I had a post recently, the link I'll add here soon, in which I protest the emphasis on math and science education in our schools, because, I believe, that is not where things are breaking.
For example, I really don't believe that if every Senator had more math and science, or even, say, twin PhDs in math and science, that they would be any better at reaching consensus than Oxford University professors are at deciding what e-mail system to purchase.
The reason is that all this "math" and "science" takes place in a social context that can magnify or neutralize or reverse essentially anything.
The following piece from today's New York Times makes it clear that having computers and "quants" doesn't really solve much. As I continue to repeat T. S. Eliot, they continue "dreaming of systems so perfect that no one needs to be good." It won't ever happen.
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September 18, 2008, 7:52 am — Updated: 5:00 pm -->
How Wall Street Lied to Its Computers
By Saul Hansell
CORRECTED 5 p.m.: Spelling of Leslie Rahl.
So where were the quants?
That’s what has been running through my head as I watch some of the oldest and seemingly best-run firms on Wall Street implode because of what turned out to be really bad bets on mortgage securities.
... I got to know bunch of quantitative analysts (”quants”): mathematicians, computer scientists and economists who were working on Wall Street to develop the art and science of risk management.
They were developing systems that would comb through all of a firm’s positions, analyze everything that might go wrong and estimate how much it might lose on a really bad day.
We’ve had some bad days lately, and it turns out Bear Stearns, Lehman Brothers and maybe some others bet far too much. Their quants didn’t save them.
I called some old timers in the risk-management world to see what went wrong.
I fully expected them to tell me that the problem was that the alarms were blaring and red lights were flashing on the risk machines and greedy Wall Street bosses ignored the warnings to keep the profits flowing.
Ultimately, the people who ran the firms must take responsibility, but it wasn’t quite that simple.
In fact, most Wall Street computer models radically underestimated the risk of the complex mortgage securities, they said. That is partly because the level of financial distress is “the equivalent of the 100-year flood,” ...
But she and others say there is more to it: The people who ran the financial firms chose to program their risk-management systems with overly optimistic assumptions and to feed them oversimplified data. This kept them from sounding the alarm early enough.
Top bankers couldn’t simply ignore the computer models, because after the last round of big financial losses, regulators now require them to monitor their risk positions. Indeed, if the models say a firm’s risk has increased, the firm must either reduce its bets or set aside more capital as a cushion in case things go wrong.
.... Wall Street executives had lots of incentives to make sure their risk systems didn’t see much risk.
“There was a willful designing of the systems to measure the risks in a certain way that would not necessarily pick up all the right risks,” said Gregg Berman...
...
But since the markets were placid for several years (as mortgage bankers busily lent money to anyone with a pulse), the computers were slow to say that risk had increased as defaults started to rise.
It was like a weather forecaster in Houston last weekend talking about the onset of Hurricane Ike by giving the average wind speed for the previous month.
But many on Wall Street did even worse, as Mr. Berman describes it. They continued to trade very complex securities concocted by their most creative bankers even though their risk management systems weren’t able to understand the details of what they owned.
...
So some trading desks took the most arcane security, made of slices of mortgages, and entered it into the computer if it were a simple bond with a set interest rate and duration. This seemed only like a tiny bit of corner-cutting because the credit-rating agencies declared that some of these securities were triple-A. (20/20 hindsight: not!) But once the mortgage market started to deteriorate, the computers were not able to identify all the parts of the portfolio that might be hurt.
Lying to your risk-management computer is like lying to your doctor. You just aren’t going to get the help you really need.
They would have gotten things right if only they were fed the most accurate information. Ms. Rahl said that it was now clear that the computers needed to assume extra risk in owning a newfangled security that had never been seen before.
“New products, by definition, carry more risk,” she said. The models should penalize investments that are complex, hard to understand and infrequently traded, she said. They didn’t.
“One of the things that has caused great pain is complex products,” Ms. Rahl said.
....And, ultimately, the most important risk-management systems are the ones that have gray hair. “It’s not just the Ph.D.’s who must run risk management,” Ms. Rahl said. “It is the people who know the markets and have lifelong perspective.” And at too many firms it is those people who failed to make sure the quants really did their jobs.
(c) 2008 the New York Times Company
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