Part 1 – Wired Markets


Financial Markets – Electronic Markets

Not too long ago, going to a stock market meant you would meet lots of new people who were energetically shouting, running around, and making a mess with great quantities of paper. No more. Visiting a financial market now is more like visiting a telephone exchange. Computers and network gear hum in racks. Fans blow. Rows of tiny lights flicker. Occasionally someone shows up to replace a disk.

Technology did not suddenly transform our markets. It has been a gradual process, and understanding how we got here, and the simpler machines we used along the way, provides insight into today’s complex markets. In that spirit, the first chapter in this part, an illustrated history of market technology, gives an informative perspective on today’s wired markets.

Computers make a dramatic entrance into financial markets at the conclusion of Chapter 1 – An Illustrated History of Wired Markets.

“So how did that work out?” you might ask. Chapter 2 – Greatest Hits of Computation in Finance answers that question, surveying some of the greatest technological hits influencing the markets.

Electronic markets are at the top of our greatest hits list. They are about the mechanics of trading, that is, the implementation of investment decisions (in contrast to actually making those decisions). Chapter 3 – Algorithm Wars is a more in-depth view of one of the most dynamic areas in electronic markets.

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Forward by Ted Aronson


Nerds on Wall Street Forward by Ted Aronson

Quantitative finance is not a topic usually associated with laughter. That is about to change with the publication of Nerds on Wall Street.

I was first exposed to Dave Leinweber’s wit when he delivered a speech entitled “Nerds on Wall Street.” I believe the event happened 20 or 25 years ago at a CFA Institute conclave. He was a dude obviously knowledgeable about the investment business, with impressive credentials (MIT, Harvard, RAND), alluding to technical aspects of numerical finance and getting into the minutiae of electronic trading. Certainly on Wall Street such qualifications aren’t unique. But, oh, how he delivered his message! His rapid-fire sense of humor was worthy of Henny Youngman or Shecky Greene.

Dave’s speech was augmented by equally hilarious visuals. (Unfortunately, some of Dave’s props are so rare they are no longer available. Rats!) On a particularly memorable occasion (one of ITG’s famous conferences), Dave did his shtick with a drummer punctuating his one-liners with rimshots. I kid you not! The crowd, loosened up by cocktails, was reduced to tears from laughter.

Now, decades later, I’ve heard Dave deliver numerous speeches and presentations with various titles. But they are always roughly the same subject — yup, you guessed it — “Nerds on Wall Street.” So sit back and be prepared to be educated by a master. The education will come with images, illustrations, and humor you will not soon forget. It will be love . . . at first sound bite!

Theodore R. Aronson
Managing Partner, Aronson_Johnson_Ortiz
Past Chairman, CFA Institute

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Introduction to Nerds on Wall Street


Introduction to “Nerds on Wall Street

I hope people think of this book as sort of a Hitchhiker’s Guide to Wired Markets. There are no robots parking cars for six million years, but there are robots trading millions of shares in six milliseconds, so maybe that’s close enough.

In 2006, I got a call from another nerd on Wall Street (NOWS), Rich Lindsey. At the time, Rich was president of Bear Stearns Securities (Bear Stearns’ prime brokerage company) and a member of the board of the mother ship firm. I had met him nearly 10 years earlier when he was in charge of market surveillance at the New York Stock Exchange (NYSE). A former Yale professor, Rich is a veritable poster boy for nerdy Ph.D.’s who break out of the pure geek world to become general all-around Wall Street BSDs.(1) He was putting together a book called How I Became a Quant: Insights from 25 of Wall Street’s Elite, and invited me to write a chapter. Proceeds were going to the Fischer Black Foundation for needy students. I knew this was for real, and not like those offers high school kids get to be in the Who’s Who of American Teens, and then they have to buy five copies. Plus the book had the kind of flattering title that gets people to write for free, but is more subtle and less of a bald-faced lie than, say, Insights from 25 of Wall Street’s Hottest Hunks. No one does a free chapter for Another Bunch of Middle-Aged Financial Guys.

The other people writing for the book included some of the smartest kids on the block and some old friends, so I said yes on the spot. There are chapters by pillars of the quant world, authors of the standard texts, and writers of oft-cited papers. Others did interesting and rewarding things with technology and markets. Emanuel Derman, author of My Life as a Quant: Reflections on Physics and Finance ( John Wiley & Sons, 2004), made this point in the first line of his review for the Wall Street Journal: “By my reckoning, several of the 25 memoirists in How I Became a Quant are not true quants, and they are honest (or proud) enough to admit it.”(2)

I am, no doubt, high on the list of poseurs, and I will be the first to admit it. Information technology applications in financial markets aren’t physics and closed-form solutions; they fit more in the zone of engineers and experimental guys, but they’ve been around forever. At the top of the heap we find Thomas Edison and Tim Berners-Lee, inventor of the World Wide Web. At the low end, they include more than a few potentially dangerous tinkerers like this guy:

500x218_intro_time-travel

As an experimentalist, I rank way below Edison but way above the time travel guy. I was fortunate to be a participant over the past 20 years as one of Wall Street’s nerds — when the world’s financial markets turned into a whopping computer network, a place for both theoretically sound and downright wacky financial ideas to come alive as programs.

The next section in this Introduction is an adaptation from my contribution to How I Became a Quant ( John Wiley & Sons, 2007). This expanded version goes into more depth, and includes pointers to material in the book that shows exactly what these references are about. Some chapters published in the past, and updated; some are new for this volume.

No Hedge Fund in My Tree House

I wish I could tell one of those stories about how when I was in the eighth grade, I noticed a pricing anomaly between the out-of-the – money calls on soybean futures across the Peruvian and London markets and started a hedge fund in my tree house and now I own Cleveland. But I can’t. In the eighth grade I was just a nerdy kid trying to keep my boisterous pals from blowing up my room by mixing all my chemistry set chemicals together and throwing in a match. In fact, I can’t tell any true stories about eighth graders starting hedge funds in tree houses and buying Cleveland. Make it college sophomores in dorm rooms who buy chunks of Chicago, Bermuda, or the Cayman Islands, and we have lots of material.

A Series of Accidents on the Way to Becoming a Quant Finance Nerd

My eventual quant-dom was not the culmination of a single-minded, eye-on-the-prize march to fulfill my destiny. It was the result of a series of accidents. In college, my interest in finance was approximately zero. I came to MIT in 1970 as a math major, as did many others, because I didn’t know much about other subjects, like physics or computer science.

I quickly discovered that the best gadgets were outside the math department. And the guys in the math department were weird, even by MIT standards. Today you can buy fine laptops without taking out a second mortgage, but this was back in the days when even a pretty crummy computer cost more than a really nice house. A good one cost millions, and filled a room the size of a basketball court. MIT, the ultimate toy store for geeks, had acquired a substantial inventory of computing machinery, starting as soon as it was invented — or sooner, by inventing it themselves. The professors kept the latest and greatest for themselves and their graduate student lackeys, but they were happy to hand over last year’s model to the undergrads.

Foremost among these slightly obsolete treasures was the PDP-1-X, which is now justly enshrined in the Boston Computer Museum. The PDP-1-X was a tricked-out version of the PDP-1, the first product of the Digital Equipment Corporation (DEC). The story of DEC is an early computer industry legend, now fading in an era where many people believe Bill Gates invented binary numbers.

DEC founder Ken Olsen worked at MIT’s Lincoln Laboratory, where the Air Force was spending furiously to address a central question facing the nation after World War II: “What do we do about the Bomb?” Think about the air war in World War I: guys in open cockpits wearing scarves and yelling, “Curse you, Red Baron!” By the end of World War II, less than 30 years later, they were potential destroyers of worlds. Avoiding the realization of that potential became a central goal of the United States.

If a Soviet bomb was headed our way, it would come from the north. A parabolic ballistic trajectory over the pole was how the rockets of the era could reach us. This begat the distant early warning (DEW) and ballistic missile early warning (BMEW) lines of radars across the northern regions of Alaska and Canada. The DEW and BMEW lines, conceived for military purposes, drove much of the innovation that we see everywhere today. Lines of radars produce noisy analog signals that need to be combined and monitored.

Digital/analog converters were first on the DEW line, now in your iPod. Modems, to send the signals from one radar computer to others, were first developed to keep the Cold War cold. Computers themselves, excruciatingly large and unreliable when constructed from tubes, became transistorized and less excruciating. This is where Ken Olsen comes in. Working at MIT to develop the first transistorized computers for the DEW line, he and his colleagues built a series of experimental machines — the TX-0 (transistor experiment zero), the TX-1, and the TX-2. The last, the TX-2, actually worked well enough to become a mother lode of innovation. The first modem was attached to it, as were the first graphic display and the first computer audio.

Olsen, a bright and entrepreneurial sort, realized that he knew more about building transistorized computers than anyone else, and he knew where to sell them — to the U.S. government. Federal procurement regulations in the early 1960s required Cabinet-level approval for the purchase of a computer, but a programmable data processor (PDP) could be purchased by a garden-variety civil servant. Thus was born the PDP-1, as well as its successors, up to the PDP-10, like the one at Harvard’s Aiken Comp Lab used by a sophomore named Gates to write the first Microsoft product in 1973.

Today, almost all teenage nerds have more computational gear than they know what to do with. Back then, in the 1970s, access to a machine like the PDP-1, with graphics, sound, plotting, and a supportive hacker(3) culture, was a rare opportunity. It was also the first of the series of accidents that eventually led me into quantitative finance.

I wish I could say that I realized the PDP-1 would allow me to use the insights of Fischer Black, Myron Scholes, and Robert Merton to become a god of the options market and buy Chicago, but those were the guys at O’Connor & Associates and Chicago Research and Trading, not me. I used the machine to simulate nuclear physics experiments for the lab that adopted me as a sophomore. They fl ew me down to use the particle accelerators at Brookhaven National Laboratory to find out the meaning of life, the universe, and everything by smashing one atomic nucleus into another — sort of a demolition derby with protons. But sometimes a spurious side reaction splattered right on top of whatever it was they wanted to see on the glass photographic plates used to collect the results. My simulations on the PDP-1 let us move the knobs controlling electromagnets the size of dump trucks so the spurious garbage showed up where it wouldn’t bother us. …

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All notes for this Introduction to Nerds on Wall Street

1. A term of respect popularized by Michael Lewis in his 1989 book, Liar’s Poker (W.W. Norton).

2. Emanuel Derman, “Finance by the Numbers,” Wall Street Journal, August 22, 2007.

3. Much of Steven Levy’s 1984 book Hackers: Heroes of the Computer Revolution (Doubleday) takes place in the PDP-1 lab at MIT. Hacking had no criminal connotation at the time. The book is still in print.

4. Start with Herman Kahn’s On Thermonuclear War (Princeton, NJ: Princeton University Press, 1960) for a weighty tome, or “How RAND Invented the Postwar World,” by Virginia Campbell, in Invention & Technology magazine (Summer 2004) for a much more compact read.

5. Thanks to John Wiley & Sons for including this tribute to Kevin Lewis. Yes, it has nothing to do with finance, but this is shaping up as a year when we can all use a laugh. Along with other RAND colleagues, I put a longer version of the story in the article about Kevin on Wikipedia. It included his other gag papers such as “The Glide Tank,” featuring a flying tank with stubby little wings that a surprising number of defense contractors failed to recognize as a joke. The Wikipedia patrol does not have much more of a sense of humor than Don Rice did, and it keeps getting edited out and replaced by dry bibliographic material and biographical details. Fortunately, they can’t erase a book. Never underestimate the ability of people not to get the gag. Chapter 6, “Stupid Data Miner Tricks,” is very much in the spirit of “The Tumescent Threat,” but I still get calls asking about current butter production in Bangladesh.

6. It is now complete, and is utterly awesome. See the video at www.deltawerken.com/The-Oosterschelde-storm-surge-barrier/324.html. This is one of the premier flood control projects in the world, and particularly instructive when compared with the misplaced concrete slabs in New Orleans.

7. RAND had some distinguished financial alumni, foremost among them Harry Markowitz and Bill Sharpe. The ideas of operations research and optimization of risk and reward under constraints in military problems generalized, as we have seen, to a wide swath of finance.

8. I was the more junior of two co-leaders on this. The big dog was one of the grand old men of the Cold War, Bruno Augenstein, who was widely credited as the architect of the intercontinental ballistic missile (ICBM), and the man who in his DoD days signed the first check to develop the SR-71 Blackbird. He had some fine if spooky tales to tell.

9. LISP was the favored computer language of the artificial intelligentsia.

10. Stephen was a really nice guy who gave a lot of parties. His equally nice son, Noah, was a struggling actor, working as a waiter to make ends meet. Noah used to fold the napkins at Stephen’s parties. He worked at snazzy Hollywood restaurants and did great napkins — swans, stars, tulips, butterflies. Noah eventually got work as Dr. Carter on ER, so Stephen farms out the napkin folding.

11. Stallman, it turned out, had the right idea about open source, but also had a prodigious talent for annoying people, so GNU’s progress toward open source Unix was slow. They did a fine eMacs, though. Linus Torvalds’s greater skills in nerd-to-nerd diplomacy got there with Linux.

12. Quotron is another example of the “don’t build special purpose computers” rule. They did, and went from being synonymous with “electronic market data terminal” to being nowhere in a remarkably short time. The first Quotrons were so alien to Wall Street types that they rearranged the “QWERTY” keyboard to be “ABCDE.” Schumpeter was right about capitalism being a process of creative destruction.

13. Large is a relative term here. The bleeding-edge machines of the mid-1980s had 32M of memory. Fifteen years earlier, the onboard computers used on the lunar landings had 64K.

14. Evan’s fine account of his career is in Alan Rubenfeld’s book, The Super Traders: Secrets and Successes of Wall Street’s Best and Brightest (McGraw-Hill, 1995), pp. 227 – 252.

15. If you believe this, please contact me regarding some lucrative real estate transactions and a not-to-be-missed opportunity to help out a fine fellow in Nigeria.

16. Andre Perold and E. Schulman, “Batterymarch Financial Management (A), (B),” Boston: Harvard Business School, 1-286-113/5 (rev. 2/88).

17. For details of this and other horror stories, see Chapter 11.

18. Many of these are described in Chapter 2 ( “Greatest Hits of Computation in Finance” ).

19. This crowd includes many of the same rubes who thought a machine might someday beat the world chess champion! Ha! Can you believe these guys? What? Oh… Never mind.

20. Kurzweil’s ideas on machine intelligence are at www.kurzweilai.net/. His site ( www.fatkat.com/ ) discusses his approach to investing.

21. A vintage literary antecedent to this is found in the early days of the HAL 9000 computer from Arthur C. Clarke’s story and Stanley Kubrick’s film 2001: A Space Odyssey. HAL, we recall, learned to sing simple songs. The singularity machine would already know them, encoded from the connections in the memory of its biological model. Astro Teller’s novel, Exegesis (New York: Random House, 1997), is a fascinating and much more serious exploration of a first encounter with a sentient machine.

22. This book is not intended as a detailed text on market technology. Progress is so fast that the Web is a primary source. A good recent book is Introduction to Financial Technology by Roy Freedman (New York: Academic Press, 2006).

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Chapter 14 – Nerds Gone Green – Nerds on Wall Street, off Wall Street


Clean Energy and Nerds off Wall Street

This book closes with another chapter that, like the previous two, I didn’t expect to be writing. Recent headlines (Wall Street layoffs could reach 200,000, Citigroup is cutting 50,000 jobs) imply that many nerds on Wall Street (NOWS), mostly innocent bystanders in the meltdown, may soon find themselves on the real street. The scramble to create electronic markets for the stealth securities that caused the mess will allow some to find their way back to applying their experience in finance, but many NOWS will not.

Technology has a way of spreading outside its original zone of application. The Internet started out as a way for the Department of Defense to link military computers. Similarly, there are future uses for market technology that may rival those involving CUSIPs.(1) Efficient environmentally sound use of energy is one of the most important. We hear from voices as diverse as Thomas Friedman, T. Boone Pickens, and Ted Turner that energy technology is the next big thing. The last two so-called next big things, dot-coms and extreme finance, turned into fabulously bursting bubbles, so pessimists may want to stockpile long-dated batteries.

There is no denying that clean energy is a critical issue for the future. Actually, though, that is only true in the reality-based community. The Governor Caribou Barbie wing of the Republican Party maintains that global warming is just a run of bad weather caused by Al Gore and gassy polar bears, but the rest of us remain concerned and want to do something about it. The area of the energy and environmental complex where financial market technology is likely to have the largest payoff is the electric power sector. There are some strong commonalities across electricity and financial markets.

Financial Market Technology and the Electric Power Sector

First, innovation is accelerating. We are just beginning to see the decentralized use of information technology in this industry. The laws of Moore and Metcalfe are only now starting to be felt outside of the control room. Go look at your electric meter. It is probably just like the meter your parents had, a spinning disk device with dials. This won’t be the case for your kids.

Second, there are multiple buyers and sellers. The multiple buyers obviously include everyone who gets an electric bill. The multiple sellers side is more subtle. Most of us can only find one place to purchase electricity. At a household level, today, this is true. In many states, the distribution and generation of power are separate, so distribution and generation firms already participate in a market. Recall the tapes of the Enron power traders cackling as they manipulated prices paid by distribution utilities.

A proliferation of small and cottage-scale providers is emerging as solar, wind, and other technologies that produce a small amount of power become more important. No one builds a small nuclear reactor or coal plant, but just about anyone can have a wind generator in the yard, or an array of solar cells on the roof.

Third, regulators loom large. People who complain about the fragmented regulation of the securities industry by the Commodity Futures Trading Commission and the SEC will get little sympathy from the electric power people. There are 50 state agencies to deal with, many with an independent streak, with the feds at the Environmental Protection Agency (EPA) and the Department of Energy thrown in as well. Much of the regulatory structure is badly in need of rethinking. Many states create incentives for exactly the wasteful behavior we want to eliminate. The Electric Power Research Institute reports that “in all states except California and Hawaii, utilities are now, in effect, rewarded for selling energy and penalized for reducing customer sales. . . . Profits must be decoupled from energy sales. We need to provide incentives to utilities to lower customer energy use so that energy efficiency can be measured as part of a profitable business.”(2)

Fourth, there are so-called fat tails that are extremely significant. Over the past 10 years, an investor who was fully and broadly invested in U.S. stocks (the Wilshire 5000) would have gained 13 percent (up to the end of October 2008). If he or she missed the market’s 20 best days, the portfolio would have lost 57 percent — a minus 70 percent difference just by missing the market’s 20 best days. That is a fat tail in the distribution of returns.

Electrical Energy Consumption and Peak Load Demand

A Brattle Group discussion paper(3) describes a similar fat tail effect in electricity markets: “The demand for electricity is highly concentrated in the top one percent of hours [during a year]. In most parts of the U.S., these 80 – 100 hours account for roughly 8 to 12 percent of the maximum or peak demand. In the 12 Midwestern and Northeastern states . . . they account for 16 percent.” Note that these percentages are not referring to total energy consumption , but to the level of total power (the rate of delivering energy) that has to be provided over the year. In the electric world, this is called lowering the peak of the load duration curve.

Understanding load duration curves is the first lecture in Power 101 class. If you want to understand bonds, you need to know about the yield curve. The load duration curve is equally important if you want to understand electricity. Figure 14.1 shows a load duration curve and how it would shift with the use of the technologies discussed in this chapter. Lowering the peaks on these curves is important economically, environmentally, and geopolitically, because the plants needed to meet them are expensive, and often oil fueled.

Figure 14.1 Reshaping the load duration curve. Bonds have the yield curve. Power has this. Source: GridPoint.

Figure 14.1 Reshaping the load duration curve. Bonds have the yield curve. Power has this. Source: GridPoint.

Software applied to the electric grid offers unprecedented flexibility in reshaping the load duration curve. Utilities can either reduce customers’ nonessential loads or discharge distributed stored power, separately or in concert, to manage peak periods in a cost-effective, energy-efficient manner. Lowering the peaks (on the left of the chart) has tremendous value in cutting both cost and carbon emissions.

The commonalities between electronic financial markets and electronic energy markets suggest that skills in the former can be applied in the latter. The state of both means that there are likely to be more than a few readers contemplating this transition. This last chapter is a gentle introduction to and a survey of more in-depth resources on this topic.

Accelerating Innovation in Green Technologies and Peak Electrical Demand

There are over a million hybrid Toyota Prius vehicles on the road, and in Berkeley, California, it often seems that they are all parked on the same street. With only one model and a handful of colors, you need a distinctive bumper sticker to find yours. “Obama ’08” does nothing to help here. “Support Your Right to Arm Bears” with a rifle-toting polar bear is a little better, but still not that unusual in these parts. “2B or D4” is more distinctive.(4)

The current generation of hybrids makes its own electricity using a small generator under the hood. They have no impact on the demand for electricity from utilities. The next wave of fully electric vehicles and plug-in hybrids will be different. A movie trailer for a scenario from the Union of Concerned Scientists ( www.ucsusa.com ) might be “Imagine a society with ten million electric cars. Suddenly, they all pull into their garages between 5:30 and 7:00, and plug in to recharge. Imagine the 160 new power plants we need to keep the lights on while this happens.

Be afraid. Be very afraid. “Drill, baby, drill!” Something has to give. In this case, the “something” is immediacy for the consumers of power. A simple timer system, spreading out the scheduled power over 10 night hours (allocated by last digit of street or IP address) reduces the number of power plants needed by an order of magnitude. …

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All notes for this chapter about Clean Energy, Electrical Energy Consumption, and Peak Load Demand

1. CUSIPs are issued by the U.S. Committee on Uniform Security Identification Procedures; they are nine-character alphanumeric security identifiers. See www.cusip.com for more than you need to know.

2. Brent Barker and Lucy Sanna, “Turning on Energy Efficiency,” EPRI Journal (Summer 2006): 4 – 13, http://mydocs.epri.com/docs/public/000000000001013720.pdf

3. Ahmad Faruqui, Ryan Hledik, Samuel A. Newell, and Johannes Pfeifenberger, “The Power of Five Percent: How Dynamic Pricing Can Save $ 35 Billion in Electricity Costs,” Electricity Journal , October 2007, www.brattle.com/Publications/BooksArticles.asp?PublicationID=922

4. This book’s title does start with the word nerds . In hexadecimal, D4 is the complement — negation — of 2B, so this is “To be or not to be.”

5. “Engineers Push Fuel Economy to Front Seat at Auto Summit,” Detroit News , April 11, 2005, www.detnews.com/2005/autosinsider/0504/12/A01-146552.htm

6. Some things that seem to never change, change. Dingell has been replaced by Henry Waxman as chair of the House Energy and Commerce Committee.

7. “Market Mechanisms for Competitive Electricity: Final Report,” Shmuel Oren, Project Leader, University of California, Berkeley, Power Systems Engineering Research Center, Publication 02-42, November 2002, www.pserc.org/ecow/get/publicatio/reports/2002report/oren_marketmech_finalreport.pdf

8. David Leinweber, “Real Time Pricing and Deregulating the Electricity Market,” RAND Paper P-6448, www.rand.org/pubs/papers/P6448/

9. If anyone reading this has a copy of “The Tumescent Threat,” please contact me. The fact that this footnote is here says it all about how effectively this has been vanished, and about the sorry state of my garage filing system.

10. “Rogers Calls for ‘Paradigm Shift’ to Realize Full Potential of Energy Efficiency,” Edison Electric Institute press release, February 2007.

11. Faruqui et al., “Power of Five Percent.”

12. http://cift.haas.berkeley.edu/

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Chapter 13 – Structural Ideas for the Economic Rescue – Fractional Homes and New Banks


Structural Ideas for the Economic Rescue – Fractional Homes and New Banks

Mom used to say, “If you don’t have something nice to say, don’t say anything at all.” I clearly ignored that advice in the previous chapter, with the “mad as hell” opening and analogies to an exploding meth lab run by the neighbors. This chapter is more polite and more positive. It is about two ideas that can help us out of the mess we are in. Both have a systems analysis flavor, and both are from MIT graduates, who have the predilection and training to think this way.

The two ideas discussed here, fractional home ownership and a new American bank initiative, each have a great systems analysis soul — removing unnecessary complexity and negative feedback loops and creating positive feedback via incentive structures to make them work. One of the best examples of a structural approach to societal problems occurred in Germany in the 1970s. Some German rivers had become so polluted with factory waste that they would catch fire. Some were paved over and declared industrial sewers. Plants were simply required to take in their water just downstream from where they pumped out their waste. The garbage became their problem instead of everyone else’s. River fires became a thing of the past, and the concrete covers were removed.

Fractional Home Ownership

John O’Brien is one of the founding fathers of the field of financial engineering. He understands the field as well as anyone, from both academic and practical experience. As a founder of Leland, O’Brien, and Rubinstein (LOR), he was one of the inventors of portfolio insurance, a dynamic hedging strategy for equity portfolios to reduce downside risk.(1) Portfolio insurance worked very well in relatively stable markets, and by October 1987, firms managing over $60 billion in assets were using the system. The basic idea was to sell futures in declining markets to protect the underlying assets, and the desired results were achieved.

However, when the stock market tanked on October 19, 1987, there was insufficient liquidity in the futures markets to absorb the selling by portfolio insurers and others, and the volume of selling drove down the futures prices and in turn the stocks themselves. Portfolio insurance was not the only or even the principal cause of the crash, but it may have contributed to the speed and size of the decline.

John has taken the lessons of portfolio insurance to heart, and perhaps more than others, considers the unintended consequences of financial ideas. In that spirit, he proposed what I believe is a particularly well thought out approach to dealing with the underlying cause of the Mess of ’08 — the collapse of home prices. His idea lets people remain in their homes, avoiding the displacement, grief, and blight that are plaguing many communities. This is possible by creating simple, transparent securities that allow the vast collection of investors to participate in solving this problem. Fed Chairman Bernanke (yet another MIT grad, Ph.D. in economics, 1979) suggested the general outline of this plan in his March 2008 speech entitled “Reducing Preventable Mortgage Foreclosures”:(2) The fact that many troubled borrowers have little or no equity suggests that greater use of principal write-downs or short payoffs, perhaps with shared appreciation features, would be in the best interests of both borrowers and lenders.

John has put meat on the bones of this suggestion. The remainder of this section is from his exposition of this idea.(3)

Sharing the Risk, Sharing the Rewards of Home Ownership

Stabilizing the housing market effectively and equitably requires more innovative approaches than just lowering mortgage interest rates and extending mortgage maturities. The two key objectives should be: (1) avoiding preventable foreclosures, and (2) increasing the affordability of the existing housing stock, thus increasing housing demand. Both of these issues can be addressed by allowing home financing to include a minority, passive equity partner. With such a partner, homeowners can right-size, i.e. adjust to an affordable level, their financial obligations by owning less than 100 percent of their homes, while maintaining all the benefits of home ownership. With a properly standardized fractional home ownership security, institutional investors could and would be that partner.

The Innovation: A Home Equity Fractional Interest Security

Currently home purchases are financed entirely with the owner’s personal capital (down payment) and debt (mortgage). There is no opportunity for the homeowner to get external equity financing, where a passive investor shares in the financial gains and losses of the home’s value.

At present, therefore, a homeowner who wants to live in a $300,000 home must bear $300,000 of exposure (and expense) to the housing market. The homeowner’s consumption of housing equals the homeowner’s investment in housing. Arguably, this makes no sense, because owning a home — rather than renting — is partly a lifestyle choice and partly an investment choice. Choosing home ownership should be possible either as a 100 percent owner with a large mortgage or a majority/controlling owner with a smaller mortgage, with the exact mix determined by the homeowner’s financial circumstances and personal preferences. There is no reason why home ownership must be all or nothing.

A home equity fractional interest (HEFI) security would separate the consumption and investment decisions. For example, a homeowner might own 80 percent of a $300,000 home (with $240,000 financed by a down payment and mortgage) and an outside, passive equity investor would own the other 20 percent. The homeowner consumes housing at the $300,000 level, but has only $240,000 of exposure (and expense) to the housing market.

This innovation would have major short-term benefits for foreclosure mitigation and long-term benefits for stabilizing home prices. And it is possible now.

Mitigating the Mortgage Foreclosure Crisis — Avoiding Preventable Home Mortgage Foreclosures

The majority of preventable home mortgage foreclosures consist of an owner-occupied home where the owner wishes to remain in the home, but only has the financial capacity to maintain a mortgage of, say, 80 percent of the home’s current market value. A foreclosure could be prevented if the lender restructured the current mortgage to 80 percent of the current market value plus an HEFI security.

The homeowner pays for the mortgage reduction with the HEFI. Because the homeowner now has equity in the home (previously, the mortgage likely exceeded the home’s current market value) and a sustainable mortgage expense, foreclosure is unlikely. This restructuring is not a bailout, doesn’t risk taxpayer money, and is not unfair to responsible homeowners or renters.

Stabilizing Home Prices — Balancing Housing Supply and Demand

Traditionally, a home seller must find a buyer who both wants to consume the shelter and amenities provided by the home and has the means and desire to purchase it. This double-match problem makes it harder to match buyers and sellers, thus reducing effective housing demand and putting added pressure on home prices. The HEFI solves this problem — if the buyer wants to own a large house without taking large exposure to the market (and the resulting added cost), passive equity investors can make up the difference. This increases effective housing demand, which would help absorb the nation’s excess housing supply, thereby stabilizing prices at a higher equilibrium price than would otherwise be possible.

A Capital Market for Home Equity Fractional Interest Securities

The HEFI security represents a passive investor interest in a home — just as a share of stock represents a passive investment in a company. Institutional investors such as pension and endowment funds would be interested in HEFIs to achieve diversification beyond stocks and bonds. The single-family, owner-occupied (SFOO) equity asset class is as large as the entire U.S. stock market, around $10 trillion. To be properly diversified, institutional investors should …

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All notes for this chapter about Economic Rescue from Global Economic Collapse, Fractional Home Equity Ownership and New Banks

1. Andrew Kupfer, “Leland, O’Brien, and Rubinstein: The Guys Who Gave Us Portfolio Insurance,” Fortune , January 4, 1988, http://money.cnn.com/magazines/fortune/fortune_archive/1988/01/04/70047/index.htm

2. Ben S. Bernanke, speaking at the Independent Community Bankers of America Annual Convention, Orlando, Florida, March 4, 2008, www.federalreserve.gov/newsevents/speech/bernanke20080304a.htm

3. John O’Brien, “Stabilizing the Housing Market,” working paper, November 11, 2008. A similar article appeared in the Christian Science Monitor , November 26, 2008, www.csmonitor.com/2008/1126/p09s02-coop.html . Links to further discussion of this topic are found at CIFT Berkeley, http://cift.haas.berkeley.edu/systemsview.html and at Home Equity Securities LLC , www.homeequitysecurities.com/

4. It’s ahead of the Home Shopping channel, but way behind CNBC and Bloomberg, and, on most days, ESPN.

5. You can watch those 15 minutes here: www.youtube.com/watch?v=_ZAlj2gu0eM , or search YouTube for “CNN: Understanding the Crisis.” A variation of this idea was first suggested to Sal Khan by Todd Plutsky, his friend and classmate from Harvard Business School.

6. All 650 videos can be seen at www.youtube.com/user/kahnacademy

7. http://cift.haas.berkeley.edu/nabi-intro.html . This will doubtlessly evolve further past the date of this writing; the current version will be kept at the CIFT page.

8. http://paul.kedrosky.com

9. Barry Ritholtz, Bailout Nation: How Easy Money Corrupted Wall Street and Shook the World Economy (New York: McGraw-Hill, 2009), excerpted here: www.boingboing.net/2008/11/25/bailout-costs-more-t.html

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Chapter 12 – Shooting the Moon – Stupid Financial Technology Tricks


Stupid Financial Technology Tricks and Global Economic Collapse

Like many others from the stock side of greater Wall Street, I felt blindsided by the events of 2008. “Blindsided” is actually a gross understatement; I felt like the guy who comes home and finds the neighbors were running a meth lab that has exploded and flattened the block. I have tried to moderate this “mad as hell” attitude in writing this, and recognize that many participants did in fact realize that something was very wrong. One commented, “Bit by bit, we iterated toward more dangerous things, and each step seemed okay.”

It is an understatement to say the steps were okay. This was not a natural event, like Hurricane Katrina, or an external attack, like 9/11. This was a case of “Honey, I think I broke the world financial system.” To repeat the disclaimer of professional expertise on this subject: Of the billions in institutional assets I managed in the 1990s, exactly zero were invested in collateralized debt obligations ( CDOs ), credit default swaps ( CDSs ), and mortgage-backed securities ( MBSs ). I knew what they were, and particularly enjoyed the stories in Michael Lewis’s book Liar’s Poker of how the inventors of mortgage-backed securities at Salomon Brothers would shut down the market occasionally for food orgies of Roman proportions.

Our market neutral portfolios would often be equitized, putting back the market return with a simple futures position. Sometimes clients would want so-called portable alpha using futures in a market other than the one used for the stock portfolio, so we could add our return to a bond market, or an international stock market, as described in Chapter 5 ( “A Gentle Introduction to Computerized Investing” ). That was as far as we went with derivatives. There was little or no leverage due to the institutional constraints we had for pension accounts, and our strong desire not to blow up our clients’ portfolios and our income stream by turning what would be a moderate drawdown into a disaster. Lehman Brothers’ leverage was widely reported to be more than 30:1 when they turned out the lights, and other firms were equally overextended, which, while not without precedent, proved particularly toxic when applied to what proved to be nearly incomprehensible securities.

Faulty Financial Engineering and Lousy Derivative Securities Risk Management

Robert Merton, who shared the Nobel Prize for economics in 1997, was also one of the founders of Long Term Capital Management, the firm at the center of a $ 5 billion crisis in 1998. At the time there was a sense of great peril, and the size of the rescue, which now seems quaint, seemed overwhelming. Merton wrote, As we all know, there have been financial “incidents” and even crises that cause some to raise questions about the innovations and scientific soundness of the financial theories used to engineer them. There have surely been individual cases of faulty engineering designs and faulty implementations of those designs in building bridges, airplanes, and silicon chips. Indeed, learning from (sometimes even tragic) mistakes is an integral part of the process of technical progress.(1)

This is not the place and I am not the person to fully explain the morass we have fallen into. I did ask the people I knew, at Berkeley and on Wall Street, to give me a crash course so I could understand how technology contributed to the crisis, how it could help get us out of it, and how to avoid a repetition. I have real and virtual stacks of articles, papers, books, and links; it would take a book this size to cover them all. A particularly clear and incisive non-technical discussion can be found in Vanity Fair , by historian Niall Ferguson ( “Wall Street Lays Another Egg,” December 2008).

One resource stands out for an audience looking to get some traction on the global financial mess, and looking for pointers to current quality material from primary and media sources: the Baseline Scenario web site(2) started for exactly this purpose by MIT Sloan School of Management professor Simon Johnson, who returned to MIT in August 2008 after a year as director of research for the International Monetary Fund. Instead of picking up where he left off in his research and teaching, he devoted his energy to starting and maintaining the Baseline Scenario site. The place to start there is “The Financial Crisis for Beginners.” It begins:

We believe that everyone should be able to understand how the financial crisis came about, what it means for all of us, and what our options are for getting out of it. Unfortunately, the vast majority of all writing about the crisis — including this blog — assumes some familiarity with the world of mortgage-backed securities, collateralized debt obligations, credit default swaps, and so on. You’ve probably heard dozens of journalists use these terms without explaining what they mean. If you’re confused, this page is for you.(3)

At this site you’ll find links to radio programs, mostly National Public Radio ( NPR ), and video material that will bring you up to speed quickly. The main portion of the site, also used for an MIT course on the subject, is updated regularly with more in-depth material on the latest turns in the financial crisis. Having franchised out the discussion of the origins of the crisis, and the larger issues around it, we can turn to the subject of this chapter, the role of technology in this mess.

To Protect and to Serve: Market Transparency in Financial Theory and Free Markets

In financial theory, market transparency is a necessary condition for a free market to be efficient. In practice, at a micro scale it means that we can see the prices to buy and to sell securities (quotes) and the prices at which transactions actually occur (trades). A macro view of market transparency is that information about the securities being traded should be similarly reliable. Assuring that markets are transparent is a key role for regulators.

Public participation in the stock market grew dramatically in the early part of the twentieth century, and without regulation, abuses such as fraudulent information, extravagant fees, and extreme leverage became common. The last financial crisis of the magnitude we are seeing today made the need for regulation apparent. The Securities and Exchange Commission (SEC) explains its origins on its web site ( http://sec.gov ):

When the stock market crashed in October 1929, public confidence in the markets plummeted. Investors large and small, as well as the banks who had loaned to them, lost great sums of money in the ensuing Great Depression. There was a consensus that for the economy to recover, the public’s faith in the capital markets needed to be restored. Congress held hearings to identify the problems and search for solutions.

Based on the findings in these hearings, Congress — during the peak year of the Depression — passed the Securities Act of 1933. This law, together with the Securities Exchange Act of 1934, which created the SEC, was designed to restore investor confidence in our capital markets by providing investors and the markets with more reliable information and clear rules of honest dealing.

The mission to provide investors with reliable information is what makes all of the quant-textual approaches based on SEC filings (described in Chapter 9 and elsewhere in this book) both possible and valuable. It is why the micro-scale market data — trades and quotes — are visible on the bottom of every business television station and financial web site.(4) (See Figure 12.1 .)

Figure 12.1 All levels of detail are available for stock and option markets, down to individual trades and quotes. Market transparency to the max. Nothing remotely like this exists for CDOs, CDSs, and the rest. Source: NYSE.

Figure 12.1 All levels of detail are available for stock and option markets, down to individual trades and quotes. Market transparency to the max. Nothing remotely like this exists for CDOs, CDSs, and the rest. Source: NYSE.

Simple derivative securities like futures and put or call options transfer risk in readily understood ways. Futures markets started so farmers could protect themselves from a drop in crop prices that might keep them from covering their costs and being able to keep their farms for another harvest season. Consumers of agricultural commodities (e.g., wheat) could lock in prices that would let them fill their commitments to deliver products made with those commodities (e.g., bread) at the prices they had agreed to sell them, without risk of ruin. These commodity derivatives were also used by pure speculators with no underlying business interest in the price of wheat (or silver or oil) to make large bets on the direction of prices, since the futures markets could be many times larger than the actual physical supply of the underlying commodity. Speculative misbehavior was the inevitable result, and again, the federal government stepped in to regulate the market, this time by creating the Commodity Futures Trading Commission (CFTC), as explained on its web site at http://cftc.gov: …

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All notes for this chapter about Stupid Financial Technology Tricks and the Global Economic Collapse

1. Robert C. Merton and Zvi Bodie, “The Design of Financial Systems: Toward a Synthesis of Function and Structure,” Journal of Investment Management 3, no. 1 (First Quarter 2005): http://www.people.hbs.edu/rmerton/Designpaperfinal.pdf

2. http://baselinescenario.com

3. “Financial Crisis for Beginners,” Baseline Scenario, http://baselinescenario.com/financial-crisis-for-beginners/

4. OTC markets are not inherently a bad idea; they work for corporate debt and other securities. A lack of reporting for these toxic derivative securities created a dark market on an unprecedented scale.

5. Carol Loomis, “Robert Rubin on the Job He Never Wanted,” Fortune , November 28, 2007, http://money.cnn.com/2007/11/09/news/newsmakers/merrill_rubin.fortune/index.htm

6. Marking to market is the process of evaluating a security to reflect its current market value instead of its purchase price or book value. Marking to market is generally a good idea, but there are circumstances when it can serve to amplify the effect of what might otherwise be a short-lived mini-panic. A discussion is beyond the scope of this chapter.

7. Ben Bernanke, “Reducing Systemic Risk,” Jackson Hole, Wyoming, August 22, 2008, http://federalreserve.gov/newsevents/speech/bernanke20080822a.htm

8. “PWG Announces Initiatives to Strengthen OTC Derivatives Oversight and Infrastructure,” November 14, 2008, www.ustreas.gov/press/releases/hp1272.htm . 9. Rosenblatt Securities, “Trading Talk,” October 17, 2008, http://rblt.com/newsletter_details.aspx?id=38

10. Sharon Weinberger, Imaginary Weapons: A Journey Through the Pentagon’s Scientific Underworld (New York: Nation Books, 2006).

11. The 1940 newsreel of the collapse is not to be missed; see it here: www.youtube.com/watch?v=HxTZ446tbzE , or just search YouTube for “Tacoma Narrows Newsreel.”

12. See the “Top 10 Worst Engineering Disasters” at http://listverse.com/science/top-10-worst-engineering-disasters/

13. Chairman’s Letter, 2002 Berkshire Hathaway Annual Report, pp. 13 – 15, www.berkshirehathaway.com/2002ar/2002ar.pdf

14. Charles Duhigg, “Pressured to Take More Risk, Fannie Reached a Tipping Point,” New York Times , October 4, 2008. http://www.nytimes.com/2008/10/04/business/worldbusiness/04iht-05fannie.16689176.html?_r=1&scp=10&sq=duhigg%20fannie&st=cse

15. Alan Greenspan, October 24, 2008, hearing, House Committee on Oversight and Government Reform, http://oversight.house.gov/story.asp?id=2256

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