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In Practice: Performance Chasing, Evaluated

Our research shows that three-year outperformance isn’t a great predictor, and maybe fund investors aren’t so fickle after all.

Jeffrey Ptak, 04/06/2012

This article originally appeared in the April/May 2012 issue of MorningstarAdvisor magazine.  To subscribe, please call 1-800-384-4000.

“Everybody loves a winner.”

That saying holds at least partly true for fund investors, who have tended to cast their lots with funds that have enjoyed recent success while fleeing laggards. Assets have flowed disproportionately at times to the “winners”—funds that have put up the best numbers in recent years.

Some industry practices reinforce this dynamic. For example, “gatekeepers” are sometimes loath to recommend funds that have shorter track records and, thus, have not received a performance rating. What’s more, they might be reluctant to approve smaller funds for fear they have not achieved operational viability or lack distribution heft. In that sense, gatekeepers might be more prone to present investors a menu that skews to recent winners.

This raises a few questions. First, are three-year returns—a common litmus test for defining “winners”—predictive of future performance? Second, with the rise of open-architecture platforms in recent years, have assets become more concentrated in winners? Third, to the extent that a category becomes more concentrated in its best performers, how are those winners likely to fare in subsequent periods?

Our Study
To address these questions, Morningstar Investment Services compiled net asset, Morningstar category, and return data for every active and obsolete U.S. open-end equity mutual fund in Morningstar’s database for the 19-year period ended Jan. 31, 2009. (Morningstar’s U.S. mutual-fund asset dataset is complete back to 1993, explaining why we commenced the study in that year.)

We assembled peer groups for every single month of the study period using the historical Morningstar category classification data. In this way, we could better simulate the peer groupings that actually existed at each relevant time in the past. (Current category assignments do not necessarily represent a fund’s past classification; for example, today’s large-value fund could have been a mid-value fund last month, and so forth.)

Using these point-in-time category snapshots and the historical return data, we calculated category percentile rankings based on each fund’s rolling three-year returns. We then tallied the assets invested in the different category quartile groups at each point in time, as well as the percentage of overall category assets that the quartile accounted for. For example, as of Jan. 31, 2008, there were 26 top-quartile large-growth funds. Taken together, those funds accounted for roughly $36 billion, or about 27%, of the category’s $137 billion in assets at the time.

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