A PDF version of this post is available for download here.
Summary
- In an ideal world, all investors would outperform their benchmarks. In reality, outperformance is a zero-sum game: for one investor to outperform, another must underperform.
- If achieving outperformance with a certain strategy is perceived as being “easy,” enough investors will pursue that strategy such that its edge is driven towards zero.
- Rather, for a strategy to outperform in the long run, it has to be hard enough to stick with in the short run that it causes investors to “fold,” passing the alpha to those with the fortitude to “hold.”
- In other words, for a strategy to outperform in the long run, it must underperform in the short run. We call this The Frustrating Law of Active Management.
A few weeks ago, AQR published a piece titled Craftsmanship Alpha: An Application to Style Investing[1], to which Cliff Asness wrote a further perspective piece titled Little Things Mean a Lot[2].
We’ll admit that we are partial to the title “craftsmanship alpha” because portfolio craftsmanship is a concept we spend a lot of time thinking about. In fact, we have a whole section titled Portfolio Craftsmanship on the Investment Philosophy section of our main website.[3] We further agree with Cliff: little things do mean a lot. We even wrote a commentary about it in May titled Big Little Details[4].
But there was one quote from Cliff, in particular, that inspires this week’s commentary:
Let’s just make up an example. Imagine there are ten independent (uncorrelated) sources of “craftsmanship alpha” and that each adds 2 basis points of expected return at the cost of 20 basis points of tracking error from each (against some idea of a super simple “non-crafted” alternative.) Each is thus a 0.10 Sharpe ratio viewed alone. Together they are expected to add 20 basis points to the overall factor implementation inducing 63 basis points of tracking error (20 basis points times the square-root of ten). That’s a Sharpe ratio of 0.32 from the collective craftsmanship (in addition to the basic factor returns).
[…]
But, as many have noted in other contexts, a Sharpe ratio like 0.32 can be hard to live with. Its chance of subtracting from your performance in a given year is about 37%. Its chance of subtracting over five years is about 24%. And, wait for it… over twenty years the chance it subtracts is still about 8%. That’s right. There’s a non-trivial chance your craftsmanship is every bit as good as you think, and it subtracts over two full decades, perhaps the lion’s share of your career. Such is the unforgiving, uncaring math.
Whether it is structural alpha, style premia, or craftsmanship alpha: we believe that the very uncertainty and risk that manifests as (expected) tracking error is a necessary component for the alpha to exist in the first place.
The “unforgiving, uncaring math” that is a result – the fact that you can do everything right and still get everything wrong – is a concept that in the past we have titled The Frustrating Law[5] of Active Management.
Defining The Frustrating Law of Active Management
We define The Frustrating Law of Active Management as:
For any disciplined[6] investment approach to outperform over the long run, it must experience periods of underperformance in the short run.
As if that were not frustrating enough a concept – that even if we do everything right, we still have to underperform from time-to-time – we add this corollary:
For any disciplined investment approach to underperform over the long run, it must experience periods of outperformance in the short run.
In other words, even if a competing manager does everything wrong, they should still be rewarded with outperformance at some point. Talk about adding insult to injury.
For the sake of brevity, we will only explore the first half of the law in this commentary. Note, however, that the second law is simply the inverse case of the first. After all, if we found an investment strategy that consistently underperformed, we could merely inverse the signals and have a strategy that consistently outperforms. If the latter is impossible, so must be the former.
For it to work, it has to be hard
Let’s say we approach you with a new investment strategy. We’ve discovered the holy grail: a strategy that always outperforms. It returns an extra 2% over the market, consistently, every year, after fees.
Ignoring reasonable skepticism for a moment, would you invest? Of course you would. This is free money we’re talking about here!
In fact, everyone we pitch to would invest. Who wouldn’t want to be invested in such a strategy? And here, we hit a roadblock.
Everyone can’t invest. Relative performance is, after all, zero sum: for some to outperform, others must underperform. Our extra return has to come from somewhere.
If we do continue to accept money into our strategy, we will begin to approach and eventually exceed capacity. As we put money to work, we will create impact and inform the market, driving prices away from us. As we try to buy, prices will be driven up and as we try to sell, prices will be driven down. By chasing price, our outperformance will deteriorate.
And it needn’t even be us trading the strategy. Once people learn about what we are doing – and how easy it is to make money – others will begin to employ the same approach. Increasing capital flow will continue to erode the efficacy of the edge as more and more money chases the same, limited opportunities. The growth is likely to be exponential, quickly grinding our money machine quickly to a halt.
So, the only hope of keeping a consistent edge is in a mixture of: (1) keeping the methodology secret, (2) keeping our deployed capital well below capacity, and (3) having a structural moat (e.g. first-mover advantage, relationship-driven flow, regulatory edge, non-profit-seeking counter-party, etc).
While we believe that all asset managers have the duty to ensure #2 remains true (we highly recommend reading Alpha or Assets by Patrick O’Shaughnessy[7]), #1 pretty much precludes any manager actually trying to raise assets (with, perhaps, a few limited exceptions in the hedge fund world that can raise assets on brand alone).
The takeaway here is that if an edge is perceived as being easy to implement (i.e. not case #3 above) and easy to achieve, enough people will do it to the point that the edge is driven to zero.
Therefore, if an edge is known by many (e.g. most style premia like value, momentum, carry, defensive, trend, etc), then for it to persist over the long run, the outperformance must be difficult to capture. Remember: for outperformance to exist, weak hands must at some point “fold” (be it for behavioral or risk-based reasons), passing the alpha to strong hands that can “hold.”
This is not just a case of perception, either. Financial theory tells us that a strategy cannot always outperform its benchmark with certainty. After all, if it did, we would have an arbitrage: we could go long the strategy, short the benchmark, and lock in certain profit. As markets loathe (or, perhaps, love) arbitrage, such an opportunity should be rapidly chased away. Thus, for a disciplined strategy to generate alpha over the long run, it must go through periods of underperformance in the short-run.
Can We Diversify Away Difficulty?
Math tells us that we should be able to stack the benefits of multiple, independent alpha sources on top of each other and simultaneously benefit from potentially reduced tracking error due to diversification.
Indeed, mathematically, this is true. It is why diversification is known as the only free lunch in finance.
This certainly holds for beta, which derives its value from economic activity. In theory, everyone can hold the Sharpe ratio optimal portfolio and introduce cash or leverage to hit their appropriate risk target.
Alpha, on the other hand, is explicitly captured from the hands of other investors. Contrary to the Sharpe optimal portfolio, everyone cannot hold the Information ratio optimal portfolio at the same time[8]. Someone needs to be on the other side of the trade.
Consider three strategies that all outperform over the long run: strategy A, strategy B, and strategy C. Does our logic change if we learn that strategy C is simply 50% strategy A plus 50% strategy B? Of course not! For C to continue to outperform over the long run, it must remain sufficiently difficult to stick with in the short-run that it causes weak hands to fold.
Conclusion
For a strategy to outperform in the long run, it has to be perceived as hard: hard to implement or hard to hold. For public, liquid investment styles that most investors have access to, it is usually a case of the latter.
This law is underpinned by two facts. First, relative performance is zero-sum, requiring some investors to underperform for others to outperform. Second, consistent outperformance violates basic arbitrage theories.
While coined somewhat tongue-in-cheek, we think this law provides an important reminder to investors about reasonable expectations. As it turns out, the proof is not always in the eating of the pudding. In fact, track records can be entirely misleading as validators of an investment process. As Cliff pointed out, even if our alpha source has a Sharpe ratio of 0.32, there is an 8% chance that it subtracts from performance over the next 20-years.
Conversely, even negative alpha sources can show beneficial performance by chance. An alpha source with a Sharpe ratio of -0.32 has an 8% chance that it adds to performance over the next 20-years.
And that’s why we call it The Frustrating Law of Active Management. For investors and asset managers alike, there is little more frustrating than knowing that to continue working over the long run, good strategies have to do poorly, and poor strategies have to do well over shorter timeframes.
[1] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3034472
[2] https://www.aqr.com/cliffs-perspective/little-things-mean-a-lot
[3] https://www.thinknewfound.com/investment-philosophy
[4] https://blog.thinknewfound.com/2017/05/big-little-details/
[5] To be clear that we don’t mean a “law” in the sense of an inviolable, self-evident axiom. In truth, our “law” is much closer to a “theory.”
[6] The disciplined component here is very important. By this, we mean a strategy that applies a consistent set of rules. We do not mean, here, a bifurcation of systematic versus discretionary. Over the years, we’ve met a large number of discretionary managers who apply a highly disciplined approach. Rather, we mean those aspects of an investment strategy that can be codified and turned into a set of systematically applied rules.
Thus, even a discretionary manager can be thought of as a systematic manager plus a number of idiosyncratic deviations from those rules. The deviations must be idiosyncratic, by nature. If there was a consistent reason for making the deviations, after all, the reason could be codified itself. Thus, true discretion only applies to unique, special, and non-repeatable situations.
Note that the discipline does not preclude randomness. You could, for example, flip a coin and use the result to make an investment decision every month. So long as the same set of rules is consistently applied, we believe The Frustrating Law of Active Management applies.
[7] http://investorfieldguide.com/alpha-or-assets/
[8] Well, technically they can if everyone is a passive investor. In this case, however, the information ratio would be undefined, with zero excess expected return and zero tracking error.
Your Style-age May Vary
By Corey Hoffstein
On August 12, 2019
In Portfolio Construction, Risk & Style Premia, Weekly Commentary
This post is available as PDF download here.
Summary
When quants speak about factor and style returns, we often do so with some sweeping generalizations. Typically, we’re talking about some long/short specification, but precisely how that portfolio is formed can vary.
For example, one firm might look at deciles while another looks at quartiles. One shop might equal-weight the holdings while another value-weights them. Some might include mid- and small-caps, while others may work on a more realistic liquidity-screened universe.
More often than not, the precision does not matter a great deal (with the exception of liquidity-screening) because the general conclusion is the same.
But for investors who are actually realizing these returns, the precision matters quite a bit. This is particularly true for long-only investors, who have adopted smart-beta ETFs to tap into the factor research.
As we have discussed in the past, any active portfolio can be decomposed into its benchmark plus a dollar-neutral long/short portfolio that encapsulates the active bets. The active bets, then, can actually approach the true long/short implementation.
To a point, at least. The “shorts” will ultimately be constrained by the amount the portfolio can under-weight a given security.
For long-only portfolios, increasing active share often means having to lean more heavily into the highest quintile or decile holdings. This is not a problem in an idealized world where factor scores have a monotonically increasing relationship with excess returns. In this perfect world, increasing our allocation to high-ranking stocks creates just as much excess return as shorting low-ranking stocks does.
Unfortunately, we do not live in a perfect world and for some factors the premium found in long/short portfolios is mostly found on the short side.1 For example, consider the Profitability Factor. The annualized spread between the top- and bottom-quintile portfolios is 410 basis points. The difference between the top quintile portfolio and the market, though, is just 154 basis points. Nothing to scoff at, but when appropriately discounted for data-mining risk, transaction costs, and management costs, there is not necessarily a whole lot left over.
Which leads to some interesting results for portfolio construction, at least according to a recent study by Axioma.2 For factors where the majority of the premium arises from the short side, tilting less might mean achieving more.
For example, Axioma found that a portfolio optimized maximize exposure to the profitability factor while targeting a tracking error to the market of just 10 basis points had a meaningfully higher correlation than the excess returns of a long-only portfolio that simply bought the top quintile. In fact, the excess returns of the top quintile portfolio had zero correlation to the long/short factor returns. Let’s repeat that: the active returns of the top quintile portfolio had zero correlation to the returns of the profitability factor. Makes us sort of wonder what we’re actually buying…
Source: Kenneth French Data Library; Calculations by Newfound Research.
Cumulative Active Returns of Long-Only Portfolios
So, what does it actually mean for long-only investors when we plot long/short equity factor returns? When we see that the Betting-Against-Beta (“BAB”) factor is up 3% on the year, what does that imply for our low-volatility factor ETF? Momentum (“UMD”) was down nearly 10% earlier this year; were long-only momentum ETFs really under-performing by that much?
And what does this all mean for the results in those fancy factor decomposition reports the nice consultants from the big asset management firms have been running for me over the last couple of years?
Source: AQR. Calculations by Newfound Research.
We find ourselves back to a theme we’ve circled many times over the last few years: style versus specification. Choices such as how characteristics are measured, portfolio concentration, the existence or absence of position- and industry/sector-level constraints, weighting methodology, and rebalance frequency (and even date!) can have a profound impact on realized results. The little details compound to matter quite a bit.
To highlight this disparity, below we have plotted the excess return of an equally-weighted portfolio of long-only style ETFs versus the S&P 500 as well as a standard deviation cone for individual style ETF performance.
While most of the ETFs are ultimately anchored to their style, we can see that short-term performance can meaningfully deviate.
Source: CSI Analytics. Calculations by Newfound Research. Results are hypothetical. Results assume the reinvestment of all distributions. Results are gross of all fees, including, but not limited to, manager fees, transaction costs, and taxes, with the exception of underlying ETF expense ratios. Past performance is not an indicator of future results. Year-to-Date returns are computed by assuming an equal-weight allocation to representative long-only ETFs for each style. Returns are net of underlying ETF expense ratios. Returns are calculated in excess of the SPDR&P 500 ETF (“SPY”). The ETFs used for each style are (in alphabetical order): Value: FVAL, IWD, JVAL, OVLU, QVAL, RPV, VLU, VLUE; Size: IJR, IWM, OSIZ; Momentum: FDMO, JMOM, MMTM, MTUM, OMOM, QMOM, SPMO; Low Volatility: FDLO, JMIN, LGLV, OVOL, SPLV, SPMV, USLB, USMV; Quality; FQAL, JQUA, OQAL, QUAL, SPHQ; Yield: DVY, FDVV, JDIV, OYLD, SYLD, VYM; Growth: CACG, IWF, QGRO, RPG, SCHG, SPGP, SPYG; Trend: BEMO, FVC, LFEQ, PTLC. Newfound may hold positions in any of the above securities.
Conclusion
In our opinion, the research and data outlined in this commentary suggests a few potential courses of action for investors.
Academically, we might be able to argue for one approach over another. Practically, the appropriate solution is whatever is most suitable for the investor and the approach that they will be able to stick with.
If a client measures their active returns with respect to academic factors, then understanding how portfolio construction choices deviate from the factor definitions will be critical.
An advisor trying to access a style but not wanting to risk choosing the wrong ETF might consider asking themselves, “why choose?” Buying a basket of a few ETFs will do wonders to reduce specification risk.
On the other hand, if an investor is simply trying to maximize their compound annualized return and nothing else, then a concentrated approach may very well be warranted.
Whatever the approach taken, it is important to remember that results between two strategies that claim to implement the same style can and will deviate significantly, especially in the short run.