The data feeds for EAM portfolios come from Turing Technology Advisors, a fintech software company whose work includes data analytics and predictions. Turing co-founder Alexey Panchekha, along with Tull, where two of the authors of the EAM white paper.
As explained by Tull, the EAM investing model works like this: Turing downloads the daily closing net asset value of mutual funds that’s provided by Fund/SERV, a system launched by the National Securities Clearing Corporation that processes and settles mutual fund, bank collective fund and other pooled investment product transactions between fund companies and distributors.
“Turing has the technology to reverse engineer the holdings daily based on NAV changes and the profiling they’ve done on prospectuses, and they’re doing more than $4 trillion a day in assets,” Tull said. “That’s the big data component.
“Because the technology has improved since 2018, we now know within about a 99% accuracy on a daily basis what’s in those funds because you pull in all of the data of all of those closing prices from the exchanges, you pull in the daily NAV changes, and from that you can discern what they hold,” he added.
The second piece of this step is pulling out the high-conviction stock picks of specific groups of mutual funds.
“The models I’ve licensed to Tim had a list of 15 mutual funds that I selected because I know the managers and the strategies very well,” Tull said. “From there, we know what they hold, so which of those holdings are greater than the benchmark index or the prospectus. Then we build a consensus across that grouping of managers. From that, every two weeks Turing produces a select group of 50 stocks that have been chosen based on the managers, their expertise . . . and we leverage that through EAM to produce these portfolios.”
So while Turing grabs a ton of mutual fund data each day, the bi-weekly feeds it sends to Melius and Pegassets for their respective EAM portfolios are focused on just the active fund managers the two firms have selected.
“The reason it’s limited in number is because when we were doing a lot of early work on this we found there’s a law of diminishing returns by going past more than 20 managers in a grouping,” Tull explained.
Live Models
Nine of the 10 portfolios on the Melius platform have been running as live models for at least 10 months, and according to Melius all of them have produced net-of-fee excess returns versus their primary benchmarks through April 30. The outperformance ranges from 0.3% to 17.9%.
The newest model, the Melius Sector Disruptors that went live on February 20 just before the pandemic hit, was down 8.6% during the next two-plus months (though it still beat its benchmark, the Russell 1000 Growth Index, by 0.5% on a net-of-fee basis).