If you invest in mutual funds, your portfolio is probably, at least in part, managed by machine. Many managers use computers to screen through thousands of stocks, allowing them to focus only on those with the best prospects. "It is mandatory to have some method of sorting through the massive information flow," says Thomas Madden, who oversees domestic equity investing at Federated Investors.
But a growing subset of managers known as "quants" are granting the computer a more active role in stock selection. It's hard to generalize about quant funds. Many are new, their methodology is complex and often secret, and their goals are diverse. With the stock market hovering near an all-time high, having a dispassionate computer assisting with buy and sell decisions might be comforting. And lately many quant funds are turning in impressive results.
Vanguard Quantitative, which seeks to mimic the characteristics of the Standard & Poor's 500-stock index while outperforming it, has returned an average 12.34% for the past five years, while Vanguard's plain vanilla S&P index fund has averaged an 11.9% five-year return. Quantitative Numeric, a small-cap fund recently closed to new investors, just earned a five-star Morningstar Inc. ranking, thanks to a 31% three-year average annual return. And Brad Lewis, who runs several quant funds totaling $4 billion in assets for Fidelity Investments, is positively gloating over his new "black box" model, which has helped him rack up year-to-date returns of over 31% on his Stock Selector and Small-Cap portfolios.
"I don't think there is enough evidence to conclude that quant investing is always better than traditional research," says Amy Arnott, senior editor at fund-rater Morningstar. "But it's going to become more and more popular." Assets are flowing into many of these funds, and new ones are springing up. The Quantitative Group of Funds in Lincoln, Mass., has added three new funds in the past year alone. The most successful quant funds invest in domestic equities. If you already have a U.S. stock fund, adding one could enhance your mix. "Diversification of styles is important for investors," says Lewis.
Unless you have a penchant for a somewhat eerie realm of computer science called artificial intelligence, you probably don't want to know the details of how these models work. Suffice it to say that the managers turn their investment theories into computer models, mostly using the same fundamental measures and economic data that traditional managers do. But quant managers take into account complex relationships between factors and do the analysis much more quickly and dispassionately than traditional spreadsheet analysts ever could.
"OUR INSIGHTS." Instead of looking at a handful of variables, such as cash flow, earnings growth, and price-earnings ratios, quant managers can program the computers to review 30 or 40 variables. Managers are constantly tinkering with their models, updating them as they find new patterns and relationships to exploit. "It's our insights" guiding the model, says John Bogle Jr., who manages Quantitative Numeric. "We just programmed the computer so it can think like we do." Adds John Nagorniak, manager of Vanguard Quantitative: "It's not like it has eliminated the need for good judgment and common sense."
Managers do more than just send the printout to the trading desk after the model sorts through the data, spitting out a list of stocks with the highest forecasted returns. Even die-hard quants check their models' handiwork. Often, the managers will weigh such unquantifiable variables as new-product development and executive changes. Lewis says he runs picks by Fidelity's research department, but rarely do the analysts contest his findings.
NEWS DEFICIT. The models aren't perfect, though. One danger is that managers might rely on them too much, failing to keep on top of changes at the company, says Madden. Screens showed IBM to be a great value play when its stock price was falling in 1992, says Madden. That's because models couldn't pick up that its mainframe business was losing out to personal computers. The models also won't be much help in times when the markets' main influences are news events. For example, models could not react to financial fiascos of the past year, such as Mexico's crisis, Orange County's bankruptcy, and the collapse of Barings.
Most of these funds are designed to pick stocks, not time the market. Still, some quant managers see signs (for example, in comparing the relative values of stocks to bonds) that the stock market is overvalued. If ittakes a turn for the worse, quant funds won't ride out the storm untossed. But you still might be glad to have a steady hand, steering by computer, at the helm.