Note: Sorry for the break in posting. I'm back. Also look out for book-related events coming this fall.
The Sunday New York Times carried an article about "econophysics", described as a new sub-field of economics (or physics) in which researchers analyze business cycles by analogy to seismic activity. The following excerpt explains the premise well:
Financial crises are difficult to predict... because markets are not, as some traditional economists believe, efficient, self-regulating, and self-correcting. The periodic upheavals are the result of a cascade of events and feedback loops, much like the tectonic rumblings beneath the Earth's surface.
One sees how these researchers usurp the orthodoxy in economics: "markets are not efficient!", "markets don't self-correct!" (i.e. don't tend to an equilibrium), etc. Not the stuff we were taught in Econ 101.
The author finds little room to provide some context -- not surprising for this kind of article. I think two additional points are salient: that a large body of work exists in related areas of statistics; and that models borrowed from the natural sciences are ill-suited to explaining human behavior.
The new theory relies on several advanced statistical concepts, things left out of my book. One is the so-called "power laws", an example of which is the 80-20 (Pareto) rule. In the 1900s, Pareto discovered that 20% of Italians owned 80% of the land. Power laws are related to the "long tail" or "heavy tail" or "fat tail" phenomenon, popularized by Chris Anderson and Nassim Taleb (his Extremistan). Even though the concept only went mainstream in the past decade, statisticians have studied it since the 1950s, even earlier.
The other important concept is "long-range dependence". This is the part about aftershocks, about how one big earthquake leaves the earth trembling long after. In elementary statistics, we make the assumption that the world operates according to a series of coin flips, that is to say, what happens next is a new coin flip (this is called "independence").
Later, students learn that some systems have memory, and then we assume that the present state of the world captures everything that has happened in the past (this is called the "Markov" property). Google's page rank algorithm is a famous application of this principle.
Neither of these assumptions prove useful when it comes to modeling financial markets. But this is not really new. Benoit Mandelbrot is usually given credit for recognizing this in the 1960s; see his "The (Mis)Behavior of Markets" for a gentle overview of his work. Another useful reference is Barabasi's "Linked". Nassim Taleb is its most recent, and vocal, evangelist.
These concepts have been actively studied by statisticians, most notably by those working in environmental statistics, the study of earthquakes, floods, etc., and also by actuaries in the catastrophe insurance sector. More recently, Internet systems are thought to exhibit similar behavior.
Speaking of Taleb, I find his quote in the NYT article intriguing. He said, "The physical world cannot surprise us massively. The financial world can." The reporter uses it in support of the emergence of econophysics. I interpret Taleb to be voicing caution about over-hyping this emerging field by pointing out the futility of thinking that human behavior can be fully characterized by physical equations.
What separates econophysics from earthquakes and floods is the human element. Volatility in the markets are hugely profitable for some people, and volatility in markets can be humanly induced (unlike earthquakes as far as we know). People's moods, greed, passions, fears, flakiness, irrationality are not to be contained by equations. This inherent "uncertainty" can be incorporated into a scientific model but the resulting forecasts will also be less certain, which does not lend itself to predicting future crises, let alone finding ways to prevent them.
A few months ago, I presented a summary of the materials about controlling traffic congestion on highways (in Chapter 1) to electrical engineers at Princeton. These engineers are experts in thinking about congestion in communications networks (like phone networks and the Internet), and they immediately recognized that highway congestion presents a whole new challenge. In the information highway, engineers can program the routers to send data packets here and there, and the packets will follow their instructions; on the highway highway, traffic engineers can "advise" drivers what to do but the drivers will do whatever they want.
So there you have it, some context for thinking about this new field. I hope they help break new ground.