Explaining Market Crashes

The body of academic theories for market crashes explores a number of possible explanations. Why do markets crash? There may be some event that sets everything in motion, but why and when does a decline turn from an ordinary slide to a crash? Didier Sornette wrote a book and did a TED talk on the subject. Scholars as illustrious as Fischer Black and Myron Scholes weighed in on the subject. There are four main theories addressing this phenomenon:

1. Leverage effects: Drop in prices increases leverage both operating and financial thus exacerbating volatility when businesses and investors have to raise capital to cover leverage or by reducing leverage
2. Volatility feedback: When bad news arrives, the risk premia magnifies the direct effect of the news
3. Stochastic bubbles: Crash occurs when a buble pops thus resulting in a low-probability event that produces large negative returns
4. Investor heterogeneity: Different investors have varying constraints when it comes to short-sales. The more bearish group of investors subject to short-sales constraints may just sell all their sales, a suboptimal solution, and thus their information is not fully included in the market

The oldest theory is focused on leverage effects. The idea is that a drop in prices raises operating and financial leverage thus exacerbating volatility. This theory is articulated by Fischer Black and Myron Scholes in 1973 "The Pricing of Options and Corporate Liabilities" in the Journal of Political Economy. Andrew A. Christie further explores the idea in "The Stochastic Behavior of Common Stock Variances--Value, Leverage and Interest Rate Effects" in the Journal of Financial Economics 1982.

What is really interesting about Quantitative Behavioral Finance

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Quantitative behavioral finance has not been with out for a very long time. As a relatively recent development and area of discourse, it has only begun to gain a following. One very interesting aspect of this field is the use of experimental asset markets. These studies are based on experiments conducted on a small group of people (but with real money hence a real market) to examine where rational expectations and classical game theory fails to explain human behavior. This is basically small-scale version of the prediction markets such as the Iowa Electronic Markets, Intrade, and Betfair. However, unlike prediction markets where the ultimate objective is to predict an external event, experimental asset markets are more interested in the mechanics and patterns of the market itself. Caginalp, Vernon Smith (Nobel Memorial Economics Prize recipient of 2002), and David Porter have a couple of papers on experiments in this mode. Both experiments examine how financial bubbles can happen. Some of the take-aways are that excess cash and information asymmetry due to lack of an open book may exacerbate bubbles. I think the matter of information asymmetry is very salient. Despite all the effort and money invested in improving information infrastructure by banks and hedge funds, ultimately information is distributed non-uniformly to market participants. This is most obvious in the case of the retail investor who neither has the time nor resources to obtain and analyze all the market information.

The Scientific Method and Epistemology

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Listening to a past Intelligence Squared discussion on whether "Science will have all the answers", or as interpreted by one of the panelist "science is the only route to knowledge." This question lies in the purview of epistemology, the study of the nature of knowledge and the limits of that knowledge. Curiously enough, all this question is ultimately wrapped up in mathematical logic. Taking a step back, consider for a moment when you were first introduced to the scientific method. Hypothesize, predict, and test. It sounds all nice and intuitively rigorous, but where does it come from? Why does it supposed to intrinsically make sense? It turns out that there is nothing really fundamental about this formulation of investigation. My sense of the matter is that people still treat science very superstitiously as if it were some kind of magic or dogma. From grade school on, we were taught the one true answer as to how the natural world works. We revere Galileo and Darwin, and their respective scientific discoveries as if they received the discoveries from the heavens and did not require experimentation, hotly debated peer review, and eventual validation by other work. Moreover, we were taught at least implicitly that these great scientists were never wrong. Their theories never had to be revised or be subject to independent validation. Moreover, it seems as if we think that their theories are and were always the only reasonable answer. There is a kind of survivor's bias in science education. We laugh off Lamarck and others as being so obviously wrong and even as absurd forgetting that they were real scientists too despite not having directly produced the prevailing theory of our time. In fact, I dare say that it would be difficult to say what our understanding of the world would look like today if not for these other scientists upon whose work still contributed to the development of our current understanding of the world. Even the scientific method itself is treated as received knowledge and not as an amalgam of multiple reasonable routes of scientific investigation. Science itself is presented as a winner-takes-all activity.