A reader asked, “What’s your view of the quant world going forward? Especially in the institutional world and in Europe, Asia, etc? How about relative to “traditional” ways of investing, such as value or GARP?”

All I know is what I read and interpret from the outside of the industry, and what I guess about human nature. My definition of quant is probably larger than the typical definition. I would include anything that was data-driven, empirical, objective, and deterministic as quantitative, and that would include a lot of value strategies and GARP strategies. I could share a backtest on Price/Operating Cash Flow related to Estimated Earnings Growth and you could see it either as a quantitative strategy that was to be executed mechanically, or you could see it as a GARP screen from which you did your qualitative research, talking to management, reading proxies, understanding the business model, etc.

I think the more typical definition of quant is pigeonholed into a few subcategories, like the high-frequency trading that really is more like glorified computerized market-making, or the derivative strategies on illiquid contracts that require complex valuation modeling to estimate the market value of positions, or black box covariance methods for determining position weighting. There are some quant shops who view stock selection in terms of factor models, and they cross from the “typical” view as I characterize it, into my point of view as to the broad definition of quantitative trading. Like the Bear Sterns EAFE Plus, or the model I examined in the TRPITS posts, I believe they tend to overcomplicate the issue.

I don’t think quant management (from the “typical” definition) is going away anytime soon, and is probably getting stronger as the tools progress. To a man with a hammer, everything looks like a nail, and computer power is pushing the limits of what can be done with the data. Additionally, there’s that fascination with complexity, and the marketing tool that complexity provides, which will manage to sell the product. In Europe and Asia, where these things are less well-explored, I think it’ll grow faster than it’s growing here.

For what it’s worth, I see the same thing happening in insurance ratemaking, where simple approaches are probably measurably better, all things considered, than the complex approaches, but the trend is towards complexity. Nobody believes in blocking and tackling, they all want to use trick plays.

Now, the more traditional ways of choosing stocks, like value, GARP, growth, forensic accounting, etc. are all still effective and pretty much all could be quanitified if you took the time to do it. Given the lack of “flash” in these approaches, and their supposed ease of replication relative to “typical” quant models, I don’t see these gaining in popularity relative to quant.

I find the institutional desire to invest in models that (look as if) only a physics or finance “Piled High and Deep” could have built them to be hilarious, because the “Piled High and Deeps” that run these things all came from the same half-dozen schools or so, all read the same research papers, all know each other, and all have the same data sources to play with. In reality, what they come up with will be rather easily replicated by competitor firms, precisely because of that “groupthink.”

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