Innovative portfolio strategies, once a dime a dozen, now appear as scarce as a buffalo nickel.
Not that many years ago, it seemed another new school of portfolio management popped up every year. A new generation of quantitative investment managers cranked up their computers to pick stocks (and sometimes bonds) using increasingly esoteric approaches: artificial intelligence, global tactical asset allocation, portable alpha, behavioral finance and so on.
Of course, those approaches haven't disappeared. In fact, they are being applied more widely and are being integrated with traditional asset management. But the most recent innovations generally are variations on existing themes.
What's more, some quant strategies are in retreat. "If anything, the industry is recoiling from those purely quantitative approaches," said Peter L. Rathjens, managing partner and chief investment officer of Arrowstreet Capital LP, Boston, which blends quantitative and traditional techniques.
The painful thing, he said, is "many of these strategies go through a period of doing well, (followed) by a period of spectacular blowups," notably Long-Term Capital Management's 1998 disaster, which required intervention by the Federal Reserve. The hedge fund manager used sophisticated quant models, but was hammered by "hidden" factor bets, explained H. Russell Fogler, principal, Fogler Research and Management Inc., Gainesville, Fla.
Academics and institutional investors said a number of factors are responsible for the paucity of new thinking.
Mr. Fogler cited two factors: back-tested quantitative strategies underestimated trading costs; or strategies failed to raise enough assets to justify the research and operating costs involved in sophisticated quant modeling.
The costs of executing some trading strategies in various countries were higher than expected at Quantel International Inc., Berkeley, Calif., said Paul Pfleiderer, principal at Quantel, and William F. Sharpe Professor of Financial Economics and co-director of Stanford University's financial management program, Palo Alto, Calif.
"Significant alphas in (some) countries were eaten up," he said.
Other experts observed that many quantitative strategies rely heavily on historical data. While that might work when markets work in a more normal fashion, the experience of the past few years blew many of these models out of the water.
"The markets have been so bizarre," said Theodore R. Aronson, chief investment officer and managing partner at Aronson + Partners, Philadelphia, whose value-oriented models were pummeled in the late 1990s.
In addition, a preponderance of quant models appear to be biased in favor of value stocks because of the ready availability of data, such as price-to-earnings and price-to-book ratios, and less subjectivity than is needed to pick growth stocks.
But the failure of some quant models to perform during the late 1990s doesn't explain it all.
"There's a whole bunch of stuff that happened in the '70s," said William Jacques, chief investment officer for Martingale Asset Management, Boston, ticking off the capital-asset pricing model, arbitrage pricing theory and options pricing theory. "I think it took 25 years to digest all that stuff."
Three decades later
Others agreed there has been relatively little groundbreaking academic work since the pioneering work in the 1970s by Harry Markowitz, William Sharpe, Fischer Black, Myron Scholes and others. In addition, it took years for computers to become powerful enough to process data to implement those theories.
Frank Sortino, director of the Pension Research Institute, Menlo Park, Calif., also decried the hostility that traditionally greets radical thinking in academia and on Wall Street. "Innovation is not welcome. It makes people uncomfortable; it certainly makes the establishment uncomfortable," he said in a phone interview. "I would say the financial community is the least interested in innovative ways of doing things."
Citing Thomas Kuhn's classic book, "The Structure of Scientific Revolutions," Mr. Sortino said it often takes many years and a crisis for new thinking to be accepted. "It was 20 years after Harry Markowitz proposed a radical change in the way portfolios were managed before the old-guard fundamentalists grudgingly paid any attention," Mr. Sortino wrote in an e-mail.
"Maybe we've got enough of a crisis for people to start searching about (for new ideas)," he said in the interview.
However, Peter L. Bernstein, president of the eponymous New York-based consulting firm and consulting editor to the Journal of Portfolio Management, said the recent past has been an anomaly. "I'm very suspicious about anything that is derived from the experience of the last five years," he said.
The late '90s aside, some quantitative managers have been looking to traditional portfolio management for ideas.
"From the quantitative perspective, we can learn a lot from ... traditional managers," said Ron Kahn, head of active equities for Barclays Global Investors, San Francisco.
Traditionally, quant managers have looked at financial ratios, such as p/es, but those criteria don't fit all industries. With software companies, for example, "p/es don't matter; people are looking at future earnings," Mr. Kahn said. BGI has latched on to insights from traditional managers and applied them "much more systematically," he said.
Mr. Fogler sees two trends emerging. First, larger managers are more often using quant techniques for risk control and sometimes using traditional analysts to enhance security selection. Second, hedge funds limit their size, and "sometimes focus more on esoteric quant research to assist them, explicitly integrate trading models and controls," he wrote in an e-mail.
Mr. Rathjens said quants realize investment strategies for the future need to be "more anticipatory." "It's easy to buy a consistent process and hope the world is not changing."
But voicing skepticism was Josef Lakonishok, William G. Karnes Professor of Finance at the University of Illinois at Urbana-Champaign and principal and chief executive officer of LSV Asset Management, a Chicago-based quant shop. "There are so many things that are changing; it's so difficult to quantify," he said. "I am very leery about trying to predict all those moving parts."