Traders’ arbitrage activity made the pricing model appear empirically true

Evidence

That the Black-Scholes-Merton model had, in the CBOE’s early years, a tendency to price options lower than its competitors gave it a certain general selective advantage, so long as it did not expose those using it to undue risks (a topic to which we return below). Above all, though, the model could readily be adapted for a simple arbitrage (feasible even for individual market makers) that had been used since the CBOE’s foundation: spreading, looking for discrepancies in the prices of different classes of options on the same underlying stock, buying relatively underpriced options and selling overpriced ones (Galai 1977). The offsetting positions insulated the spreader from many forms of risk, without demanding that one hedge using stock. … A key aspect of what Rubinstein did was to check the empirical validity of a basic feature of the model: “that all options on the same underlying asset with the same time-to-expiration but with different striking prices should have the same implied volatility” (Rubinstein 1994, p. 772), in other words that the graph of implied volatility against strike price should be a flat line. When spreaders used Black-Scholes to identify discrepancies, it would be precisely deviations from that flat line that their activities tended to arbitrage away. The model was, therefore, helped to pass its central econometric test by the market activities of those who used it. — Donald MacKenzie & Yuval Millo, Constructing a Market, Performing Theory, 126

Categorization

• DEEPTHINKING: The reflexive loop — users performing the model make the model pass its own empirical test — is the heart of performativity theory, dense enough to sit with for days.
• XREF: Connects directly to MacKenzie’s performativity program and the ‘Barnesian performativity’ concept, as well as to Callon’s work framing economics as performing the economy. — connects to: Arbitrageurs’ price gaps drove stock buying, not panic or sentiment — Donald MacKenzie, An Engine, Not a Camera: How Financial…, 838; Other traders imitated LTCM’s successful arbitrage models and strategy — Donald MacKenzie, An Engine, Not a Camera: How Financial…, 155; Relative price confirmations depend on arbitrageur positioning, not just quality flight. — Donald MacKenzie, An Engine, Not a Camera: How Financial…, 1083 (+20 more)
• SEED: An essay angle: econometric tests of financial models may measure not reality but the degree to which market participants have internalized the model.

Related

• Traders using the pricing model actively made market prices conform to the model (similarity 0.93)
• Econometric model tests can be passed because traders’ arbitrage removes model deviations. (similarity 0.92)
• Traders arbitraging model discrepancies directly improved the model’s econometric test results (similarity 0.91)
• Traders used the model’s own arbitrage logic to profit in the market. (similarity 0.89)
• The model’s use helped create the price patterns the model predicted (similarity 0.86)
• Arbitrage is the chief channel achieving Barnesian performativity in finance (similarity 0.86)
• Market conditions moved toward the model’s assumptions partly because of the model itself (similarity 0.85)
• Option pricing theory did not describe markets but remade them in its own image (similarity 0.84)
• Constrained arbitrage allows finance-theory models to diverge from actual prices. (similarity 0.84)
• Option market prices initially diverged from the Black-Scholes model but converged (similarity 0.82)
• The model’s assumptions became more realistic as markets restructured around it (similarity 0.82)
• Barnesian performativity means models create the price patterns they describe (similarity 0.81)
• Modern options pricing derives from arbitrage logic, not directional beliefs. (similarity 0.81)
• The market changed to fit Black-Scholes rather than the reverse (similarity 0.81)
• Option prices are set entirely by arbitrage, independent of risk attitudes or probabilities (similarity 0.81)

Broader Connections

• Traders arbitraging model discrepancies directly improved the model’s econometric test results #corroborates (0.95) — Donald MacKenzie, An Engine, Not a Camera, 146
• Arbitrageurs’ price gaps drove stock buying, not panic or sentiment #expands (0.85) — Donald MacKenzie, An Engine, Not a Camera, 838
• Financial pricing formulas actively construct the markets they purport to measure #expands (0.85) — Max Haiven, Cultures of Financialization, 84
• Relative price confirmations depend on arbitrageur positioning, not just quality flight. #corroborates (0.80) — Donald MacKenzie, An Engine, Not a Camera, 1083
• Other traders imitated LTCM’s successful arbitrage models and strategy #corroborates (0.75) — Donald MacKenzie, An Engine, Not a Camera, 155