How is economic sociology different from behavioral finance?

In the past ten years, and especially in the wake of last year’s credit crisis, the field of behavioral finance has seen an extraordinary rise in influence. Academically, this is clear in the success of the work of Robert Shiller. On the policy front, the rise of Austan Goolsbee at the White House’s, and the administration’s proposal proposal to create a Consumer Financial Protection Agency

So the economists have accepted that “the social” matters. But now that they have rediscovered sociology, it is up to sociologists to explain how does their discipline differs. I experience this myself every week. Whenever I am introduced to finance colleagues at the LSE in the Senior Dining Room, they all respond to my statement that “I’m a sociologist of finance” with the well-intentioned remark, “ah, yes, behavioral finance — very topical.” And thus, on to a peaceful lunch.

But their reaction is not just a trip of the tongue. In drawing the lines around behavioral finance, Shiller claims sociology without bothering to read it. Shiller (2003: 83) writes,

Behavioral finance -that is, finance from a broader social science perspective including psychology and sociology-is now one of the most vital research pro- grams, and it stands in sharp contradiction to much of efficient markets theory.

But, surprise, when one turns to the article’s bibliography, there is not a single sociologist there. No Merton , not even Granovetter.

Thin sociality

Sociologists, it is clear, need to make clear where do they stand. My position is clear, and it comes from my ethnographic research. In my latest piece with David Stark, we examine an limited instance of financial crisis — an “arbitrage disaster” — and consider whether it matches what behavioralists argue. Our conclusion is that it does not. What behavioral finance offers is a thin view of sociality in which there are no material artifacts and no distributed cognition. A world, in other words, of fools with tools.

Behavioral accounts of systemic risk center on two versions. The social accounts blame systemic risk on herding and information cascades: if an investor makes the wrong decisions and others imitate her, the risk spreads out. The alternative account, Black Swans, centers on technical problems such as the use of financial models. If models are built on past occurrences, infrequent but disastrous events will not be sufficiently taken into account.

Fools with tools

Both behavioral approaches are unsatisfying. Straight imitation, as the concept of herding contends, is simply impossible in modern markets — they’re anonymous. And even if it weren’t, it is unlikely that the brainy eggheads that trade derivatives would do it. It goes back to the dilemma of cheating in school. The kid right next to you might have answered (a) where you wrote (b)… but if you decide to go with his answer, how do you know he’s right? The traders we know are professionals, not school kids. They pride themselves on arriving at their own conclusions. So one cannot blame systemic risk on social factors alone without understanding the technological context.

Take the Black Swan now. How irresponsible does a trader need to be to just follow the model blindly? Sure, we all make some critical decision simply on the basis of what the machine says. We use planes, gadgets, have medical treatments… without fully knowing what the consequences will be. There’s a measure of doubt in a high-tech society. But as users, we still know is that others have done so as well, are doing so now, and nobody seems to have problems. I would argue that professionals are even more careful. The bottom line is that one cannot blame technology without accounting for the social context in which it is used.

If you bother to check what actually goes on in a trading room…

Empirically, neither herding nor the Black Swan explains what we saw. I will not go into detail here. It’s in the paper. But this is how we summarize what we observe:

Our ethnographic observations in the derivatives trading room of a major investment bank demonstrate that systemic risk arises from the precautionary efforts of traders. Traders check for errors in their own calculations by using models in reverse that represent the positions of their anonymous and impersonal rivals. We thus find traders modeling social cues. Such reflexive use of models leverages the dissonance among rival traders, but in the absence of requisite diversity such dissonance turns to resonance. If enough traders overlook a key issue, their mistake will reverberate to others. The resulting cognitive lock-in leads to arbitrage disasters. The trading room we observed suffered one major such disaster. Our analysis challenges behavioral accounts of systemic risk by locating its roots in the socio-technical mechanisms of reflexivity rather than individual biases.

A sociological approach

How, then, is behavior social in markets? In my own sociological account, technology and the organization of work combine to create rich and durable sociality. Traders use co-located teams and equations because they make them smarter, not foolish. This needs to be recognized. By the same token, this does not mean that problems do not exist. Understanding “the social” in markets requires that we look at technology and social cues as a whole, not as forces that act independently to make us dumb.