Factor Investing Explicitly Tries to Look Lousy on Active Share

by Clifford Asness, Ph. D. AQR Capital Management, Inc.

There has already been much ink, and maybe even some blood, spilled debating the merits of ā€œActive Shareā€ for judging an investment fund. There was the original paper, a critique of that paper written by some of my colleagues, a reasonable (which doesnā€™t mean I agree with it) response to AQRā€™s piece, and even a seriously derangedĀ  1 Ā response to my colleaguesā€™ work (thankfully Iā€™m known for a certain aplomb and even sangfroid in such tense situations and have helped calm everyone down). I donā€™t seek to re-open this debate but, rather, to focus on one aspect of it.

Admittedly itā€™s an aspect near and dear to my heart and wallet. I believe (hope) this aspect of the debate is so clear that all sides can agree. Active Share may or may not make sense for judging traditional active discretionary stock pickers (and when I say ā€œmake senseā€ I mean on its own and versus other measures such as tracking error). However, Active Share clearly makes no sense, and is, in spirit, explicitly backwards for judging direct factor investors (or quantitative investors, or smart beta investors, or style investors, or structured investors; all of which I consider near synonyms with different marketing labels ā€” I havenā€™t even come very close to covering all the possible options so let the semantic wars rage on!).

Hereā€™s a brief and probably insufficient review. Having a metric to judge how much long-only active portfolios differ from their benchmarks is clearly useful. While obviously useful to know how much relative risk one is taking, itā€™s also particularly useful for judging the value proposition of such an investment. That is, paying a lot in fees for small deviations (closet indexing) is probably a bad idea. The proponents of Active Share argue that besides detecting closet indexing itā€™s also a good metric for judging these managersā€™ average skill and a better metric than some other possible candidates. That is a bit different and goes further. Theyā€™re saying higher Active Share (bigger bets vs. the index on the Active Share scale) is, on average, also indicative of delivering more alpha (with all the difficulties judging ā€œalphaā€ can present) and other major alternatives not as useful.

Explicitly or implicitly Active Share is, and must always be, judged against alternative methods of making similar judgments. The most prominent alternative is ā€œtracking error.ā€ Active Share essentially doesnā€™t use statistics. It simply adds up the size of the active managersā€™ deviations from the index without regard for whether theyā€™re making an active bet in a volatile stock versus doing so in a calm stock, or whether many or few of their active bets are highly correlated with one another. For instance, if an active manager took ten separate stock bets all the same dollar size and each bet was overweighting stocks in the same industry, tracking error would invariably say this is riskier (a bigger active bet) than if the stocks were all in very different industries (a more diversified and thus lower tracking error bet). In contrast, Active Share is indifferent and would report the same result either way. You can make an argument for either tracking error or Active Share (and the linked papers above certainly do!). Active Share has the virtue, and perhaps handicap, of great simplicity where tracking error perhaps has the negative of being dependent on estimates of the volatilities and correlations among stocks (that is, two different analysts calculating Active Share will usually come up with the same number while this is not necessarily true for tracking error 2 ). I think itā€™s pretty clear, at least in this and in similar examples, that tracking error isĀ a better estimate of the risk taken versus the benchmark (ignoring the correlation and volatility of bets, even if measured imperfectly, seems pretty serious for estimating risk). That would, presumably, not surprise Active Share proponents as itā€™s not their main goal. Where it gets interesting is evaluating claims that one or the other measure also tells us where manager skill is likely to exist.

Now why would Active Share be better than tracking error as a proxy for manager conviction and therefore, perhaps, manager skill? 3 Ā For instance, it may be the case that managers are really good at one part of what they do (e.g., picking stocks within industries to continue with that example) but really bad at other things (e.g., picking industries 4 ) so, in this hypothetical case, if higher tracking error comes from industry concentration it is actually not more value for the fee dollar but just risk without reward. In this case, tracking error may be the better estimate of the actual risk taken (again youā€™d certainly hope so) but not a better measure of where skill or value-added comes from. Shocking to no one, I tend to side with AQRā€™s arguments that cast doubt on Active Shareā€™s ability to forecast where skills lies (in the absolute and relative to tracking error). But, I do think there are reasonable points and arguments on both sides and the debate should continue (sans the most seriously deranged contributions).

All that brings us to my real point (I had you worried I wouldnā€™t get there, right?). Direct factor investing (or any of its near synonyms) is a different ball game from traditional active stock picking. Specifically, Active Share, in particular when compared with tracking error, makes little to no sense for direct intentional factor tilted long only portfolios. These portfolios arenā€™t just different on the surface from traditional active stock picking. They are different in a far deeper way. They are only about getting exposure to the desired factor or factors while taking as little other exposures as possible (in this essay I always mean exposure as versus the index ā€” the same exposure/risk that Active Share and tracking error deal with). That entails minimizing exposure to unwanted factors (everything but the desired factor or factors) and maximizing exposure to desired ones (the desired factor or factors). Perhaps most importantly, it implicitly entails taking as little specific stock risk as possible while pursuing the earlier goals (the ā€œrightā€ factor exposure). For instance, a running issue in my life is, when questioned by the media, sometimes, even after we explicitly ask them not to, I still get asked ā€œwhatā€™s your favorite stock?ā€ I usually respond, often to an incredulous questioner who looks at me like Iā€™m just a little slow or addled, ā€œI donā€™t knowā€ (truth be told I say that even if I do know as itā€™s kind of fun and lets me go on to make the bigger point).

Put another way, an imperfect yet useful way to think of factor or smart beta investing is an attempt, relative to the index, to bet on the factor or factors you believe in, not bet on those you donā€™t, while otherwise implicitly minimizing Active Share. 5 Ā One can like or dislike these products (shockingly, please put me mostly in the ā€œproā€ camp) but it seems really odd to judge them on whether they have enough Active Share when minimizing Active Share is a lot of the point!.

Factor or smart beta products simply drive the biggest wedge between the simple ways like Active Share and the more complex (though not really that hard) methods like tracking error. You can get a lot of tracking error with factor bets 6 Ā ā€” but, if done competently, itā€™s all about the factor bets not about stock specific risk which, again, factor investing explicitly tries to minimize. This is a case, judging the active risk of factor or smart beta portfolios, where tracking error is tailor made to pick up this kind of deviation from the index (factor bets) while Active Share is tailor-made to ignore most of it. I venture if we look for portfolios where tracking error and Active Share give the most different answers, weā€™d find direct factor investing yields some of todayā€™s extremes, and are much more prevalent today than in 2009 (the publication date of the first Active Share paper).

Others have, while not generalizing it as I do here, done a good job of recognizing this too. For instance, Research Affiliates has a piece where they say:

Because RAFI portfolios are broadly diversified, they tend to have a relatively low Active Share of 30%. RAFI portfolio excess returns are made more attractive because they are achieved in a smooth fashion, with a low tracking error of 4% (relative to 8% for active managers). Accordingly, the RAFI approach provides the best of both worldsā€”strong excess returns without the big out-of-index risks active managers takeā€”as Table 1 shows.

Note, they are explicitly and correctly bragging about having a low Active Share (remember, the proponents of Active Share believe that tends to indicate a bad economic deal and, even more controversially, a lack of conviction that they claim leads to poorer relative returns). Research Affiliates gets it right here. As a provider of factor or smart beta products they are, and should be, proud of a low Active Share. Itā€™s really quite obvious ā€“ again, for the same factor bet youā€™re doing it better if you can deliver it with a lower Active Share. And the argument that low Active Share means low conviction, and perhaps poorer results, is obviously inapplicable when stock-by-stock selection is explicitly eschewed and minimized and the conviction you have is all about the factor bets!

So, by all means, letā€™s all continue to explore and debate the relative merits of Active Share, tracking error, and perhaps other methodologies. Letā€™s continue to debate these, both for the notion of ā€œwhat am I getting for the fee paid?ā€ and for the related, but separate, point of ā€œcan any of these measures indicate more or less skillful managers?ā€

But, I hope we can all agree that factor or smart beta portfolios represent an important special case where Active Share is not a particularly applicable measure and may even be backwards. 7 Ā In fact, if future research can ex ante distinguish funds by whether they are systematic factor or smart beta portfolios by design, perhaps weā€™ll even get better empirical evidence on the very questions about Active Share vs. tracking error weā€™re debating, as weā€™ll exclude the places where we know Active Share makes little sense.

But, for now, factor investors shouldnā€™t be ashamed of, but rather should wear their low Active Share measures proudly, as itā€™s kind of the point.

This post was originally published at AQR Capital

Copyright Ā© AQR Capital

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