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lity of securitized lending, at least in its current form. The argument for this change—one that I admit I once accepted—was that it would shift the risk of term-transformation (borrowing short to lend long) out of the fragile banking system and onto the shoulders of those best able to bear it. What happened, instead, was the shifting of the risk on to the shoulders of those least able to understand it.”

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Widely acknowledged as the dean of world financial commentators, Martin Wolf outdid himself in these prescient comments made during the early days of the global financial crisis of 2007–2010. Going deeper, Gretchen Morgenson’s book Reckless Engagement argued that a self-dealing network of politicians/lobbyists/regulators/bankers enriched themselves at the expense of the broader public. Greed on stilts! While Wolf, Morgenson, and many others are right in what they say, they fail to point out that much deeper forces were at work here—forces that would transform the US housing market collapse into a veritable Perfect Storm. These deeper forces were identified only 15 years ago by means of a completely new concept of market risk developed by Mordecai Kurz at Stanford University. Kurz’s new theory of “endogenous risk” (risk that bubbles up from inside an economic system) teaches us that, while greed, incompetence, and conflict of interest stressed certainly exacerbate Perfect Storms, they are not in fact necessary for the occurrence of such crises. Something bigger is going on.

The primary purpose of Chapter 4 is to explain how such storms arise, and to do so from first principles utilizing the paradigm introduced by Professor Kurz. His theory represents the particular form of “deductive logic” I utilize in this chapter to help resolve an otherwise intractable problem. Because this new theory permits an identification of the true causes of market risk, and does so at a deeper level than ever before, it makes possible two other important advances. First, it can help policy makers identify valid policies for preventing, or, at least, mitigating future financial market storms. That is, the field of risk management receives a boost. Without understanding exactly what causes Perfect Storms to arise, meaningful storm-prevention policies cannot be identified. This point is often overlooked as legislators vent their rage at“the system.”

Second, the field of risk assessmentreceives a boost. There are, of course, many perspectives on market risk, including the popular “fat tail” theories celebrated by Nassim Taleb in his delightful book The Black Swan. But these theories usually describe risk rather than explain it at a fundamental level. Once again, without an understanding of the factors that give rise to risk in the first place, how could risk be properly assessed? For reasons stressed by Taleb and others, it is simply not enough for “quants” to massage historical data in an effort to determine meaningful probabilities of future events. For the probabilities of future events such as market meltdowns that define future risk cannot be assessed without first assessing the probabilities of the underlying causes of such events.

One caveat is in order here at the outset. The global financial crisis of 2007–2010 consisted of two parts. In the first part, the mortgage banking crisis in the United States and the United Kingdom held center stage. In the second part, the crises in these two nations spread across the globe like wildfire immediately after Lehman Brothers was allowed to go under in September 2008. I shall focus on the first stage because this is where the greatest confusion reigns. I ignore the second stage because the causality here is well understood: The collapse of Lehman Brothers and AIG precipitated a panic-driven cessation of interbank lending among all major financial institutions. This in turn caused the crisis to go global, and to impact the Main Streets as well as the Wall Streets of the world.

The Four Origins of the 2008 Financial Crisis: Figure 1 offers a summary of the four principal sources of the Global Financial Crisis. The contents of the boxes should be intuitively clear, with the exception of the first box: Poor Economic Theory. This is at once the least understood, yet arguably, the most important issue, along with Excess Leverage appearing in the fourth box on the right. It turns out that the two are closely interrelated, since poor financial theory provided bogus justification for levels of leverage that proved catastrophic to the entire world.

Financial economics between 1960 and 1990 was dominated by a highly problematic economic theory. This theory is usually referred to as Efficient Market Theory. More technically, economists refer to it as the theory of“Rational Expectations.” A theory (whether in physics or economics) is problematic if it neither explains nor predicts real-world data and if, at a deeper level, its Basic Assumptions are indefensible. In the case of good theories, the reverse is true: the Basic Assumptions from which the theory is deduced are judged“eminently reasonable,” and the resulting theory has the power both to explain and predict real-world data. Additionally, a good theory must be“falsifiable” in Karl Popper’s sense.



In what follows, Kurz’s new theory will be a foil against which the deficiencies of classical financial theory will become crystal clear. For it is a good theory in the precise sense just articulated. In particular, whereas classical theory could only explain about 19% of stock market volatility between 1900 and 1980 when tested by Robert Shiller at Yale in his classic 1981 essay, Kurz’s new theory can explain some 90% of observed risk. This represents remarkable progress. Regrettably, his new theory has been set forth in articles that are very demanding mathematically, and for this reason, his work is not yet widely known. This is SOP in the history of science.

Root Problems With the Efficient Market Theory: In the case of finance, the Efficient Market Theory is a poor theory insofar as: (1) It posits as a basic assumption that participants in markets never make mistakes, properly defined; (2) It assumes that all risks can be hedged, as well as that hedges never melt down—a pair of assumptions which, when combined with the no-mistakes axiom, imply that leverage will rarely cause significant problems; (3) It assumes that everyone in a market knows how to correctly “price” the news once it is announced—there are no disagreements as to how to interpretnews; (4) It predicts a level of volatility that is about one-fifth of what is observed in reality—with no Perfect Storm being possible; (5) It gave rise to the creation of new financial securities that did not perform as they were supposed to, and in fact became weapons of massive financial destruction; and (6) It implies that markets left to themselves will almost always function well, and will not break down.

As the following case study will show, poor financial theories—not just poor policies—can be very deleterious to the public welfare. They affect how we think, and thus how we regulate markets, or deregulate them, for that matter. As years go by, the Global Financial Crisis of 2008 should remind us of the extent to which bad thinking can lead to bad policies, as well as the extent to which bad policies really matter.

Superiority of the New Theory of “Endogenous Risk”: I believe that the new theory of endogenous risk developed at Stanford University is the appropriate antidote to the Efficient Market Theory, and the disaster which its models helped to foster. Like most good theories, the new theory does not reject the predecessor theory—Efficient Market Theory—but rather generalizes it. That is, it includes classical finance as a special case that will only work under idealized conditions that will rarely, if ever, be encountered in the real world. This was the case with Einstein’s general theory of relativity, which incorporated Newton’s theory of gravity as a limiting special case. Specifically, if and when space-time can be approximated as “flat,” not curved, then Newton’s laws work just fine, as they do in everyday life.

My job is now to explain the new theory, and convince you of its power. I shall demonstrate how it can explain the emergence of Perfect Storms—one form of those“fat-tailed” events that are usually described, but rarely explained from First Principles. Moreover, once the new theory is understood, the true deficiencies of classical Efficient Market Theory will become crystal clear. In particular, it will become clear how traditional financial theories have blinded policy makers, bankers, quants, and investors alike to the true magnitude of risk and, hence, the true likelihood of Perfect Storms.

Explaining Financial Perfect Storms Without Assuming Malfeasance: Can a Perfect Storm arise even if there are no greedy bankers, and no regulatory authorities beset by conflicts of interest—the conditions stressed by Martin Wolf in the opening citation above? The new theory of endogenous risk demonstrates that such crises can indeed arise without malfeasance. Of course, malfeasance will always exist, and its ancillary role is to amplifythe story we are about to tell. But malfeasance turns out not to be a necessary condition for Perfect Storms.



Please consider Figure 2. You see here the conditions that lead to a Perfect Storm, even when greed and self-dealing play no role. The best way to make sense of the four factors in the four outer boxes is to understand how and why each is a violation of the strict (and wholly unrealistic) assumptions of the Efficient Market Theory reviewed above.

Precondition 1: The Right-Hand Oval—Correlated Mistakes:In the world of efficient markets, it is assumed that all agents learn from historical data the true probabilities of all future events and prices. Thus, all agents share the same probability forecast. Moreover, given the assumption that the random process generating historical data cannot change—so the past is a perfect predictor of the future—then all agents’ forecasts will be the correct forecast. Accordingly, the concept of “mistake” does not arise in classical finance, and in no finance textbook will you find this word. A mistake occurs when someone looks back and says: “Gosh, the world has changed (e.g., global warming occurs, OPEC arises, derivatives are invented), and the betting odds I calculated from historical data were wrong.” Given the reality of “structural changes” that often make historical data unreliable, investors end up with a plethora of different forecasts. Since at most one forecast will be correct, most everyone will end up wrong, to one degree or another. What a contrast this is to the calm of an efficient market world in which no one ever says “I was wrong,” or rushes to change his portfolio.

Once mistakes enter the picture, market risk is transformed, a point central to Kurz’s new theory of risk. More specifically, it turns out that what matters to market prices and volatility is not merely that people’s bets are wrong, but additionally how correlatedtheir mistakes are. It is when most investors are wrong in the same direction that the greatest portfolio adjustments occur, and that prices change the most; for most everyone will either sell or buy, and the price swings accordingly. This is not the case when your bet ends up 15% high of reality, whereas mine is 15% low of reality. In this case, our mistakes cancel out, and prices do not move.

A classical example of a “correlated mistake” were bets on US house prices as late as 2006. Almost no one assigned high probability to the inconceivable 35% drop in house prices that transpired. The market response was fast and furious. Correlated beliefs of this kind are an important source of what Kurz calls “endogenous risk.”

Precondition 2: The Left-Hand Oval—Problematic Hedging: Life would be a lot less risky for almost all of us if we could perfectly hedge all the risks in our lives, the “complete hedging markets” assumption of classical financial theory. But as Professor Robert Shiller of Yale and others have shown, many of the most important risks in our lives cannot be hedged at all. These include the probability of unfairly being fired, the probability of having to sell a house when house prices are low rather than high, the probability of a good marriage remaining a good marriage and not ending in divorce, and the probability of stock prices being high versus low during the month we retire and seek to annuitize our wealth for a guaranteed lifetime income. The problem here is known within economic theory as the problem of“missing markets.”

You might suppose that non-hedgability of this kind has become much less of a problem than it used to be as instruments for improved risk-hedging become more available (e.g., many types of “derivative” securities). While there has been great progress along these lines in recent decades, it is well known in the economics community that many of the most important risks will never be able to be hedged due to problems of “moral hazards” and other related issues in economic theory.

In addition to the non-existence of hedges for smoothing out some of the bumpiest moments in our lives, there is the reality that hedges that do exist can melt down and malfunction just when they are most needed. Recall the terrifying U.S. market crash of October 1987, “Black Monday.” Also recall the collapse of the hedge fund Long-Term Capital in 1997. In both cases, distress was compounded and hence “risk” was greater when numerous hedges ceased to function. To conclude, problematic hedging is the second source of Financial Perfect Storms.

Precondition 3: The Lower Oval – Pricing Model Uncertainty: This condition is a bit more technical in nature. Have you ever been in a car with other impatient passengers, vainly trying to locate a destination on a roadmap when you cannot read the map? Confusion and mistakes result. The same idea arises in finance due to investors’ inability to read another kind of map. Do you recall from school the idea of a “function” F? For example, consider Y = F(X), expressing the concept that variable Y is a function F of some other variable X. Suppose X denotes “the news” in some market, and Y denotes market price. Then the function F transforms or “maps” this news X into price Y. In traditio sMortgagedealslending Mortgage Deals Lending B Cash Mortgage Szh 1 Mortgage Deals Lending My China News Digestv l Mortgage Deals Lending oMortgagedealslending Mortgage Deals Lending B Cash Mortgage Szh 1 Mortgage Deals Lending My China News Digestj Lending