Models don’t kill people – greed and laziness do

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Now that the major central banks have bought some time for the credit markets, teams are surveying the damage from the summer, pausing in their walks across the battlefield to shoot a wounded hedge fund and rifle its pockets for collateral.

Back in the staff tents, managements are attempting to identify the errors that led to huge losses – so long, that is, as the errors were not theirs.

One of the questions they ask, along with politicians and the media, is whether the “models” were to blame for everything. Mathematical models of financial instruments have become the new witchcraft for people looking for someone, or something, to blame for their own inattention and greed.

Even if the National Rifle Association says it, it is still true: guns don’t kill people; people kill people. And financial models do not destroy value; for that, blame greed, laziness and stupidity on the part of the people who put the wrong data or parameters in their financial analytics.

Drive a car without brakes and, guess what, you are going to get into an accident. Allow a trader to put on positions, using a self-serving pricing model that does not match what the back office or the risk managers have, and you will also have an accident. Or, rather, a predictable disaster.

There are some fundamental limits on the probabilistic models used to value securities, and derivative securities in particular. The models assume liquid, continuous markets. Illiquidity, or systemic freezes during which market participants cannot get bids for securities (or offers, for those in a short squeeze), would appear to be hard to model. And yet illiquidity happens.

That was not, however, a secret before the summer crunch. And even with the known limits to existing probabilistic models, there was a lot that could have been done that was not done by the buy and sell sides in the credit markets.

Back in July, I had an interesting conversation with the people at Numerix, a leading provider of pricing and risk analytics in New York. Numerix is active in the forex, equities, inflation derivatives and hybrid markets. But it is particularly dominant in producing the key software for valuation and risk modelling in the credit markets. I had wondered what use the Federal Reserve and other regulators had made of their software in monitoring what was then a developing crisis.

The answer: none. The Fed does not subscribe to the service. It still does not, by the way. And it wonders why it did not see the crunch coming.

I went back to Numerix to get its after-action report. Steve O’Hanlon, president, told me: “In my opinion [credit market people] did two things wrong. One, if you are going to manage positions in hard-to-value securities, you have to do it consistently across trading, operations and risk management. They weren’t doing that. Two, they were making stupid bets because of lazy greed.”

The second problem is a universal and permanent aspect of human nature, which can only be countered with self-control and a strong institutional culture of honesty and risk recognition. The first one is more technical and can actually be fixed.

For example, as Mr O’Hanlon points out: “Traders like to use Excel-based models, because Excel is so flexible. But from an operations point of view, Excel is the worst, because it is so free-form. For operations, you want to lock everything down.” That way, accounting and management can be consistent.

“For risk control, you want to use the same model configuration from one day to the next, so when you do profit and loss, and mark to market, you don’t get drift because [the traders] are setting up their models differently every day.”

If the trading models are not integrated with the risk models, you can be certain the traders will game the risk management models to do things they should not. They will do that either for the desks’ P&L (and their bonuses) or for favoured customers.

To my surprise, Numerix had lost only one customer firm to the market mayhem. “The partners will be back. They learnt their lesson. I’m not as sure about whether their IT guy will be back.” Apparently, he hadn’t done that whole integrate-the-trading-model- with-the-risk-management-model thing.

Over the next several weeks, we are going to have entertaining public excoriations of the ratings agencies and other Wall Street institutions. The ratings agencies have proved they do not deserve their monopoly privileges. And if any industry deserves to be downsized, it is Wall Street. There have been too many incompetents and people consumed by that “lazy greed”.

It will not, however, be possible to go back to the old system of banks and insurers directly allocating credit through committee systems. And, yes, analytics need to be tweaked and their parameters examined more carefully by the designers and users.

A bigger issue, though, is the defective culture of many of the firms using them. The main problem in the recent crisis was not the complexity of credit analytics, but the intentional obscuring of who benefited from the mispricings of risk.

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