When I was a boy, a “Butter and Egg” man lived down the street in our suburban village outside Chicago. Our fathers called him that, even though the exchange on which he traded commodity futures had, in his grandfather’s day (in 1919), renamed itself the Chicago Mercantile Exchange. His family was not conspicuously well-to-do, even though the exchange’s business had grown by then to include onions and pork bellies. A handful of traders who earned their livings trading grain on the better-established Board of Trade lived in the more prosperous town to the west.
But by the time the Butter and Egg man’s son followed him into the business, the Merc was booming, trading a bewildering array of futures and options. Instead of taking the streetcar or the train to work, the son flew his helicopter from his hobby farm in northwest Illinois. And, for all I know, he was on the floor the day when the austere and fastidious applied mathematician Fischer Black made an appearance, and cigar-chomping traders broke into prolonged applause.
I have been reading An Engine, Not a Camera: How Financial Models Shape Markets, by Donald McKenzie — the third of three books to appear in the last year about attempts to understand asset prices. In each of them, Fischer Black plays a central role. In William Poundstone’s book about Claude Shannon, Edward Thorp and John L. Kelly, Jr., Black is the inventor who, off-stage, scoops up the marbles with his options pricing formula. Perry Mehrling’s biography of Black (the subject of last week’s Principals) is a searching portrait of the man himself. MacKenzie’s book does the best job by far of putting developments in perspective, but you have to wade through a great deal of philosophizing to get the picture.
MacKenzie’s title derives from a famous phrase of Milton Friedman’s — economic theory as an engine intended to analyze the world, not a camera expected to faithfully reproduce its fine-grained facts. But MacKenzie has subtly altered the meaning of the phrase, in order to tell the story of the rise of financial economics in the 1960s and ’70s. The engine, he says, has begun actively transforming the environment. Its analysis has become operational.
This is familiar territory to readers of Peter Bernstein’s 1992 chronicle of the development of financial theory, Capital Ideas: The Improbable Origins of Modern Wall Street. That famous first draft of history stands up very well indeed. MacKenzie emphasizes the debt that he and all future historians of financial markets will owe to Bernstein, a successful money manager who sought to convey the vast changes taking place around him. Still, we are nearly fifteen years on from that volume. What’s become clear that wasn’t clear then? What has been settled? What is still up in the air?
For MacKenzie, a professor of sociology at the University of Edinburgh, a good deal remains unsettled. A longstanding interest in patterns of technological development has convinced him that technology is far from being governed strictly by its internal logic. In Inventing Accuracy: A Historical Sociology of Nuclear Missile Guidance (1990), he traced the political and military pressures that gave rise to a series of weapons systems thought to be capable of ever-increasing precision. In Mechanizing Proof: Computing, Risk, and Trust (2001), he delineated two ideals of proof — the classical version of the geometers and mathematicians, and the new statistical variety of those who predict the behavior of elaborate computer-basted technologies, such as power grids, weapon systems and the global banking regime.
In An Engine, Not a Camera, McKenzie is interested in something he calls “performativity.” Instead of simply saying that at a certain point, theory begins to inform practice, performativity occurs when the practical adoption of an aspect of economics makes economic processes more like their depiction by economists. There is, of course, a heavy measure of politics in this. His “generic” performativity (when market participants themselves already talk that way) may be my “effective” performativity (when a model facilitates transactions that wouldn’t otherwise occur) and your “Barnesian” variety (a fancy term for “self-fulfilling prophecy”). But life is short. Never mind. To a dedicated reader, the philosophizing is no worse than a heavy accent.
There are wonderful stories here of how the new analytical, mathematical financial economics emerged, battled with older descriptive traditions whose natural homes were in business schools and government departments and, eventually, triumphed. David Durand is here, a professor of industrial management at the Massachusetts Institute of Technology who fought a gallant but unsuccessful rear-guard action against the new ideas. So is Benoit Mandelbrot, the polymath for whom wild variability (as opposed to mild variability) is a still a central part of the story.
But mainly there are clear, coherent and detailed accounts of the major developments. How business school dean Lee Bach’s ambition to turn Carnegie Tech (Carnegie Mellon University today) into a redoubt of science-based professionalism unleashed upon an unsuspecting world the Modigliani-Miller theorem (that in a perfect market there would it would make little difference whether a corporation financed its dealings by equity or debt, since its cost of capital would be unaffected ultimately by the mix) and the rational-expectations hypothesis. How the University of Chicago in turn contributed portfolio theory, the Capital Asset Pricing model and the efficient-market hypothesis to the new movement.
How at MIT Fischer Black, Myron Scholes, Paul Samuelson and Robert Merton competed among themselves and ultimately cooperated together to solve the fundamental problem of option pricing — and of the volatility skew or discrepancy between market prices and the Black-Scholes expectation of them that has emerged since the 1987 market break. How Butter and Egg man Leo Melamed, a refugee from Poland, assembled the necessary academic testimonials and regulatory permissions to get the Chicago Exchanges running in their new lines of business, refusing all offers of compensation from the fellow traders (whom he was making rich) until the 1987 crash finally forced him to accept a salary. (That’s counter-performativity in MacKenzie’s book!).
MacKenzie is especially good on the tension between theorists and practitioners as the new developments occur. Traders are ambivalent and frequently hostile. Options trader William R. Power explains the system of “godfathers” he discovers after he moves to Chicago. “This [Chicago] is a place where people think in very simple terms of people and markets. Black. White. Good. Bad. There’s an invisible sheet with an invisible line down the middle of it. This is a good guy. This is not a good guy. Nobody’s on that line. They’re either a god guy or a bad guy. Very long memories.”
So how did Fischer Black become a good guy in Chicago? There are no photographs in MacKenzie’s book — a pity, but it’s not that kind of book. As it to prove that a picture really is worth a thousand words, though, there is a reproduction of a page of the tip sheets that Black compiled and sold to traders during the short interval before his options- pricing formula was programmed into hand-held calculators. The Black Option Service cost $300 a month for sheets with three volatility estimates for each of 100 stocks traded on US options exchanges — or $15 a month if you just followed just one stock. Cumbersome, to be sure — but those columns and columns of numbers turned out to be a nearly sure-fire guide to bargains.
“Chicago floor traders in general were not and are not in awe of professors,” writes MacKenzie. And the math was definitely hard, at least until the micro-proceesor came along. But the basic model could be talked about and thought about relatively straightforwardly. “Sell the 280s and drive a Mercedes” became the motto of one small band of traders who had discovered a high strike price ($280) on heavily traded calls on IBM, one interview subject told him.
And that, as much as anything else, explains to my satisfaction how it is that the sons of my long-ago neighbor, the Butter and Egg man, succeeded so well in the world that Black and the other finance professors made for them. For what distinguished those boys, aside from their access to a family fund of background knowledge and a network of friendships, was a robust physicality bordering on fearlessness. They weren’t athletes (though perhaps they were good with their fists).They were simply well-prepared for the rough and tumble of standing in the pits, jostling for position, shouting to be heard, skills useful, too, it turned out, for flying helicopters. And if the first thing they now needed to know when they walked into a pit was no longer, “Would the company meet its earnings targets?,” but rather, “What’s the skew like?,” well, then, they could learn that too.
On how and what they learned — if you are interested — Donald MacKenzie sheds much light.