Alpha’s Not Dead!
Some of you may recall the early ’80s punk rock rally cry, “Punk’s not dead!” Given the recently announced Rage Against The Machine (RATM) tour, I would tend to agree. We can quibble later over whether RATM falls into the same category as the Dead Kennedys, Black Flag, Suicidal Tendencies, Channel 3 and of course, The Sex Pistols (spoiler alert: IMHO, they do if only for the energy and anti-establishmentarianism), but the point here is that alpha—despite what you may have read and heard—is indeed very much alive and well.
Before we discuss the hows and whys behind alpha not being dead, let’s take a look at what is meant by “passive.”
From a spherical cow-land perspective, I would say the only indexes that are truly passive are those labelled as “composites” like the NYSE Composite Index, which is simply the index of everything listed on the NYSE—no sector, no market cap constraints, earnings or other factors and arguably other bias being considered for selection, no seasoning; if you’re listed, you’re in, from your IPO date until you delist.
The Russell family of indexes has an underlying methodology that is fairly agnostic as well with market capitalisation, domicile and listing venue as primary drivers for inclusion. There are some eligibility rules around voting rights, but nothing that speaks directly to components’ fiscal health or viability as an ongoing concern.
Is The S&P 500 Index Active?
Let’s shift now to the $7+ trillion gorilla in the room, the Standard and Poor’s 500 Index (SPX)—the benchmark of benchmarks, the standard bearer of passive investing.
There are some broad rules around market capitalisation, liquidity and surprisingly, financial viability and earnings.
Depending on your point of view, these rules are either general mechanisms to help simplify the process of focusing on relevant components, or they are conscious decisions meant to shape the constituent pool into one with desirable (as deemed by S&P) characteristics.
Either way, the effect of these rules is to create a universe of components that are ready to run the gauntlet of the next set of rules that will get us to the final list of index constituents.
Index constituent selection is covered on page 10 of the methodology. Here we go. Here’s how the SPX sausage gets made: “Constituent selection is at the discretion of the Index Committee and is based on the eligibility criteria.”
Some may want to read that again…
How often are index components reviewed for suitability? Does that happen on an annual or semi-annual basis?
From page 26, “Changes to index composition are made on an as-needed basis. There is no scheduled reconstitution.”
So outside of some pretty wide gate rules, final component selection for SPX is completely discretionary and can occur at any time deemed appropriate by the index provider?
Isn’t this the very definition of an actively managed portfolio?
This methodology is used for the S&P 500 (SPX), the S&P Midcap 400 (MID) and the S&P Smallcap 600 (SML). I’m not saying that S&P has been deceiving us all these years. Clearly this information has been available for some time.
It does, however, set the stage for some further revelations and discussions. If SPX, MID and SML are actively managed indexes, then any derivative of them is also an actively managed index, including Select Sector Indexes.
We all know that the holy grail of active investing is to consistently outperform SPX. What then is the holy grail of passive investing? To deliver the exact returns of the tracked index? Operationally yes, but if you talk to an average passive money manager, their holy grail is finding (or in some cases creating) an index that will outperform SPX.
If the target isn’t SPX, then guess what? Those managers want to provide their clients with the best representation of the chosen strategy. What strategy? Where do these investing ideas come from? How are they generated?
Where It Gets Interesting
One of the hallmarks of research and investing is the Global Industry Classification Standard (GICS), which was developed in 1999 by Standard and Poor’s and MSCI. When investors talk about “financials” or any of the other 10 sectors, they really mean to say, “listed equities of companies that generate revenue from activities determined by S&P and MSCI to fall into the category of financial services.”
Many investors have come to rely on GICS as the springboard for not just classifying companies but creating a framework for discussing those segments of the economy. What happens when the economy decides to start colouring outside the GICS lines?
To paraphrase, if a new economic sector emerges, and there’s no mapping for it, does it make a sound? The answer here is that those companies end up getting misclassified, and that emerging segment of economic activity isn’t acknowledged at all.
In my career, I’ve developed a number of indexes tracked by ETFs focusing on emerging areas of economic activity, including wind energy, cloud computing, cybersecurity, e-payments, video games, big data, immunotherapy and cyber/privacy. Some of these were developed entirely from whole cloth and others with research partners, most notably Ted Pollak, Brad Loncar and Tematica Research (on cyber/privacy).
To be clear, when I say “emerging areas of economic activity,” I mean that there are now enough companies with high enough revenue exposure to support a diversified 1940 Investment Act or UCITS qualified investment vehicle at scale. What is important to also note is that, up until recently, tracking an index was essentially the only way to get an exchange-traded product approved and out to market.
The one thing all of these strategies have in common is that these segments did not (and still do not) have unique representation in the GICS framework. The other thing that these strategies share is the outlook that these groupings of stocks will outperform the market. These strategies are not GICS sector or SPX rebranding exercises. They are all alpha seeking. Some have been more successful than others, but the goal here is performance.
I think what some investors forget is that the end of the pre-Regulation Fair Disclosure (Reg FD) world not only coincided with the exponential growth of the internet but (especially in the last 10 years) the rise of the information age. In today’s Python-enabled world, your average investor has access to not only the same information but many of the same tools (or has the ability to develop them) as just about any investment firm.
The markets have become vastly more efficient, and as hunting for individual names has gotten easier, everything seemingly has become a crowded trade. If your definition of “alpha is dead” means everything is a crowded trade, you might as well be standing in the middle of the Frozen Orange Juice Futures pit shouting, “Turn those machines back on!”
Alpha seeking has evolved from those hard-to-find single-name high variance trades into one of two things:
- Brute-force-optimised quant models (smart beta/factor investing)
- Qualitatively focused thematic portfolios (macro trends/emerging economic activity)
For large firms looking to enter the ETF marketplace using the “bring your own assets” approach, the safest way to transition those assets is to model out their existing active approach (smart beta/factor). For newer or smaller firms, capturing lightning in a bottle with a novel strategy can be very rewarding. The (literal) trials and tribulations of small firms are best left for another article.
In any event, my point still stands that, regardless of label, all investors (even shareholders of defined outcome products) are alpha seeking, and that alpha—despite what you may have read and heard—is indeed alive and well.
Now who’s got tickets for that Rage Against The Machine show?
This Featured Article has been produced by Tematica Research LLC. Rize ETF Ltd make no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability or suitability of the information contained in this article.
 S&P Global, “S&P U.S. Indices Methodology”, Page 10, Available at: https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-us-indices.pdf