Last few years saw something of a gold rush into quantitative investment strategies. Their appeal is obvious as a way to put discipline into trading and take the emotion and stress out. Quantitative strategies might even help improve performance. Here’s how Black Rock President Rob Kapito articulated the industry hopes:
“As people get the data and learn how to use the data, I think there is going to be alpha generated and, therefore, will give active managers more opportunity than they‘ve had in the past to actually create returns.” [1]
In pursuit of the great expectations, Black Rock assembled more than 90 scientists, 28 of them with PhDs and even went as far as poaching one of Google’s leading scientists, Bill McCartney to develop the BlackRock’s machine learning applications. In practice Black Rock’s and other firms’ results have proven to be a mixed bag at best and it seems that most quantitative strategies have tended to underperform or even generate losses. The question is, why? Continue reading