Quants merge with humans

By Felix Salmon
September 2, 2010
Eleanor Laise has found an interesting trend in the world of quant funds: a lot of them are looking much more human, these days.

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Eleanor Laise has found an interesting trend in the world of quant funds: a lot of them are looking much more human, these days.

Quants are seeking to win back investors not just with their characteristic number crunching but also with a bit of soul searching. Many of the funds’ managers are seeking to make their models a little more like people, by making them more responsive to changing circumstances. That can mean revisiting computer models more often, tweaking their components, or incorporating measures of macroeconomic risk rather than just stock-specific information.

Quant managers need to understand “that financial markets are better understood through the lenses of a biologist rather than a physicist,” says Andrew Lo, a finance professor at the Massachusetts Institute of Technology who also manages quant funds.

My feeling is that what we’re seeing here is the beginning of a kind of Hegelian synthesis in the fund-management world. The thesis was that a talented active manager, with experience and insight, could outperform the market. The antithesis was that active managers, being human, had a distressing tendency to do exactly the wrong thing at exactly the wrong time. Instead, computers had in reality the discipline that human traders have only in theory, and can stick to any given strategy through thick and thin, just as the backtesters intended.

The synthesis, in this view, is that it’s not always smart to stick to a failing strategy, although humans can definitely benefit from the sheer computational power embedded in quant models. So the humans use those models, to a greater or lesser extent, to inform their investment decisions.

At that point, it all comes together: quant funds are the ones which minimize human meddling, while other fund managers who would never consider themselves quants still use sophisticated models to help them pick stocks and strategies. But in reality they’re not so far apart.

I do think that Lo is right, and that it’s never particularly smart to simply stick to a single strategy in an attempt to outperform the market. (In fact, I’m not a big fan of even trying to outperform the market in the first place, but that’s a separate question.) On the other hand, given that human tendency to do the wrong thing at the wrong time, I fear that human-inflected quant funds are just going to end up abandoning strategies just when they would have started to work.

What I’m not seeing, anywhere, is a dynamic quant strategy which automatically makes significant changes to its investment style depending on market conditions. Quant funds tend to be perfected by humans and then released into the wild; any further changes, at that point, are also performed by humans, who don’t trust the computer model to optimize itself on the fly. Sure, computers can buy and sell stocks as conditions change. But they don’t change the rules governing which stocks to buy and sell: those are fixed unless and until humans change them.

That’s probably just as well: I’m not sure the world really needs investment strategies being set without any fund manager having a clue what they actually are. But at the same time, a purely computer-generated strategy might provide some interesting diversification from the madness of crowds. I doubt we’ll see anybody admit to using one any time soon. But for all I know it’s already happening at some hedge fund somewhere. Maybe it’s even the secret of RenTech’s famous and mysterious black box.

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