Exchange traded funds (ETFs) are currently all the rage. One reason why that might be the case is that they are still index or strategy-based investments. Therefore the composition of the ETF portfolio is solely model driven. This quantitative approach has been catching on with both ETFs and open-end mutual funds. Despite their increased media mindshare ETFs still trail traditional mutual funds in terms of assets under management: $324 billion vs. $9,316 billion. (via

We previously posted on how investors can go about tracking down mutual funds from entrepreneurial and innovative fund managers. One fertile area for research are these quantitatively managed funds. Reginald Laing at looks at their favorite quant funds. Maybe more important than their actual fund recommendations may be the reason why quant funds may be an attractive path to follow.

Quant funds have a lot of intuitive appeal. First, they strip away at least some of the human bias that trips up active managers, who often buy into market trends at precisely the wrong time and overlook real values. Also, quant models allow a manager to sift through thousands of securities and pick out ones that have the characteristics, or factors, he thinks are predictive of high future returns. What takes a model minutes to compute would take a team of analysts weeks–time for market conditions to change and discovered opportunities to disappear. Moreover, managers who have faith in their quant models are unlikely to deviate from their strategies, thereby avoiding the inconsistency that hurts many active managers.

Given the relative success of quantitative methodologies in other fields we should not be all that surprised that the same processes may work in investing. Douglas Heingartner in an interesting piece at the New York Times uses research on management decision making to examine the growing influence of quantitative methods.

The main reason for computers’ edge is their consistency — or rather humans’ inconsistency — in applying their knowledge.

“People have a misplaced faith in the power of judgment and expertise,” said Greg Forsythe, a senior vice president at Schwab Equity Ratings, which uses computer models to evaluate stocks.

Quantitative investing is not a panacea by any means. There clearly are situations and times where the underlying data simply do not capture the relevant information. However in a growing number of situations quant models are performing with aplomb. Remember this when you think about the basis of many discretionary methods – the interview.

“People’s overconfidence in their ability to read someone in a half-an-hour interview is quite astounding,” said Michael A. Bishop, an associate professor of philosophy at Northern Illinois University who studies the social implications of these models.

Just keep this quote in mind when you hear a portfolio manager on CNBC brag about how many CEOs they met with over the past year.