New research from the University of Maryland’s Robert H. Smith School of Business pioneers a way to sift through the thousands of active mutual funds to winnow them down to a set of the best ones to invest in.
The research, from finance professor Russell Wermers and three co-authors, is the lead article for 2021 in the Journal of Financial Economics, a top scholarly journal. Wermers, chairman of the finance department and director of Maryland Smith’s Center for Financial Policy, says the paper uses a cutting-edge algorithm that makes picking the right mix of investments more about data-based science than an art.
“Basically, you use this new econometric technique, which compares each fund with every other fund,” says Wermers. “It does numerous comparisons between pairs of funds and whittles down the thousands of funds from which you’re choosing to a handful that you wish to have in your set.”
The algorithm is simple, says Wermers, all based on funds’ past returns: “We base this purely on a statistical evaluation or comparison of each fund with each other fund, using their historical monthly returns, adjusted properly for risk. And that’s it. That’s the simplicity of this.”
This has especially big implications for 401K plans and all other types of defined contribution plans, he says. The trustees who choose the funds for those plans can use this research to pick the best funds, but it isn’t limited to that setting.
“There could be cases where an individual investor wants to choose the 10 best mutual funds to invest in,” says Wermers. But gathering the data and running the algorithm takes a fair amount of computing power, he says – the kind wielded by a 401K fiduciary with the big muscle of a professional services firm like PricewaterhouseCoopers. Or, he says, individuals could hope that a firm like investment information provider Morningstar Inc. or Lipper starts using the algorithm so they can benefit from the findings. Right now, Morningstar just gives all funds a star rating and doesn’t offer comparisons between them.
“They could use this algorithm in the future to help people select a portfolio or to create baskets of funds that they recommend as packages to individual investors,” he says. “There are a lot of details in the econometrics that go beyond the star-rating technique that dictate how you should winnow down those five-star funds into a set of the best funds that you can expect to perform going forward.”
Wermers hopes the research will catch the attention of financial services firms or fund managers to give people the opportunity to benefit from the findings.
“It’s more for the guys who pick sets of funds for the rest of us to invest in.”
Read the full research, “Picking Funds With Confidence,” in the Journal of Financial Economics.
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