The Failure of Risk Management, 2nd Edition

CHAPTER 10Where Even the Quants Go Wrong: Common and Fundamental Errors in Quantitative Models

There is perhaps no beguilement more insidious and dangerous than an elaborate and elegant mathematical process built upon unfortified premises.

—THOMAS C. CHAMBERLAIN, GEOLOGIST (1899)

In theory there is no difference between theory and practice. In practice, there is.

—YOGI BERRA

When it comes to improving risk management, I admit to being a bit biased in favor of quantitative methods in the assessment, mitigation, or deliberate selection of risks for the right opportunities. I think the solution to fixing many of the problems we've identified in risk management will be found in the use of more quantitative methods—but with one important caveat. In everything I've written so far, I've promoted the idea that risk management methods should be subjected to scientifically sound testing methods. Of course, we should hold even the most quantitative models to that same rigor. They get no special treatment because they simply seem more mathematical or were once developed and used by highly regarded scientists. Even though in the previous chapter I criticize a lot of what Nassim Taleb says, this is where we are in total agreement.

The idea that the mere use of very sophisticated-looking mathematical models must automatically be better has been called crackpot rigor (recall the discussion of this term in chapter 8) and a risk manager should always be on guard against that. Unfortunately, ...