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* Watch this video to hear from Tim Cohen, CIO of Equities, as he highlights key points from new research. He finds that by using two straightforward filters, we can select a subset of U.S. large-cap equity funds that, on average, have outperformed their peers.
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Hello, I'm Tim Cohen, a chief investment officer in the equities division at Fidelity Investments, and I'd like to discuss some of our new research into the performance of actively managed equity mutual funds.
There's a persistent debate in investment circles about whether it's better to invest in active funds or passive funds. A commonly held belief is that active stock pickers have a harder time beating benchmarks in highly efficient markets like U.S. large cap stocks than they do in less efficient markets. If you look at average performance data for a few different markets, there's some evidence to support this view.
For U.S. large-cap funds, the historical data show that the average actively managed fund has trailed its benchmark index after fees. But in other market segments, like U.S. small-cap or international large-cap, the average active fund has outperformed its benchmark. These markets are sometimes seen as less efficient than U.S. large-caps.
Also notice that in all three fund categories, passive index funds have consistently trailed their market benchmarks. This underperformance isn't surprising, given that the objective of passive funds is to try to match the market before fees, while this data shows net returns after fees.
Looking at this history for U.S. large-cap funds, we wondered whether there was any deeper story behind the data in these averages.
Our first idea was to screen for funds with low fees. Fund fees are clearly disclosed, so this is a factor within investors' control.
Not surprisingly, when we looked only at U.S. large-cap funds with fees in the lowest quartile, we saw that the average return for this subset was better than for the entire fund universe, for both active and passive funds. For passive funds, the main objective is to mirror the index before fees, so funds that charge lower fees should logically show better returns.
On the other hand, for actively managed funds, fees are important, but often not the most important factor driving net returns. Active fund managers are scouring the markets to search for stocks that will perform better than the benchmark index. That's why for any individual active fund, lower fees don't necessarily translate into better net returns.
With that in mind, we decided to ask: what happens if we focus on funds that may have the most resources to help identify better investment opportunities? For actively managed funds, we assumed that assets under management, or "AUM," would be a reasonable proxy for investment resources. We looked at an overall fund family's AUM within U.S. large-cap equity funds, because we assumed that all other things being equal, an active fund family with one hundred billion dollars in AUM would likely have greater resources it can apply to researching and trading stocks than a firm with only one billion dollars in AUM.
For our cutoff, we selected the top five fund families by AUM in U.S. large-cap, which together represent about 10 percent of the total number of funds in that category. For passive funds, there are fewer fund families overall, so the exact same filter didn't help the results very much. Instead we looked at the top 10 percent of passive index funds as measured by AUM in the funds, to make a fair comparison.
Once again, the filter had a positive effect for both active and passive, identifying a subset of funds with a higher historical average return than the full universe of funds.
And combining the two filters had a bigger impact, with an improvement for both types of funds, but particularly for actively managed funds.
Choosing passive index funds with the lowest fees and the highest AUM resulted in improved performance that was only 3 basis points below the benchmark, a nice improvement over either individual filter alone.
But for actively managed funds, the results of these combined filters were even more powerful. The average fund went from minus-67 to plus-18 basis points of annual return above the benchmark.
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