A Demon of our own Design

Time for another book report. I just finished this book today. Another worthwhile read. Book deals with hedge funds, a timely subject.

Richard Bookstaber, “A Demon Of Our Own Design” (Markets, Hedge Funds, and the perils of Financial Innovation), John Wiley & Sons, Inc., Co., 2007

Note: Author, Richard Bookstaber, runs an equity hedge fund.

Wall Street’s paradox: Investors are more sophisticated than ever, are enabled by unprecedented technology, and protected by more govt oversight and regulation than at any other time in history. Yet Wall Street is becoming a riskier and riskier place. Today’s worst financial crises do not arise from economic instability or acts of nature, but from the very design of the financial markets themselves. Bookstaber explains why the best efforts of institutions on the front lines to create safeguards, manage risk, and regulate the markets may end up contribution to instability. He argues that many of the financial innovations and regulations that are supposed to level the playing field instead make the markets more dangerous for all the players, big and small.

Bookstaber identifies the key areas that make markets vulnerable: liquidity that begets greater leverage; innovation that creates greater complexity; and a structure that demands a nonhuman level of rationality. The twofold solution he suggests—reducing complexity and breaking the tight coupling of transactions—goes against the prevailing winds of Wall Street, but will lead to a more robust and survivable market.

My Notes:
pg. 3: A troublesome facet to our modern market crises is that they keep getting worse. Two of the great market bubbles of the past century occurred in the last two decades. First, the Japanese stock market bubble, in which the Nikkei index tripled in value from 1986 though early 1990 and then nearly halved in value during the next nine months. The second was our own Internet bubble that witnessed the NASDAQ rise fourfold in a little more than a year and then decline by a similar amount the following year, ultimately cascading some 75%.

This same period was peppered with three major currency disasters: the European Monetary System currency crisis in 1992; the Mexican peso crisis that engulfed Latin America in 1994; and the Asia crisis, which spread from Thailand and Indonesia to Korea in 1997, and then broke out of the region to strike Russia and Brazil. The Asia crisis triggered losses that wiped out the majority of the market value that the Asian “Tiger” economies had amassed in the prior decade of booming growth. LTCM seemed just as cataclysmic at the time, but it centered on a single $3 billion hedge fund in 1998, albeit one that had more than $100 billion at risk (extraordinary leveraging). As a debacle, it was later overshadowed by the spectacular failures of Enron, WorldCom, and Tyco after the dot-com collapse. Yet, did anyone even notice the convertible bond collapse that erupted for no apparent reason in 2005 or the $6 billion of losses by Amaranth in September 2006?

Pg. 9, 1987 Portfolio Insurance: is a strategy designed to protect a stock portfolio from dropping below a specified floor value. The strategy works by using a hedge—selling S&P 500 futures, for example. If the portfolio increases in value and moves above the desired minimum floor value, the hedge is reduced, allowing the portfolio to enjoy a greater fraction of the market gain. If the portfolio declines in value, the hedge is increased, so that finally, if the portfolio value falls well below the floor price, the portfolio is completely hedged. Thus the portfolio is hedged when it needs it and is free to take market exposure when there is a buffer between its value and the floor value. The hedging method of portfolio insurance is based on the theoretical work of Fischer, Black, Robert Merton, and Myron Scholes. By 1987 portfolio insurance was the driving force in trading decisions, with more than $60 billion of assets being hedged with the technique.

Pg. 14, If one small portfolio uses this “portfolio insurance” strategy, liquidity will not be an issue. If everyone in the market is trying to do it, it can become a nightmare such as happened on October 19, 1987. Everybody who was running a portfolio insurance program pulled out the computer runs from Friday’s record drop. Some firms had been caught by surprise, so they poured sell orders into the S&P futures pit by the truckload. The market had reached a point where one drop in the market would trigger another, each tied to portfolio insurance hedging and each magnifying the previous one.

Pg. 31, October 19, 1987 ushered in the context for a type of risk that would embrace the markets in the future. At the root of the crash were two things: One was computer-assisted liquidity, which took the form of rapid, programmed cash-futures execution. The other was an innovative product, portfolio insurance, that demanded that liquidity for successful implementation. The market was developing to allow lightning-fast reactions while at the same time driving complex innovations in market instruments and strategies that required ever more time for investors to analyze and absorb. This combination of speed and complexity would be the source of many future crises.

Pg. 111, LTCM Lousy with Leverage: For all of its sophistication, LTCM used simple historical analysis to assess the trading opportunities for unleashing their $3 invested for every $100 controlled leverage. The partners identified market relationships that they believed had long-term stability, such as the interest rate differential between Treasury bonds and high-grade corporate debt. They then compared the current level with the historical levels. Predicated on their conviction that the relationship had long-term stability, they would take positions based on the assumption that it would return, or converge, back to that historical value. What they did not appreciate was that they had changed history. There had never been someone trading hundreds of billions of dollars in the middle of this relationship before.

LTCM had scrupulously modeled and monitored its market risks. It prided itself on having broad diversification across the globe and across markets. The firm’s risk models looked at past price variability and provided the partners with assurance that they could survive the financial equivalent of the 100-year flood. The problem was that their models assumed they were in a “game against nature” where their decisions did not alter the playing field. In a normal market environment, with small players, this is a reasonable assumption. The risk that LTCM missed was that they could cause the flood. The more people write financial insurance, the more likely it is that the disaster will happen because the people who know you have sold the insurance can make it happen. This feedback of positions only become problematic when a crisis dries up liquidity or forces trades to be done quickly at any price.

Pg. 135, Accounting has failed us as investors and managers. Accounting should be about generating sufficient statistics to assess the state of a firm. It is more than simply taking numbers and putting them in the appropriate bin based on generally accepted accounting principles (GAAP). In an ideal world, the role of an accountant is to take the mass of all of the transactions of a company—from the purchase of materials to the sale of products, from money that is borrowed to wages that are paid—and boil them down to a set of statistics that provide a picture of the company’s performance sufficient for the equity holders to make investment decisions. And the accounting statistics should not only have a high correlation with the company’s value and prospects; they should also be standardized across firms for comparison purposes. Accountants have not been doing a very good job of this, and if anything they are marching backwards, doing worse and worse over time.

One reason for this failure is the well-known problem of conflict of interest. Accountants have a financial incentive to be on the audited company’s good side so they can keep their mandate and garner additional consulting work. This conflict was the main reason for the erosion in the quality of financial reports over the course of the 1990’s. While Arthur Andersen’s failure was the most visible, with the restatements and liability arising from Enron, Waste Management, Sunbeam, the Baptist Foundation, and global Crossing, the accounting firm may have not so much been an aberration as the most unlucky.

During the 1990’s, the number of restatements, which is generally viewed as a factor that is correlated with the number of instances of fraud, rose rapidly. In the early part of the '90s decade, the number of restatements for publicly held corporations averaged less than 50 a year. In 1997 the figure rose to nearly 100, then to 150 for 1999 and 2000 and held at a level over 200 for the next three years. Even if you fix this, the problem still remains because accounting is mired in historical methods and standards that are increasingly less relevant to the way businesses operate.

Pg. 137, For real assets such as physical plant, assembly lines, machinery, and real estate, valuation in terms of costs is logical: A business can reproduce the enterprise by simply going out and buying each of the component parts that constitute the production process. But the relationship between the cost of assets and the value of the enterprise does not work as well for companies with intangible assets, and these increasingly form the basis of economic value today. Intangible assets—ideas, patents, proprietary software, brand names, trade secrets, trademarks, and copyrights—have values that cannot be extracted from their costs. By some estimates, intangible assets now make up 80% of the value of the S&P 500.

Pg. 183, The principal reason for intraday price movement is the demand for liquidity. This view of the market—a liquidity view rather than an informational view—replaces the conventional academic perspective of the role of the market, in which the market is efficient and exists solely for conveying information. Why the change in roles? For one thing, it’s harder to get an information advantage, what with the globalization of markets and the widespread dissemination of real-time information. At the same time, the growth in the number of market participants means there are more incidents of liquidity demand. They want it, and they want it now.

Pg. 209, Academics apply Mathematics to the Market. Despite its benefits, the mathematical focus created limits for economics that have endured for several generations. In classical physics, any number of real-world effects such as friction or air resistance are assumed away to make mathematical analysis more tractable. Perfect vacuums and ideal gases provide a set of simplifying assumptions that allowed for the development of theories of the physical world. Similarly, in the study of economics it is necessary to assume a construct of frictionless markets to build a market theory out of the tools of mathematics.

This assumption of frictionless markets included instantaneous and costless transactions devoid of real-world constraints. Buyers and sellers bought or sold at posted prices, with no associated fees, and their actions had no impact on the market—in the nomenclature of economics, the market participants were atomistic. Moreover, to permit sophisticated spanning arguments and the application of fixed-point theorems from topology, it was assumed there were securities available for every possible contingency; every risk and possible event or state of nature not only was identified, but was also represented by a market security. Economics could be successful only if it predicted the behavior of people, but if real people were brought into the equation—people who don’t think like a computer, don’t perform mathematical optimization before every decision, and don’t (or can’t) process all available information before they take action—it would get in the way of the mathematics that filled the pages of the academic journals. So in order to apply the tools of mathematical optimization, the idealized financial world also assumed perfect rationality on the part of the market participants, all of whom make investment decisions with complete information. Hence, the efficient market theory.

Pg. 215, Primogeniture and the Role of Liquidity. The economic way of life in medieval England was framed by two economic realities: Virtually all wealth was in the form of land, and the land could not be sold. This is the very definition of an illiquid market. Wealth was held in land—even up to the seventeenth century it was the universal outlet for savings in England—primarily because there were not many alternative investments. And because land was the preponderant store of wealth, it was also the source of social stature and political power. As early as 1066, land could not be sold or even used as collateral for a loan because feudal lords exchanged it for a knight’s military service. By the late 1200’s, this limitation on the right to transfer land carried the weight of law; primogeniture, which restricted land transfers. All landholders now had a right to their land only for the course of their lives, after which the deed was transferred according to the rules of primogeniture, which meant it generally passed to the oldest son. Even in the case of treason, the land would be forfeited only for the generation in question and then would be reinstated to the next, based on primogeniture.

Pg. 217, With wealth locked in land, the medieval man, whether squire or serf, had no freedom. Both nobles and peasants were bound to their land or their trade, and the world remained unchanged from one lifespan to the next. However by the 1500’s many landed gentry began to demand liquidity for their land-locked wealth. Various artifices became employed to circumvent the rules of primogeniture. This emergence of liquid wealth lies at the genesis of the Industrial Revolution. Liquidity allows capital to migrate to greater opportunities.

Pg. 221, The Limits of Knowledge. In 1911 Bertrand Russell and Alfred North Whitehead completed a ten year 1,800 page work whose goal was to provide a formalized logic for all mathematics, to develop the full structure of mathematics where every premise could be proved from a clear set of initial axioms. But in 1931 Kurt Godel, using this document, demonstrated that the goal they had pursued was unattainable. About the same time, Werner Heisenberg’s celebrated Uncertainity Principle had delineated the limits of inquiry into the physical world thus destroying Laplace’s causuality concept. These limits to measurement imply limits to prediction. After all, if we cannot know even the present with complete certainty, we cannot unfailingly predict the future. Heisenberg showed that if there were a law of causality in nature, no one but God would ever be able to apply it. Just as the atomic world turned out to be more complex than Laplace conceived, the financial world may be similarly complex and not reducible to a simple causality.

Pg. 241, The Danger To The System Is The System. As experience has shown, the problems that lead to crisis emerge from within the market. In the case of the Internet market bubble, it was the coalescence of trading views, leading all those remaining in the market to bid against one another, encouraged at each turn by the increases in prices that were nothing other than their own doing. In the LTCM meltdown, it was the liquidation forced by the creditors, which led prices to drop, causing the successive liquidations that pushed creditors to take even more draconian actions. In the 1987 crash, it was the hedging actions that led to the price declines, which, through the nonlineraity of the strategies, led to even more aggressive hedging.

Conclusion: Simpler financial instruments (less complexity) and less leverage. And it ain’t gonna happen. Th..th..that’s all folks.