Interviewer: "Have you ever thought your ideas may by wrong?"
Maldacena: "Yeah, this is possible; however the mathematical structure is probably going to be useful for whatever theory is the correct theory. And, what we do … at least is generate good interesting mathematics that is useful for other things in physics, and I think if it’s not string theory, it will be probably something similar to it."
And so it is with modern finance, which fully expects the yet unknown risk solution to be built out of the mathematical edifice already created, because the elegance and power of what has been created seems not just capable, but necessary to be any reasonable solution. The stochastic discount factor approach encapsulating CAPM is surely not a coincidence to these researchers. As Mark Rubinstein states about the Capital Asset Pricing Model (aka CAPM Betas):
More empirical effort may have been put into testing the CAPM equation than any other result in finance. The results are quite mixed and in many ways discouraging…At bottom…the central message of the CAPM is this: the prices of securities should be higher (or lower) to the extent their payoffs are slanted towards states in which aggregate wealth is low (or high)…The true pricing equation may not take the exact form of the CAPM, but the enduring belief of many financial economists is that, whatever form it takes, it will at least embody this principle.
The problem is, as the data have become clearer, the theory has become less clear. This is not a sign of a successful theory. Risk started out as merely nondiversifiable volatility, and now assets with really high nondiversifiable volatility presumably have low risk via some spooky risk factor, and behavioral biases are applied piecemeal to various anomalies (anchoring, preferring positive skew, or negative skew).