May 31, 2010

RISKING OTHER PEOPLE'S MONEY USING OTHER PEOPLE'S FORMULAE TO PAD YOUR OWN WALLET:

BREAKING THE CYCLE: A Conversation with Emanuel Derman (Edge, 5.27.10)

Eventually Wall Street came knocking at the door, as a result I believe of rising interest rates in the late '70s. Wall Street suddenly started having a lot more trouble managing their inventory when interest rates became a risky business. They were hiring more and more computer people and applied mathematicians, physicists. I took a job at Goldman Sachs in late 1985. I wasn't quite the first of the people who went from physics to finance or the first of the quants, but I was among the early group. It was very exciting because Goldman was small in those days, maybe 5,000 people. A few years earlier it had probably only been 2,000 people. So you got to know everybody and see them in the cafeteria and it was intimate in a good way.

There was a very close linkage between people who were doing technical work and people who were trading or doing sales. There weren't a lot of barriers to dealing with different people. It was a place that valued you if you had a skill, no matter what it was, if you were a good lawyer or if you were a good computer programmer. They might treat you as a geek if you were more of a scientist than a businessman or an MBA or a lawyer. Nevertheless they needed what you had and they respected it. So I really enjoyed working there. For me it was a shot in the arm after being at Bell Labs and having felt like I had quit physics. I suddenly got excited again about doing something new.

In terms of how physics figured into Wall Street at that point, I was among the first physicists there. I don't know if I was literally the first, but I was certainly among the first few, although there had been three of four engineering people in the group I was in who had been there a few years longer.

It was kind of a natural match for physicists because first of all options and interest rates were becoming big in terms of sales and marketing and hence valuation and hedging were necessary. Most of the models that had been developed in the financial world for treating the risk of bonds or the risk of options or valuing options were all essentially diffusion models, related to diffusion of heat in classical physics. Physicists spend their life doing this kind of stuff, so even if they didn't know much finance, it was very easy. In fact, when I came, the guy I worked for said to me, read this paper by Cox, Ross and Rubinstein over the weekend and then start trying to fix this program that I wrote for valuing options which seems to have some problem for bond options rather than stock options. I literally spent the week reading this paper and learned economics out of it.

Now Wall Street is much more sophisticated. The hurdle is higher. You really have to know something before you start. But in those days it was enough just to be a reasonably smart person who was willing to learn. So I leapt into it. There weren't a lot of textbooks. It was very exciting to be in a field where there wasn't much traditional stuff to learn and to study.

Although it was economics, the mathematics was very similar to that of physics, and physicists are kind of jack of all trades in that they can do modeling, they can do mathematics, they can do numerical analysis and they had to do their own programming pretty much. They were not like business people who needed somebody they could give the programming to.

To build a model of options — there are a lot of little things that can go wrong. If there is a gap between the person who understands the model and the person who does the implementation, then a lot of little things can go wrong which you have an incredibly hard time rooting out because the person who understands the theory can't implement it and the person who understands the implementation can't understand what might be wrong when you get some mistake. [...]

There's a lot of talk about the role of algorithms and the change in markets. The financial world has changed a lot since I worked in it and the biggest change is more people are playing with more of other people's money. When most of the banks were partnerships, they had to be in it for the long run because people who were partners were playing with their own capital and taking risk with their own assets. Their money was tied up for 10 or 15 years. Even if somebody retired, they still couldn't take their money out of there. They just got paid interest while it was being used and drawn down. So there was a certain culture of not taking extreme risks because you didn't really have limited liability. Ultimately you could be broken completely by your company going bankrupt. With trading houses going public, they're playing with other people's money. They're immediately liquid in terms of stock and cash payment. The culture in all of these places has changed in that it's make money liquid and fast. The way this crisis has been treated exacerbates that attitude in that if you do badly, the government bails you out and if you do well, you keep the profits.

I used to hear 10 years ago at Goldman from colleagues that there was going to be doom one day at Fannie Mae and Freddie Mac because they were hedge funds in disguise. To some extent the government and regulators have encouraged this and they still haven't tackled the problems at Fannie Mae and Freddie Mac and are doing with them what they accuse Wall Street banks of doing, which is treating them as off-balance sheet and not counting the money they are spending on them as real money.

In terms of algorithmic trading, that's a big change too. I'm not against it — it's inevitable from a technology point of view. You trade airline tickets with computers. You buy things off the internet. There is no way people are going to trade stocks in vast amounts by making verbal or written orders. Stocks are going to be traded electronically and eventually bonds, currencies and everything else will be traded electronically too.

It's unfair, though, to allow high-frequency traders to get what essentially amounts to insider trading, to getting an early look at trades and deciding what to do because they are allowed to put powerful computers closer to the stock exchange. That doesn't make it a flat playing field.

Also, people who benefit from it tend to over-accentuate the need for efficiency. Everybody who makes money out of something to do with trading tends to say, oh, we're got to do this because it makes the market more efficient. But a lot of the people who provide this so-called liquidity and efficiency are not there when you really need it. It's only liquidity when the world is running smoothly. When the world is running roughly, they can withdraw their liquidity. There is no terrible need to be allowed to trade large amounts in fractions of a second. It's kind of a self-serving argument. Maybe a tax on trading to insert some friction isn't a bad idea, just as long term capital gains are taxed lower than short term gains.

Economics is a strange field. One of the things I noticed on Wall Street was that firms use the economists to talk to clients but their trading desks don't necessarily pay attention to what the economists are saying. Unexpected things happen unexpectedly and damage positions and net worths. I don't think there is a good quantitative solution to all of this. I sometimes get letters from mathematicians in Europe saying that they have come up with a better formula for capturing risk or for valuing risk or for trying to control or measure risk. You can do better than VaR but there isn't one formula, one number, that is going to save you in the end.

More important is incentives and disincentives and making sure that people understand they are going to pay the penalties for their own mistakes and somebody isn't going to bail them out. Jim Grant, who writes a newsletter called "Grant's Interest Rate Observer" that I like, had a column recently pointing out that in Brazil they haven't had a big banking crisis and that there, anybody who runs a trading firm is personally responsible for losses. It's not company risk. It comes down to their own assets. So they are much more cautious about this. Those kinds of incentives are going to make a much bigger difference than finding a better mathematical formula for handing risk.


Posted by Orrin Judd at May 31, 2010 7:00 AM
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