The Subprime Crash of 2008 has been called the capital market’s perfect storm. Not since the Great Depression has the financial system faced such severe challenges. The real estate bubble burst when the economy was weak with massive levels of personal, corporate, and sovereign debt that rendered remedial metrics uncertain.
But unlike natural storms where storm chasers try to reduce the number of potential victims by giving them early warning of the dangers they see coming, or where hurricane-hunter aircraft fly into tropical depressions to collect weather data for models that forecast the time and location of the storm’s landfall and the maximum intensity of wind and storm surge, no financial storm hunters built models to better-manage capital market activity surrounding market crashes and crises. To the contrary, there has been a troubling trend of larger and more frequent financial storms that have negatively affected a greater percentage of people.
Why? You can't manage what you don't measure. It is an old management adage that William Edwards Deming made famous in the early 1950s, but unless you categorize and measure something—it is hard to tell what it is and whether governance is getting better or worse. For example, was the subprime bubble a crash or a crisis? Was the subprime bubble caused by governance ineffectiveness or inefficiency? We address these questions by arguing that not only does one-size-fits-all (OSFA) deterministic metrics create errors of conflation resulting in vapor assets, but such mischaracterization is the foundation upon which future boom-bust business cycles are built. The critical flaw lies in the preoccupation with scale as in Too-Big-To-Fail (TBTF) financial institutions. These institutions are, in reality, Too-Random-To-Regulate (TRTR) because the underlying economic condition of uncertainty is omitted from the analysis.
Financial storms: crashes and crises
Although the terms “crash” and “crisis” are treated synonymously in much of financial literature, we differentiate the two for better governance. Stock market crashes are a sudden, dramatic, double-digit decline of stock prices. Crashes are a broad-based like a hurricane, their decline measured across a significant cross-section of the stock market. The 2008 Subprime Bubble, for example, is a crash because virtually every
citizen was somehow affected. “Crises,” by comparison, are issue specific with their decline limited to a particular event or institution. They are localized like a tornado. Madoff’s Ponzi scheme is considered a crisis; if you were not a client of the firm there is little likelihood of contagion. U.S.
Vapor assets that caused valuation distortions and trading halts are present in virtually every financial storm to the consternation of policymakers who have to group crash and crisis malfunctions as the result of either:
- Ineffectiveness that requires doing things differently because of a dysfunctional market that failed to trade as in the Subprime and 1970 Paper Crunch; and/or,
- Inefficiency that requires doing the same things better because of discontinuous pricing as in the 1987 crash.
A fundamental failure of the one-size-fits-all (OSFA) approach to governance stems from a lack of accurate information as measurements tend to be biased in support of the legacy system. Specifically, there were three corruptive information errors that were causal to the Subprime Crash:
- Misdiagnosis of renters as owners where renters received property rights that created perverse incentives relative to property foreclosures.
- Mischaracterization of the underlying economic environment that conflated risk and uncertainty resulting in mispriced subprime debt. Uncertain issues such as no-money down, NINJA MBSs have neither mark-to-market valuations nor positive cash flow from which to price investments. How could uncertain securities receive an AAA-rating?
- Misapplication of governance where policymakers responded to market excesses of the Enron crisis with regulatory excesses contained in Sarbanes-Oxley of 2002. Treating an issue-specific crisis as though it were a systemic crash resulted in disproportionate governance causing normative market commerce to migrate to economic externalities that encumbered the implementation of Dodd-Frank.
The conceptual thread that ties the governance of natural storms and capital market storms is “chaos theory.” It is a subset of complexity theory that finds underlying order from randomness. Chaos theory was formulated in 1960 by meteorologist, Edward Lorenz, while working on a weather prediction model. Thereafter, investment managers like Edgar Peters ported these concepts to the capital market. In Chaos and Order in the Capital Markets, Peters posited that market statistics do not necessarily follow Gaussian distributions. Rather, they sometime have fat tails for profit opportunities where the so-called butterfly effect shows that a small change at one place in a nonlinear, dynamic system can result in large differences to a later state.
While the body of the price curve is a Gaussian function, the tail of the curve may follow a power law that is like GAAMA Model externalities that are fractal dimensions. The GAAMA Model links neoclassical economics with Chaos Theory to analyze far-from-equilibrium commercial activity where a large number of seemingly independent elements act coherently. Neoclassical economics is devoted to the study of equilibrium. The concept of equilibrium is instructive in determining a unique end-condition, but the precision of the procedural process is misleading in that true equilibrium is difficult to achieve in volatile market conditions. Equilibrium is an axiomatic system where supply and demand functions are given to produce a unique market-clearing price for normative markets. The idea that supply and demand may be price driven was not considered by neoclassical economists; yet that is what capital market crashes and crises demonstrates.
The GAAMA Model’s calculus can differentiate its 3-dimensional, orthogonal structure into a 2-dimensional, 3x3 matrix. The matrix’s conceptual construct located in the upper left corner of the matrix (A1) illustrates how capital market catastrophes (crashes and crises) and their related causal market malfunctions (ineffective and inefficient transactions) are integrated to form financial storm categories.
Storm Hunter Matrix
Ineffective: not trading
Back-office Paper Crunch
Inefficient: bad pricing
Below is a brief description of Storm Hunter Matrix events and their related best-practice (or lack thereof) rules that arose in support of capital market standards.
Subprime Crash: things began to look bleak for the American stock market in 2008 thanks in large part to the subprime mortgage fallout. Subprime mortgages offered home loans to borrowers who posed a high credit risk. These loans were given with attractive terms, like low initial interest rates, and no down payment. In many cases, loans were made for amounts people could not otherwise afford. Notwithstanding that home foreclosures in the
increased 75 percent from 2006 to 2007, subprime mortgages were packaged as mortgage-backed securities (MBSs) and sold through financial institutions. United States
1987 Crash: from October 14, to October 19, 1987, major indexes of market valuation in the
dropped 30 percent or more. On October 20, these indexes recovered part of their loss. However, for the next four months, they were often subject to moderately large daily variation. From the close of trading on Tuesday, October 13, to the close of trading on Monday, October 19, the Dow fell by almost one third, indicating a loss in value of all outstanding United States stocks of approximately one trillion dollars. Although a number of people tried to account for the 1987 Crash, no one has yet provided a complete explanation. Blame largely focuses on: computerized trading and derivative securities, a lack of liquidity, United States budget deficits, and market overvaluation. US
As for best-practice corrective action enter the concept of “circuit breakers,” which the SEC approved on April 15, 1998 in amendments to NYSE Rule 80B (Trading Halts Due to Extraordinary Market Volatility). By implementing a pause in trading at specified price points, investors are given time to assimilate incoming information and then have the ability to make informed choices during periods of high market volatility without falling victim to herd behavior.
Back-office paper crunch: during the period 1967-to-1970, the back offices of US securities brokers were not able to handle the sharp increase in trading volumes. The number of "fails" (i.e. failures to deliver securities on the settlement date) soared and so did losses from back-office errors. Some firms tried to resolve the problems by abruptly switching to computerized systems, with generally disappointing results. Likewise, the SEC initially reacted to the back office problems by shortening the trading day in August 1967 and in early 1968, but with little success. During this period approximately 160 members of the New York Stock Exchange failed with roughly the same number either taken over or disbanded.
Where 10 million share-volume days once caused trade-halting backlogs from piles of unmatched and phantom trades, there emerged the formation of the National Clearing Corporation (NCC) that immobilized stock certificates through a continuous net settlement (CNS) process that enables the market to now settle and clear volume of two billion shares a day.
Enron: collapsed on December 2, 2001—the largest bankruptcy in
corporate history. Policymakers while reviewing the extent of the collapse and the corrupt and possibly criminal activity, did not ask, let alone answer, what were the driving forces within the company that led to such questionable behavior? Policymakers responded to market excesses of the Enron crisis with regulatory excesses contained in Sarbanes-Oxley of 2002. Treating an issue-specific crisis as though it were a systemic crash resulted in disproportionate governance causing normative market commerce to migrate to economic externalities. But where are the best-practices from this rule-writing exercise? US
For effective and efficient governance, randomness components must be segmented into predictable, risky, and uncertain regimes. It is Too-Random-To-Regulate (TRTR) not Too-Big-To-Fail (TBTF) that has resulted in flawed governance functions for crashes and crises. It is the accepted distinction between risk and uncertainty that is key. Risk is quantifiable and has foreseeable consequences; uncertainty is indeterminate and has unforeseeable consequences. When uncertainty becomes risk, that’s learning or innovation; you have greater control over your underlying economic environment. On the other hand, when risk becomes uncertainty, there is either confusion (too much information), or ambiguity (too little information). Should the uncertainty become unstable as in the Subprime Crash you have chaos when the capital markets froze.
Stephen A. Boyko is the author of "We're All Screwed! How Toxic Regulation Will Crush the Free Market System" http://readingthemarkets.blogspot.com/2009/10/boyko-were-all-screwed.html . He has over forty years of financial services industry experience that include formulating regulatory policy for the National Association of Securities Dealers (now FINRA) and providing a practitioner's perspective for the privatization of the former Soviet Union in corporate governance and regulatory development of the Ukrainian Capital Market. Contact: email@example.com
I want to thank the authors for their excellent article for the Blog. They continue to publish articles and books of importance to the financial and regulatory sector. Steve published the book "We're all Screwed!" and has been on active speaking engagements. I am pleased to call him a friend and he has agreed to be an active contributor to the blog!
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 The Saffir-Simpson Hurricane Scale and the Fujita Tornado Scale separates tornados into five different categories based on wind and related damage potential.
 With the exception of the 9/11 disaster, all financial storms involved the creation of vapor assets that led to excesses and an overvaluation. For a more detailed analysis see “We’re All Screwed: How toxic Regulation Will Crush the Free Market System,” Stephen Boyko, p. 8-42.
 “We’re All Screwed: How toxic Regulation Will Crush the Free Market System,” Stephen Boyko, p. 8-9.
 A Ponzi scheme is a fraudulent investment operation that pays returns to investors from their own money or money paid by subsequent investors rather than from any actual profit earned. The Ponzi scheme usually offers returns that other investments cannot guarantee in order to entice new investors, in the form of short-term returns that are either abnormally high or unusually consistent. The perpetuation of the returns that a Ponzi scheme advertises and pays requires an ever-increasing flow of money from investors in order to keep the scheme going.
 NINJA is an acronym for “No Income, No Job or Assets and MBSs is an acronym for Mortgage-Backed Securities.
 GAAMA: A New Perspective for Emerging Markets (Volume IV, Number 2)
 Capital market standards are represented by the FLITE model of Fairness, Liquidity, Integration, Transparency and Efficiency. See: Think before you regulate: Choose a better model, SFO Magazine, May 2009, Stephen A. Boyko, http://www.sfomag.com/article.aspx?ID=1338&issueID=c
 Rule-writing is the proscriptive description of an undesirable situation. It is ad hoc policymaking that Band-Aids over the current problem. It expects buy-in from society by describing the undesirable situation and prefacing it by saying “don’t do this.”
 “We’re All Screwed: How toxic Regulation Will Crush the Free Market System,” Stephen Boyko, p. 61.