Investment Returns from the Long Tail and the Marginalization of Wall Street Research
A particular statistic has been burning a hole in my head since I first read it in Alan Abelson’s Barron’s column this weekend - according to Rich Bernstein, Chief Investment Strategist at Merrill Lynch, the best of 40 trading strategies tracked by the firm’s quants in 2006 was to buy the 50 S&P 500 stocks least covered by the sell-side analyst community. Huh? The return of this strategy was 24.6%, fully 11% better than the 13.6% return generated by the S&P 500 for 2006. This isn’t outperformance - this is an a**-kicking. But the real question is why, and what might the implications of this be?
Alan made a funny reference to the legendary investor Gerald Loeb, and his view on the usefulness of security analysts: “In bull markets, you don’t need ‘em; in bear markets, you don’t want ‘em.” Now Gerald wasn’t the most socially sensitive guy, but you kind of get his point. I am personally more curious as to why “orphan” stocks outperformed better-covered shares, because, on its face, one might find this counter-intuitive. Could it be that more information levels the playing field, rendering the ability to develop and act on truly differentiated information extremely difficult? Or that there is so much data, good and bad, around an actively covered share that it is hard to separate information from noise? Might it possibly be that a valuable piece of information on a lighly-covered stock has much greater marginal value, both because of lighter trading volumes (thereby pushing up the stock on a big buy program) and the resulting follow-through from momentum-based traders?
I’d argue that it is these and many other factors that can explain the difference in performance cited by Rich, but that it is hard to argue that the marginal value of information on a less-covered stock is apt to have a greater impact on price than that same piece of information on a more actively-covered stock. Why? Because the information is less expected; is less likely to be discovered before-hand; and the trading volumes are likely to be smaller. If one buys these arguments, and if one views the S&P 500 as a microcosm of the overall equity market, then it stands to reason that there is one very straight-forward way to generate outsized returns: get more and better information on poorly-covered stocks in the face of weak sell-side analyst support. But how?
By using powerful tools to look for “long-tail” information that can augment information that is generally available through conventional media outlets. My company and a handful of others have recognized this and are trying to bring this capability to the investment community. I am firmly convinced that we are entering the “Third Wave” of information for investors: with Reuters pioneering dissemination of news with undersea cables in the late 1800s; Bloomberg revolutionizing granular cross-market pricing data and analytics leveraging client server technology in the 1980s; and tools for extracting valuable and timely information from the Internet in the 2000s. And this Third Wave has the potential of being even bigger than the first two, principally due to the proliferation of content on a global basis finding its way onto the Web, and the increasingly high-quality sources contributing to the global dialogue on companies, products, and macro themes on a 24-7-365 basis.
This is extremely exciting stuff that is screaming for new tools and technologies. And we are very early in the evolution of the Third Wave. It is just when people like Rich Bernstein crunch the numbers and highlight the fascinating yet counterintuitive that it makes the inexorable trend towards more and better internet information increasingly clear.
