There’s an even more basic problem with blaming fancy mathematical models for today’s mess:
we’ve had booms and crashes for as long as markets have existed. 9 You can point a finger at
computers, CNBC, the Black-Scholes options pricing model, securitization, credit default swaps,
or any other innovation or technology as the source of the problems today. But the same pattern
has unfolded time after time before any of these alleged culprits existed.
The models and technology were accessories to the crime, not the perpetrators. The common
denominator in financial crises through time is human nature. Specific aspects include the role of
incentives and how they shape behavior, how people interact and influence one another, and that
humans are capable of creating systems they do not understand. If regulation is to succeed, it
has to address these fundamental issues.
Still, we cannot let the quants and their models off the hook totally. One persistent challenge is
the problem of induction, or generalizing about the future given a limited sample of the past. This
is a major issue in quantitative finance because historical data do not always reveal a system’s
riskiness and the statistical properties of markets change over time. Quantitative modelers are
well aware of these problems, but when a model yields good profits for a time the quants have a
tendency to let their guard down.