Engine, Camera

There are two ways to approach MacKenzie’s book. One is to play well with others, get in the spirit of the seminar, and tackle the thorny questions of performativity, the application of the social studies of science to finance, and the relationship between economics and sociology. The second way is to approach the problem in a slightly more Howard Becker-ish fashion, investigating the organization of derivatives trading. This second way, perhaps unfairly, sidesteps the theoretical problems raised in MacKenzie even as it gets us closer to what is really going on in the world. Positive versus normative, indeed. Let me take the first way first.

Performativity works well in the study of scientists. Latour and Woolgar’s (1979) analysis of the creation of facts in labs stands as compelling evidence that what purports to be ‘discovered’ by scientists is more accurately understood as being discovered, polished, standardized, conventionalized, and disseminated by a science community. Ted Porter’s (1995: 13) brief recounting of the dissemination of the cyclotron – Lawrence noted that “it would be foolhardy to attempt to build a cyclotron without sending someone to work with one is his Berkeley laboratory. ‘It is rather ticklish in operation’, he explained…'” – gives the flavor of how theories make the world make the theories make the world.

And the world of finance seems ripe for analysis, with Milton Friedman justifying the creation of the IMM: “Melamed asked ‘if I [Friedman] would be willing to write a little paper for them on the case” for a currency futures exchange. Friedman replied ‘”I’m a capitalist first,” and I [Melamed] said “How much?” I immediately knew what he meant and he liked that. He liked that. He said “$5000.” I said, “It’s done.” Just like that'” [157]. Financial economists were early and continual participants in the markets they modeled, and the dis-entanglements they produced seem an awful lot like the scientists at the bench. Non-economist practitioners? Economists-in-the-wild, argues Callon.

Note at the outset that this is not at all a perfect analogy. People are not proteins, and the participation of economists in markets is not the same as biologists and molecules. I haven’t thought this through enough, and cases come to mind that disrupt my narrative (like pure, created strains of anthrax or something), but hard science types create a parallel world that looks like their theories – by creating purified elements, collaboratively calibrating machinery, and the like – that they then use to describe the world. This seems somehow qualitatively different from economists and financial markets. You can change regulation around financial markets to make them look more like theories (e.g., eliminating rules that distinguish banking and insurance, or shifting tax liabilities for derivatives) in a way that you can’t in the biological sciences. You don’t release more nitrogen into the atmosphere so that it looks more like your lab samples.

Note also that markets (and fairly complex ones, per Swedberg [1995]) pre-date economics, and by a lot. So what we’re talking about is a specific historical moment, what MacKenzie calls ‘high modernity’ – this is not necessarily a generalizable model. But this again is a bit slippery. I once suggested to Callon that he was romanced by the strawberry market, and he replied to the effect that they’re all strawberry markets. But lets take this case, this moment.

MacKenzie’s biggest strength is to take self-fulfilling prophesy, transform it into more social-construction terms, and then to show how it worked with respect to arbitrage, spreads, options, and derivatives. The story line that Black-Scholes originally differed pretty dramatically from the prices of options in the real world, then was used to actively trade these options, which then brought the prices into line with the theory, is the most straightforwardly-compelling story in the book. Period. That prices after 1987 incorporated the skew (the collectively Post-Traumatic Stress Disorder of the 1987 crash, really) doesn’t change the argument, and actually makes it more convincing. See sociologists? Social construction that changes the world, but tempered by reality! And since we’ve secretly suspected that economists push people to act like homo economicus makes it even more compelling.

But, as Kieran and others note, the further from the trading floor, the more ambiguous this story becomes. Porter, and later Espeland, argue that cost-benefit analysis has had a similar performative effect; except in those instances the points at which reality didn’t conform to the models, reality didn’t shift towards the models but was rather re-measured, re-cast, re-constituted. Tubing down the river wasn’t able to be modeled and added to the cost-benefit ratio for the Orme Dam, and so it was not included in consideration. Did reality shift to conform to the model? No, but yes. Inner tube recreators still recreated, but they became invisible to the decision-makers. Even in the field of economics, feminist economists have for years pointed to the stupid assumptions behind homo economicus in contrast to the completely altruistic family. Women must have a taste for subordination and child-rearing! Performativity!

MacKenzie does think through these kinds of cases, in showing the monsters and anomalies faced by the EMH modelers. You do kind of feel for Mandelbrot – if he were an ethnographer who somehow found the same stuff, rather than a hard-science / math / physics guy, he’d have been weighed, measured, and found wanting years ago. As it is, he remains more ‘iconoclastic’ than anything. But the problem I am trying to identify is still not captured by the theoretical concept of performativity. I want to keep calling it visible/invisible reality, but I don’t quite have the language I need yet.

This leads me to a second way to approach the finance/sociology split. Not by studying what financial economists say they do, but by studying people on trading floors. What I do want, though, is more about these monsters. I studied traders who know precisely not a single thing about Black-Sholes, and made fortunes trading ‘what’s in front of them’ and by standing in front of their brothers-in-law getting fed easy, winning, lucrative trades.

For instance, I can’t seem to get Partnoy out of my head:

“I will do you the favor of omitting many of the complex topics you might find in a derivatives treatise, topics bearing frightening names such as modified duration, option adjusted spread, put-call parity, bond basis, and negative convexity. My advice, even to investment bankers reading this book, is don’t spend even one minute thinking about these concepts. They will not make you any money – ever…Of course, if you can use knowledge of complex derivatives mathematics as a smoke screen to hide important facts from your clients, fine. But if you actually want to acquire knowledge that has no monetary value, forget it. You’re in the wrong business. Later, I’ll educate you as to how Wall Street has made, and continues to make, huge amounts of money on derivatives by trickery and deceit” (1997: 30).

Trickery? Deceit? Brothers-in-law? Where are the models? What about the ‘taking advantage of inefficiencies’? That financial models shape markets is possible, and plausible, but accounts for a small – quite probably growing – fraction of the gajillion-dollars of profits pulled in by Wall Street. The point is that MacKenzie seems to discount the possibility that his respondents’ accounts (‘testimony’, he says on p. 104) may be a bit self-delusional. For instance, (totally unsubstantiated) rumors circulated for years that some members of the leadership of some of the Chicago exchanges would get, and trade on, economic numbers before they were released. If these models discipline traders, traders routinely discipline the models right back, through means both legal and otherwise.

This is especially true for LTCM. MacKenzie dismisses Lowenstein’s hypothesis that LTCM was done in by greed/gambling and blind faith in models, but somehow misses Lowenstein’s most convincing argument: when some firms, most notably Goldman Sachs under the watchful eye of now-governor John Corzine, had the opportunity to completely fuck over LTCM in the midst of the crisis, they sure did it. Lowenstein reports rumors that GS was frankly downloading LTCM positions into their laptops and actively trading against them.

In fact, what strikes me in MacKenzie, as it does in Callon, is not the extent to which real-world markets almost conform to financial economists’ models, but the opposite – the extent to which, barring the constant vigilance of arbitragers, market threaten constantly to spill out all over the place. I get the impression of arbitragers not so much herders of errant sheep as constantly shoveling shit against the tide. And, if DeLong is right, the ultimately limited resources of these keepers of market order make their jobs ultimately impossible.

I think MacKenzie is wrong precisely where Kieran thinks he’s right. If BSM produced a model that was off by a factor of 2, and the collective resources of the US, EU, and Asian governments acted on it with persistence, why wouldn’t it produce a market that looked that way? Discovery about the real world or not, enough leverage and money, and you can make even huge markets move the way you want them to.

In the end, the book is excellent, the kind of careful ethnography and intellectual craft that is enviable, more so given that the underlying reality is not schools or a shop-floor, where we know already how things work. This stuff is pretty esoteric, and complicated to explain and understand. And MacKenzie gets his empirics right. It’s the concept that I can’t seem to get behind. The project of financial economics is to provide positive, tractable, predictive models, and to normatively get markets to act more efficiently in order to ostensibly provide the best possible distribution of societal resources at the lowest cost. I think the project sociologists might be interested in is more trying to understand how that works, and less about trying to understand how well that works.

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