The Smartness Mandate by Orit Halpern;Robert Mitchell;

Author:Orit Halpern;Robert Mitchell;
Language: eng
Format: epub
Tags: Neoliberalism; Smart technologies; Smart cities; Artificial intelligence; Machine learning
Publisher: MIT Press

3.1    Black-Scholes model summation. Source: “Black-Scholes-Merton,” Brilliant.org, https://brilliant.org/wiki/black-scholes-merton/.

While Black and Scholes’s quite technical and seemingly narrow approach meant that they initially encountered problems in finding a publisher for their article, once the piece was published, multiple groups began offering software for such pricing equations.12 This was not least because Black and Scholes’s premises allowed buyers and sellers of options to come to relatively easy agreement on option prices. While it had been difficult to settle on option prices if one assumed that sellers and buyers of options had to agree on the objective health of the company, the only unknown variable of the Black-Scholes option pricing model was the future volatility of the stock, and Black’s volatility charts allowed sellers and buyers to find common ground here. The success of Black and Scholes’s equation was also in large part a consequence of the fact that the model joined communications and information theories with calculation in a way that made their equation amenable to algorithmic enactment.

As individuals created more complex derivative instruments that tied together many types of assets and markets, computers became essential both for obtaining data about price volatility and for calculating option prices. An entire industry, and the financial markets of today, were born from this innovation and its new understanding of noise. And because derivatives are bets on the future value of an asset, the derivatives markets can be—and in fact are—far larger than the world’s current gross domestic product (GDP). (The amount of money at play in the derivatives market currently exceeds the world’s GDP by 20 times.) Since the 1970s, these markets have grown massively (e.g., 25 percent per year over the last 25 years). In this sense, the derivative pricing equation is indicative of the emergence of a broader new epistemology that transformed conceptions of agency, the agent, and decision-making in the postwar period.

If the Black-Scholes model implied a new model of how to value options on stocks, it also implied a new model of the economic agent. Black and Scholes had begun working together in the late 1960s while consulting for investment firms. Their work involved applying computers to modern portfolio theory and automating arbitrage.13 Scholes and Black began “The Pricing of Options and Corporate Liabilities,” the article in which they introduced their option pricing equation, with a challenge: “If options are correctly priced in the market, it should not be possible to make sure profits by creating portfolios of long and short positions.” They reasoned that since people do make money, options therefore cannot be “correctly” priced, at least in the traditional sense that the option price is a function of an underlying objective value of the stock. Mispricing—that is, the imperfect transmission of information—must be essential to the operation of markets. Noise is the only source of arbitrage.

“Rational” investing in options thus did not mean attempting to determine the true value of the underlying asset. Because the market is full of noise—the market exists, in fact, only because of noise—the economic agents

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