Why active funds usually underperform
Active funds try to beat the market and charge considerably higher fees for the attempt. Over long periods, only a minority succeed, and there's no way to identify in advance which ones they'll be.
An active fund has a manager who picks stocks. For that, they typically charge between one and two percent a year, sometimes plus a front-end load of up to five percent on purchase.
The problem is simple arithmetic. All investors together are the market. Before costs, they earn the market return. After costs, they necessarily fall short, and whoever pays more in costs falls further short.
Over long periods, only a minority of active funds beat their benchmark index. Over ten years and more, that minority shrinks a lot. And the funds that succeed are rarely the same ones as the decade before.
That leaves you with the real problem: you'd need to know today which fund will be among the few in twenty years. The past barely helps with that. That's why the recommendation for beginners is almost always the index.
The core argument comes from William Sharpe and is purely arithmetic: since the sum of all actively managed portfolios before costs equals the market, the average actively managed dollar must underperform the average passively managed dollar after costs. That holds regardless of market conditions, efficiency assumptions, or manager skill. It isn't an empirical claim, it's an identity.
Ongoing evaluations like the SPIVA reports empirically confirm this picture: over ten- to twenty-year periods, a clear majority of active funds fall short of their benchmark in most markets. Survivorship bias further skews the statistics in favor of the active side, since closed or merged funds drop out of the data. Adjusted for that, the picture looks even worse.
On persistence: studies of return persistence find only weak evidence that past outperformance predicts future outperformance. Part of the observed excess return can also be explained by known factor premiums like size, valuation, or momentum, which can be captured more cheaply through rules-based funds. That doesn't invalidate every active strategy, but it shifts the burden of proof considerably.
| Index ETF | Active fund | |
|---|---|---|
| Selection of holdings | tracks the index | a manager picks them |
| Ongoing costs | often 0.05 to 0.3% | commonly 1 to 2% |
| Front-end load | none | up to 5% possible |
| Trading | on-exchange, any time | usually once a day |
| Transparency | holdings visible daily | usually quarterly |
| Goal | match the market return | beat the market |
| Over 10 years | gets the index return | 98% recently fell short of it |
Summary
- Before costs, all investors together are the market; after costs, they fall short.
- Over ten years and more, only a minority of active funds beat their index.
- Past outperformance barely predicts future outperformance.
Did you get it?
Why is the case against active funds arithmetic rather than empirical?
Because all active portfolios together make up the market. After costs, they must on average fall behind.
What is survivorship bias in this statistic?
Closed or merged funds vanish from the data, making the active side look better than it actually was.
Does the past help pick a good fund?
Barely. The persistence of past outperformance is empirically weak.
Sources and further reading
- The SPIVA reports from S&P Dow Jones Indices publish ongoing comparisons of active funds against their benchmarks. View source ↗
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