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By Christine Benz | 10-17-2013 08:00 AM

Ferri: Why Passive Portfolios Are Better Than Active

Research by author Rick Ferri took the active-passive debate beyond individual investments and found passive-oriented portfolios will likely outperform active portfolios across time spans, number of holdings, and asset types.

Christine Benz: Hi. I’m Christine Benz for I recently attended the annual Bogleheads Conference, where I had the opportunity to sit down with investment advisor and author, Rick Ferri. We discussed his recent research on indexed versus actively managed fund portfolios.

Rick, there’s been a lot of research comparing how actively managed funds have done versus their passively managed counterparts. You recently issued a white paper, where you looked at actively managed portfolios versus index fund portfolios. I’d like to start by discussing briefly your methodology, how you assemble those active portfolios and also what you looked at in assembling the index fund portfolios.

Rick Ferri: There's a lot to that answer because there is a lot to the study. But what we were interested in is moving the debate between active and passive to a different level. It has always been on the individual asset-class level: How many large-cap U.S. active funds outperform the S&P 500? How many bond funds outperform the Barclays Aggregate Bond Market Index? We thought that we need to move this to a different level, which is we need to be looking at indexing versus active management on a portfolio level because people just don't own one large-cap U.S.-equity fund and they're done, or just a bond fund and they’re done. They combine U.S. equities, international equities, bonds, perhaps Treasury Inflation-Protected Securities, different asset classes, real estate.

We wanted to look at how at a diversified portfolio of index funds would perform relative to a diversified portfolio of actively managed funds from the same categories. We wanted to see whether the index funds at a portfolio level had better results than at the individual level or worse results, and that was the purpose of the study.

Benz: When assembling that portfolio of active funds, the natural question is how did you decide how to assemble those portfolios? I know you used the CRSP database; that’s a survivorship bias-free database, meaning that it incorporates dead funds, funds that have gone away oftentimes because they were lousy. But how did you come up with those portfolios, and how did you attempt to account for the fact that investors oftentimes do use some screening when they put together their active portfolios? Maybe they look for strong-performing funds or funds with low expense ratios or whatever it might be?

Ferri: Again, that’s a long answer. The database itself needed to be cleaned because within each category--there were categories in the CRSP database. But let’s say the large-cap U.S. category also contained some more mid-cap funds and balanced funds, so we had to take those out. They also contained all different classes; A shares, B shares, C shares, institutional shares. So, B shares, of course, are back-end load and they have high fees, so we took out B shares. C shares are a level load, with a high fee all the way through. So we took those out. Institutional shares you have to have $1 million to buy, which we took those out. So we were left with the A shares, which a lot of times have front-end loads, but we didn’t count the loads and all of this.

We had to cull out the database based on the costs and the different share classes, and also clean the database to make sure that there were no funds in there that really shouldn't have been in that category. For each of the different categories--there were 10 different categories that we came up with--we did that. Now, as far as constructing the portfolios, we constructed an index fund portfolio, which we used a very simple one. It was a three-fund portfolio of total U.S. stock market, total international, and total bond index funds. We used the Vanguard funds initially in this three-fund portfolio design because they have the most history. We didn’t do any hypotheticals. We used actual fund performance that investors could have gotten these returns in these funds. It was all actual. So we used investor share class, which is the highest-cost Vanguard fund, and we always used the index fund because that was the oldest for each of the categories. They weren’t all Vanguard funds. There was a few iShares funds in there as well in a couple of categories because they were the oldest index funds.

But then we just simply put a portfolio together very simply of 60% stock, 40% bonds. Of the stock portion, it was 40% in U.S. total stock market, 20% international total market. Then the 40% was in the Vanguard Total Bond Market Index fund, and we carried that forward. Over here on the active side, from each of those three categories, we randomly selected a mutual fund that was in the database. Now, as you said, this is a survivorship-bias-free database. If we randomly selected a U.S. equity fund and then started running forward and that fund merged or liquidated, then we stopped at that point, picked another U.S.-equity fund randomly from what was available at that particular time, and then we kept going forward.

So we had a consistency of the portfolio of active funds [to mimic] what an investor would do. We tried to mimic as close as we could the investor experience, at least randomly selecting funds. Then we compared the two together to see what the performance was, and we did it 5,000 times. That was the breakpoint that if you did it more than that, it didn’t really make any statistical significantly different outcomes. If you did it less than that, there was some statistical difference in the outcome. This is what we did for all 32 of the studies that we did with this.

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