Wall Street Clowns and Their Models

Recently I cited an Economist article in Economist on the Peril of Models. While walking through the airport this Businessweek cover story, Not So Smart, caught my eye. I found the following excerpts to be interesting.

The titans of home loans announced they had perfected software that could spit out interest rates and fee structures for even the least reliable of borrowers. The algorithms, they claimed, couldn't fail...

It was the assumptions and guidelines that lenders used in deploying the technology that frequently led to trouble, notes industry veteran Jones. "It's garbage in, garbage out," he says. Mortgage companies argued their algorithms provided near-perfect precision. "We have a wealth of information we didn't have before," Joe Anderson, then a senior Countrywide executive, said in a 2005 interview with BusinessWeek. "We understand the data and can price that risk."

But in fact, says Jones, "there wasn't enough historical performance" related to exotic adjustable-rate loans to allow for reasonable predictions. Lenders "are seeing the results of not having that info now..."

At this point in probably sounds like I am seriously anti-model. That isn't really the case. The points I cited from Businessweek involve inserting arbitrary values into models. Non-arbitrary data is based on some reality, such as "historical performance" for an appropriate past period, looking forward into an appropriate future period.

Incidentally, one of the articles I read cited the Intangible Asset Finance Society, which is "dedicated to capturing maximum value from intellectual properties and other intangible assets such as quality, safety, security; and brand equity." That sounds like something to review.