The More Unique Your Portfolio, The Greater Its Potential
If there is a lot of overlap between your portfolio and the market, there is only so much alpha you can earn. This is obvious. Still, when you visualize this potential it sends a powerful message. Active share—the preferred measure of how different a portfolio is from its benchmark—is not a predictor of future performance, but it is a good indicator of any strategy’s potential excess return. As you’ll see below, the higher your active share, the more extreme your performance can be, good and bad.
Active share, most simply understood, is a percentage between 0-100 that tells you the percent of a portfolio which is different from the benchmark. An active share of 90% means that only 10% of the weight in that portfolio overlaps with the weight of the market (say, the S&P 500). An index fund has an active share at or near 0%–perfect overlap with the index itself.
Imagine you had perfect foresight and knew every year how every stock in the S&P 500 would perform over the next 12 months. Even with perfect knowledge, if you were limited by how active/different you could be from the benchmark, you’d be unable to realize the full potential of your power.
Here is what we do. On every date through history (1962-2015), we build portfolios that will achieve the highest possible 1-year forward excess return at each level of active share between 0% and 90% . We use only stocks in the S&P 500 itself and allow a maximum position size of 5% in the portfolios, to avoid piling into just a few of the best-performing stocks.
This chart shows the maximum possible excess return (average of all historical periods) vs. the S&P 500 by active share level.
The more overlap with the market (lower active share), the less potential alpha exists. If you could only have 10-20% of your portfolio distinct from the benchmark, your Cassandra-like foresight would allow you to outperform by 20-30% per year. If you move up to an active share of 80-90, your potential expands to 80-90% per year.
Here is the same data for each calendar year:
Some years, like 2009, hold enormous potential for active management to outperform. Other years, like 1984, hold less potential. But every single year has the same characteristic upward slope.
The Bad News
At this point, I am sure you are thinking: “great, but this “potential” cuts both ways. Being more active also means I can
underperform
by wider and wider margins.” Well, that is very true. Here is the dark side of active share.
On the dark side, the years with the greatest potential for underperformance are big up years for the market. In 1998, with the S&P up 30% or so, it was possible to build a portfolio with an active share of 90% that was down 51% overall, for an underperformance of 81%. After 1998, the next years with the greatest potential for underperformance were 1999, 1982, 1997, 1991, and 1995–all years where the S&P 500 was up big.
The years with the widest spread of potential (the widest gap between potential on the upside and potential on the downside) were, in order, 1999, 2009, 1991, 1998, 2000, and 2003. Years with the narrowest spreads were 1977, 1966, 2006, 1984, and 1964.
Bottom line
What is amazing is that in the early 1980’s, well over half of mutual funds had an active share above 80%, but as of 2009, only 20% or so of funds were this active[i]. In 1950, between 7-8% of the market was managed by large institutions. In 2010, that number was 67% [ii] . Investment “products” are increasingly homogenous, coalescing around indexes and titled variations of those indexes.
In the final chart, we combine best and worst and show the spread between them. At any given level of active share, the “potential” excess return skews more to the positive (dotted-line). More active portfolios have more potential for excess than less active portfolios. No one has perfect foresight, so nobody achieves alpha like this with any consistency. But these “best case scenarios” show the potential of being different–both good and bad.
Note: thanks to Manson Zhu for running the optimizations behind these charts
http://hvst.co/1Rh10dp
