonds, which are confusingly termed "equity" or "preferreds". The flow of mortgage cashflows down from the safest to the riskiest MBS bonds is normally called the "waterfall". As you would imagine, those who hold the riskiest tranche want a very high return for doing this. Those who hold the senior, safest tranche will receive a more modest return.

Enter the bond ratings agencies. Before the mortgage-backed securities are issued, bond raters (S&P, Fitch, and Moody's) give these securities a rating. The ratings are very important because many of the best customers for these products, such as pension funds, are only allowed to purchase "investment-grade" (AA or higher; sometimes AAA) bonds. Additionally, the MBS bonds issued by the bank-sponsored SPVs would need to compete with those guaranteed by Fannie Mae and Freddie Mac, who used/abused their privileged government status and had the vaunted AAA rating.

It is important to understand that the buyers really wanted these things to be given an investment-grade rating: a AAA-rated MBS is deemed to have the same level of safety as a bond issued by, say, the US Government or the World Bank, but may also carry an attractive 5-6% coupon. For an insurance company, that combination may prove to be irresistible. The analysts at GaveKal Research put it another way: "(as a result of the dot.com crash)...pension funds and insurance companies around the world found themselves undercapitalized. The regulators, always keen to close the barn door once the horses have fled, decided to prevent the undercapitalized institutions from buying more equities. This left pension funds and insurance companies with a pressing need: how to replace equities, the high return part of their portfolios? Since, according to the new regulations, they could only buy more bonds, they were forced, if they wanted to boost returns, to buy very low quality bonds, offering very high yields. The problem was of course that the regulators had told them that they could not buy bonds below 'investment grade'...and that, as a result for the massive demand for yield around the world, the returns on investment grade bonds were far below the returns on equities that they now had to replace...So all of a sudden, here was a new need: the low quality bond with a high rating."

A bank that was going to be sponsoring an SPV and MBS issuance could "shop" the product around to various rating agencies and see which one would give the highest rating. In order to make things more transparent, the rating agencies would share their valuation process with the banks, so that the banks could structure MBS or CDO tranches in accordance with the known requirements to get, say, a AAA rating on the senior tranche. By diverting more of the cash flows from the MBS bonds to the highest-rated tranche, the SPV could "over-collateralize" the senior tranche of a CDO and achieve a high rating from the agencies. The logic here is intuitive: if fifteen people owe $10 each to three of us, and I get exclusive access to the payments of ten of those people, I am fundamentally safer to loan money to than is my associate who only has access to two $10 payment streams.

This leads us to our next character, the credit default swap. Without getting into the details, a CDS is an insurance-like contract that a purchaser buys in order to insure against the risk of a bond issuer defaulting. These derivatives are traded over-the-counter, which means that they are privately negotiated agreements that take place off of an exchange. The traditional narrative for a CDS is that Firm A holds many bonds issued by, say, General Motors and is concerned that GM is going to default. Firm A goes to Firm B, probably an insurance company, and buys a CDS. If GM does default Firm B has to pay Firm A. Along the way, Firm A has to make quarterly premium payments to Firm B.

CDS play an important role in this story for several reasons. First off, CDS prices were widely used for CDO tranche ratings (discussed in the next section). Second, the size of this market was absolutely huge (approximately four times the size of the entire US economy). Third, because they were not considered "insurance", CDS could be written without the purchaser needing to even own the bonds of the company on which the default concerns were raised---this is a bit like taking out fire insurance on your neighbor's house and being paid if it burns down (there is a moral hazard in this). CDS thus became an important speculative vehicle as well as a hedging/risk management vehicle, but they were not being traded on an exchange and thus lacked transparency. Fourth, the regulatory opinion that CDS were not not insurance contracts allowed insurance companies like AIG and the Monoline insurers to enter into all kinds of credit default swaps, since CDS did not require the same prudential capital reserves to be set aside that traditional insurance did.

Mortgage securitization served as a very useful process. It helped banks to take mortgages off of their balance sheets, which allowed them to make more mortgages. It helped Fannie Mae and Freddie Mac to carry out their affordable housing mandate. It helped investors who had yield requirements due to future liabilities (pension funds, insurance companies) to meet standards for both bond quality and performance.

The next installment will focus on the models used to try to calculate the risks of mortgage defaults, the way that a CDO structure built of subprime components can turbo-charge losses if a "default vector" sweeps through the underlying mortgages that fund the mortgage-back securities that the CDO owns, and the attempts made to insure against these risks by using credit default swap (CDS) contracts.

Tuesday, December 8, 2009

The Steering Wheel: Government Housing Policy

In 1999, the New York Times stated: "In a move that could help increase home ownership rates among minorities and low-income consumers, the Fannie Mae corporation is easing the credit requirements on loans that it will purchase from banks and other lenders...Fannie Mae, the nation's biggest underwriter of home mortgages, has been under increasing pressure from the Clinton Administration to expand mortgage loans among low and moderate income people and felt pressure from stockholders to maintain its phenomenal growth in profits."

I submit that the Federal National Mortgage Association (Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie Mac), acting under relentless political pressure to execute a popular, bipartisan affordable-housing mandate, played a significant role in directing the excess liquidity generated by the Fed towards a particular dangerous section of the housing market (a general housing bubble would probably have formed, regardless, but the special toxicity of this particular situation was created by government policy). Thus, government policy was the "steering wheel" that drove the car into the wall, or crowd of innocent people, or whatever disaster metaphor is most appropriate.

Let's start with a brief overview of what Fannie and Freddie do. The two for-profit companies are simultaneously also "Government-Sponsored Enterprises" (GSEs), meaning that they fall under the authority of the Department of Housing and Urban Development (HUD) and enjoyed implicit---now, in the wake of their failures, explicit---government protection. Fannie Mae and Freddie Mac do not originate mortgages; rather, they purchase them from originating banks, and this allows the banks to avoid having 30-year or so commitments to service the mortgages. Instead, the banks get to take a lot of the money now, and are then free to originate more mortgages and to collect the origination fees (which is what many local branches would prefer to specialize in because they allow managers to show near-term performance). The effect on the housing market is to increase liquidity and mortgage access.

In the traditional "originate and distribute" model, the mortgages would be purchased by Fannie and Freddie, securitized, and sold on to other investors with guarantees attached. In fact, as time went on, the GSEs were primarily using their implicit government-protected status to borrow at low rates and then use the cash to repurchase mortgage-backed securities and house them on their own books. The firms became enormously leveraged. As a result of the exposure to interest-rate risks, they also began carrying out dynamic interest-rate hedging operations.

Because they are the giants in the industry and enjoy special privileges, Fannie and Freddie have great power over the origination channel and the standards employed at that initial phase. A local bank has little incentive to be particularly careful with screening mortgage applicants if it knows that the mortgage is going to be turned around and sold to Fannie Mae, and that Fannie Mae not only does not care about the screening process, but also wants screening standards to be lowered.

By creating a voracious appetite for subprime and Alt-A mortgages, Fannie and Freddie transmitted a "demand" signal to the banks. The incentives for the banks were to satisfy this demand; indeed, it would be irrational for them to have not done so, particularly given the implicit government backing of the two mortgage GSEs.

It is not that there was a complete absence of concern among politicians regarding the expansion of Fannie and Freddie. For example, Congressman Ron Paul of Texas said in Congressional testimony in 2003 that "the special privileges granted to Fannie and Freddie have distorted the housing markets by allowing them to attract capital they could not attract under pure market conditions. As a result, capital is diverted from its most productive use into housing. This reduces the efficacy of the entire market and thus reduces the standard of living of all Americans...Despite long-term damage to the economy inflicted by the government's interference in the housing market, the government's policy of diverting capital...creates a short-term boom in housing. Like all artificially created bubbles, the boom in housing prices cannot last forever. When housing prices fall, homeowners will experience difficult as their equity will be wiped out. Furthermore, the holders of the mortgage debt will also have a loss. These losses will be greater than they would have otherwise been had government policy not actively encouraged overinvestment in housing."

Even Alan Greenspan, whose previously-discussed departures from the Taylor Rule fueled the massive credit expansion that made so much of this possible, testified in 2005 that Fannie and Freddie were becoming dangerous, almost to the point of becoming doomsday machines: "The Federal Reserve has been unable to find any credible purpose for the huge balance sheets built by Fannie and Freddie other than the creation of profit through the exploitation of the market-granted subsidy...(if they) continue to grow, continue to have the low capital that they have (my note: $30 billion in capital to finance an estimated $2 trillion in mortgages!)...they potentially create ever-growing systemic risks down the road...by enabling these institutions to increase in size...we are placing the total financial system of the future at risk."

Others clearly disagreed. The same year, Congressman Barney Frank, the ranking member of the House Committee on Financial Services (later to become its chairman) and a key architect of the affordable housing push, argued that Fannie and Freddie were "not facing any kind of financial crisis...The more people exaggerate these problems, the more pressure there is on these companies, the less we will see in terms of affordable housing...(critics of the GSEs) conjure up the possibility of serious financial losses to the Treasury...I believe that we, as the Federal Government, have probably done too little rather than too much to push them to meet the goals of affordable housing and to set reasonable goals. I would like to get Fannie and Freddie more deeply into helping low-income housing and possibly into something that is more explicitly a subsidy. I want to roll the dice a little in this situation...". Of course, Frank had been blocking attempts to control Fannie and Freddie since the early 1990s.

Fannie's top client was Countrywide Financial Corporation, the wild subprime enthusiast that blew up in 2008. Countrywide gave special below-market "VIP loans" to various targeted individuals (including, brazenly, the HUD Secretary, CEO of Fannie Mae, and the Chairman of the Senate Committee on Banking, Housing, and Urban Affairs) as part of its "Friends of Angelo" program (named for Countrywide CEO Angelo Mozilo). When we get to political contributions and attractive private arrangements involving Fannie and Freddie themselves, the story becomes even more interesting.

The GSEs spent millions in campaign contributions and were seen as a sort of political warchest/piggybank for the Democratic party (although support was often non-partisan). In 2004, when Bush expressed concerns about the riskiness of the GSEs, 76 Congressional Democrats---including Frank, Nancy Pelosi, Maxine Waters, and Charley Rangel---sent him a joint letter making the case that "an exclusive focus on safety and standards is likely to come, in practice, at the expense of affordable housing." Many of the letter-writers would later blame Wall Street excess and "deregulated markets" for the housing crisis and debt-deflation, and would call for greater government controls and more central planning. Even well into 2008, Senator Christopher Dodd (himself a recipient of a "Friends of Angelo" VIP loan), incredibly, continued to report that Fannie and Freddie were "on a sound footing."

The Office of Federal Housing Enterprise Oversight---the regulatory agency overseeing the two GSEs---issued a very critical report of Fannie Mae after finding numerous accounting irregularities at the firm. In response, Senator Kit Bond (a Republican) sought to have the OFHEO's leadership culled and budget frozen pending an investigation. Barney Frank concurred, stating that "it is clear that a leadership change at OFHEO is overdue."

While deeply complicit at other times, Republican Senators of the Banking Committee did ultimately make a (futile) attempt at substantive GSE reform in 2005. All Democrat members opposed the bill. A group of Republicans attempted to gather support for a full Senate vote, saying, "If effective regulatory reform legislation ... is not enacted this year, American taxpayers will continue to be exposed to the enormous risk that Fannie Mae and Freddie Mac pose to the housing market, the overall financial system and the economy as a whole." The vote was not called after extensive anti-reform lobbying by Fannie Mae.

It is still difficult to determine the size of the exposures that Fannie and Freddie ultimately had to subprime mortgages. They were clearly monstrous---the direct taxpayer-driven bailout stands at around $350 billion, while the Fed is holding at least $1 trillion of toxic paper, housed in non-mark-to-market darkness, that was purchased from them. Bernanke is apparently going to try to unwind the paper through complex, opaque reverse-repurchase agreements in which market players will purchase the paper but the Fed will retain all of the credit risk. God only knows how that one is going to work out. The opacity extends to Fannie and Freddie because neither were exactly known for accounting transparency---even prior to the crisis, they were rocked by accounting scandals totaling $11 billion (the errors were related to how hedging activities were accounted for and led to senior executives receiving far more generous bonuses than they otherwise would have). I have heard estimates that the two GSEs had exposures totaling at least $1.5 trillion, possibly over $2 trillion.

We do know that, by mid-2006, the ratings agencies were voicing their concerns that the default rate assumptions used in packaging and selling various MBS (mortgage-backed securities---to be discussed in a different post) had been too conservative and the models used had been optimistic. At this point, JP Morgan Chase had never really entered the game in a big way, Deutschebank had also been wary, and Goldman, clearly scared, had purchased protection through both credit default swaps sold by AIG (more on that firm later) and, at least as has been related to me by an insider, a large in-house "Black Swan" bet that the housing market would collapse. The ratings agencies had issued warnings and would begin downgrading ratings in about a year, yet UBS, CITI, Bear Sterns, Lehman, Merrill Lynch, and, most importantly, the GSEs continued to aggressively push subprime-based products. Credit risk analysts at Fannie had voiced their concerns back when senior executives at the firm had started demanding to "make markets" in the subprime space; the most vocal of them was apparently fired as an example, the others effectively muzzled.

There were other programs and policies that encouraged subprime lending, including the Carter-era Community Reinvestment Act (CRA) that was given new life during the Clinton Administration and used as a hammer by prominent community organizers/activists. If the Fannie and Freddie purchases represented the "carrot" side of the game, the CRA represented the "stick"---it opened banks up to crushing lawsuits if they failed to meet the goals of various subprime-biased lending initiatives.

While clearly not without blame, Fannie and Freddie were essentially doing what they were told. The most troubling part is the incestuous feedback loop of lavish campaign contributions, special private loan arrangements (laundered through the Countrywide "Friends of Angelo" program), and even post-political life private-sector job opportunities that existed between key political supporters and the mortgage giants. As GSEs, they were inescapably political organizations and their abilities to attract capital at very attractive rates depended on their special, guaranteed status. In terms of our public servants, one may ask why, naked political ambitions, economic self-interest, and "community leadership" narcissism/messianic complexes aside, government officials at least notionally representing the public good would have pushed for NINJA-type loans and other forms of extremely relaxed lending standards, especially magnified to the level of the Fannie Mae and Freddie Mac exposures.

Perhaps I am naive, but I think that many of the politicians involved were probably acting from good---if somewhat vague---intentions, and saw affordable housing as a legitimately noble policy goal. This is anecdotal, but I know Mel Martinez, former HUD Secretary under Bush and now Senator, and his wife personally. My parents were involved in his election to Orange County Chairman back in the late 90s, and his mother-in-law worked with my dad at the Florida Audubon Society many years ago. He has always seemed like an affable, genuinely concerned individual---why wouldn't he have done more to discipline the mortgage GSEs?

My personal belief is that there were the obvious reasons for the affordable housing push ("homeownership is part of the American Dream") and the attractiveness of housing in terms of bringing home tangible results to one's political constituents, but there was also a more subtle effect at work: by operating through the GSEs and then through the private banks, it appeared that a quasi-"market solution" for the affordable housing issue was being applied. Rather than an outwardly foolhardy, directly Socialist effort such as some kind of nationwide home-price controls policy, politicians could feel that they were simply applying a humanistic incentive package to the market and then allowing it to work out the details in its own, efficient way. As we found in the case of the Federal Reserve and as George Cooper argued in his book, the most dangerous modern threat may be the attempt to have our cake and eat it, too, by trying to combine incompatible free market, decentralized price discovery mechanisms and centrally planned social engineering programs. What makes this so sinister is that the central planners may get a free "put option" to blame the free market and deregulation when things don't work out as planned.

The next blog entry will discuss structured financial products, particularly credit derivatives, that became "weapons of mass destruction" during the crisis. The techniques of structured finance, particularly a seemingly-benign mathematical theorem called the Gaussian copula, were perhaps inadvertently used to make subprime-based securities seem far less dangerous than they turned out to be.

For Further Reading: The great Thomas Sowell's "The Housing Boom and Bust" is a wonderfully witty and erudite account of the politics of affordable housing.