This Is the End


Markets, Risk and Human Interaction

August 16, 2007

Creating a Differentiated Quantitative Hedge Fund Product

One part of the solution to the quant hedge fund problem is to use a strategy no one else is using. (The other part, in case you are wondering, is not to lever so much). Of course, it is hard to know if you are really differentiated from what other quant shops are doing – it is not like everyone gets together and presents papers at hedge fund symposiums. But, in any case, I think this is hard to accomplish.

The reason I think this is for the same reason the quant funds ended up with very similar strategies in the first place: they use the scientific method.

The key to the success of the scientific method is the reproducibility of results. If you do the same experiment I do, you will reach the same conclusion. More than that, if you and I start with the same hypothesis and apply the same data, you will discover what I discover. That is why we see so many races for the prize in the pure sciences. Even with the spectacular discovery by Watson and Crick, there were others nipping at their heels.

With the quant funds, we have well-trained professionals applying the scientific method to capture anomalies in the market. Most are trained at the same handful of institutions, they have read the same academic literature, and they are applying the same statistical tests, using the same analytical tools, to the same sets of data. So it is no surprise they come up with similar models.

That is not to say you can’t be successful doing this sort of thing. Think of Jim Simmons and Renaissance. Granted his longer-term fund has been in the same boat as Goldman and others, but his high frequency fund has made money with uncanny consistency for years. But he has a number of things working for him. First of all, he has huge scale; there are about two hundred top-notch scientists in his firm. He also has had years to amass a proprietary knowledge base, so he does not need to rely as heavily on the existing academic research. So it is reasonable to think he could stay ahead of the curve – others might get to where he has been, but by then he is another step ahead.