Active managers, long-suffering from lackluster performance, have taken a page from baseball talent scout Billy Beane’s playbook by using data analytics to boost performance. This according to a recent article in Institutional Investor.
Beane, who rose to fame as a scout for the Oakland A’s baseball team, used data analytics to “build a stellar roster on a shoestring budget,” the article explains, adding that these techniques have proven effective for struggling active managers thanks to data collected by the technology research and development firm Turing Technology Associates using so-called “ensemble methods”—in which the firm uses artificial intelligence to track recent results from live portfolios.
The article quotes Turing co-founder Alexey Panchekha, a PhD in math and physics: “Asset management is a dinosaur. It’s the last industry that hasn’t embraced ensemble methods yet.” But now that the data is emerging, he thinks things will change. Specifically, Turing data shows that 34 portfolios using the techniques have outperformed their benchmarks during the 51 weeks they have been operating, and 71% of the portfolios outperformed their peer group through October 31st.
The article notes that “while back tests have shown that ensemble active management significantly improves the performance of active managers, this is the first test of live results.” For some, like John Sabre, CEO of Mount Yale Advisor Services, it’s a “game changer” that “tips the scale back to active management and stock selection.”
