Machine Learning Can’t Pick Winning Funds. But It Can Help You Avoid Losers

A new study overturns claims that AI can generate positive alpha in mutual funds. Here are some practical takeaways for investors

n recent years, machine learning has been touted as a game changer for investment management. The authors of “Machine Learning and Fund Characteristics Help to Select Mutual Funds With Positive Alpha,” published in the December 2023 issue of the Journal of Financial Economics, claimed that machine-learning methods could identify long-only mutual fund portfolios earning significant out-of-sample annual alphas of 2.4% net of all costs. For believers in active management, this was the financial equivalent of the search for the Holy Grail.

What New Research Uncovered About Machine Learning

Two years later, a new set of researchers performed a replication analysis of the 2023 study for their own paper, “Does Machine Learning Really Help to Select Mutual Funds With Positive Alpha?” These researchers found that the original results were driven by a coding error that inadvertently gave the algorithms access to future information—a classic case of look-ahead bias.

The error was technical but consequential. When constructing portfolio returns, the original code updated portfolio weights using next month’s returns rather than the current month’s returns—essentially peeking into the future when making investment decisions, which is impossible in real-world investing. After correcting this error, the impressive outperformance vanished entirely. The annual returns dropped by 1.37 to 1.42 percentage points for the best-performing algorithms, and none remained statistically significant. The authors also identified a survivorship bias in the original study.

You can read the rest of my Morningstar article here.