I say this as someone who is as addicted to efficiency as anyone I know. I have a chart – not a mental chart, but an actual on-paper chart – of which of the three specific routes I should take to my office by day and time. I almost never schedule same-day meetings because I find it disruptive to planned periods of work on certain projects. I set up a mise en place for making Kraft Mac & Cheese for my kids, for God’s sake. My biggest average allocation to public markets in non-taxable accounts for several years has been to risk parity. Much of the rest has sat in systematic trend-following and behavioral premia strategies. I am an optimizer, y’all.
Yet I have also spent my career as an allocator to investment strategies observing what both explicit and implicit goal-seeking does to investors and their processes.
I’m not really talking about the robustness of objective-function optimized portfolios to changes in key variables or estimation methodologies, although just a shred of epistemic humility in portfolio construction would go a long way with some quants. I’m also not really talking about the mean-variance frontier-plotting and JP Morgan GTTM-driven Monte Carlo slides I see being put in front of clients (and which I have, from time to time, put in front of them myself). Feel seen? Throw a rock in the air and you’ll hit someone guilty.
But what I really mean is this:
Our need to manage common knowledge about multiple competing objectives in an optimization-centric framework makes us into professional cartoonists.
The Lip-Service Cartoon
I’m not saying anything outlandish here. If you’re a professional investor, you’ll be familiar with this – especially the lip-service cartoon. This is the one where we pretend – and ask everyone else to pretend – that our secondary and tertiary objectives or constraints are conveniently totally achievable without impacting our primary pursuit, even when they’re not.
I have written about this recently in context of post-secondary education, where optimization’s effects are obvious. The stories we tell about college are that it ought to serve three objectives, usually all at once:
College should broaden horizons, providing a foundation of historical, philosophical, aesthetic and scientific knowledge and the critical thinking needed to process problems raised by or answerable using that knowledge;
College should prepare students to enter and be successful in a profession; and
College should provide an environment for the socialization, personal growth and independence of young adults.
In practice, by any realistic measure of revealed preferences American universities don’t really optimize for any of these things. As we have argued, we think they mostly target maximizing the signal sent about the underlying intellectual, temperamental and socioeconomic and demographic traits of their degree-holders, because, well, that’s what our culture has permitted and what alumni donors demand.
Is it true that critical study of history, philosophy and language can improve the quality of thinking? Of course it is! If you’ve been reading Epsilon Theory very long, you will know that we believe the same Big Ideas tend to permeate almost every area of human activity, and that identifying those variants and their memetic attachments in the wild can be a meaningful advantage to our thinking. You’ll also know that we are passionate about the human importance of art and creation. The cartoon isn’t in recognizing the importance of these things. It isn’t even in recognizing that they may have some value for multiple objectives. The cartoon is in our pretense that coursework in music theory and the emergence of proto-Celtic language and cultures from other Beaker societies will be just as important to professional pursuits or personal growth of young adults as it is to living an enriched life. By corollary, however many hours you spend studying Kant, it won’t make you as good at your job as spending the same amount of time doing that job or preparing more directly for it.
To maintain the cartoon, we must pretend that it will.
Our pressure to create these cartoons can be traced to our sensitivity to common knowledge about those secondary and tertiary objectives that we are ‘balancing’. It is untenable – unacceptable – to be seen as not seeking out those objectives, and it is desirable under almost every governing narrative of the Zeitgeist to be seen as pursuing them. The inevitable result is that they get only as much of our energy and attention as is necessary to maintain the cartoon.
If you want to see this in financial markets, look no further than the methods your value managers provide for avoiding value traps (which will, I assure you, be disregarded as not being relevant in this particularcase when it suits them), most ESG overlays, and almost every risk report provided by a non-integrated risk team to the portfolio management team. Pro-tip: the more a PM you are interviewing goes on about how much having daily access to these risk statistics has really changed their thinking, the more full of shit they are.
In fairness, it isn’t that they’re lying – it’s that the cartoon permits them to act as if the balancing of multiple objectives is serendipitously bereft of any tradeoffs. Their process is just that good.
The Measurement Cartoon
Sometimes our cartoon isn’t that we wave our hands at potential tradeoffs between our objectives, pretending that some magical alignment of our ideas permits the kind of synergy never found in nature. Instead, the cartoon is the pretense that we have the capacity to measure what those trade-offs are, even when we don’t.
The most inevitable cartoons of this variety, I think, are those built around liquidity. Our industry gets the occasional reminder that liquidity matters, such as with the recent Woodford business in the UK, or the Third Ave blow-up a few years back. After those events, there’s usually a 12-18 month cycle in which people Really Care about it. They add a few more questions to their DD questionnaires, and once the answers from fund managers congeal around some standardized answer, the questions largely stop, other than in the most perfunctory way. That is, until the SEC passed 22e-4, a rule establishing the requirement for a liquidity risk management program for open-end investment companies. It requires the mapping and publishing of position liquidity in four different categories.
In this case, we have a rule requiring the creation of a cartoon, and lest anyone is laboring under any delusions here, that’s exactly what investors will get. I’ve provided below a helpful example of the rule, its standards, the cartoon responses investors will receive and the real response investors would get if the industry were concerned about telling them the truth:
The point, of course, is not that liquidity isn’t important. When it matters, it matters a lot. And when it matters a lot, things are happening that are often not quantifiable in ways that will make sense under any objective quantification scheme in a normal environment. Asset class flows, manager-specific flows, market direction and available position-level liquidity are all pro-cyclical. As has almost always been the case, these cartoons will tell a happy story about liquidity to investors…until it’s too late. In other words, the value ascribed to a liquidity bucket is an ephemeral, practically useless figure that gives false comfort and context to manager and investor alike.
There are other examples of how we optimize for multiple objectives by turning a complicated secondary objective that deserves our respect into a cartoon we hand over to ALPS, BNY or our internal risk management team. Highly leveraged funds whose managers have ever uttered the words ‘Cornish-Fisher expansion’ to a client, you are correctly detecting side-eye. In all such cases, there’s nothing disqualifying or wrong about using guideposts or systematic measures, but when we optimize for some key objective (return or volatility-adjusted return) and explain away others (maintaining adequate liquidity)by constructing a cartoon to ‘measure’ them away, we’re gonna have a bad time.
The Mitigant Cartoon
In still other circumstances, we know that we can’t measure a secondary thing we care about, so the hand-waving takes a different form. We don’t have measurements. We have mitigants.
To be fair, mitigants are real things. AND they are often the basis of cartoonish abstractions that allow us to dismiss important things we ought to honestly, fully consider. We know that excessive leverage and concentration in this strategy creates potentially outsized risks to the portfolio, but worry not: in portfolio transparency we have a powerful mitigant. We know that there’s an unusual capital structure which could permit the intentional impairment of our class of interest, but the principal is a public personality with long-term clients in the same class. These are strong mitigants, you see.
The problem with mitigant cartoons – and what distinguishes them from actual mitigants, is that they are among the most basic tools of confirmation bias. They provide ready answers to our concerns which, like our other cartoons, miraculously seem to support the unbridled pursuit of whatever our primary objective was in the first place.
When we build too much of our thinking around optimization instead of good-faith, knowingly messy, honest evaluation of conflicting facts and circumstances, we will inevitably find that all of our problems become just-so stories. They willperfectly explain, measure or mitigate away the things we have to be seen to care about but don’t. They will perfectly support our single-minded pursuit of the things we docare about.
The Half-Happy Horror
Look, the idea here isn’t that we can’t walk and chew gum at the same time. An incredible share of life is obviously about finding balance between conflicting things, priorities and ideas – whenever it’s possible to do that, that is. The idea also isn’t that we shouldn’t adopt systematic methodologies -quite the opposite, as I frankly think these tendencies to optimize are stronger for those who don’t constrain their processes to rules (yes, it is clearly quite possible to systematize predispositions in such rules, too).
The idea is simply that optimization of decisions involving multiple objectives and constraints – whether fully systematic, rules-based or discretionary – is the kind of thing that should always cause the responsible investor and citizen to step back. Especially when the alternative is often a solution that will make everyone half-happy, which in a zero-sum game is no solution at all.
What can that person do?
We can (try to) be honest with ourselves. If we have a constraint, a risk, or a secondary objective in our strategy we’re trying to balance with another, are we giving them lip service? Are we draping them in unwarranted quantification so that we can consider them ‘solved’? Are we clothing them in ‘mitigants’ so that we can check the box and move on?
We can focus on ANDs. The language we use to talk about multiple objectives often betrays our attention and the considerations we would just as soon wave our hands at. In my experience, it is critically important to start from a place that considers all facts as ANDs, rather than presuming their relationship to one another.
We can try to simplify our decisions. Where possible, simplifying decisions and our responses to them so that we truly can focus on a narrower set of objectives – not through abstraction, but in truth – can help a great deal. With portfolios, maintaining a lens to conceptualizing pools of capital as serving discrete objectives can be an effective management tool.
What’s next for U.S. equity markets, and what historical analogs might provide some insight? There are plenty of bullish pundits citing renewed monetary policy easing as a catalyst for higher equities – some even suggesting a melt-up could yet occur. While a surprise (at least to us) cut this week could propel equities higher for one last gasp, I’d not chase. Since my 2019 Outlook, I’ve been suggesting a ‘tale of two halves’ narrative for risk assets. In it, my team and I described a first half characterized by a correlated risk-on resulting from improved central bank communication, more reasonable valuation, and more favorable optics around China trade. This has largely occurred. In particular, our mid-year target for the S&P 500 was and remains 2,800, while our year-end target remains well below street consensus at 2,500.
The recent rally in U.S. equities is largely a result of market participants believing they can have their rate-cut cake and eat it, too.
Market participants’ Pavlovian response to a cut of any kind – regardless of context – has been well reinforced over the past ten years. As my team and I have pointed out, and as Figure 1 illustrates, a cut now would bode ill (as a signal rather than a cause) for the U.S. economy over at least the next year. Will the Fed cut in June? While in play, we don’t think the Fed will cut, as it would amount to preemptive action. There are three relevant precedents upon which market participants have relied to justify such preemptive Fed action.
Some argue that market conditions are analogous to 1995, when the Fed cut preemptively. I disagree. In our BIG Picture piece entitled Fed Reaction Function (dated April 20, 2019), my team and I presented our view that current conditions did not resemble 1995, and we continue to hold that view. As Figure 2 shows, when the Fed decided to cut in 1995, economic conditions were significantly worse than they are today. ISM manufacturing was deep in contraction, and at 5.6%, the unemployment rate was significantly higher than it is today. That said, the view has consistently been that the Fed will cut if equity markets risk-off by more than 15% or if there is a hard turn in the economic data, neither of which have occurred quite yet. Such conditions will likely manifest later in the year, especially if rates markets are as predictive as we think they are. It’s a matter of when – not if.
Eurodollar futures markets (ED1 – ED3
= 40bps) are implying an 80% chance of two cuts between June and December. This
suggests the Fed is too tight relative to economic conditions (Figure 3). The correlation between
10-year rates and ISM manufacturing show that ISM will move into contraction in
the near future (Figure 4).
Nonetheless, we don’t believe that the Fed will move before that happens – nor
should it. The equity markets and rates markets are severely disconnected, and
that disconnect is the result of expectations for market intervention from the
Fed, upon which markets have become far too reliant. My expectation is that
equity market volatility will precede the Fed’s next move. Certainly, with the
S&P 500 at ~2,900 amidst a global slowdown and flat U.S. earnings, the
risk-reward appears poor to owning U.S. equities.
Looking at another potential historical precedent, I also do not believe that the current situation is analogous to the early 1970s when President Nixon appointed Arthur Burns as the Chairman of the Federal Reserve. While we will leave the reader to his or her own conclusions about the similarities between Donald Trump and Richard Nixon, it would appear that Chairman Powell is far less naïve than the academic, Burns. On February 1, 1970, Burns, known as a Republican loyalist, took office. Preceding the 1972 election, Nixon is alleged to have instructed Burns to cut rates. Burns lowered funds starting in mid-1971 from 5.75% to 3.5% into March of 1972; GDP growth picked up to 5.6 % in 1972 from 3.3% the year prior. Inflation rates rose to 5.3% from 3.6%. This may have helped exacerbate the impact of the oil shock, which occurred as a result of an OAPEC oil embargo, which was retaliation for U.S. aid to Israel during the Yom Kippur War. While clearly there was a complex brew of potential causes, this policy period was followed by a considerable amount of asset volatility.
the kind of central bank coordination that occurred in February 2016 at G20 is
unlikely. Recall the backdrop from 2015 into 2016. A burgeoning China slowdown
and fears of an aggressive devaluation of the yuan catalyzed two selloffs – one
in late summer of 2015 and the other in early 2016. Complicating the U.S.
backdrop was a U.S. earnings recession and a rise in default rates amongst
energy companies that risked sparking a broader U.S. default cycle. The G20 meeting that year was in February in
Shanghai. At the time, my team and I failed to appreciate just how aggressive
and coordinated the global central bank policy response would be. After a
largely correct markets call for 2015, we failed to pivot bullishly enough on
this stimulus. Could we be making the same mistake here? We don’t think so.
For one thing, global central bank balance sheets are no longer expanding in aggregate. Figure 5 shows that 2015 equity market volatility (green lower panel) was quickly suppressed by an expansion of global central bank balance sheets (on a stable Fed balance sheet). Now conditions are quite different with the ECB no longer buying new bonds and the Fed selling its holdings. While rates volatility caused by higher rates has abated this year, rates are considerably higher here in the U.S. than in the rest-of-the-world and most developed market central banks remain on hold after only recently being in normalization mode. Lastly, there is no longer a post-crisis chorus of Kumbayah coming from world leaders. Instead, the world’s largest economies are embroiled in what appears to be a prolonged trade war. This makes coordination more difficult especially because many central banks are not independent of the governments engaged in the trade dispute. Lastly, we do not think the Fed wants to hand President Trump a rate cut into the G20 meeting simply because he asked for it. There must be an objective basis for Fed action.
we see a change in Fed’s modus operandi
in June that results in a cut? We believe a cut in June would require a
philosophical change in approach, as we would take it to be a preemptive move
influenced by the executive branch. This is why June is such an important
meeting. Were it to cut, policy would begin the slide down a slippery slope – a
slide back to ZIRP and back to QE (quantitative easing). While we hold the
unfortunate belief that all central banks will be at zero interest rates and
aggressive QE (including the Fed) in the not-so-distant future, we also think
the Fed wants to resist moving in that direction too quickly. Why? For one, the
Fed understands the inadvertent redistributive effects of its policy decisions.
compensate labor. Interest compensates owners of capital – credit investors, in
particular. As a result, rate cuts, which set the cost of capital, implicitly
make a wealth redistribution decision from credit investors to labor (in the
form of lower unemployment). Moreover, not only do central bank decisions lead
to wealth redistribution from creditors to labor, but low rates typically also discriminate
against credit investors in favor of equity capital providers (as the ‘Fed
model’ implicitly acknowledges). Moreover, a central bank decision to maintain
low rates effectively discriminates against retirees in need of income; thus,
there is an additional, unintended demographic consequence. Overall, current
workers and equity investors tend to be favored over retirees and credit
The unintended redistributive impact of Fed (and all central bank rate policy) comes largely without explicit legislative authority outside the Federal Reserve Act. Thus, in our view, the Fed still recognizes that the bar for central bank action in a capitalist economy should be relatively high. Historically, the Fed has generally viewed it as such through its data dependent approach and through its mandate to “maintain long run growth of the monetary and credit aggregates commensurate with the economy’s long run potential to increase production, so as to promote effectively the goals of maximum employment, stable prices and moderate long-term interest rates.” We would also note that “moderate long-term rates” seems to exclude both extremely high rates as well as extremely low rates. With the current condition of policy (as shown by Figure 6), the Fed would appear not to have cause to act just yet. Indeed, it’s our view that the Fed will eventually be compelled to move back to ZIRP (zero interest rate policy) over the course of the next couple of years as yet lower rates are required to maintain even the most meager of growth rates. Because we believe the Fed wishes to maintain precedent as well as its independence, it will remain reactive to the data – at least for June – but the data continues to evolve as we foresaw it in the beginning of the year.
 The 2019
Outlook was published on January 4th, 2019.
 To be clear:
I do think U.S. economic conditions will warrant a Fed cut in late summer and
another in fall. My team and I have been arguing strenuously since mid-year
2019 that global economic conditions were beginning to deteriorate and the U.S.
economy would follow late this year.
 While true,
the lean is clearly much more dovish than just a month ago, and emerging market
central banks have already started to move with Russia, for example, cutting
for the first time in 2-years.
 Statement on Longer-Run Goals and Monetary Policy Strategy, adopted effective January 24, 2012; as amended effective January 29, 2019.
If Don Corleone had all the judges and the politicians in New York, then he must share them, or let us others use them. He must let us draw the water from the well. Certainly he can present a bill for such services; after all… we are not Communists.
– Don Barzini, “The Godfather” (1972)
I catch a lot of grief for all of the Godfather references I make,
but for men of a certain age it remains the most powerful cinematic if not cultural
touchstone we’ve got. It’s also just really good narrative art.
This dinner of the Five Families is the heart of the Godfather
story arc. It’s where Vito realizes the scope and power of the plot against him
Barzini all along!”), and where he sets in motion a strategy of
revenge and redemption that plays out over a decade through his son, Michael.
Vito Corleone played a
mean metagame, the big picture game-of-games that can
define a life. Vito was a
clever coyote who, unlike most clever coyotes, didn’t allow
himself to be blinded by the passion of whatever immediate game was thrust upon
him, but was able to excel in the long game. In this case, the really long
What drove Vito in his metagame play?
What was his motivation?
“I worked my whole life, I don’t apologize, to take care of my family. And I refused to be a fool dancing on a string held by all of those big shots.”
I was at a dinner of about 20 Epsilon Theory pack members
down in Houston last month. I’ve been doing a couple of these meet-up dinners
of late, and I intend to do a lot more over the next 12 months. I got a
question at this dinner that I had never been asked before, a question that –
like Vito’s dinner with the other Dons – forced me to crystallize my metagame.
Hey, Ben, I think what you’re saying about society and politics and finding your pack is really important, and you say it really well. Why are you wasting your time talking so much about markets and investing? Why aren’t you writing full-time about what’s truly important?
It’s a question that I’ve thought about a ton, but never talked
about publicly. So here goes.
My goal in all things, but especially my metagame, is to act
non-myopically and in a way that treats others as autonomous ends in
themselves. It should be your goal in all things, too. You know the drill … Clear Eyes,
Full Hearts, Can’t Lose.
Acting with a full heart means two things: acting for Identity and
acting for Cooperation.
Or as Socrates would have said, Know Thyself, and as Jesus would
have said, Do Unto Others As You Would Have Them Do Unto You.
See, there’s really nothing new under the sun. Everything we write
in Epsilon Theory has been written before – and better – by teachers who
lived hundreds or even thousands of years ago. All you’re getting here is old
wine in a new bottle. It’s just really, really great wine. And a half-decent bottle
with Godfather quotes or farm animal stories on the label. You could do worse.
What’s my Identity?
I am a solver of puzzles and a player of games. This is who I have
always been, from my first childhood memories. This is my motivation. This is
my intrinsic spark and reward. This is my Aristotelian entelechy, to use a ten-dollar
phrase. This is my I AM, to use the Epsilon Theory lingo.
The market is the biggest puzzle there ever was. That’s why I
can’t stay away.
So in keeping with my Identity and our metagame at Epsilon
Theory, today I want to share with you a puzzle that I think Rusty and I
are solving. Not solved, because a) that’s impossible
in a three-body problem like the market, and b) it’s still early
days in the Narrative Machine research program. But we’ve completed enough
testing and research to have convinced ourselves at least that we are
onto something cool and important.
This is the market puzzle that we introduced in March with this note:
It’s our effort to apply our narrative research to an actual, honest-to-god practical investment question – can you measure the structure of financial media narratives in a way that gives a useful signal for underweighting or overweighting big market structures like S&P 500 sector ETFs?
At the conclusion of that note, after laying out our research
thesis and the way we were operationalizing our tests, I wrote this:
So I’m not going to talk about results until I can do it without telling a story, until I can show you results that speak for themselves. It’s like the difference between qualitatively interpreted narrative maps and algebraic calculations on the underlying data matrix … the difference between what we THINK and what we can MEASURE.
I know, I know … kind of a tease. But today I think we have
results that DO speak for themselves, so that’s what I’m going to let them do.
First a recap on our test procedures, although I’m going to keep
this really brief because you can read more in “The Epsilon
In addition to measuring the Sentiment of each article within a batch of financial news articles (something everyone does and we think is better thought of as a conditioner of narrative than as a structural component of narrative), we also measure the “weight” of one narrative structure relative to all the other narratives within a universe of media – what we call Attention – and the “center of gravity” of a narrative structure relative to itself over time – what we call Cohesion.
These are massive data matrices that we are evaluating, so the narrative map visualizations that we often publish in Epsilon Theory notes should be thought of as tremendous simplifications (2-D flattenings of many-D matrices) of the measurements we’re taking here. Still, I’ll incorporate some visualizations where I can.
For example, on the left is a 2-D visualization of the Attention score of the Utilities sector in December 2014. Every faint dot (also called a node) in the graph is a financial media article talking about the S&P 500 in some way, shape or form. There are thousands of these nodes, of course, clustered by all the different topics that drove stock market narrative that month. The dark nodes, few and far between, scattered among several different clusters, are the articles that are about the Utilities sector.
On the right is a 2-D visualization of the same data query and the same data sources for January 2015. What’s pretty clear even in this inherently truncated visualization is that the narrative Attention paid to the Utilities sector – the amount of media drum-beating about the Utilities sector – is much higher in January than in December.
We think this is a short signal for February 2015, by the way.
To be clear, we have ZERO insight into the fundamentals of the Utilities sector going into February 2015. We are NOT actually reading any of these media articles, and we really DON’T CARE what everyone’s opinion about the Utilities sector might be. All we know is that the financial media is shouting at investors to focus their attention on the Utilities sector in January 2015 … or at least shouting in a relative sense to how they were talking about Utilities in the prior month … and we believe that all this shouting has an effect on investor behavior. We believe that investors probably plowed into the Utilities sector in January 2015, so we want to be short (or underweight) this overbought sector in February 2015.
We came up with eight testable hypotheses like this, based on
states of the narrative-world as measured by Attention, Cohesion, and
Sentiment, and we ran a five year backtest on each hypothesized strategy for
its signals in overweighting or underweighting S&P 500 sectors on a monthly
basis. Importantly, we came up with the hypotheses before we did any
backtesting or simulations, and we did zero tweaking or retesting after
we did any backtesting or simulations. These sector rotation strategies are
deductively derived, based on our professional intuition of investor behavior
and our professional knowledge of how the Common Knowledge Game works.
Also importantly, these are slow-twitch strategies, where we take
our measurements at the end of each tested month to generate a signal for the
following month. All of the financial media articles are publicly available. There’s
no massaging of the data or change in the search queries over time. There’s no
discretionary input. We are testing on the Select Sector SPDR ETFs, each of
which have no appreciable liquidity constraints, and we take into account ETF
fees in our performance simulations. We do not take into account trading costs,
although we would expect these to be minimal.
Of the eight hypothesized narrative-driven sector rotation
strategies, we found that six of them “worked”, meaning that in our backtest
simulations they generated excess returns over the S&P 500 and had an
information ratio > 0.6 (again, I’m going to let our findings speak for
themselves, so if you need a primer on “information ratio” and some of the
other terminology here, that’s on you). We then took a simple, non-optimized
equal weighting of each of the six working strategies to create an
unconstrained “Beta-1” portfolio strategy, meaning that we let the individual
strategies do whatever they signaled as far as underweighting or overweighting
the individual sectors relative to their baseline S&P 500 sector weights, and
then we added whatever vanilla S&P 500 index long or short exposure was
required to make a fixed portfolio net exposure of 100% long. So if you’re
keeping track of these things, the unconstrained Beta-1 portfolio of strategies
averaged about 12 separate sector signals per month, an average gross exposure
of around 200%, and is the rough equivalent of a 150/50 strategy.
Now before I show you the results of the portfolio simulation, I
want to say the following really clearly. I’m not saying this as boilerplate,
and I’m not saying this in tiny text or in ALL CAPS, both of which are signals
for you to stop paying attention. These are simulated, backtested returns.
You could not have invested in these strategies. You cannot today invest in
these strategies. Even if you did, there is no guarantee your results would
reflect those of the backtests I’m going to show you. We have treated all of
this as a research puzzle we are trying to solve, and so should you.
We understand that many investors are not allowed to be short anything, even an S&P sector ETF, so we also modeled a constrained long-only portfolio of strategies, where we cap all underweights at zero exposure, creating a 100% gross exposure, 100% net exposure portfolio strategy, with no shorting of any sector ETF. As you would expect, the performance statistics are muted compared to the unconstrained version, but still quite powerful.
Crucially, these excess returns are uncorrelated to all major factor categories – Momentum, Value, Low Vol, and Quality.
So there you have it.
We think we are identifying a novel and predictive signal of
investor behavior from our systematic measurement of narrative structure in
publicly available financial media.
Now, savvy readers will note that I started this note by talking
about metagames and Identity, but cut that discussion short to get into the
meat of this investment research puzzle that I think we are solving. Savvy
reader will ask themselves if there’s another shoe to drop here. Savvy readers
would be right.
What’s my metagame?
Let’s start with this blanket statement: I will do anything for my
pack. I’ll be the patsy. I’ll make unreasonable sacrifices. I’ll give away the
store if that’s what’s required. But here’s the thing – my pack would never
require this of me. At every level of my pack, from nuclear family to the ET
epistemic community, we do unto each other as we would have each other do
To put it in Kipling’s poetic terms about the pack, we drink
deeply, but never too deep.
To put it in Dungeons & Dragons terms, we are lawful good but
not lawful stupid.
So hell yes, we’re going to charge money for access to and
information about our investment research. Second Foundation Partners is a completely
independent company. It’s me and Rusty doing a high-wire act with no net. Our
research and puzzle-solving is not only an expression of our Identity … it’s
also how we preserve our independence so we CAN write about more than markets
If you’d like to draw water from this research well, you’ll need an ET Professional subscription. It’s the only place we will be sharing our insights and plans for developing the Narrative Machine for investment applications.
It's easy to get waaaay too precious when it comes to professional kitchens, whether we're talking about restaurants or a trading desk.
But credit default swaps are like chef knives. They're not an affectation, but a necessary tool for so many tasks. Even if you don’t cook or trade a portfolio professionally, you’ll want to own a good knife and you’ll want to know the mechanics and the rationale of a CDS trade . . .
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Every winter, we lose something here on Little River Farm. It’s
like a tithe that nature takes, year after year after year. This winter was
particularly tough. Polar vortex and all that, I suppose.
None of the bees made it.
Sigh. I’ve lost hives before. It happens. But it’s never easy.
Never anything but sad. They work SO HARD at staying alive through a New
England winter and they’re all boxed away for months and you can’t open the
hive to check on them because that would weaken them for sure and it wouldn’t
do any good anyway and so you wait and you worry and you do all you can to set
up windbreaks and you don’t know if they’re hanging in there and it finally
gets warm enough to crack open the hive and get them some help and … death. Nothing
We respect our animals in life and in death. Especially in death. So I remove the bee husks and the old comb and I make a small fire and I give them to the flames. Because it doesn’t seem right to put bees into the ground. They are of the air in life, and they should be of the air in death.
And we begin again. Always.
But this isn’t a note about beginning anew after a polar vortex of
a winter. Well, it kinda is, so hold that thought in the back of your head. But
the narrative structure for this note isn’t about winter and ice and the tithe
of death. It’s about winter and ice and the miracle of life.
There were two animals I was certain the winter would take from
us, and those are the goldfish that live in the horses’ outdoor water trough.
Yes, we put goldfish in the water trough last spring. The horses are careful
not to eat them or drink them in, and the goldfish are great at keeping the
trough clean. Not
industrially clean, of course, but fingernail clean. The way
a real, living farm should be.
I figured this was a brick of ice in the dead of winter. I figured there was no way on god’s green earth that two little fish could sit outside in what amounts to a big pail of water through a Connecticut winter. Good lord, we had DAYS and DAYS of sub-zero temperatures this January. And yet … there they were, glints of orange-red swimming around in the trough here in late March.
A miracle? Yes. But not the kind of miracle you’re thinking of. Not the miracle of some sort of cryogenic suspension, where the goldfish are like Captain America, thawed out from a giant block of ice after 40 years, ready to pick right back up fighting supervillains or eating algae or whatever it is one does after resurrection.
No, the miracle here is the non-linear nature of water.
See, we all know that when gases or liquids get colder, they get
denser. They get heavier. The molecules in the gas and the liquid are less
energetic as they cool off. They bounce around less. They sink. This is why
pool water and lake water and ocean water gets colder the deeper you go. It’s a
perfectly linear relationship … the
colder the water, the heavier the water … the colder the water, the more it
But when water gets to 4 degrees centigrade, this nicely linear relationship between temperature and density stops happening. In fact, it REVERSES. It’s not only non-linear, it’s non-monotonic (a ten-dollar word that means reversal). As water gets colder than 4 degrees centigrade, it no longer gets heavier. It no longer gets denser. It no longer sinks.
Instead, this miraculous substance called water gets lighter as it nears its freezing point. It’s still a liquid. There are no solid ice crystals forming here that have a different density than liquid water. It’s still exactly the same substance in form and chemistry and everything else at 3 degrees centigrade as it was at 4 degrees centigrade, but somehow it is now lighter than it was before. And so it rises. And it rises still more at 2 degrees centrigrade. And still more at 1 degree centigrade. And so ice does not form at the bottom of a Connecticut pond or lake or water trough, but instead forms at the top of a Connecticut pond or lake or water trough, where it forms an insulating barrier against the cold air reducing the liquid water temperature still further. That’s how the goldfish survived. There was liquid water at the bottom of that deep horse trough, even as the polar vortex raged above.
Without this non-linear, non-monotonic property of water, life as
we know it would hardly exist.
Every Ice Age would be every bit as much an extinction event as a
giant meteor of death. Every lake or pond above or below a certain latitude
would be as lifeless as the moon.
It’s a miracle of life
that liquid water – the foundation of life on our planet – gets lighter instead
of heavier right before it changes state into solid ice.
There’s no reason why this non-linear property of water should
And yet it does.
If you were predicting the behavior of water from a theory of thermodynamics,
there is no way you would predict 3-degrees
cold water would be lighter than 4-degrees cold water.
And yet it is.
Facts don’t care about your feelings? Yeah, yeah … cute. Here’s the far more serious truth:
Facts don’t care about your theories.
The only way to learn the non-linear nature of water is through empirical observation, through actually living with water and ice rather than simply theorizing about water and ice. Because once you SEE that very cold water becomes lighter rather than heavier, then you KNOW that there must be something WRONG with your theory of thermodynamics, because this behavior is IMPOSSIBLE within a theory of thermodynamics. There must be something ELSE acting on the behavior of water than thermodynamics, something BIGGER and more FUNDAMENTAL than thermodynamics.
In the case of H2O, it’s the asymmetric positioning of the two hydrogen atoms connected to the single oxygen atom. It’s the atomic structure of the water molecule that creates the miracle of life.
Same thing with economics.
Because money, like water, is non-linear.
Because you think you can explain and predict human behaviors
around money based on a macro theory of monetarism (the supply and price of
money), and usually that’s true, but sometimes it’s not.
Because there is a more fundamental theory of money – an atomic structure theory of money based on
human risk-taking and human social narratives – that subsumes and improves
on your macro theory of monetarism.
Does lowering the price of money from 8% to 7.5% create more
risk-taking? Does it increase the velocity of money through the real economy as
corporate and household risk-takers are willing to borrow and spend and invest
MORE at 7.5% than they were at 8%? Yes.
How about lowering the price of money from 7.5% to 7%? Yes.
7% to 6.5%? to 6%? to 5.5%? to 4%? Yes, yes, yes, and yes.
It’s a nicely linear relationship.
It’s exactly as one would predict from a theory of molecules and thermodynamics monetarism and macroeconomics.
So I understand why central bankers believe that lowering the
price of money from 1% to 0.5% would act on risk-taking in the same linear fashion.
And from 0.5% to 0%. And in the case of Europe, from 0% to negative interest
rates, and from slightly negative interest rates to really negative interest
rates. They have a linear theory of monetarism and macroeconomics. Lower
interest rates have a specific and direct relationship with risk-taking
economic behavior and expectations. The lower the interest rate, the greater
the spur to “inflation”, by which central bankers mean risk-taking economic behavior.
Inflation not being spurred? Lower the price of money more.
Inflation still not being spurred? Lower the price of money still
Inflation STILL not
being spurred? Lower the price of money MOAR.
But it’s not working, people. Lower and lower interest rates are
demonstrably not spurring risk-taking economic behavior in the real economy. Lower
and lower interest rates are empirically
not spurring inflation.
When the price of money gets really cold low, like close to
zero degrees percent low, risk-taking behavior changes. The rational risk-taker
in a zero interest rate world does NOT invest in property, plant and equipment.
The rational risk-taker does NOT borrow more and spend more to invest in the
future. No, the rational risk-taker believes
the central bankers who say that interest rates will be ultra-low forever and
ever amen, that future growth rates are moribund and miserable, that our world
persists in a long gray slog of deflation just as far as the eye can see.
What do rational risk-takers do in a zero interest rate world? They
buy back stock. They buy profitless revenue. They engage in financialization.
They minimize risk and maximize return. They are greedy AND they are fearful. They demonstrate the atomic behavior of rational greedy/fearful human beings since the dawn of freakin’ time.
This is profit margin without labor productivity growth.
This is the zombiefication and the oligarchification of the US economy.
This is the smiley-face perversion of Smith’s invisible hand and Schumpeter’s creative destruction.
This is the profoundly repressive political equilibrium of an entrenched State and entrenched Oligarchy that masks itself in the common knowledge of “Yay, capitalism!” and “Yay, military!” and “Yay, college!“.
That’s a thick layer of ice above us, growing
thicker by the day. But we are still the goldfish on Little River Farm, still
swimming in a small pocket of water, not yet encased in a solid block of ice. We aren’t yet the bees. Not yet. What must we DO to avoid the bees’ fate? What must we DO to end this
winter that is imposed on us?
We have to Break the Wheel.
We have to break the tyranny of ideas that nudge us into service to the entrenched State and the entrenched Oligarchy, without replacing those ideas with a tyranny of our own.
How do we do THAT?
Well … I know it’s all the rage to rip the Benioff/Weiss screenplay in the post-George RR Martin seasons. I’m pretty bummed myself. But this line by Tyrion in the finale shows the way.
What unites a people? Armies? Gold? Flags?
There’s nothing more powerful in the world than a good story. Nothing can stop it. No enemy can defeat it.
How do we Break the Wheel?
Not by revolution. Not by dragon fire. It didn’t work for Daenarys,
and it won’t work for us.
We break the wheel with a better story, with a better theory.
Because that’s what a theory is … a story about how the world works.
By the way, this is how science works. By the way, it’s always
science that breaks the wheel.
The story of the Masters is that the market is a macro clockwork
machine, governed by linear, mechanistic “laws”. I have a better story.
Fire is not magic. Fire is not somehow separate from science or rigorous human examination. We know how to start fires. We know how to grow and diminish fires. We know how to put fires out. In a technical sense, Ray Dalio, you can classify fire as a machine.
But you’d never think that you could possess an algorithm that predicts the shape and form of a bonfire.
You’d never think that if only you stared at the fire long enough, and god knows humans have been staring at fires for tens of thousands of years, that somehow you’d divine some formula for predicting the shape of this or that lick of flame or the timing of this or that log collapsing in a burst of sparks.
No human can algorithmically PREDICT how a fire will burn. Neither can a computer. No matter how much computing power you throw at a bonfire, a general closed-end solution for a macro system like this simply does not exist.
But a really powerful computer can CALCULATE how a fire will burn. A really powerful computer can SIMULATE how a fire will burn. Not by looking for historical patterns in fire. Not by running econometric regressions. Not by figuring out the “secret formula” that “explains” a macro phenomenon like a bonfire. That’s the human way of seeing the world, and if you use your computing power to do more of that, you are wasting your time and your money. No, a really powerful computer can perceive the world differently. It can “see” every tiny piece of wood and every tiny volume of oxygen and every tiny erg of energy. It “knows” the rules for how wood and oxygen and heat interact. Most importantly – and most differently from humans – this really powerful computer can “see” all of these tiny pieces and “know” all of these tiny interactions at the same time. It can take a snapshot of ALL of this at time T and calculate what ALL of this looks like at time T+1, and then do that calculation again to figure out what ALL of this looks like at time T+2.
This is an atomic theory of markets. This is the intuition and the technology roadmap to provide a better theory. It’s not that macroeconomics and monetarism are wrong … there’s no such thing as right or wrong when it comes to theory. It’s that macroeconomics and monetarism are not as USEFUL a theory as one formed organically from the risk-taking economic behaviors of actual economic actors.
Look, central bank cultists will never change their beliefs that
they are the thin blue line between order and chaos, or that academic economics
is the One True Path for enlightenment and the maintenance of that thin blue
line. Change isn’t going to come from attacking the Fed or from a snarky
blogger. I mean, I did just call them cultists.
No, no … change will come from a Fed economist reading this note (on her gmail account, of course) and dropping the assumption – because it IS an assumption – that, for all prices of money, there is a monotonic relationship between change in the price of money and change in the velocity of money employed for productive economic purposes. Change will come from this economist allowing for the possibility of a non-linear and non-monotonic relationship between interest rates and inflationary behaviors at very low interest rates, loosening her stochastic assumptions accordingly, and then TESTING this possibility against the actual empirical evidence of the past ten years. Change will come from this economist presenting her findings from within the proper academic forms as an extension and progression of what came before, so that the institutional imperative to self-servingly mansplain our place in the world (you’re welcome!) can be maintained.
Daenarys and her city-destroying dragons couldn’t break the wheel.
Moana and her Maui-tolerating wayfinding could.
In a thousand small steps … this is how theory changes. This is how
science advances. This is how progress is made. This is how the story that we
tell ourselves about who we are evolves into something that subverts institutions from within, not something that attacks
institutions from without.
To be honest, it’s a longshot that we’ll be able to pull this off.
After all, we’re not characters in a Disney movie. Or even an HBO show.
One of my favorite authors, Kurt Vonnegut, wrote a lot about theory
and non-linear systems and humanity’s place in all that. You wouldn’t know it
from a cursory read, because he could spin a yarn, but that’s what most of his
books are about. Cat’s Cradle is the novel
most obviously connected to my particular theme, as the plot is driven by the
invention of a substance called ice-nine, an isotope of water that freezes at
room temperature and replicates itself in any ordinary water it touches, thus
spreading ice throughout all the liquid water in the world. You know, kinda
like negative interest rates.
Along the way to the end of the world, there’s a nihilist religion called Bokononism to explore, with this wonderful quote:
The Fourteenth Book is entitled, “What can a Thoughtful Man Hope for Mankind on Earth, Given the Experience of the Past Million Years?”
It doesn’t take long to read The Fourteenth Book. It consists of one word and a period.
This is it: “Nothing.”
Vonnegut would probably say we don’t stand a chance against the
Nudging State and the Nudging Oligarchy, armed to the teeth with
narrative-controlling instruments that promote their Wheel-preserving ideas, convincing us to sign away our autonomy
Like how the narrative of Yay, capitalism! subverts our liberty (and responsibility) to Make.
Like how the narrative of Yay, military! subverts our liberty (and responsibility) to Protect.
Like how the narrative of Yay, college! subverts our liberty (and responsibility) to Teach.
Yeah, he’s probably right.
But then again, Kurt, why did you write?
It’s why I write, too.
I’m publishing this note on Memorial Day for a reason. You get it.
I know you do.
We are the human animal.
We are non-linear.
We ARE a song of ice and fire.
It’s a song that has built cathedrals and fed billions and taken us to the moon.
It’s a song that can do all of that and more … far, far more … if only we remember the tune.
Each month we update our five narrative Monitors and summarize the main findings from each.
The big reveal for May? There’s a tremendous amount of narrative complacency out there, particularly on Trade and Tariffs, which means this market has a long way down if the narrative focuses on negotiation failure. It’s not focusing there yet, but that’s what you want to watch for . . .
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The Secret of life is honesty and fair dealing. If you can fake that you’ve got it made.
These are my principles, and if you don’t like them … well, I’ve got others.
I’m not crazy about reality, but it’s still the only place to get a decent meal.
A child of five could understand this. Send me someone to fetch a child of five.
Last March, I wrote a long note on the cartoon that labor statistics present, called The Icarus Moment. To set the scene:
Once you start looking for these cartoons, you will see them EVERYWHERE.
It’s not a Karl Marx world of alienation. It’s a Groucho Marx world of alienation.
The cartoon of our monthly theater regarding labor statistics, particularly wage growth, rests in the fact that they are reported as hourly wages. Even though the majority of wages in 2019 America are paid biweekly against an annual salary, the Bureau of Labor Statistics (BLS) reports ALL of our wages as if they were paid hourly. Why? Because in 1915 America, when the theater of labor statistics began, this was how most people got paid. Even today, the abstracted idea of hourly wages connects with people more effectively than the abstracted idea of weekly wages. Put that together with bureaucratic inertia, and that’s why this cartoon exists.
But here’s the problem with the hourly wage abstraction. It requires introducing a new data estimation into the mix, one that has nothing (or at least very little) to do with the real-world concept we’re trying to represent, which is whether you’re taking home more money today than you did this time last year. That additional layer of abstraction is the average length of the work week.
The root data collected by the BLS consists of the weekly wages paid by US businesses to their employees. That number is then divided by the total number of people being paid, and the result is the average weekly wage for Americans. Here is that abstracted data for the past 7+ years.
But instead of reporting the annual percentage change on a month-to-month basis, the BLS also calculates the “average work week” so that they can maintain the cartoon of hourly rather than weekly wage reporting. Here is that abstracted data.
For the past 7+ years, the average work week has averaged 34.45 hours, with a range from 34.3 hours to 34.6 hours. That’s 2,067 minutes, ranging from 2,058 minutes to 2,076 minutes. Here’s a graph of that.
This is not a variable. This is a constant.
From a statistical perspective, given the inherent errors of measurement, any month-to-month difference of 6 minutes here or 6 minutes there is a totally random event.
Measured changes in the average work week are not real.
And yet they have very real effects on the narrative.
Here’s the year-over-year wage growth data from the singly-abstracted measure of weekly wages:
These are the “true” results, or at least the most basic abstraction of what we’re after.
And now here’s the year-over-year wage growth data from the doubly-abstracted measure of hourly wages:
These are the results that are reported to us and create the political and investment narrative.
And now here’s the difference in the two data series, with weekly wage increases subtracted from hourly wage increases. The numbers here are how much the reported wage growth result overstates or understates the actual wage growth result.
In 2016, reported wage growth massively overstated actual wage growth. Wage stagnation going into the 2016 election was actually much worse than you were told. Did this make a difference in the Midwestern states that swung the election, in that actual labor conditions were worse than everyone thought they were? I think yes.
In 2018, reported wage growth massively understated actual wage growth. Wage growth all last year was actually much better than you were told. Did this make a difference in the current Fed/Wall Street/White House narrative that inflation is dead and the easy money punchbowl can be maintained without consequence? I think yes.
What does all this mean for our investments? Here’s the money quote from The Icarus Moment:
Honestly, I still don’t have a good answer to this question.
Do I invest on the basis of what I can see happening in real-world or do I invest on the basis of what I can see happening in narrative-world?
Ultimately, I STILL think that real-world wins out.
But the path for that … the timing of that … it’s utterly narrative dependent.
Narratives can be powerfully emotive influences. Overplayed narratives often lead to extremes in investor sentiment, and extreme sentiment may reverse quickly alongside a change in the narrative.
It has done so twice since mid-year 2018.
Late last year, markets collapsed as the narrative shifted from Fed as dovish father to the Fed as a deadbeat dad. The sub-narrative also changed from one of synchronized global growth to one of synchronized global slowdown. The narrative reversed yet again early this year upon the return of the Fed as a dove.
While U.S. equity markets over-reacted to the Fed’s hawkish December communication, they are now doing the same in response to its dovish pivot.
We see little in the way of catalysts to new U.S. equity market highs as sentiment begins to wear thin on a rollover in data into the second half of the year and as the Fed remains on hold – as it should.
The new narrative around the Fed as dove has helped create some striking cross-asset dislocations. Global rates markets are telling a slowdown story. The U.S. yield curve inverted from 3-months to 10-years just a month ago, even after the Fed pivot. Both JGBs and Bunds are either negative or close to it. Funding markets are also showing signs of strain, as funds trade above IOER more and more often. 
Importantly, the dollar has been strengthening despite little change in real rate differentials. Its strength looks to be a product of a U.S. economy that remains strong relative to the rest of the world. The dollar’s strength will also have deleterious impacts on emerging markets (EMs), which are responsible for most of global growth. Economic performance in Europe has on balance continued to deteriorate, even as China stimulated its way to PMI expansion for March (and for April which fell closer to contraction once again). Japanese and European PMI’s have been abysmal, and the rates markets in Europe and Japan reflect it.
Yet, U.S. equity markets just made a new high.
How to reconcile this? What has really changed since January that should lead to a sustained rally in equities beyond current levels?
The bullish narrative for U.S. equity risk makes sense only if one accepts a narrative that the Fed will proactively move to prevent a U.S. slowdown before it happens.
The bullish narrative further presumes that the current global slowdown will somehow miraculously reverse or somehow not touch U.S. growth. (We have argued that U.S. growth will fade alongside its developed market peers as the benefits of the tax cuts wane). With the exception of Japan, central banks generally have been and remain reactive rather than proactive. Before central banks act preemptively using a Japanese-style modern monetary theory (MMT) approach, two things must happen. First, they must lose their relatively well-defined, current mandates. Second, they must lose their independence. We don’t expect this to happen to the Fed until after the next risk repricing is complete. Thus, even though Fed Funds futures markets remain convinced of a cut at well over a 60% probability, market participants ought to be more skeptical.
He writes: “Ultimately, though, the policy shift could help investors avoid getting lulled into the kind of complacency that leads to ‘Minsky moments,’ such as the 2008 financial crisis. And it would certainly help Main Street, by refocusing the Fed’s efforts on ensuring a stable economy.”
Kocherlakota demonstrates a profound lack of understanding about what caused the 2008 crisis, but that’s a topic for another time.
For today, let’s take his argument to an extreme. Under the ‘full employment’ mandate and at the first sign of any wobble, the Fed could create reserves, and then use them to buy Treasuries. The Treasury sale proceeds could then be earmarked to fund social programs established to guarantee each citizen a job. Kocherlakota’s argument creates a slippery slope towards a central bank that lacks independence and fosters social agendas at the pleasure of incumbent politicians. The hurdles required for each ‘wobble’ in the data would likely be lower and lower until finally anything would qualify.
As a result, my views have been responsive to the more volatile conditions that may be associated with late cycle equity markets. Further, it’s my belief that late 2018’s volatility was not a denouement; rather, it was the beginning of a deeper slowdown. Let’s take a look at 1995 and 1998 as possible analogies supportive of the narrative that the Fed will cut proactively. In 1995, the Fed cut in response to a string of government statistics that showed a sharp slowdown in business activity, on the heels of a catastrophic Japanese earthquake in early 1995, and after the Tequila crisis late in 1994. In 1998, the Fed cut in response to LTCM’s collapse and the Russian financial crisis. In my view, neither analogy is durable. 
There are two major differences: the monetary policy mosaic and globalization.
In stark contrast to the present, 1995 Fed funds were 6%. Today, the Fed has little room to cut already so close to zero, and it has just recently normalized after 9 years of extraordinary policy intervention, which included quantitative easing (QE). Its peer central banks are similarly low on ammunition outside of renewed QE. Moreover, prior to cuts in 1995 and 1998, the Fed had quickly hiked from 3% to 6% on funds at 50bps per month over the course of only a year. This contrasts to a much slower pace of recent hikes (at 25bps per hike over 3 years).
The other important difference is globalization. For example, the Eurozone did not exist, and emerging markets accounted for only a small proportion of global growth (30% versus over 60% today). Thus, neither the European Central Bank (ECB), which did not exist, nor the People’s Bank of China (PBoC) were relevant central bank actors. Even the now frenetic Bank of Japan (BoJ) was sleepy. What’s the point? The Fed has other banks in its corner that are doing some of its work for it. It needs to lead the way towards normalization.
Today, the BoJ stands in an extreme position and currently in stark contrast to the Fed. The BoJ appears to act proactively at the slightest sign of trouble since the global financial crisis. Japan’s central bank is not independent, and its approach has been in response to criticisms it was slow to act after its debt bubble burst in the early 1990s. All things considered, Japan’s strategy hasn’t worked well, as GDP has averaged only 1.4% since September 2009 despite a balance sheet that has grown by $4 trillion dollars since mid-2018 (now $5 trillion). The increase of roughly $365 billion dollars/year is about 7% to 10% of GDP ($4.9 trillion nominal GDP 2018). Since early 2016, after the Shanghai Accord, both 10-year and 2-year JGBs began to yield less than zero. 2-year yields in Japan have yielded no more than 15bps since late 2009. Thus, we are in the fourth year of both 2 and 10-year bonds with negative yields and in the 10th year of near-zero short rates.
Were a recession or equity market panic to lead to a bid for the Yen, Japan might have nothing left but to sell newly created Yen reserves and buy U.S. Treasuries. We’ve had conversations with those close to the Japanese central bank, and they’ve indicated this is an option they might consider.
In contrast, the Fed’s just not there yet on MMT; American exceptionalism prevents it… at least for now. Eventually, as we wrote in our previous Epsilon Theory’s In the Trenches, all of the world’s central banks will eventually buy many different classes of private and publicly held assets. At that point, all central banks will likely have lost their independence and social policy will no longer be an implicit goal but rather an explicit one. It’s simply a matter of when rather than if; however, it’s no time soon.
Indeed, we remain fairly convinced that the Fed will not cut this year. Equity market performance has been just too strong and the data remains just good enough. The Fed will react only if risk assets and the economic fundamental data justify action. U.S fiscal stimulus (the fumes from tax cuts) will prop up U.S data just for long enough to prevent Fed action while the rest of the world is continuing to slow. Inaction is the Fed’s only logical choice right now.
In a world moving towards BoJ-style modern monetary theory (MMT), one might argue that cycle analysis itself is anachronistic. This is the most persuasive challenge to many of the arguments made here. Indeed, because of QE and globalization, things are different this time. Yet, market participants ought to be skeptical that the Fed is willing to proactively prevent all business cycles just yet.
Monetary policy was never designed to set capital costs over long periods of time. That’s what free markets do best. When intervention lasts too long, it creates distortions and bubbles. These distortions were acknowledged in Austrian business cycle theory (ABCT), which views business cycles as the consequence of excessive growth in credit often due to the artificially low interest rates set by a central banks. Historically, the lenses that create these distortions tend to shatter.
I would expect nothing different this cycle, as the Fed will not act preemptively enough to stop the excess its own policies have already created. Sadly, if the Fed and ECB finally decide to go all-in and become proactive rather than reactive, markets will no longer be markets. Markets will no longer price assets or risk based on market information. Social policy will set asset prices. All central banks would then become political, as Japan’s central bank and China’s central bank already have – unless there is a concerted effort to stop it.
 We have written and CNBC has now reported Fed officials are
considering a new program that would allow banks to exchange Treasuries for
reserves, a move that could bolster liquidity during difficult times and also
help the Fed shrink its balance sheet. This conversation has occurred as Fed
Funds has risen above IOER. As reported, proponents of the so-called standing
repo facility see the program as a relatively risk-free way of giving banks a
release valve in times of financial tightness, while also allowing the Fed to
pare back its bond holdings with minimal market disruption. We view the
standing repo facility as a stealthy form of quantitative easing. Indeed, one
form of QE is the conversion of long-dated treasuries into Federal Reserve
Burgess wrote: “Investors are most pessimistic on the Americas, followed by
Europe and then Asia. Cantor Fitzgerald strategist
Peter Cecchini embodies the current sentiment. In a week when the
S&P 500 Index closed at a record of 2,933.68, Cecchini boosted
his year-end target for the benchmark, but only to 2,500 from 2,390, according
to Bloomberg News’s Vildana Hajric. For those without a calculator handy, the
new forecast represents a 15 percent drop from current levels. “We do not
foresee an inflection in U.S. economic growth or S&P earnings growth in the
second half as global growth continues to slow and
costs rise,” Cecchini said. “We also do not foresee a Fed cut as
likely. With slower growth and a Fed that is slow to cut, we think equities
will struggle in the second half.” It’s not like Cecchini is some
foaming-at-the-mouth bear; he rightly urged investors to buy the dip in January
after the big sell-off in late 2018.”
 Perhaps, a better analogy might be the coordinated global central bank response that began in February 2016 to stabilize the Chinese yuan. The so-called Shanghai accord came in response to two prior shocks in global equity markets in response to fears of a devaluation of the Yuan. Central banks acted in concert with the Chinese authorities to assure that capital could flow into China and prevent a destabilizing depreciation. It worked, and likely prevented what could have been a broader default cycle here in the U.S. on the heels of defaults in the energy industry. I, for one, was too bearish in 2016 on an analogy to pervious default cycles. So could 2019 be a repeat of 2016? It doesn’t seem likely. Central bank policy was synchronous back then, and there was no trade war division. Balance sheets were expanding and central bankers were not in normalization mode. No major pivot was required. Moreover, at that time, there was no fiscal stimulus in the United States. Thus, U.S. growth was arguably more fragile were a global shock to occur. We think a bigger wobble in financial asset markets and the domestic economy is needed (and should be required) before the Fed cuts rates.
I remember when I first knew where I wanted to go to college.
I also remember the look on my dad’s face, sitting on a bed in the Holiday Inn in Cherry Hill, New Jersey. I could tell he was struggling with whether we could manage it. It would mean taking out about $25,000 in federal loans in my name. About $60,000 in his. We had never even considered taking out loans for me to go to college before. This was more debt than the mortgage my family had taken out on our house. A campus visit and a childhood spent building up credibility as a sober-minded, serious kid later, and we would be in for 85 grand. If I could get in, I knew, I had to do it. I had earned it, you see.
I deserved it.
did 45 million other starry-eyed young Americans. At the (often literal) push
of a button, we created debt now amounting to more than $1.6 trillion out of
the ether to give each of us what we declared
we deserved: Validation. Credibility. Credentials. All we had to do was reach
out and take it. All we had to do was believe the myth.
And yes, Virginia, the importance
of post-secondary education in America IS a myth – one of our most powerful.
that doesn’t mean that college and its attendant experience don’t hold
intrinsic value. It also doesn’t mean that the credential offered by these
institutions isn’t a real currency. It means that the Common Knowledge
underlying that currency is far more powerful than whatever the truth about college is. It means that
the stories we tell about college are more important in almost every way than
the facts. It means that whenever we talk about college in America, we are nearly
always talking about the meme of college!
College! is a meme of equality, something we raise our hands for because we believe in the importance of socioeconomic mobility, the American Dream.
College! is a meme of human progress, something we raise our hands for because we believe that expanding education, research and knowledge will power ingenuity, innovation and prosperity.
College! is a meme of meritocracy, something we raise our hands for because we believe that talent and hard work cross all biological, social, racial and gender boundaries, and that systems which reward merit permit the destruction of those artificial constraints.
The Myth of College is an idea which permits us to declare it to be synonymous with these principles. The consequence of this declaration is that we may also declare that any opposing idea denies those principles. You don’t hate equality, innovation and merit…do you?
hold up our ‘Yay, College’ signs in the same way as we do ‘Yay, Military’, ‘Yay, Capitalism’ and ‘Yay,
signs, because not doing so is to say that we oppose the right-sounding
principles that form the basis of the myth. And just like ‘Yay, Capitalism’, well…capitalizes
on our desire to signal our deeply held belief in the power of rewarding
economic risk-taking to convince us to permit distortions in economic risk-taking, ‘Yay, College’ exploits our
belief in equality, innovation, merit and education to convince us to permit distortions in the capacity of our
university and degree system to deliver ANY of those things.
myth has also driven us to create a system of laws and policy that have, in
turn, produced a very real student loan crisis. As a political issue, this is
far more powerful and far more connected to the political zeitgeist of 2019
than most people want to believe. It is a case for Clear
Eyes and Full Hearts.
particularly clear eyes nor an especially full heart are needed to recognize
that educational attainment has been on a steady, long-term rise in the United
States for more than half a century. This is a good thing. In 1950, only 34% of
American adults had finished high school. Today, that’s about how many have
completed at least a bachelor’s degree program. There are all sorts of studies
documenting other positive developments in educational attainment, too, not
least the convergence of opportunities across gender and, to a lesser extent,
across racial and socioeconomic boundaries.
what is the right level? Leaving
aside the Myth of College for a moment, do somewhere between a third and a half
of jobs in the United States require what an undergraduate program teaches? I
don’t know. Sorry. It’s not an objectively answerable question, and the responsiveness
in what those programs teach to what is perceived as being needed complicates
the question further.
I am happy, however, to give you my opinion. I think the number of people who need to attend college from a knowledge and skills perspective is far, far less than one-third of adults. Yes, engineering professions and those in biomedical and applied sciences require a base of knowledge that takes time to accumulate. Same for those preparing for post-graduate research and teaching roles across subjects. I think that you can make an argument for elementary and secondary education on the basis of the breadth of subject knowledge that is theoretically required, too. Based on 2016 data, those subjects account for about 22% of undergraduate degrees granted, plus however many you want to count as being necessary to refill post-graduate teaching posts – a vanishingly small figure.
all, I am confident there is a vocational
need for four-year college for no more than 10-15% of adults. Am I saying that
the tens of millions of programmers, financial analysts, writers, designers,
bankers, managers, accountants, product marketers and sales personnel out there
could function at equivalent or higher levels with less than a year of focused
vocational training, if such a thing existed? Yeah, that’s exactly what I’m saying. Am I saying that only 10-15% of adults should go to 4-year universities? No!
preparing for a career isn’t the only reason you might think about spending
four years at a university. But most of the reasons we provide are also
conflations of the type that are so common when we deal with other abstractions,
myths and memes. In other words, because these ideas have become attached to the Myth of College, it
takes little more than a rhetorical flourish to shut down criticism of the value
of post-secondary education. Simply assert that someone who is skeptical of our
approach to post-secondary education opposes these ideas!
are these ‘conflations’ and ideas? How about ‘it’s about discovering yourself’,
as if one couldn’t achieve that by traveling the world? I am sure you’ve heard
‘it’s about learning how to think critically’ or ‘learning how to problem solve
in a group setting’ or ‘developing confidence and communication skills’, too,
as if college is somehow better equipped than other settings to deliver these
lessons. We are also fans of ‘it is an important opportunity to network’ or ‘to
build lifelong friendships’, which are great, but also tautological rather than
fundamental (i.e. college is important because others consider it important).
There is one reason – and in my opinion, one reason only – to attend college that does not relate to vocation, preparation for a life of research or teaching, or the fact that a critical mass of one’s age cohort is already there:
Because college permits us to be
wrong, offensive and awkward in exploration of new and uncomfortable ideas and
knowledge in a setting with low consequences.
you would be forgiven for wondering whether universities are committed to this
one critical, indispensable function. I think most still are. This function alone, for
many – for me – would justify the investment of 5% of life and 10% of lifetime
earnings. It is huge. Truly. It also has almost nothing to do with why most people choose college. Even if we grant
credit for ‘to be intellectually challenged and stimulated’ below, most of the
reasons people go to college are either things 4-year college isn’t unusually
well-suited to deliver, or else vocational in nature.
If that’s one part of the story, we can find a lot of the rest in selected degrees. In the 19th Century, American universities were institutions that turned liberally educated student-philosophers into lawyers and clergy. In the early-to-mid 20th Century, American universities swapped out clergy for businessmen, and started teaching women to be teachers, but otherwise were much the same. Today? American universities are officially in the business of vocational training for white-collar professions.
Co-Option of Credential
Except even that isn’t exactly true. Here is what I think is true:
The Myth of College is that it grants invaluable life experience, broadened horizons and deeper skills that no other 4-year experience for a young adult could match.
The Zeitgeist of College is that it is now (grudgingly) really about preparing workers for long and prosperous careers.
The Reality of College is that it sells a license to use a credential.
What do I mean by a credential? I mean the portfolio of Useful Signals that are sent by the achievement of a university degree. Beyond the attachment to the ideals of the Myth of College, much of that signal, I think, exists in our Common Knowledge about what traits a student needs to be admitted to that particular degree-granting institution. You know, intelligence, creativity, breadth of talents, work ethic, having the correct parents and grandparents, things like that. Much of whatever is left exists in the signal from completing the degree. Can you follow instructions? Are you comfortable pulling all-nighters? How do you feel about sitting at a desk with a laptop for 60 hours a week?
And no, like the related question of what share of jobs truly requires the skills gained in four-year college, the question of the share of the observable value of a college degree we can attribute to skill gain vs. credential is neither provable nor falsifiable. So, doubt it and tout the anecdotally valuable lessons of a college education all you want.
But if you do doubt it, you’ll have to explain why all the private equity partners, lawyers, former actors and celebrities caught up in the admissions scandal paid that kind of money to get their kids admitted. Would you have us believe it’s because they really wanted little Jimmy to discover who he was? To be able to recall Black-Scholes on demand? You’ll have to explain, as Bryan Caplan suggests in The Case against Education, why, if the value of college is really in the knowledge and experience, more locals don’t just audit lectures to reap all the benefits. You won’t get caught. I promise. You’ll have to explain the sheepskin effect, why college graduates out-earn high school grads as janitors and bartenders, and all sorts of other things, too.
Regardless of whether you think a degree is valuable because of some intrinsic skill and knowledge gain, or because of the signal value of the credential it offers, the degree itself IS unquestionably valuable. It is socially, economically and politically valuable. And despite all the growth in degrees granted by US universities, the income premium those degrees offer has been stable. College grads earn about 75-80% more than their high school graduate peers.
there’s a problem with this, too.
There is an income premium from university degrees, but also emerging evidence of an evaporating wealth premium after we have adjusted for family size and life cycle. The below exhibit comes from research conducted by the St. Louis Fed’s Center for Household Financial Stability. White college graduates born in the 1980s and afterward do make more money than their high school-only peers, but it isn’t translating into net worth in the same way that it did for prior generations at comparable life and family stages.
Things are even worse for college-educated black Americans. On the basis calculated by the St. Louis Fed, cohorts beginning as early as the 1960s have enjoyed almost no net worth advantage against their high school-educated peers.
did the erosion in college’s net worth premium begin earlier for minorities?
There are probably a lot of reasons, ranging from fewer investment services
offered to underbanked black communities for much of this period, to predatory
lending practices that have routinely sucked wealth out of those communities on
a disproportionate basis. What most whites consider standard financial services
products have simply not been available on the same basis to blacks and
I think there’s more to the story – and this IS a story I’m telling you, not a
fact. I think that the growth in credentialism has also created an arms race
among institutions and a greater separation of the credential value of
so-called elite institutions from the rest. I think that legacy policies and
other admissions structures have effectively shut many minorities out of
capturing this premium. And there IS a premium to getting Team Elite stamped on your
leave net worth differences between demographic groups in each age cohort
aside. Are the post-1980 cohorts intrinsically lazy, irresponsible and
unwilling stewards of assets? Or is there, perhaps, a less stupid (if still
only partial) explanation for the slow disintegration of the college degree net
Happened to College?
how and why did the college credential rapidly grow, then lose its power to
drive differences in wealth, all while keeping all the attendant mythology
The credential value of the university degree became Common Knowledge at the same time that the economic means to significantly expand secondary and post-secondary education in the US became a reality, and at the same time that agricultural and manual labor went into secular decline.
Good-intentioned Americans who wanted their children (parents) or their charges (educators) to experience better, more prosperous lives rightfully and justifiably celebrated college specifically – and education more broadly – as the engines which produced social mobility, wealth, career prospects and lifestyles that were better than those experienced by each generation’s parents
Similarly good-intentioned Americans went into public office with visions of expanding this dream to include more and more people for whom these early efforts were insufficient. We created lending programs, guarantees and a system of laws to permit the extension of almost limitless credit to aspiring students and their families – and to make much of that debt nearly impossible to discharge. Because everyone deserves to go to college.
In doing all of this, the values we ascribed to ‘college’ became narrative. That narrative became the Zeitgeist. That Zeitgeist became the Myth of College. And in our obsessive celebration of the Myth of College instead of the direct celebration of its wondrous underlying traits, we unwittingly granted our university system unabridged letters patent to oversee the right of Americans to earn a good living.
In short, we created a guild. You
know, what the Romans called ‘collegia.’
guilds, our universities set the terms of trade in their credentials. They
decided who could participate and who could not. They accumulated power and
prestige through levies assessed on any who wished to practice a trade for
which they held the patent. No, our modern guilds couldn’t keep us from learning what they knew – give me three
weeks, kids, and I’ll teach you what you need to know to be a banking analyst –
but they could absolutely withhold their
credential, the thing which allowed those trades to be practiced.
did they do with this power, you ask?
They did this. They extracted every ounce of the credential premium for themselves as a license fee.
Don’t blame the parents, guidance counselors and high school principals who genuinely wanted their kids to have better lives than they did (even if some of their other behaviors belie that sentiment). Don’t blame the good-intentioned politicians who saw expanding this dream as good public policy. Don’t even blame the universities for simply following the opportunity the market provided. Okay, blame them a little bit. But truly, blame all of us. Because it really took all of us to create the Common Knowledge which imbues our most prized traits in a single social institution.
And no, college debt isn’t the sole cause of whatever is (not) happening to the net worth of college graduates. Timing of favorable investment environments, the inability of these generations to acquire real estate assets, and the concentration of jobs with these remarkable income differentials in cities with extreme rent costs all play a role, too. Obviously. Still, feel free to take “We didn’t JUST create a system to extract wealth premium from college students through debt-fueled, brutal college cost inflation, we ALSO pulled forward financial asset returns to benefit existing asset owners through the use of extreme monetary policy and extracted a portion of that wealth premium through NIMBY housing policies in every major US city outside of Texas” for a test spin and see how it feels.
The worst part, at least in my book, is that each one of these actions has abused our collective belief and trust in beautiful principles attached to our various cultural myths (Yay, Capitalism! Yay, Local Culture! Yay, Home Ownership! Yay, College!) to permit interference in those markets designed to suit one social group over another.
People, we sold a generation of starry-eyed students a ceiling on their potential and called it a starry sky.
we’ve got to figure out what to do about the hell we created on the paving
stones of good intentions.
are those problems?
Unnecessary Productivity Loss: We lose an average of 2-3 years
of productive, asset-building, creatively valuable years of happiness and
freedom across each generation of Americans by effectively forcing millions of
Americans to pay a toll to post-secondary educational institutions that they
neither need nor wish to pay.
Paths to Prosperity: Through
hundreds of billions in non-dischargeable debt, we are stifling the traditional
paths to prosperity for just about anyone who won’t inherit money from their
parents, or who doesn’t strike it rich in an entrepreneurial venture.
Relating to a Generational Wealth Gap:
We are creating a generational wealth gap that presents meaningful risks to various
capital and non-financial asset markets, and most importantly, entrepreneurial
Hampering Household Formation: We are piling on top of already
challenged demographic trends with an additional bias toward later and less
frequent household formation, which has both social and economic
people of a similar political persuasion to me would say the right answer is to
do nothing. It’s sad, sure, but all those people signed on the dotted line. The
market says this is what a degree is worth, and so families can choose to pay
it or not. Either way, they live with the consequences. I hear you. I paid my
college loans and feel the temptation to go full geroff-my-lawn about those
grousing today. Except there is nothing
natural about this market. The price students paid / are paying for these
credentials is a reflection of decades of public policy permitting and
encouraging the extension of credit for college to anyone and everyone who
requests it. The demand side of the market has been aided by the artificial
impact of twelve years of publicly funded curricula, messaging and ‘education’
designed explicitly to feed as many students as possible to the guilds of
post-secondary education. It is a distorted market.
like Senator Warren, have said that the solution is ‘jubilee’, to make college
free (or much cheaper) and to permit the discharge of significant quantities of
debt. There are shades of MMT here, and you will hear some make the very stupid
argument that the important thing is that the proposal isn’t really an outlay
but rather the elimination of a non-cash government asset. Oof. Look, this is a
good-intentioned policy that sees the plight of tens of millions of Americans
and searches for a direct solution. I’m empathetic. Proposals like Warren’s would begin to address some of the
structural problems created by historical government interference in the market
for education noted above. We can’t pretend the money comes from nowhere – no
matter how you look at it, it would be a tax on asset owners. It’s a tough
thing for me to get me to believe that layering on more public policy will ever
fix the distortions caused by public policy, but maybe it’s time for an
intergenerational compact – a Boomer-Millennial summit of sorts to figure out
how we share responsibility and commitment here.
Alas, it’s moot, anyway. The Jubilee proposals don’t just fail to get to the root of the problem. They exacerbate it – grievously. The biggest underlying social problems above are (1) that we are railroading entirely too many students into college programs whose skill gains could be provided much more efficiently in alternative, less time-consuming and less expensive ways than four years at Whatever Private College, and that (2) a combination of public policy and our collective cultivation of the Myth of College have permitted guild-like universities to raise tuition to demand a kingly share of any wealth premium offered by the credentials they confer. The debt problem is a problem in-itself, but it is also a subsidiary problem caused by these two problems. Guess how much the like of Bucknell, Tufts and SMU will adjust their planned annual tuition hikes over time in response to a policy providing $50,000 in debt jubilee or college cost reductions? If you answered $50,000 (or more), you win a free subscription to Epsilon Theory. Congrats.
don’t have a full answer, because I can’t
have a full answer. The student loan crisis is the kind of Big Deal that requires
us to come together to decide what our compact with one another is going to be,
if it’s possible for us to do that kind of thing any more. I will tell you that
I think any real answer that isn’t just good-sounding election season political
theater will have at least these traits:
Moves college lending outside of
government purview and off government balance sheets;
Permits charging off college debt
and really, truly assigns those losses to capital; and
Extracts cost limitation
agreements and expanded commitments
to fund underserved / lower income student costs from universities in exchange
for the ability to retain not-for-profit status.
yes, I’m dead serious about that last one. I believe challenging the assumption
of university entitlement to not-for-profit status is the sine qua non of ANY
solution to the student loan crisis.
for the Myth of College? I don’t know how we move away from it. Y’all, both
conservatives and progressives love to talk New Artisans and the Glories of
Welding. One group just talks about it over a beer at the bar, and the other
listens to it on This American Life. Same damn thing. But rejecting credentials
remains a for-thee-and-not-for-me
kind of thing. There IS no first-mover advantage to saying that you and yours
are choosing to build lives based only on true things like what you know and
how hard you work rather than a credential. Clear eyes, folks. This is another competition game, another stag
Whatever we decide, the issue IS coming to a head. I worry that it is going to come to a head in the ‘just do something’ variety that will lead us to a policy error which aggravates the core problem instead of resolving it. Education, colleges and the student loan crisis sit at the very center of our non-financial zeitgeist. Below is a network map of all the non-financial articles in the LexisNexis Newsdesk database over the last year, arranged by the similarity in the use of language. The highlighted cluster in the right graph? That central cluster is the one that’s all about education, colleges and student loans.
Network Graph – Non-Financial Stories (4.20.18 – 4.20.19)
language we use to write and speak about education is powerfully connected to
everything else we write and speak about for two reasons. First, it is
powerfully connected because education is topically
connected. Health care institutions are attached to colleges. University
research studies influence industry, technology and commercial research.
Graduates take jobs in industry. But its powerful connection is also the result
of similarity in the meaning we
attach to education, and how that meaning is shared with topic-crossing ideas
like justice, creativity, discipline
That is what I mean by the Myth of College. It’s a real thing, and it will take all the full hearts we can manage to dispose of it. It is no trivial task to do those things while celebrating the principles like innovation, creativity, hard work, passion, equality and opportunity that we have attached to the Myth of College as synonyms, principles which we have allowed the credential to parade as part of itself. It will be the work of a generation. Our grandchildren are worth the effort. They deserve it.
Log of notes in series available here All notes optimized for viewing in PDF form PDFs available to subscribers only
Part 2: Addition By Subtraction
Trivia Question #7 of 108.
Taken as a
group, the 51 countries or dependencies comprising Asia are home to a bit more
than half of the world’s 44,000 or so listed companies. What is the median number of sell side
research analysts following the roughly 22,000 Asia-based firms just referenced? Hint:
the correct answer equals the number of no-hitters pitchers in Major League
Baseball (MLB) have thrown on their birthdays, which itself equals the number
of times two batters on the same team have “hit for the cycle” (single, double,
triple, home run) in the same game. As
regular readers know, approximately 220,000 MLB games have been played since
big league competition commenced in the 1870s.
Answer appears below.
Pre-Game Jitters. Tired of waiting for the best MLB player of this and perhaps any generation — 27 year old Angels outfielder Mike Trout — to make his next appearance in MLB’s best ballpark? Me too. Frustrated it’s taken me so long to take this swing at the curveball I left hanging in Part 1 of this post when it got published several weeks ago? Me too. Skeptical I can smack the curveball just referenced — i.e., outline investment policies conducive to the achievement of plump real returns over the next few decades of Trout’s blessed existence — or indeed convey useful thoughts of any kind via sentences comprising fewer words than the number of times Trout reached first base on walks in 2018 (a stunning 122 times in 608 plate appearances)? Can’t blame you: as a guy who’s spectated many games in the ballpark alluded to above without wishing any would end sooner than they did, I have a natural if unfortunate tendency to craft sentences that run longer than most readers presumably prefer.
Obviously, there’s nothing I can do to accelerate Trout’s next appearance at Fenway (on August 8). But I can scratch the other itches hinted at above — codifying concisely policies conducive to long-term wealth enhancement — and do so below via a series of tenets, none of which comprises more words than Trout’s age when he and the Angels inked recently the largest contract ever awarded a pro athlete: a deal that’ll pay Trout a total of $432 million pre-tax from 2019 through his age 38 season in 2030.
Of course, since no one knows for sure how the economy and inflation let alone tax rates will evolve between now and 2030, no one knows for sure what goods and services the roughly $17 million per year in after-tax dollars Trout stands poised to earn under current tax schedules will buy him over the course of his newly-signed 12-year contract. If, for example, inflation over the next dozen years runs as hot as it did during the most inflationary 12-year span in US history (1970 – 1981), the $17 million in after-tax income Trout is slated to pocket in 2030 will buy him the equivalent of a mere $7 million in goods and services if purchased today, CPI inflation having eroded the dollar’s purchasing power by roughly 60% over the 12 years ending 1981.
Adding insult to potential injury, quite apart from potential surtaxes on certain outlays a highly compensated pro like Trout might reasonably be expected to make from time to time (e.g., hefty levies on fuel for private jet travel), wealth taxes of the sort proposed by certain politicians of late could prevent Trout from amassing even as remotely as much real wealth over the next 12 years as he would if the dominant zeitgeist for this interval were to resemble that of the 12 years beginning in 1981, i.e., disinflation and generally reduced tax rates.
Similar anxieties confront most
individuals, families and indeed institutions that have already amassed
substantial wealth as 2019 unfolds, including well-endowed non-profits that IMHO
would be unwise to assume their investable wealth or current income produced by
same will remain untaxed indefinitely.
Indeed, even if the wealth just referenced is subjected to little or no explicit taxation in coming years and beyond, it could as noted above be subject to the implicit tax known as inflation: to currency debasement of the sort that, along with other ugly and corollary trends, led ultimately to the appointment of the investment maven on which Part 1 of this two-part paean to Hittin ‘Em Where They Ain’tfocused: Yale CIO David Swensen. (Part 1 focused as well on a baseball maven discussed further below: Branch Rickey.) Other observers may disagree, but I doubt Yale would’ve hired a 30-something finance geek with no investment experience to run its endowment in 1985 if it hadn’t suffered a 60+% erosion in endowment purchasing power over the prior 35 years.
What Trout Needs. Like all investment home runs of which I’m aware, the riches that Yale has garnered by tapping Swensen as its CIO 30-odd years ago constitute just if not inevitable recompense for deducing correctly that the perceived risks of such a move exceeded the actual risks. This isn’t to say that the latter were non-existent: Swensen might have proven inept in crafting investment policies responsive to Yale’s presumed needs, or the policies he ultimately devised might have proven infertile if the investment zeitgeist that subsequently unfolded had been different. To Swensen’s credit, and Yale’s great and good fortune, the investment model he built embodied nicely if somewhat unwittingly an attribute inherent in all sound approaches to conscious risk-taking: asymmetry.
“Heads I win, tails I don’t lose.”
That’s the ticket, we’d all agree, as reflected among other happy
investor tales in this arresting fact: for more than a quarter century
following Swensen’s assumption of his current post, a key tenet of his model essentially
proved fallacious, with high quality bonds of the sort Swensen’s model disfavored
producing returns roughly equal to marketable stocks as a group. Of course, Swensen didn’t invest in the broad
stock market during the quarter century in question (1985 – 2010), nor has he
done so since. Rather, he’s employed
more or less exclusively active equity strategies, with a hugely
profitable tilt toward privately-traded equities, including venture capital.
The undeniable fact that such strategies bent but never quite broke Yale nor Swensen when they produced large unrealized losses in 2008 – 2009 merely reinforces the point made above respecting asymmetry: wittingly or not, Swensen has deployed Yale’s endowment in a manner that’s caused its unitized as well as total value to grow materially in real terms since 2009 under conditions resembling in certain ways those that caused such values to shrink materially in real terms over the 30-odd years preceding Swensen’s appointment as CIO, i.e., “guns and butter” fiscal policies coupled with large dollops of central bank largesse.
Where would Yale’s finances and
in turn Swensen’s reputation be today if such largesse hadn’t materialized over
the last decade? Reasonable people can
reasonably disagree in answering that counterfactual question. Ditto for a question that’s top of mind for
me if not also you and should certainly be top of mind for investment pros
fortunate enough to be advising Trout on the deployment of his investable
wealth: will the dominant investment zeitgeist over the multi-decade horizon
under discussion here be marked by the continuance of such largesse on a more
or less globalized basis? I doubt it, but I wouldn’t bet the ranch against
it. Rather, I’d do what all fiduciaries
worthy of the name try earnestly to do when engaged in policy-making: craft policies
likely to produce tolerable results at worst across the widest plausible
range of market scenarios and pleasing results at a minimum if the
scenario or zeitgeist deemed most probable does indeed unfold.
Less is More. What zeitgeist did I deem most probable in formulating the policies commended below — an investment model if you will intended to function effectively over a time horizon rivaling the span that’s elapsed since Swensen activated “the Yale model” many years ago? Truth be told, I didn’t spend much time crafting a best guess or base case scenario for the global economy and capital markets when building the model below — not because scenario planning isn’t valuable if done astutely but rather because ET’s co-founders have shown convincingly in their writings that less is almost certainly more for investors seeking to divine economic and market trends in coming years and beyond.
Indeed, so convinced or more precisely humbled am I by Ben Hunt’s core message in Three Body Problem— “there is a non-trivial chance that structural changes in our social worlds of politics and markets have made it impossible to identify predictive/derivative patterns” — that I’ve adopted a base case scenario even leaner than that sketched by Ben in his masterful notes on zeitgeists entitled You Are Here and This is Water.
Specifically, while not
questioning Ben’s perspicacity in divining all four phenomena flagged in the nearby
box, the worldwide and necessarily long-term prism through which I ponder
policy options makes me wary of policies premised on a fully globalized and sustained
flowering of the first three trends.
This isn’t to say that I think the trends Ben espies will peter out or reverse in the foreseeable future. Indeed, I think such trends could very well accelerate, especially in the US and Old Europe, and more particularly if Rusty Guinn’s forebodings in Free Range Kids / Free Range Capitalismprove prescient; as Rusty notes, if taken too far, the ongoing transformation of capital markets into utilities could render investors as a group “utterly incapable of determining whether we should provide capital to a business or government venture, and under what terms.”
As for the fourth element of
Ben’s perceived zeitgeist as summarized above — the displacement of cooperative
games by interminably competitive ones — I’ve assigned a high probability to
this condition in crafting the policies outlined below. Fortunately and crucially, the less
sound this premise actually proves in coming years and decades, the better
I would expect the investment program sketched below to perform. That may seem delusional — most attempts to
exploit perceived asymmetries in capital markets produce strikeouts or singles rather
than extra base hits or homers — so the onus is on me to defend the assertion
just made. I try to do just that as the
modeling exercise below unfolds — one that begins logically (for a series
exploring parallels between investing and baseball) with a favorite example of less
being more in baseball.
Addition by Subtraction. As regular readers will recall, Note #1 in
this series opened with a trivia question concerning a Hall of Famer catcher
who posted a 75-3 record as a pitcher in high school. The rocket arm that made Johnny Bench (MLB
1967 – 83) nearly invincible as a high school hurler spawned ultimately a
seemingly odd stat for Bench as a big league catcher: a relatively low number
of runners nabbed stealing bases via throws from Bench. The throws themselves were unfailingly swift
and accurate, as one might expect from an athlete who’d practiced them countless
times as a youngster albeit over twice the 127’ span between home plate and
second base on a regulation diamond. (Bench’s
father and first baseball tutor knew well how to show young Johnny tough love.) In fact, Bench’s arm strength became so widely
respected in MLB circles that managers of opposing teams nixed base stealing
attempts by all but their swiftest players when doing battle against Bench’s Cincinatti
Though such circumspection by Cincy’s opponents didn’t prevent the “Big Red Machine” from winning six divisional titles plus four league and two world championships during Bench’s 17-year playing career, it did boost opponents’ odds of beating the mighty Reds. Addition by subtraction, one might call it: achieving more by doing less — by shunning endeavors in which one lacks a reliable edge or would otherwise confront unattractive odds.
Edge and Odds. I haven’t canvassed creatures fortunate enough to inhabit Little River Farm to ask how often Farmer Ben mutters “edge and odds” as he tends to their needs, but judging from how often Dr. Hunt chants that mantra in human interactions I’m guessing they’ve heard it many times indeed. With good reason: in addition to pursuit of attractively asymmetric returns — the stated if sometimes unachieved aim of active managers and the only legitimate reason to invest in broadly diversified indexes like the S&P 500 on a buy-and-hold basis — savvy investors logically seek to focus their energies on opportunity sets in which they have an actionable edge in exploiting favorable or mispriced odds.
Millions of words having been
written or spoken about “edge” in investing, I’ll say nothing about it
here except that I’m defining it for purposes of this model-building gambit as know-how
useful to the generation of above-market net returns if and when applied in an
effective manner. As noted above — and
this is crucial to the model commended below — “edge” as just defined is most
productively applied to markets in which an investor enjoys favorable or
Successful examples of such productivity include the two mavericks on whom Part 1 of this post focused. As the first MLB GM to add black and Latino players to the talent pool from which his teams drew, Branch Rickey enhanced hugely his odds of assembling world-beating rosters; and while MLB franchises not headed by Rickey weren’t long in expanding imitatively their own talent pools, by the time they took such steps Rickey and his subordinates had developed a valuable edge in discerning which players of color most merited pro contracts.
Similarly, David Swensen has enhanced Yale’s odds of partnering with market-beating managers by tilting Yale’s portfolio toward asset classes in which manager returns tend to be most dispersed; and while other allocators (big and small) weren’t long in expanding their own portfolios to include such holdings after Swensen showed the way, by the time they ramped up allocations to private equity, venture capital and other size-constrained niches favored by Yale, Swensen and his subordinates had developed a big edge in discerning which PE and VC managers most merited funding. Fortunately for Swensen, and regrettably for allocators keen to be “like Yale”, this edge compounds over time, with Yale being a coveted client for managers seeking to maximize time spent investing by minimizing time spent fundraising. Ain’t no better way to do that at present than to have Yale serve as one’s bell cow.
Pinpointing the Problem. And there ain’t no better way to convert a big fortune like the one Trout is poised to amass into a small one than to invest in volatile but potentially high returning assets without knowing them well enough to avoid ill-considered sales during inevitable bouts of punishingly poor returns. What might Trout do to avoid such impoverishment? Presuming as I do that he lacks the time if not also peculiar personal qualities needed to gain and hold an edge in investing, Trout should do what most individuals, families and institutions logically do when deploying substantial wealth: delegate the task to trustworthy pros who walk the talk set forth above — who focus their mental bandwidth and in turn clients’ capital on opportunity sets in which they have or can develop an actionable edge exploiting favorable or mispriced odds.
Tautologically, no opportunity set or selection universe meeting the criterion just specified can be boundless, because no pro’s or team of pros’ circle of competence is boundless (Herb Washington’s diverse talents notwithstanding). Conversely, no person’s or team’s investment edge in a given asset class or sub-class is so acute that they can safely be relied upon to achieve the ambitious aims conjectured here (5+% annualized real returns over a multi-decade span) without doing one or both of two things: (1) deploying at least some capital outside their chief hunting ground or (2) violating liquidity and volatility constraints typically applied in the stewardship of substantial fortunes.
Accordingly, when crafting limits on how capital under their ultimate control might be deployed, thoughtful principals strike a sensible balance between edge and odds, preserving needed flexibility while also keeping the breadth of assets or strategies deemed eligible for use within bounds consistent with the time-tested principle of knowing what you own and owning what you know. After all, the seemingly boundless skills of an all-star allocator like Swensen or an all-star baseballer like Trout notwithstanding, in investing as in athletics, no one knows it all — not even Bo. 
Admiring Tackling the Problem. Assuming the long wind-up above hasn’t caused Rusty ET faithful to dismiss me as a charlatan for merely Admiring the Problem, I’ll tackle the challenge conjectured here by outlining as concisely as I can the game plan I’d propose if Mike Trout or other well-endowed principals sought my best thinking on means of achieving 5+% real returns over the next few decades.
As promised at the outset of
this note, none of the tenets comprising my game plan contains more words than
Trout’s current age of 27. Nor do any of
these tenets address directly the concern most commonly raised when I’ve shared
the blueprint below with US-domiciled principals seeking my counsel, such as it
is: shouldn’t investors who pay their bills in US dollars invest primarily in dollar-denominated
assets? My answer, in a nutshell: not necessarily
— not if one assesses currency risk as we all should on a rigorously
look-through basis, dissecting all anticipated liabilities to reveal the
currencies underlying such potential outlays while dissecting similarly the
currencies underlying assets available for investment. Of course, the latter task is often easier
said than done, with the true attributes of even seemingly straightforward
assets like dollar denominated S&P 500 index funds differing greatly from
their perceived attributes due to the geographic breadth of constituent firms’
Hold that thought — and the corollary thought that currency shifts tend to be accompanied over time by offsetting valuation shifts — as I outline my preferred investment analog to the convention-busting views on baseball that Rickey felt compelled to serve up in the Life magazine piece celebrated in Part 1 of this note. Like Rickey, and indeed like Swensen when he submitted his preferred approach to capital deployment to Yale’s trustees for their initial approval back in the day, I recognize that what follows might be “most disconcerting” to many allocators; like Rickey — from whose Life piece I drew the self-aware red flag just quoted plus the following phrasing — I’ve “come upon [a method for deploying capital] that has compelled me to put different values on some of my oldest and most cherished theories.” As will be seen, the game plan I’ve devised owes much to contemporary thinkers and doers who’ve displayed Rickeyesque cheek in challenging what Rickey referred to unflatteringly as “considered opinion”. Here’s the plan, with its key tenets listed from most general to most specific and with noteworthy premises underlying such tenets appearing beneath each:
Tenet 1 – Create
and maintain a sub-portfolio comprising cash, or liquid investments reducible
thereto, in proportions equal to at least three years’ net cash needs
under worst case conditions.
In theory, cash is a drag on
returns of equity-oriented portfolios like the one commended here. So too is an all-purpose hedge viewed even
more skeptically by most allocators: gold.
Unwilling as I am to deem impossible over the multi-decade planning
horizon conjectured here either of the disasters that can befall
equity-oriented portfolios — depression-induced deflation or very high rates of
unanticipated inflation — I deem it imprudent to “park” less than the
equivalent of three years’ net cash needs in the “low returning” assets just
mentioned, with a bias toward high quality debt instruments whose currency
profile resembles closely that of the net cash needs such hedges seek to
Tenet 2 –Favor ownership over creditorship, with the maximum feasible bias
toward the only type of equities worth owning on an indefinite basis: stocks of
owner-operated companies (OOCs).
Though further research on this all-important topic remains to be done, studies done by Steve Bregman and his colleagues at Horizon Kinetics (HK) suggest that more than 100% of the vaunted “equity risk premium” that Yale’s equity-centric approach to endowment management presupposes is attributable to OOCs. You read that right: exclude OOCs for purposes of comparing stocks’ long term rewards to bonds’ and the latter take the crown. Needless to say, as has happened with every verifiably superior investment (or baseball!) gambit ever devised, the excess returns or “alpha” derivable from OOCs will likely get arbitraged away in due course. That caveat having been filed, there are parts of the world where the supply of OOCs (listed as well as private) continues to expand invitingly — geographies that the investment model commended here rather fancies, as will be revealed shortly.
Tenet 3 –Maintain a very high bar for private investments, accepting
long-term lock ups only when doing so provides exposures to specific forms of
capitalistic activity not obtainable via other means.
Venture investments occasionally clear this bar, though less frequently than most allocators currently clamoring for such exposures surmise. As discussed in prior notes in this series (hereand here), private equity (PE) investments clear the bar under discussion here even lessfrequently — a dirty little secret about the current apple of many an allocator’s eye that’s becoming less secretive by the minute as a young investment pro with Rickeyesque gifts for clear thinking and writing intensifies his assault on “considered opinions” respecting PE. If you’re among the rapidly shrinking universe of allocators not yet exposed to Dan Rasmussen’s admirable assaults on such opinions, you’d do well to get acquainted with same via the musingsposted on his firm’s website, including especially Dan’sfine essay in the Spring 2018 edition of American Affairs.
To be sure, the company attributes that Dan and his team have come to fancy, including small market caps, limit how much capital he or other investors using similar screens can deploy without causing potential returns to sink below tolerable levels. Since these screens, like the OOC-focused (and partially overlapping) screens that Bregman et al at HK employ, work at least as well outside the US as within it, Verdad deploys capital on a global basis — just as HK does, and just as Rickey did when populating his innovative farm system for the St. Louis Cardinals nearly a century ago.
Tenet 4 – Favor equity investments in companies employing or serving primarily people with abundance as distinct from scarcity mindsets.
For reasons flagged in multiple works by another Rickeyesque researcher — demographer par excellence Neil Howe —the US and major European economies generally flunk the test just articulated: like not a few “rich” families with which I’ve had the pain privilege of interacting, the world’s “richest” nations at present (measured by GDP per capita) comprise an overabundance of individuals who lack the skills or drive needed to generate fresh wealth commensurate with their appetites and social ambitions. Small surprise then that the “widening gyre” and related societal maladies that Howe as well as Ben and Rusty discuss so arrestingly in their writings are most conspicuously manifest in corners of the global economy characterized by (1) relatively but perhaps unsustainably high per capita incomes (2) rising dependency ratios (i.e., retirees relative to working stiffs like me if not also you) and (3) relatively high debt ratios (i.e., unpaid bills for goods and services consumed previously).
Add to the potentially toxic mix just described such intractable problems as the Eurozone’s fatally flawed currency union, America’s unsustainably undemocratic approach to self-government, and corporate America’s unsustainable addiction to the “financialization” whereof Ben speaks unlovingly, and it’s tough for any investment pro worthy of that label to defend non-zero policy allocations to US stocks as a group or to their European counterparts.
N.B.: I’d include non-zero allocations to Japanese stocks in the list of dubious policy fixtures just furnished but my own studies of evolving business and societal norms in Japan plus insights into same provided by my go-to guy on such matters (Andrew McDermott of Mission Value Partners) suggest that abundance trumps scarcity in most Japanese mindsets, i.e., expectations are low relative to most plausible outcomes (however unexciting such outcomes might be).
Tenet 5 –Apply
the tenets set forth above to the narrowest universe of eligible
investments that gets the job done.
Having test-driven the investment model now unfolding with several savvy principals before finalizing this note for publication, I know that while Tenet 5 might appeal to my arborist friend Ben (for reasons outlined here), it won’t sit well with many readers. After all, diversification being the “only free lunch” available to investors — or so financial economists would have us believe — why would thoughtful principals view less as more respecting assets eligible for purchase?
They’d do so because, presuming sensible cash flow planning of the sort embodied in Tenet 1 and asset selection consistent with Tenets 2 – 4, the chief if not sole risk of the investment program sketched here is the potential jettisoning of inherently sound strategies during their inevitable bouts of disappointingly low returns (a/k/a whipsaw). Such bad spells are inevitable because plump net real returns of the sort targeted here (5+% annualized over meaningfully long horizons) can’t realistically be achieved without potentially prolonged periods of below-target returns.
The most reliable means of guarding against whipsaw is to know what you own and own what you know. As previously noted, the only reliable means of meeting such standards is to limit one’s universe of eligible investments to the maximum feasible extent. By my lights, the optimal universe for deployment of the total return-oriented or non-hedging part of the portfolio contemplated by the framework extolled here is one hinted at in Trivia Question #7 posed at the outset of this note: Asian equities. Leaving aside Asian nations that are off limits to western investors, or have too few or too thinly capitalized public companies to merit inclusion here, the median number of sell-side analysts following the ~22,000 stocks of Asia-domiciled companies alluded to in TQ #7 is zero. This compares to the corresponding median of seven analysts for the roughly 4,000 listed companies in the US at present (down from roughly 8,000 since I sank into money management in the early ‘80s).
How many of the ~22,000 Asian stocks referenced above meet all of the criteria embodied in the tenets propounded above? I don’t have a verifiably accurate answer to this question, for two reasons: first, because the criteria are somewhat subjective, with Tenet 4 (favoring abundance mindsets) serving as the poster child for such subjectivity; second, because I know what I don’t know (yet), namely many things I need to know about Asia in order to gain and hold an edge deploying capital in that region. Strike that: taking Tenet 5 to a logical and IMHO entirely justified extreme, if granted unfettered discretion to shape the universe of assets eligible for purchase within the total return segments of long-term portfolios of the sort conjectured here, I’d enhance my odds of both avoiding whipsaw and gaining an edge relative to other investors by focusing my attention and capital on private as well as publicly-traded companies domiciled in but a dozen of Asia’s 51 nations and dependencies, as follows:
Surrendering Preconceived Ideas. “If the baseball world is to accept this new system,” Rickey noted in the heretical essay on baseball stratagem referenced repeatedly in this post, “it must first give up preconceived ideas. I had to. The [system] outrages certain standards that experienced baseball people have sworn by all their lives.” The investment paradigm sketched above will outrage some readers, methinks, especially those who view the world’s biggest national economy at present [the U.S.] as the “safest” place to deploy capital and, as a corollary, the biggest economy making the above cut as an unsafe place to deploy capital.
told, I myself generally view China as such, due largely to its suspect
fidelity to the rule of law. That said,
the scarcity mindset growing increasingly prevalent in the US and Old Europe
poses different but clear and present dangers to the rule of law! in such geographies, with the meme just mentioned
(rule of law!) serving as shorthand
for the intricately woven but increasingly frayed fabric of legal, commercial,
social and political norms on which investors in US- and Europe-domiciled
companies have customarily relied to safeguard and indeed nurture their
ownership stakes. All of which is to say
that, while I’m as opposed to non-zero fixed or policy allocations to Chinese
stocks as I am to such rigidities respecting US or European equities, I
certainly wouldn’t exclude Chinese stocks from my hoped-for circle of
competence (defined broadly to include Asia- or China-focused managers
deploying capital entrusted to me).
Nor would I
pursue policies entailing unduly high bars to the ownership of equities
denominated in currencies issued by any of the countries comprising my
self-selected opportunity set, China not excepted. Indeed, convinced as I am that Ben has
divined rightly that “competitive and single-play games” have displaced
“cooperative and multi-play [ones]” in international politics and economics, I’d
assign better-than-even odds to the US dollar’s displacement as the world’s
dominant reserve currency within the next quarter century or so. I doubt the Chinese yuan or indeed any other
currency excepting possibly gold will ascend to the throne that USD seems
destined to vacate, of necessity or choice.
But I’m reasonably confident that by the time Mike Trout takes his
rightful place in baseball’s Hall of Fame a decade or two from now, the global
economy will be divided into three major currency blocs, with China, Germany and
the US each spearheading the bloc in which their national currencies sit.
I’m reasonably confident too that the scarcity mindset increasingly manifest in American politics and economics will produce ultimately a material downward revision in the US dollar’s value relative to both gold and a sensibly weighted basket of its “trading” partners’ currencies, with “trading” defined broadly to include services as well as goods. Obviously and perhaps sadly for Americans lacking overseas holdings or other means of profiting from dollar debasement, USD devaluation to the degree divined here would generally flatter the Asia-centric investment program delineated above, spawning as it likely would currency-related gains on non-US stocks even after factoring in valuation shifts commonly associated with major currency moves.
(If you’re unfamiliar with how and why such shifts occur, you should be especially wary of any raccoons investment pros seeking to manage your money for a fee while assuring you they have everything under control. “Investing is simple,” one often hears, “but not easy.” In fact, effective investing is neither simple nor easy, least of all for investment pros forced unavoidably and unendingly to balance their own pecuniary needs against their clients’ wants and needs.)
Finally and not obviously, in the unlikely event that America scores decisive victories in the “competitive and single-play games” in which it seems destined to participate in coming years and beyond, I’d expect the Asia-centric investment program endorsed here to produce long term returns not merely matching but likely besting those produced by US-centric alternatives. Why? Because the restoration of Pax Americana that such victories would both presuppose and promote would almost surely put strong and steady winds into the sails of the Asian economies identified in the table above, including especially India (my single favorite target for capital deployment in coming decades) as well as smaller Asian nations likely to fare better on balance if Uncle Sam’s traditional values of liberty and justice for all triumph ultimately over Uncle Xi’s evolving ethics, such as they are. Heads I win, tails I don’t lose. That’s the ticket, we’d all agree — even if we can’t agree on the surest means of dialing such asymmetry into capital allocation protocols.
Indeed, mindful as I am that the policy prescriptions proffered here may create a “widening gyre” (to quote Ben quoting Yeats) of opinions within the ET Pack respecting prudent approaches to capital deployment, I’ll try in my next note to inject centripetal forces into the mix by presenting to the Pack the single best metric known to me for gauging long term investment success. By my lights, it’s as relevant today as it was when its principal modern proponent first drew it to my and other investment wonks’ attention in 2005. Mike Trout was a young teenager playing baseball for free back then; and the so-called sabermetrics revolution that’s changed materially the metrics baseball cognoscenti employ for gauging ballplayers’ worth had only recently commenced. As will be seen, just as sabermetrics is rooted in methods devised many years earlier by the great and good Branch Rickey, the money metric I’ll discuss approvingly in Note #8 is rooted in methods of gauging financial abundance devised long before the first MLB game was played 143 springtimes ago.
 Many lovers of sport including some lovers of baseball think MLB games have become too long and devoid of action since computer-based analytics came to the fore in pro baseball several years ago. I share such concerns, with a carve out for games unfolding glacially at Fenway, and plan to discuss them plus potential remedial measures in a future note.
 You can check my math here, applying to Trout’s newly contracted pay package the 52% effective tax rate I’ve assumed here or whatever alternate rate you deem sensible given the idiosyncratic manner in which salary payments received by peripatetic entertainers like Trout get taxed. Like rock stars on tour — which Trout essentially is — MLB players pay state-level income taxes pro rated to the number of days they play in a given state each season, taking credits against their home state’s levies. As a New Jersey resident for tax purposes, Trout is poised to fork over a minimum of at least 9% of his pay in state taxes, with half or more of his salary being subjected to the ~13% tax extracted by the state in which Trout and his Angels teammates play half of their regularly scheduled games each season: California.
 As Ben Hunt wrote when elevating the term to its rightful place as a key concept in Epsilon Theory (here), “zeitgeist” “is the macro scale of our social lives as investors and citizens.”
 Bench’s extraordinary gifts as a ballplayer are captured nicely in the brief profile posted here.
 Though capitalization weighting stocks for passive investment purposes is demonstrably inferior to other portfolio construction methods on a pre-tax basis, even a cap-weighted index like the S&P 500 has displayed historically and will likely continue displaying asymmetry of the sort alluded to here: the longer one lengthens the time periods over which returns are examined, the higher the percentage of positive outcomes rises. Hence, even if the odds of investing in broadly diversified portfolios like the S&P 500 aren’t mispriced (and good luck diving inflection points in such mispricing), they are unarguably favorable in positive payoff terms for truly long-term investors. The defects of cap-weighted portfolios are catalogued cleverly in a 2006 paper by Jason Hsu posted here and in a 2018 research note by Jason and his former Research Affiliates colleagues Rob Arnott and Vital Kalesnik posted here.
 Using the least-worst available metric for gauging baseballers’ on-field contributions to their team’s success (a cumulative measure known as Wins Above Replacement or WAR), Trout’s achievements as both a batsman and outfielder since his big league career commenced at age 19 in 2011 have already elevated him to a Top 150 spot in MLB’s all-time list of players ranked by WAR: when his ninth season as a big leaguer commenced in March 2019, Trout had compiled a lifetime WAR of 64, which is roughly equal to the median WAR for the 261 players (including four 2019 inductees) comprising baseball’s Hall of Fame. Think Trout will join their ranks eventually? Me too, especially since he’s already 16th in WAR all-time among center fielders, ahead of nine of the 19 such players who’ve been elected to the Hall.
 As noted in its white paper on OOCs, HK defines an “owner-operator” as “a principal or an owner — often a founder — who is directly involved in the management of a corporation in which he or she maintains a significant portion — ideally the majority — of his or her wealth.”
 “Unsustainably undemocratic” as used here refers to the inevitable reformation of arrangements that today give roughly 30% of the American electorate a de facto veto (via the US Senate) over laws governing the residual 70%. Of course, the same imbalance is manifest in US presidential elections decided ultimately by the electoral college — an artifact of logrolling by America’s founding fathers whose eventual elimination could and likely will entail political if not also social unrest inimical to the interests of passive investors in broadly diversified portfolios of US stocks.
 Ping me via email@example.com you’d like to review data supporting this assertion. Alternatively, take a look at the characteristically fine Wall Street Journal piece that my pal Jason Zweig crafted after he laid hands on the data in question.
There are these two young fish swimming along and they happen to meet an older fish swimming the other way, who nods at them and says “Morning, boys. How’s the water?” And the two young fish swim on for a bit, and then eventually one of them looks over at the other and goes “What the hell is water?”
David Foster Wallace (2005)
It’s the perfect description of a Zeitgeist … the water in which we swim.
We can’t see it. We can’t hear it. We can kinda sorta feel it, if we focus really hard, but only kinda sorta. All the same, because it’s part of a social system and not a physical system, WE create it. Not in a conscious fashion. We can’t set out to create a Zeitgeist.
It’s like a stadium crowd holding up cards for the TV audience. They can’t see the picture they’re making … they have no idea what it looks like or what their role in its making might be. But they’re told/asked to do it. So they do.
THIS is a Zeitgeist.
What’s the matter, Ben? You got a problem holding this card up over your head? It’s for the troops. You support the troops, don’t you? Don’t you?
Yes, I support the troops. And yes, I have a problem with this.
Why? Because I don’t trust the State and the Oligarchy to use the common knowledge of “support for the troops” – the crowd watching the crowd express a public act of allegiance to the military, so that everyone knows that everyone knows that yes, it is right and proper to support the troops – for the right reasons.
Instead, I suspect that they will use my voluntary “support” (hey, no one forced you to hold up that card) to justify things like … oh, I dunno, a trillion dollars wasted and 2,000 kids dead to fight a war in freakin’ Afghanistan. Because, you know, otherwise “the terrorists win”. Otherwise we lose “credibility”. JFC.
It’s exactly the same thing with capitalism.
In exactly the same way that all of us sit in our citizenship stadium and get nudged to hold up a card creating a common knowledge display of “Yay, military!”, so do all of us sit in our investor stadium and get nudged to hold up a card creating a common knowledge display of “Yay, capitalism!”.
What’s the matter, Ben? You got a problem holding this card up over your head? It’s for capitalism. You support capitalism, don’t you? Don’t you?
Yes, I support capitalism.
AND I have a problem with holding up this card.
You should, too.
Because we can’t trust the State and the Oligarchy to use our support for the right reasons.
In You Are Here, I wrote that the investment Zeitgeist is changing in three ways.
Deflationary expectations, now 40+ years old, are becoming inflationary expectations.
Cooperative and multi-play games in both international politics and domestic politics, now 70+ years old, are becoming competitive and single-play games.
Modern capital markets, now 150+ years old, are becoming political utilities.
Time to add a fourth.
Capitalist productivity, now 200+ years old, is becoming capitalist financialization.
What is financialization?
Financialization is profit margin growth without labor productivity growth.
That sounds like a small thing, but I tell you it is EVERYTHING.
Financialization is squeezing more earnings from a dollar of sales without squeezing at all, but through tax arbitrage or balance sheet arbitrage.
Financialization is the zero-sum game aspect of capitalism, where profit margin growth is both pulled forward from future real growth and pulled away from current economic risk-taking.
Financialization is the smiley-face perversion of Smith’s invisible hand and Schumpeter’s creative destruction. It is a profoundly repressive political equilibrium that masks itself in the common knowledge of “Yay, capitalism!”.
Financialization is a global phenomenon. In China, it’s transmitted through the real estate market. In the US, it’s transmitted through the stock market.
Financialization is the zombiefication of an economy and the oligarchification of a society.
Here’s the foundational chart for these strong words.
This is a 30-year chart of total S&P 500 earnings divided by total S&P 500 sales. It’s how many pennies of earnings S&P 500 companies get from a dollar of sales … earnings margin, essentially, at a high level of aggregation. So at the lows of 1991, $1 in sales generated a bit more than $0.03 in earnings for the S&P 500. Today in 2019, we are at an all-time high of a bit more than $0.11 in earnings from $1 in sales.
It’s a marvelously steady progression up and to the right, temporarily marred by a recession here and there, but really quite awe-inspiring in its consistency. Yay, capitalism!
It’s a foundational chart for this note because I believe that the WHY of earnings margin growth in the 1990s and early 2000s is fundamentally different than the WHY of earnings margin growth since then.
WHY do we get three times as much in earnings out of a dollar of sales today than we did 30 years ago, and twice as much than we did 10 years ago?
The common knowledge answer is technology!.
By which I mean that the common knowledge answer is the meme! of technology as opposed to any actual technology. By which I mean that we can’t exactly say why technology would improve earnings margins and efficiency over the past decade, but we believe it MUST be technology. Somehow. Of course it’s technology. Everyone knows that everyone knows that it’s technology that makes anything in the world more efficient. So we mumble something-something-technology whenever anyone asks a question like this. And yes, This Is Why We Can’t Have Nice Things.
Here, hold this card up over your head. It’s for technology and progress. You support technology and progress, don’t you? Don’t you?
I used to believe this, too. I used to believe that corporate management was getting better and smarter over time, that they were making constant process improvements and technology-based productivity enhancements to squeeze more and more profits out of the same sales dollar.
And I think this used to be true. I think that during the 1990s and early 2000s – the so-called Great Moderation of the Fed’s Golden Age – when we actually had significant advancements in labor productivity year after year after year, corporate management was, in fact, able to drive earnings margins higher for the right reasons. I think the driver of profit margin growth over this period was actual technology, as opposed to the meme of technology!.
But I don’t believe this is true anymore. I don’t believe that technology and productivity advancements have been responsible for earnings margin improvements for the past decade … for some years before the Great Financial Crisis, in fact.
Here, take a look for yourself.
See, the Fed was convinced that an easy money policy would lead to corporate management investing more in technology and plant and equipment … you know, all of those things you need to drive productivity. All of those things you need to drive a 1990s style recovery, with earnings margin accretion for the right reasons.
Instead, corporate management followed the Zeitgeist.
They always do. It’s the smart move.
This is a chart of Labor Productivity growth in the US for the past 30 years. It’s how much more stuff we make or services we provide from a unit of labor. It’s how much we’re growing for the right reasons, by applying capital investment in plant and equipment and technology to work smarter and more efficiently. It’s how we generated earnings efficiency and margin growth for the right reasons in the 1990s and early 2000s. It’s how we’ve been reduced to squeezing tax policy and ZIRP-supported balance sheets for earnings efficiency ever since.
This chart IS the failure of monetary policy for the past decade.
This chart IS the zombiefication and oligarchification of the US economy.
Why do I rail at the Fed? THIS.
Trillions of dollars in QE, and all we got for it was this lousy t-shirt. Yes, I’m going to get this productivity chart put on a t-shirt.
The reason companies aren’t investing more aggressively in plant and equipment and technology is BECAUSE we have the most accommodative monetary policy in the history of the world, with the easiest money to borrow that corporations have ever seen. Why in the world would management take the risk — and it’s definitely a risk — of investing for real growth when they are so awash in easy money that they can beat their earnings guidance with a risk-free stock buyback? Why in the world would management take the risk — and it’s definitely a risk — of investing for GAAP earnings when they are so awash in easy money that they can hit their pro forma narrative guidance by simply buying profitless revenue? Why in the world would companies take any risk at all when the Fed has eliminated any and all negative consequences for playing it safe?
What’s changed since I wrote that note is that the barge of monetary policy, both in the US and everywhere else in the world, has done a 180 and is now chugging back down the easing river. No central bank in the developed world is looking to tighten today, and if anything we’re on the cusp of fiscal policies like MMT, or at least trillion dollar deficits forever and ever amen, to accelerate the shift in the modern Zeitgeist towards fiat EVERYTHING.
This is not a mean-reverting phenomenon.
This doesn’t get better going forward. It gets worse.
But wait, there’s more …
This is a chart of the S&P 500 price-to-earnings ratio in yellow, the belle of the narrative ball, together with its forgotten cousin, the price-to-sales ratio in blue.
When we grow profits through productivity growth – when our “supply” of earnings is directly connected to the same operations that generate sales – P/E and P/Sales multiples go up and down together. When we extract excess earnings through financialization – when our “supply” of earnings increases for no operational reason connected with sales – the P/E multiple becomes depressed relative to the P/Sales multiple. As the kids say, it’s just math.
Why is this important? Because a P/E multiple deflated by financialization doesn’t mean what you think it means.
How many times in the past ten years have you heard that the market is not expensive on a valuation basis? And what you’ve heard is right, as far as it goes.
Because the market narrative of valuation is completely dominated by the vocabulary of earnings, not the vocabulary of sales.
Sure, the S&P 500 P/Sales ratio is near an all-time high, but who cares about that? The S&P 500 P/E ratio today is right at 19 … neither crazy low nor crazy high … and we ALL care about that. But here’s the thing:
Without financialization, my guess is that the S&P 500 P/E ratio today would be 28.
Good luck selling that to a value investor, Wall Street.
Here, hold this card up over your head. It’s for value and a reasonable earnings multiple. You support value and a reasonable earnings multiple, don’t you? Don’t you?
But wait, still more …
This is a chart of S&P 500 buybacks per share (in blue) imposed over the ratio of S&P 500 earnings-to-sales in green. You’ll see that share buybacks spike after profit margins spike. You’ll see that share buybacks spike before and during recessions.
When do stock buybacks accelerate dramatically?
In 2006 and 2007, when management is rolling in record profits and profit margins, despite meager productivity growth.
In 2018 and 2019, when management is rolling in record profits and profit margins, despite meager productivity growth.
This is not an accident.
Here’s the past five years so you can see the temporal relationship more clearly.
Stock buybacks are what you DO with the excess earnings you’ve made from financialization.
Why? Because stock buybacks are part and parcel of the financialization Zeitgeist. They’re part and parcel of the tax-advantaged issuance of stock to management, which is then converted into tax-advantaged income for management through stock buybacks.
Here, hold this card up over your head. It’s for alignment of interests between management and investors. You support alignment of interests between management and investors, don’t you? Don’t you?
What does Wall Street get out of financialization? A valuation story to sell.
What does management get out of financialization? Stock-based compensation.
What does the Fed get out of financialization? A (very) grateful Wall Street.
What does the White House get out of financialization? Re-election.
What do YOU get out of financialization?
You get to hold up a card that says “Yay, capitalism!”.
So what do we DO about this?
I’ve got three answers, one for your life as an investor, one for your life as a citizen, and one for your life as a human being.
Whether you’re a trader or a portfolio manager or a financial advisor or an allocator, ET Pro can help you identify both the inflection points and the trajectory of the market Zeitgeist – particularly the question that any long-term portfolio owner MUST get roughly right in order to succeed: are we in an inflationary or deflationary world, and how quickly (if at all) and in what ways is that world changing . . .
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You can make a lot of money collecting Golden Age comics. The Silver Age, though? Meh. The story arcs and narratives are a joke. The art is so-so at best. The publishers are just squeezing the installed base, and the creators are just mailing it in. They're old, but so what?
Same with the Silver Age of Central Bankers. It's hard to make money, particularly in Emerging Markets, when it's every man for himself among DM central banks . . .
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Back in the day, the long/short hedge fund I co-managed was part of a larger long-only asset manager. Their biggest strategy was US mid-cap value, and it was well staffed with a bevy of really sharp analysts and PMs. But the firm also had a $4 billion US large-cap strategy that was managed by all of two people – the firm’s co-founder as PM, plus a single analyst position that was something of a revolving door … people would come and go all the time in that seat.
The solo analyst’s job, as far as I could tell, was basically to go to investor conferences and to construct massive spreadsheets for calculating discounted cash flow models for, like, Google. And sure, Google would be in the portfolio, because Google MUST be in a large-cap portfolio, but it had nothing to do with the literally hundreds of hours that were embedded in this sixty page spreadsheet. I mean … if the firm’s co-founder/PM spoke with the analyst more than once per week about anything, it was an unusual week, and there’s zero chance that he ever went through this or any other spreadsheet. Zero.
Now to be clear, I think the firm’s co-founder was a brilliant investor. This guy GOT IT … both in terms of the performance of portfolio management and the business of asset management. But here he was, managing a $4 billion portfolio with one ignored analyst, and it was working just fine. So I was talking with him one day and finally asked the question: what are you doing with large-cap?
Here’s his answer, and it has stuck with me like glue ever since.
Look, Ben, you gotta understand. Large-cap investing … it isn’t stock-picking. I gotta have the research and I gotta be able to talk about the names, because that’s what’s in the portfolio. But it isn’t stock-picking. You will drive yourself craaaazy if you’re picking large-caps, and it doesn’t do anything for you. Large-cap investing is sector-picking. What matters is whether I’m overweight or underweight a sector versus the benchmark. That’s the ONLY thing that matters.
So I asked the obvious follow-up: how do you do THAT? how do you pick sectors?
Money flows. I talk to guys about what they’re seeing. And then there are guys like Birinyi who publish books of data on this stuff every month. You can’t catch the little moves, but every now and then you can catch a big move into or out of a sector. And that’s all it takes.
He showed me some of the Laszlo Birinyi journals. They were Kabbalah-esque to put it mildly, printed page after printed page after printed page of tickers and numbers and arrows.
But I got it.
He wasn’t just playing the cards. He was playing the players.
He was reading the tape.
Now I know this will come as a shock to almost every active investor today, but reading the tape – trying to figure out the flow of money into and out of securities – was THE dominant approach to investment strategies at least through the 1960s.
Intrinsic security analysis? Graham and Dodd? The wit and wisdom of Uncle Warren and the hajj to Omaha? All of these beliefs and tenets that we hold so dear as received truths in this, the best of all possible worlds? Pffft. Sixty years ago you would have been laughed off of Wall Street.
What, you think we’re smarter than those guys sixty years ago? You think we’ve made some sort of scientific advancement that changes the social nature of markets? LOL
To a guy like Gerald Loeb, who co-founded E.F. Hutton and was Warren Buffett-level famous back in his day, intrinsic value analysis of a security wasn’t just wrong-headed, it was downright destructive to wealth creation. Only the rubes thought they knew better than the market what a stock was worth, and during the Great Depression he saw these “value investors” carted off the field by the thousands.
What’s a stock worth? Whatever the next guy is willing to pay for it, that’s what. Nothing more and nothing less. Intrinsic security analysis … gimme a break.
That’s the Wall Street gospel of Gerald Loeb. In the 1950s, everyone knew that everyone knew that Gerald Loeb was right.
No one remembers Gerald Loeb today.
It was the same with Carnegie and Gould and Vanderbilt and all of the other robber baron OGs of Wall Street. Read their memoirs, or the memoirs of the poor saps who “invested” against them … robber barons didn’t build DCF models! They figured out corners. They read the tape and they made the tape. They figured out where the money was flowing and how to get it to flow where they wanted it to flow.
All of these guys must be spinning in their graves to see what we’ve become – a nation of rubes, bowing and scraping to the Great God of Intrinsic Value Analysis, buying high and selling low constantly, in both politics and investing, for no reason other than we are TOLD that this is the Truth with a capital T here in Fiat World.
Marc Benioff gets it. Jim Cramer gets it. They have figured out the game. Why can’t we?
Because we’re really bad poker players, that’s why.
We stare at the cards in front of us and we bet them as if no one in the history of the world has ever been dealt those cards before. We bet them with zero strategic consideration of the larger metagame that we’re playing … the game of markets. We bet them as if everything we hear and see from the other players around the table, particularly the players with really big stacks, is the straightforward truth, as if their finger-wagging and Fiat News – the presentation of opinion as fact – were some sort of neutral act, some sort of public good, rather than the intentional self-aggrandizing act of people who want to take our chips away from us.
We can be better poker players.
Not by putting another 100 hours of work into our DCF spreadsheet for Google. Not by doing more “fundamental analysis” on Salesforce.com, where … don’t forget! … Trust Is The Highest Value ™.
We can’t be better poker players by playing the cards any harder.
We CAN be better poker players by playing the players a lot smarter.
We can be better poker players by applying a new technology – Natural Language Processing (NLP) – to an old idea – reading the tape.
We can be better poker players by anticipating money flow behaviors through a mathematical calculation of the narrative effort that Wall Street makes to TELL you what sectors to buy and TELL you what sectors to sell.
Just like Teddy KGB and his Oreos, Wall Street can’t help itself but signal its intentions.
This is Wall Street’s literal tell.
I know … crazy talk. Pics or it didn’t happen, right? Fair enough.
For a couple of years now, Epsilon Theory has been presenting two-dimensional representations of networks of financial media texts, what we call narrative maps. We’ve been using an NLP AI and data visualization software package developed by Quid (which is a very cool company you should check out) to process and represent the textual data. Here is Quid’s one-slide primer on what you’re looking at when you see one of these narrative maps.
I find it helpful to think of the Quid software as a microscope, as a lab instrument that we can license. It’s up to us what we DO with that microscope – how we choose something appropriate to analyze, how we prepare the “slides”, and how we interpret the results.
Here, for example, is a narrative map of financial media articles that contained the search term “private equity” over the prior six months, where each of the individual dots (nodes) represent a single unique article, where the nodes are clustered by language similarities, and where the nodes are colored by the overall sentiment score of each article.
And here is the narrative map of financial media articles over the same time span that contained the search term “hedge fund”.
What do the differences in the two narrative maps mean? A lot. We think. That is, so long as we are looking at these two-dimensional narrative maps and interpreting their differences in size and shape and coloring, we’re giving you our qualitative assessment of those differences. It’s what we THINK, not what we MEASURE, and unless the differences are pretty stark it can be difficult for the human eye to make out a meaningful difference.
Also – and this is really important – these two-dimensional visualizations of a narrative map are by necessity compressing the hell out of the underlying data. We are losing information in the creation of this visualization, and we have to get down to the level of the underlying data matrix in order to use ALL of the data and apply MATH to it.
To get a sense of the underlying data matrix and what information we can pull from it, we have to go back to what the AI of any Natural Language Processing (NLP) technology is actually doing. An NLP AI has been trained on millions of text documents in order to recognize syntax and n-grams (words and phrases with discrete meaning) across a symbolic set (a language), and it compares every n-gram in one text document with every n-gram in every other text document to create a truly massive set of n-gram comparisons, mapped to each document.
Say you’ve got 1,000 documents, each with 1,000 n-grams. One document of 1,000 n-grams processed against one other document of 1,000 n-grams generates 1 million n-gram comparisons. One document processed against all other documents generates (almost) 1 billion n-gram comparisons. Every document processed against every other document generates (almost) half a trillion n-gram comparisons. That’s a big number, and that’s why NLP has really only come into its own over the past four or five years … the data calculations themselves are pretty trivial, but you need a ton of sheer computing processing power to complete these tasks in a non-trivial amount of time.
Now let’s organize those n-gram comparisons at the node (document) level, so that we create a matrix of each node compared to every other node, with an asymmetric dimensional depth derived from the shared n-grams associated with each node-to-node comparison. This is a matrix with millions of node-compared/n-gram-shared relationships.
Now imagine the pattern of those relationships. In particular, imagine the distance between these node relationships. Because that’s all the math IS in these matrix algebra calculations … different ways of measuring the distance and the centrality of one dynamic node-and-n-gram relationship to another.
I know … still kinda ethereal and hard to wrap your head around.
The important thing to remember is that this is a big data matrix of relationships or connections between nodes. That’s the THING that we want to analyze with matrix algebra.
We want to measure two aspects of this patterning of node relationships: Attention and Cohesion.
(I’ll show examples of both in two-dimensional space, but keep in the back of your mind that what we’re doing now is applying these two dimensional visualizations onto a multi-dimensional data matrix, because math isn’t forced into seeing in only two or three dimensions like we are.)
Attention is the persistence or prevalence of one narrative sub-structure relative to all the other narrative sub-structures within a broader narrative structure.
In English, it’s a measure of how much financial media drum-beating is happening on, say, “China Tariffs” relative to all of the other financial media drum-beating that’s happening over any given time span.
This isn’t a narrative map of “China Tariffs” in February. This is a narrative map of ALL financial media in February. Nor is it a map where we have just highlighted the specific “China Tariffs” cluster of nodes, because that single cluster is a product of “flattening” the underlying multi-dimensional data matrix into a two-dimensional representation of the most prominent data relationships. This is a map of ALL financial media in February, where we have highlighted ALL of the nodes that possess a relevant n-gram connection to the narrative sub-structure of “China Tariffs”.
If you’re familiar with microscopy or medical imagery, the methodology here is similar to “staining” cells that possess some particular biological marker, regardless of where those cells live in the body or are clustered on the slide. In a very real sense, whatever narrative we’re interested in studying is like a cancer, and we’re trying to measure its metastasis over time.
Cohesion is the connectedness and similarity of language within a narrative map, relative to itself over time.
In English, it’s a measure of how focused financial media drum-beating is on, say, “Inflation” or “Brexit” over time. It’s a measure of shared meaning and centrality of meaning within a given topic. For example, both of the maps on the right are far more cohesive than their cousins on the left:
I like to think of Cohesion as a measure of the average node’s distance from the center of gravity of the overall map. It’s the difference between people writing about inflation or Brexit as a throwaway line, as something tangential to what they’re really writing about, and really writing ABOUT inflation or Brexit.
So notice what we haven’t talked about at all in this discussion of how to measure narrative. We haven’t talked one bit about Sentiment, even though that’s the only meaning most people have for the concept of narrative!
If you think you’re analyzing narratives by measuring Sentiment, you’re doing it wrong.
Why? Because Sentiment is a property of each individual node. It has nothing to do with the relationships or connections between nodes. Sentiment is a conditioner of narrative, not a structural component of narrative.
Sentiment is measured by comparing the n-grams in any given text document to a lexicon of n-grams that have been pre-scored for their level of sentimental affect. Not only does that create some weirdnesses based on how that lexicon was constructed and scored (for example, most lexicons would score “overweight” as a highly negative n-gram, even though it’s a highly positive n-gram in financial media), but more importantly there’s no comparison of one document to another. Sentiment is just a standalone score for that particular document. You can roll that up for the average sentiment of the narrative map, but taken by itself Sentiment is always going to treat each node as equally important, regardless of its relevance for the Attention and Cohesion of the narrative.
Is Sentiment an important measure? Sure. But it only has actionable meaning (we think) in connection with a structural component of narrative, like Attention or Cohesion. Bottom line: Sentiment colors narrative (literally in our maps), but it is not narrative itself.
Are there other aspects of n-grams that color narrative but are not narrative themselves? Yes. In particular, we think that there is a fiat-ness to word choice, particularly in financial and political media, where authors intentionally choose one set of words over another set of words in order to couch their opinions as fact. It’s what we’ve called Fiat News, and we’re developing our own lexicon for this conditioner of narrative.
So that’s how we measure market narratives in a rigorous way.
Now we have to connect those measures to a theory of money flows.
It’s a pretty basic connection, really, and it’s at the core of all advertising … actually, all marketing since the dawn of time: we don’t buy what we don’t notice.
This is as true for large-cap stocks as it is for soap or cornflakes, and Wall Street knows it. The way to anticipate money flows is to track the effort that the Street makes to get you to notice this sector or that sector. That effort is what we call narrative, and the greater the effort, the more we notice. The more we notice, the more likely we are to buy, particularly if that effort is coupled with a focused pitch and a positive slant.
By tracking narrative effort, focus and slant – or what we call Attention, Cohesion and Sentiment – we think we can anticipate money flows. We think that different combinations of higher or lower than usual Attention, Cohesion and Sentiment create different pressures on future money flows. Which means different pressures on future prices.
We’ve theorized four basic combinations – what we’ll call Narrative Regimes – that we think create pressure on future money flows. No doubt there are others.
Early Drumbeats: Low Attention + High Sentiment
Wavering Bull: Low Cohesion + High Sentiment
Cohesive Bear: High Cohesion + Low Sentiment
Overbought: High Attention
And we think they work like this:
There is a lifecycle to any market narrative.
It is born, it grows, maybe it reproduces, and it dies.
The birth of a market narrative often takes the form of Early Drumbeats. Here the Attention score is low but the Sentiment is high. The Street must try out different arguments, different stories before they can find one that sticks. But they WILL find the one that sticks, and the result is investor attention. Investors notice the sector. Investors hear the marketing effort. And investors buy. Can you measure Early Drumbeats in time T? Then own the sector in time T+1, because that’s when the money really flows in.
All good things come to an end. Maybe the Street is so successful in creating a compelling market narrative that Attention gets unusually high (Overbought). Measure that in time T? You’ll want to short that sector in time T+1. Or maybe the market narrative loses its focus while keeping a positive slant (Wavering Bull). That’s how a narrative slowly dies. Or maybe the market narrative keeps its focus but sours on the sector (Cohesive Bear). That happens more often than you think, particularly after a long period of positive drum-beating that didn’t particularly go anywhere. You’ll see selling when this narrative regime takes hold, too.
For the past few months we’ve been running processors and threads 24/7 to calculate Attention, Cohesion and Sentiment scores for the eleven sectors of the S&P 500 so that we can test these narrative theories of money flows. That’s an enormous amount of computational analysis and it’s gotten us … 24 months worth of data so far.
I honestly do not know where this will all end up.
I honestly do not know how to tell you about our preliminary results without TELLING YOU A STORY about our preliminary results, because that’s what preliminary results are … a story. And if you’ve followed Epsilon Theory even a little bit you’ll know what I mean when I say that’s a mighty poor way to play this metagame.
So I’m not going to talk about results until I can do it without telling a story, until I can show you results that speak for themselves. It’s like the difference between qualitatively interpreted narrative maps and algebraic calculations on the underlying data matrix … the difference between what we THINK and what we can MEASURE.
But I will continue to talk about our research program, rarely in the clear with notes like this, but openly and fully with our Epsilon Theory Professional subscribers.
If you’d like a front row seat for this research program, as we try to reanimate an old investment strategy with a new technology, please consider an ET Pro subscription. We really don’t know where this will all end up. But it will be one hell of a ride.
But these are the cards we’ve been dealt. Let’s play them as well as we can.
I’m focusing on the financial services ecosystem in these notes, because this industry has already been totally wrecked by financial asset inflation, a tide that lifts all boats and squeezes all margins regardless of skill or smarts.
It’s a margin-wrecking inflationary flood that is coming soon to all service industries.
The skinny of “Pricing Power #1 – Client Ownership” is that pricing power in a services industry is found in your proximity to the client relationship, not the product that the client is buying. The problem, of course, is that it’s really really hard to scale client relationships, or at least it’s hard to scale the relationships that are worth scaling.
The skinny of “Pricing Power #2 – Intellectual Property” is something of the reverse. If you ARE on the product side of your industry, then the only way to maintain pricing power is through narrative-rich if not mythic intellectual property. Conversely, relationship owners always think that they can scale their nice little client-facing businesses with Technology IP. They are always wrong. The one (rare) exception is the use of Content IP, but even here you are scaling your client relationship depth, not your client relationship breadth.
The skinny of “Pricing Power #3 – Government Collaboration” is that the most dependable way to protect your margins and maintain pricing power is to partner with the government to provide a politically useful service. I don’t mean an overt partnership. I don’t mean becoming a government contractor (although sure, that works, too). I mean identifying the social meaning of your services industry and implementing a business strategy that supports THAT.
I know it sounds all touchy-feely to talk about the “social meaning” of this or that, and it is, in fact, completely intangible and invisible to the naked eye. But it’s no less real for that.
For the financial services industry, the Zeitgeist boils down to one core idea, one core dynamic:
Capital Markets are being transformed into a Political Utility
After the systemic near-death experience of The Great War, French President Georges Clemenceau famously said “wars are too important to be left to the generals”.
After the systemic near-death experience of The Great Financial Crisis, all political leaders – of both the Right and the Left – are saying “asset prices are too important to be left to the investors”.
How have political leaders wrested control of price-setting from investors in the 2010s, just as they wrested control of war-setting from generals in the 1920s? I’ll start with a simple but (for many) painful fact, the end result of capital markets transformed into a political utility.
For the past 10 years, ever since the end of the GFC, active investing in general and value investing and quality investing in particular have failed.
And not just failed a little, but failed a lot.
The green line below is the S&P 500 index, including dividends. The blue line below is a market neutral Quality Index sponsored by Deutsche Bank. They look at 1,000 global large cap companies and evaluate them for return on equity, return on invested capital, and accounting accruals … quantifiable proxies for the most common ways that investors think about quality. Because the goal is to isolate the Quality factor, the index is long in equal amounts the top 20% of measured companies and short the bottom 20% (so market neutral), and has equal amounts invested long and short in the component sectors of the market (so sector neutral).
You’ve made a grand total of not quite 8% on your investment in this Quality-focused index … not per year, but over the last DECADE.
Over the same time span, your passive investment in the S&P 500 has almost quintupled. With dividends, it’s up more than 360%.
For the past TEN YEARS, Quality has been absolutely useless as an investment strategy.
Have the Quality stocks in your portfolio gone up? Yes, but it’s not because of the Quality-ness of the companies. It’s because ALL stocks have gone up, Crap and Quality alike. In lock step, with nary a blip either way.
And yes, I’m using this Quality index as a proxy for active portfolio management of all types. Because it is. Sure, quality – like beauty – is in the eye of the beholder. But the core bias of every discretionary manager, regardless of asset class or geography or whatever corner of the investment world they play in, is always the same – buy the good stuff and avoid the crap.
For the past decade, all of your smarts … all of your efforts … all of your time … all of your money … every resource you have devoted to distinguishing between good stuff and crappy stuff in large-cap public equity markets … has been wasted. I’m not using the word “wasted” in a pejorative or judgmental sense. I’m using it in the technical sense. It has given you no better results than the less smart, less hard-working, less devoted, less well-resourced investors who just plopped their money willy-nilly into crappy stuff.
It’s not fair.
But it is the truth.
As a result, your business model – which requires you to charge enough in fees to cover the cost of all these resources you have wasted – has been squeezed and squeezed and squeezed. Because no one is going to pay you more for less. Marketing alpha can only go so far. And when that runs out … well, it’s “family office” time.
Now here’s the kicker.
The failure of active management is not an accident.
The political rule-setters for markets don’t give a damn about rewarding quality companies and punishing crappy companies, much less rewarding smart investors and punishing stupid investors. They care about not doing 2008 again. Ever. Under any circumstances. They care about providing a rising tide that lifts all boats. And so that’s what we’re going to get.
The intentional transformation of capital markets into a political utility is the common thread of ALL of it … all of the QE, all of the ZIRP, all of the negative interest rates, all of the forward guidance, all of the “communication policy”, all of the Fed puts, all of the Dodd-Frank theater, all of the regulatory blindness towards too-big-to-fail banks, all of the Trump tweets about the market, all of the CNBC appearances by White House apparatchiks, all of the Chuck Schumer “buy-backs are evil” op-eds, all of the Green New Deals, all of the show trials to come (and there will be show trials). All. Of. It.
This is what a change in the financial services Zeitgeist feels like. This is what a change in the financial services Zeitgeist IS.
The Zeitgeist is a little white bunny rabbit. With killer teeth.
If you’re an active manager or a value investor, the monster isn’t hiding behind the Zeitgeist.
The monster IS the Zeitgeist.
Now I know what you’re thinking, because I’ve thought it, too.
Is there some Holy Hand Grenade of Antioch available to blow the killer rabbit to smithereens?
Sorry, but no.
The answer here is that you don’t fight the Fed. You don’t fight City Hall. In fact, the real answer is that you fight on the SAME SIDE as the Fed. On the SAME SIDE as City Hall.
You know, like Saint Warren does on taxes.
I think that Berkshire Hathaway pocketed something like $29 billion from the Trump tax cuts. But hey, rail against carried interest taxed as capital gains and you, too, can insulate yourself and your company from the Democratic 2020 anti-oligarch jihad.
Or like the Winklevi do with crypto.
I know that crypto bros (and they’re all bros) love the anti-establishment mythos around Bitcoin. The social meaning of crypto – its Zeitgeist – was absolutely the halo effect of rebellion it provided. And what a convenient rebellion it was. Owning crypto was like getting a tattoo on your upper arm … you could tease it when desired as a signifier of your counter-culture bona fides, but you could also cover it completely while working for the Man. And maybe get rich, to boot!
That’s all gone today. Instead, you’ve got the Winklevoss Twins welcoming their new SEC overlords, intentionally setting themselves up as the squares. It’s the smart move. I don’t know if it will work … without the cool kid mystique, I don’t know how you drive crypto adoption anywhere but in the neo-gold bug “just you wait until the System collapses” crowd, and that’s such a depressing space. Sure, the Winklevi try to be personally cool, but it’s just ludicrous … they come across as Fonzies, not as James Deans. But it’s the smart move. IF crypto makes a comeback, I think Gemini will dominate the exchange space.
Or like Vanguard does with passively managed investment strategies.
The most amazing thing to me about Vanguard’s advertising strategy is that sometimes I don’t think there is a strategy. Does Vanguard even have a TV ad budget? My best guess on Vanguard’s annual advertising budget is $100 million, twice what they’ve said they spent a few years back. And yet the AUM just comes rolling in, billion after billion after billion … trillion after trillion after trillion. THIS is the power of a business model that fits the Zeitgeist of capital markets transformed into political utility. You don’t have to convince people to give you money. You don’t have to construct a winning brand or marketing alpha. The secret of Vanguard is not only that they’re not wasting resources on unrewarded active investment management (in 2017, 45 employees managed $2 trillion in AUM in Vanguard’s equity indexing group … that’s $44 billion per employee!), but also that their cost of customer and asset acquisition is so low.
I can’t emphasize this point strongly enough. Financial services companies live and die on distribution. Clients come and clients go. But if you can keep your customer acquisition costs low, you will ALWAYS live to fight another day. No matter what happens to performance.
On the other side of that spectrum, you’ve got TD Ameritrade and their incessant advertising campaign for all active management, all of the time. My god, but I weary of the smarmy dude with the beard, telling me that trading options is “just like playing pool”. And yeah, go ring that 24/5 bell, Lionel. All night long. Haha. How droll.
In 2018, TD Ameritrade spent $293 million in direct advertising expenses, three times my estimate of Vanguard’s spend for one-twelfth the net asset increase. Forget about all the employee comp associated with sales and marketing, I’m just talking about direct advertising costs. For this money, the company gained 510,000 net new accounts in the year, meaning that each net new account cost $586 in direct expenses. Now is there churn on accounts, so that gross new accounts are more than 510k and customer acquisition costs are proportionally less? Yes. But I can’t see any way it costs less than $500 for TD Ameritrade to get a new client, before you even start considering employee comp. And these costs are going up. TD Ameritrade is guiding to $320 million in advertising expenses this year. Lionel doesn’t ring that bell for free, you know.
I’m not trying to make a direct comparison between TD Ameritrade and Vanguard. They play in different ballparks. I’m also not trying to say that one is a better managed company than the other. What I AM saying is that Vanguard has taken an easy business path and a robust business path, and TD Ameritrade has not. Vanguard fits the financial services Zeitgeist perfectly, and TD Ameritrade fits not at all.
All of this applies to people just as much as it applies to companies. More so, really.
There’s a great scene in “The Holy Grail” when Arthur and his squire cloppety-clop their imaginary horses through a field where two peasants are toiling, and Arthur asks them about a castle up on the hill. The peasants aren’t nearly as star-struck by the “King of the Britons” as the King of the Britons expects them to be, and it leads to this exchange:
A lot of active managers are like King Arthur here.
They think that they are somehow OWED alpha because they’re really smart guys and they think really hard about 10-Qs and 10-Ks if they’re fundamental stock-pickers, or they think really hard about national accounts and balance of payments if they’re macro guys.
For a lot of years, active managers were the king. And they acted like it. They acted like it was somehow a divine right to … not just make a lot of money, but to make orders of magnitude more money than any other profession on earth. Why? Because it was Common Knowledge – everyone knew that everyone knew – that active management worked. Benjamin Graham or Warren Buffett or George Soros or Julian Robertson or some such had handed up an Excalibur of unfailing investment knowledge and process from the bosom of their waters to these knights and kings of active management.
Today, of course, the Common Knowledge is that this was all just a farcical aquatic ceremony.
Both views are silly. But I’ll give you one guess which view fits the current financial services Zeitgeist of a public utility better. I’ll give you one guess in which direction the investment world will continue to spin.
Here’s the Truth with a capital T – the market owes you nothing. No matter how smart you are and no matter how hard you work, the market owes you nothing. But if you’re very smart and you work very hard, you can take what the market is able to give you.
Today, unfortunately, the market is not able to give you a lot.
Not because prices are inflated or earnings growth is this or CAPE ratios are that.
Not because you haven’t studied the holy texts of your investment creed carefully enough.
But because private information – which is the one and only source of edge in the investment business – is being slowly but surely sucked out of public markets as part of this transformation into a public utility.
In 2009 the SEC established an Office of Quantitative Research and an Office of Risk Assessment and Interactive Data, and – for operational surveillance – an Office of Analytics and Research within its Trading and Markets Division. In July 2013, the SEC announced the creation of a Center for Risk and Quantitative Analysis, to “provide guidance to the Enforcement Division’s leadership.” Taken together, these offices form the equivalent of the SEC’s version of the CIA. These offices are extremely well funded, draw some really top-notch people from the private sector, and coordinate closely with the FBI. Today’s SEC may not quite be the functional equivalent of the NSA from a data gathering and pattern inference perspective, but it’s nothing to sneeze at, either. And on the traditional surveillance side, the DOJ has been given amazing latitude by the courts of late to pursue widespread wire taps across a wide swath of the financial services industry.
I can’t emphasize strongly enough the importance of these surveillance institutions as a tool in the political effort to transform capital markets into a political utility.
How? By taking sleepy regulatory edicts that were on the books but extremely hard to prosecute – such as the 2003 Global Research Analyst Settlement or, more importantly, Reg FD, originally adopted way back in August, 2000 – and using Big Data and Big Compute to turn them into powerful weapons.
Reg FD requires publicly traded companies to eliminate selective disclosure of any information that could be deemed to be material and non-public. Not only does Reg FD place a burden on company management not to disclose material and non-public information to anyone unless it is disclosed to everyone, but it also places a burden on the receiving party (typically the investor) not to act on the improperly disclosed information. Prior to 2009 it was very difficult for the SEC or FBI to identify any but the most egregious infractions of Reg FD, such as an email leaked by a disgruntled employee or a massive dumping or purchase of a stock. Since 2009, however, the SEC can sift through all of the trading in a company’s stock, look for what they consider to be suspicious patterns – which is by definition idiosyncratic outperformance, i.e., alpha generation – and then work backwards to create a link with, say, a 1-on-1 meeting at a sell-side conference between the company’s CFO and an analyst from the trading firm.
Let me say that again, with feeling: since 2009, the SEC treats any idiosyncratic market outperformance in strategies they can easily monitor – i.e., stock-picking strategies – as prima facie evidence that you may have broken the law.
To investigate this potential law-breaking, the SEC now routinely questions both active managers and corporate management teams who talk to active managers, if and only if stock-picking alpha has occurred in that company’s securities.
Before Reg FD, CEOs and CFOs would meet with active portfolio managers in private all the time. Active managers were your partners, and you told them what they needed to know. That does NOT mean that you told them this quarter’s earnings results, because that is NOT what active portfolio managers and their analysts need to know. Remember, these active managers are some of the smartest and hardest working people in the world. They don’t need to be spoon-fed with insider information. They’ve done their homework.
No, active managers only need the answer to one simple question to supply all of their private information / alpha generating needs.
Is it safe?
So … if you’ve never seen Marathon Man, you have my permission to stop reading this note and go watch the movie. It’s why Laurence Olivier is an actor’s actor. It’s why it’s taken me 40 years to get comfortable with a visit to the dentist, and I’m actually just saying that to be brave – I’ll never be comfortable with a dentist.
Laurence Olivier’s Nazi torture-dentist didn’t need a full download from Dustin Hoffman’s hapless grad student. He just needed to know if his overall plan had been blown. Is it safe?
That’s all that active managers need to know, too. Has our overall investment plan been blown by … I dunno, all you Kraft Heinz value investors, maybe an SEC investigation that hasn’t been announced publicly yet and will crater the stock for a while? You’re not looking to short the stock and you’re not looking to play the quarter. You just want to get out of the way while the company goes through this rough patch, and you’ll be right back in there buying the stock soon enough. Is that too much to ask? Because you believe in this company. You’ve done your homework. You’re a long-term investor. But is it safe?
THIS is the true source of alpha back in the golden age of active management. Not your adherence to the Value Investor Bible. Not some magical Excalibur of process and smarts. Not some obvious criminality like tipping an imminent acquisition or quarterly earnings. It was all conversations like this, only in a suite at the Mandarin Oriental instead of a dentist’s office, and with hotel catering instead of root canals. Is it safe?
Even after Reg FD was instituted in 2000, CEOs and CFOs still felt pretty comfortable communicating an answer to the “Is it safe?” question with a hem and a haw, maybe a reference to a prior period in the company’s history or a generic expression of caution or excitement … body language. Private meetings between active managers and corporate management became acts of theater, with a lot more private information “slippage” and a lot more active management “error”. The private information gathering process for active managers was damaged. But not ruined. Call it the silver age of the active manager.
And then came the Great Financial Crisis. Then came the 2009 SEC surveillance weaponization.
So how do CEOs and CFOs interact with active managers today? With the knowledge that every 1×1 meeting can and will be used against them if the manager is extra successful in the stock? Today CEOs and CFOs duck the conversation entirely and have the IR VP sit in for them. Today they have large group meetings with as many people as possible in the room. Today they say NOTHING that has not already been said, word for word, in a 10-Q or an 8-K filing. Unless you’re Elon Musk, of course, and look at what a lightning rod he’s become for behavior that would have been totally ignored 20 years ago.
Now put yourself in the active portfolio manager’s shoes. You don’t want to take that 1×1 meeting with the CFO, either! But you still have to take big swings, both because you’ve got a lot of money to put to work and you have to distinguish yourself against your benchmark. Maybe you can seek safety in the consensual validation of other managers, a Common Knowledge answer to the “Is it safe?” question, which is why there is such a pronounced herding behavior among active managers today. Or maybe you move towards an activist strategy, where you can once again acquire private information about a company and influence management directly, albeit at the significant risk of locking yourself into an investment you cannot easily exit. But these are awfully poor substitutes for the private information that used to be at your fingertips, the answer to that simple question: Is it safe?
This isn’t a chilling effect. This is a polar vortex effect.
This is why active managers, no matter how smart and how hard working, can’t beat the market even BEFORE you take into consideration all of the QE and forward guidance and extraordinary monetary policy and (coming soon) extraordinary fiscal policy.
They have no edge. They have no private information. Not just because monetary policy has swamped fundamental or company-specific information as a mover of asset prices, but also because since 2009, active management outperformance has been treated with regulatory prejudice.
Regulatory prejudice is part of the killer bunny Zeitgeist, too.
In fact, I think it’s the most important part of how capital markets have been transformed into a political utility. It’s just not the most obvious.
Which leads me to what I think is the core question that active managers must wrestle with if they are to reclaim market relevance and – yes – pricing power in the financial services industry.
Where can we find legal private information about publicly traded companies?
You can rail about the Fed all you like. God knows I do it a lot. They’re not going to listen and they’re not going to change. In fact, they’re going to do more. Scratch that, they’re going to do MOAR.
You can wish for the good old days of meaningful 1x1s to return. They won’t. There’s nothing mean-reverting about the Surveillance State or the political benefits of going after Axe Capital wherever and whenever possible.
You can continue to spout the same old canards about how “you know your companies better than anyone” or how “your process works over a credit cycle” or whatever it is that you tell yourself to keep the old faith burning. Or at least smoldering. But spare me all that, okay?
Active investing is hard. It was always hard. It has gotten a lot harder over the past ten years. It will get even harder over the next ten years. It will probably never get easier, at least not in our lifetimes. That’s the thing about golden ages. It’s a one-way path down, never up.
Still with me? It’s really okay if you’re not. It’s really okay to take the Don’t Fight ‘Em, Join ‘Em road. It’s really okay to take the Winklevi/Vanguard road. It’s the smart move.
But it’s not me.
I’d rather try to solve this really hard puzzle and fail than ignore the puzzle and be a successful soma distributor in this brave new world of political market utilities.
And I think we’ve identified a promising research program for solving this puzzle, at least in part. That research program is the game theory of narrative, and the research tool is natural language processing (NLP). That’s our approach to finding legal private information about publicly traded companies, and you’re welcome to join us. Here, take a look.
I don’t know if our research program will pan out. And that’s okay. You may not like this research program or want to do it your own way or try now for something completely different. And that’s okay, too.
What I know for sure, though, is that we’re asking the right question.
Where can we find legal private information about publicly traded companies?
That’s what makes active management work. It’s the only thing that has EVER made active management work. And it’s the only thing that will make active management work again.
Log of notes in series available here All notes optimized for viewing in PDF form PDFs available to subscribers only
Part 1: Zest in the Pursuit
Keeping Busy. To help myself and perhaps other members of the ET pack move through the current MLB off-season more productively than Rogers Hornsby moved through the many off-seasons he endured, I’ve crafted a two-part note about a cardinal challenge in both baseball and investing: hittin’ ‘em where they ain’t. Part 1 focuses on pros who’ve met this challenge uncommonly well; Part 2 (slated for publication as spring training shifts into high gear later this month) will focus on means that investors might employ to meet this challenge in coming years and beyond.
The prior note in this series (Note
#5) focused on personal traits enabling
certain players to achieve greatness in investing or baseball, and ended with a
question about one such great:
What would’ve become of the PE [private equity] industry if, instead of devoting a large fraction of Yale’s endowment to PE, [Yale CIO] David Swensen had deployed all such capital via managers investing exclusively in publicly traded stocks of owner-operated firms? ‘Tis hard to say, but I’ll try … in my next note.
Before tackling the foregoing question, I feel compelled to do two things. First, I’ll encourage readers who haven’t digested fully Note #2 (on excessive “juicing” by private equity and baseball pros) and the aforementionedNote #5 (on excessive mimicry of “the Yale model”) to do so before reading what follows, parts of which may seem naïve absent such auguries. Second, I’ll raise and answer a question that’s both central to this series and worthy of more attention than it typically attracts in discourse about greatness in investing or baseball: what metrics should be used to distinguish truly great practitioners from merely good ones?
To be sure, with computer-based analytics having transformed both the playing and business of baseball since the current century dawned, pros in that arena devote not merely ample but arguably excessive airtime to quantifiable metrics when grading past or current pros, be they on-field players or execs. But there’s scant agreement on optimal metrics for divining true greatness in baseball, even and indeed especially respecting criteria for election to its Hall of Fame, and frustratingly scant discussion of optimal metrics for divining competence let alone greatness in finance.
Pray tell, when was the last time you heard Paul Krugman an “expert” in finance articulate the precise metrics and time horizon underlying whatever critique of the Fed’s evolving policies they’re serving up on Bloomberg or CNBC? Dunno ‘bout you, but I haven’t encountered such exactitude from a talking head since the San Diego Padres last won the World Series (WS). That would’ve been … never, the Padres being the longest established MLB team to never win it all: 49 years and counting.
Gold Standard. Why demand
precision respecting both the metrics being used to gauge results and
the time horizon over which they’re being applied when grading
fiat-enabled capital allocators like Fed chair Jay Powell as distinct from
return-oriented allocators like Swensen or me or perhaps you? Why not?
If, as Ben Hunt argues persuasively in You Are Here,
modern capital markets have morphed into political utilities, it seems not
merely fair but essential that we ask whether such utilities’ ongoing
administration is producing the optimal deployment of capital — taking due care
to define optimal, of course. By my
lights, optimal in this context means the deployment of financial capital that enables
the maximum number of citizens to
achieve their full potential under
whatever boundary conditions the allocators being judged are laboring and neither
created themselves nor have the power to change.
italicized caveats are crucial, as exemplified by the tenures of the greatest
and least-great Fed heads in my lifetime: Paul Volcker, Fed chair for eight
years starting August 6, 1979; and William Miller, Fed chair for 17 months
ending the date Volcker started. Miller
didn’t create the stagflation that gripped the US economy in the late 1970s;
indeed, given Volcker’s not insignificant role in Richard Nixon’s decision to
end the greenback’s convertibility to gold in 1971, Volcker arguably deserves
no less blame than Miller for the stagflationary conditions both men
encountered during their tenures atop the Fed. That said, Miller himself took no effective
steps to end such torpor — a scourgewhose
ultimate purging by Volcker makes his tenure at the Fed the gold standard for
greatness in not only central banking but arguably also in capital allocation
me, that standard or test is simply stated: did the person being graded act boldly enough for long enough to boost
materially and sustainably the achievement of human potential?
Strikingly Similar. Which past or
present players in investing or baseball meet the test for greatness just
proffered while also serving as useful case studies for contemporary readers
seeking to elevate their own games?
Many candidates come to mind, some of whose achievements were
flagged in prior notes and will be discussed further as this series unfolds,
e.g., investor par excellence Jeremy
Grantham and baseballer par excellence
Joe Torre. Here and now, however, the tidiest answer I
can give to the question just posed while also moving toward an eventual answer (in Part 2) to the counterfactual
query raised at the outset of this note is by comparing the words and deeds of
the investment pro mentioned in it to those of a legendarily accomplished baseballer
whose temperament and indeed origins resembled Swensen’s: Branch Rickey.
Clear Eyes. Like Rickey, who
lived in central Ohio from his birth through completion of his undergrad
studies at Ohio Wesleyan, Swensen trod a conventional path to and through
college, earning a bachelor’s degree from the UWisconsin branch where his
father served as dean of the college and chemistry department chair (UW-River
Falls) and from which all five of Swensen’s siblings would also ultimately earn
degrees. So far as I can tell from
published accounts of both men’s dealings as well as conversations with Swensen
himself, their early 20s were essentially the last intervals in their lives
when either Rickey or Swensen fancied gettingalong to even remotely the same
degree as getting ahead.
Indeed, as Lee Lowenfish’s fine biography of Rickey makes plain, and as the ever-expanding universe of writings by and about Swensen makes equally clear, both men rose to the top of their chosen professions by practicing doggedly what Rickey’s fellow Hall of Famer Willie Keeler preached in his oft-quoted response to a reporter’s query about hitting: “I have already written a treatise [on the subject]”, Keeler crowed, “and it reads like this: Keep your eye clear and hit ‘em where they ain’t.”
Man vs. Machine. While never easy, practicing what Keeler preached is markedly more difficult for current pros in both baseball and investing than it was in Rickey’s day. There are multiple reasons why, including the adoption in both fields of genuinely meritocratic criteria for recruitment and advancement (more on which below) as well as a more dominant catalyst for change that Rickey lived and died too soon to have confronted in the workplace (and likely mastered if given the chance): computer-based informational technologies and the quantitative methods for deploying capital they facilitate.
in both pro baseball and investing the capital being deployed via increasingly
quantitative or formulaic methods comprises human as well as financial
capital, with the latter (money) being used routinely to obtain the former
(talent) in baseball, via market-clearing contracts for free agent players and
coveted executives, and with money in the form of fees being used routinely to
obtain the asset management talent institutional investors deem essential to
achievement of their stated return goals.
Crowded Trades. As the fine folks at Vanguard among other
straight-shooting investment pros have observed,
many institutional funds are pursuing return goals they have little or no
chance of achieving. More precisely,
such funds have little chance of achieving their stated return goals with their
current policies and strategies —
means not uncommonly adopted with the specific aim of being “like Yale.” Paradoxically, as suggested in Wannabes
Beware, one reason among others why most institutional funds bent on
parroting Yale will fail in the effort is because Swensen has proven so maddeningly
effective in preaching publicly what he’s practiced during his commendably long
(1985 – present) and ongoing tenure as Yale’s CIO.
To be sure, the illiquid strategies that Swensen has used so effectively on Yale’s behalf — comprising the lion’s share of Absolute Return plus all exposures above it in the nearby graph — haven’t attracted unduly large commitments from institutional investors as a group merely because David has expounded eloquently about them. Rather, locking up capital to the degree Swensen has on Yale’s behalf has become SOP in institutional funds management because in that arena, as in pro baseball, success breeds copycats.
success surely has, as did Rickey’s in developing a system for player
recruitment and development that’s served as table stakes for MLB teams since
it began producing riches for the Rickey-led Cardinals a century ago.
[F]rom 1913 to 1917, [Rickey] experimented briefly with the idea of a farm system—direct control of minor-league teams by the major-league parent organization … The farm system was a strategy for saving money: instead of bidding against other major-league teams for minor-league players, Rickey wanted to grow his own. After World War I, when the minors were in a financial slump, Rickey put his strategy into effect … [B]y 1939, the Cardinal empire included 32 minor-league teams and about 650 players.
The Cardinals bought pitcher Jess Haines in 1920, and purchased no more players until 1945. The system did save money. But it made money, too. Rickey was able to generate such a steady supply of young talent that he could sell off the excess at a nice profit, while providing the Cardinals with enough manpower to win nine pennants by 1946 … The competition among so many young players in the system operated as a kind of natural selection. The minor-leaguers could be left on the farms until, as Rickey liked to say, they “ripened into money.” [Emphases added]
Searching Far and Wide. As noted in the nearby box, building the pro
sports equivalent of an early stage venture program was but one of several
innovations Rickey conjured to better the various MLB teams he headed.
Famously, one such
initiative bettered not merely Rickey-led teams but America’s national pastime
and indeed the nation more generally: the recruitment and ultimate promotion to
the big leagues of non-white and
Like Swensen’s move
decades later to expand materially the pool from which Yale draws money
management talent by adding a globally diverse array of proven or promising
players in illiquid investing to it, Rickey judged correctly that expanding the
pool from which his teams drew talent by adding blacks and foreigners to it
would pay off big time. It did, with the
more genuinely meritocratic criteria for roster construction that Rickey
pioneered — like other innovations with which he’s rightly credited — ultimately
becoming table stakes for MLB franchises seeking to field winning teams. Indeed, as of the most recent date for which
reliable data are available (Opening Day 2018), 38% of players on MLB rosters were African-American or foreign born,
including many of the sport’s most talented if not also most beloved stars.
Told You So’s. No one can know for sure until the blessed
day arrives how many African-American or foreign-born players will grace MLB
rosters when the 2019 regular season commences on March 28. Barring injury, however, one non-American who
made his major league debut in 2018 will likely make the cut — for reasons that
would’ve elicited cheers if not also an “I told you so” from Rickey. Born and raised in Venezuela, 27 year-old
Willians Astudillo hasn’t done anything as a pro baseballer that would’ve
commended him to MLB front offices during Rickey’s many years heading such
offices, unless they were headed by Rickey himself.
Ever heard of Astudillo
before reading this note? If yes, it’s
for one or both of two reasons: (1) an attractively brief and hugely fun video of his homer in a
recent winter league game went viral or (2) Astudillo’s remarkable consistency
in avoiding strikeouts — a prized skill indeed at any level of play in baseball
— has created a big buzz in MLB circles, teeming as they are in the post-Moneyballera with quant jocks cranking out advanced statistics.
There were no such geeks
holding full-time posts in pro baseball, and no advanced stats worthy of the
name being compiled in baseball circles, until Rickey hired an immigrant to
crunch numbers for the Brooklyn Dodgers in 1947. Over the next four decades, a Montreal native
and former NHL statistician named Allan Roth helped first the Dodgers and in
due course not fewer than 20 MLB teams develop enhanced methods for allocating
both human and financial capital — on the field (via shrewder defensive
positioning and other tactics) and off it (via shrewder personnel policies).
Roth also helped burnish
Rickey’s reputation as “the Brain” of pro baseball by ghost-writing parts of “Goodby
[sic] to Some Old Baseball Ideas” — a storm-the-ramparts
piece published in Life magazine in
1954 that Michael Lewis mentions briefly in Moneyball, his 2003 bestseller on Billy Beane’s surprisingly lonely efforts
as a modern GM to practice what “the Brain” had preached a half-century
Lonely No Longer. However lonely Beane (or
Rickey) might have felt using methods that rival GMs deemed imprudent or
distasteful, such loneliness was destined to fade. And so it did, rapidly and rather fully as
the Aughts progressed, owing partly to Lewis’s authorial skills and in larger
part to Beane’s and later Red Sox GM Theo Epstein’s conspicuous success
implementing such methods (a/k/a sabermetrics).
lonely Swensen (or his longtime and unfailingly supportive investment committee
Ellis) might have felt using methods that rival CIOs deemed
offputting, such loneliness was also destined to evaporate, owing partly to
Swensen’s powers of persuasion and in larger part to the stunningly good
returns Swensen notched in the years surrounding his pathbreaking book’s
Selfish Concerns. Having fretted publicly at the time of Pioneeering Portfolio Management’s initial publication in 2000 about its potentially deleterious impact on my longtime and highly rewarding vocation (managing money), I fretted privately at the time of Moneyball’s publication in 2003 about its potentially ugly impact on my favorite and generally lovely avocation (watching baseball).
to say, the concerns just referenced have proven well-founded, with low hanging
fruits as well as most harder-to-reach edibles in the illiquid niches that
Swensen helped popularize now getting eaten by institutional
pachyderms even before they ripen, and with MLB games getting longer
and generally more predictable as quantitative methods increasingly supplant
intuition as the primary basis for decision-making in dugouts as well as front
don’t tell my kids, whose company I’m keen to continue having for Bosox games
at Fenway, but the fraction of plate appearances ending with balls put into
play has slumped discernibly since the so-called sabermetric revolution in MLB
commenced — from about 74% in 2003 to about 68% in 2018— with strikeouts as a
percentage of such appearances moving steadily and depressingly in the opposite
direction: roughly 22% in 2018 versus roughly 16% in 2003. More on such trends — and parallel trends in
institutional investing, such as they are — as this series unfolds.)
Multi-Tasking. Don’t get me
wrong. I still love investing, and
watching baseball, and — please
don’t tell my clients — doing both simultaneously. And I’m confident both domains will continue
producing greats as defined above: pros acting boldly enough for long enough to boost materially and sustainably
the achievement of human potential.
and Swensen certainly qualify as greats by my lights, passing the test just
mentioned and in certain respects an even sterner test of greatness for capital
allocators of all kinds including but not limited to baseball execs and
endowment CIOs: did the allocator being judged not merely handle effectively
the external boundary conditions he or she confronted but take effective steps to reshape them in a socially beneficent manner?
obviously did, as Americans will be reminded anew in coming months via
festivities MLB has planned to mark the centennial of Jackie Robinson’s birth. Swensen’s reshaping of boundary conditions
governing his professional labors, while less obvious and momentous than
Rickey’s earlier reshaping of his, has been material and laudable nonetheless. By shifting meaningful fractions of Yale’s
investable wealth out of marketable securities in general and tradable bonds in
particular into illiquid assets better suited to the profitable
exploitation of endowed charities’ perpetual life status, Swensen has created the proverbial win-win,
lowering the cost of capital for enterprises in which Yale has invested while
simultaneously boosting returns on Yale’s investable wealth.
As this unlocking of institutional potential has
progressed — initially and most intrepidly at Yale and in due course at other
institutions with so-called permanent capital to deploy — it has catalyzed a parallel unlocking of human
potential, with many intelligent and energetic investment pros granted
opportunities that earlier generations of workaholics lacked to deploy such
capital in a manner befitting its
No One’s Perfect.
I recognize that the prior paragraph may make some readers gag, the illiquid
strategies it commends having destroyed perhaps more wealth net of fees than
they’ve created for institutions
employing them as a group. I recognize
too that, as could rightly have been said of Rickey, Swensen’s rigorously
data-driven approach to capital allocation hasn’t produced uniformly enlightened
decision-making. Obviously, none of
Swensen’s slips have been bad enough to knock him off his lofty perch in his
chosen profession, as happened twice to Rickey after he became a big
shot in pro baseball: “demoted” (as Rickey saw things) from on-field manager to
“business manager” (and de facto GM)
by the Cardinals in 1925, Rickey underwent similar humiliation four decades and
multiple championships later, when the same Cards terminated Rickey’s contract
as the team’s sage-in-residence following its triumph in the 1964 World Series.
Regrettably for Rickey, but fortunately for Swensen and me and perhaps you, managing money tends to be a more forgiving line of work than managing big leaguers. While there’s certainly truth in Rickey’s oft-quoted boast remark that “luck is the residue of design,” let’s be honest: to a much greater extent in money management than in baseball, pros can commit impactful errors and still come out on top. This is especially true of errors of omission, which Swensen arguably made in applying the tenets flagged in the nearby box when and how he did, and that many US-based institutional investors are arguably making as the current century unfolds.
Admittedly, none of the tenets just referenced has proven fundamentally unsound since Swensen’s painstaking studies of capital market history caused him to apply them on Yale’s behalf starting around the time the aforementioned Volcker wrapped up his winning campaign to bend general price inflation downward. That said, if it’s OK for Rusty Guinn Astros fans to disparage that otherwise superbly managed team’s 2014 decision to “outright” or fire J.D. Martinez at what proved to be the start of a multi-year (and hopefully continuing!) stretch as one of the best power hitters in baseball, it’s presumably OK for Swensen votaries including me to note that bonds have performed much better relative to stocks over the full sweep of David’s tenure than his grand design for Yale’s endowment supposed, especially on a risk-adjusted basis.
the Talk. My fellow ET contributor Peter Cecchini
examined the phenomenon just referenced in a recent post, so I won’t discuss it further here, except to
say this: as Peter hints, applying data-driven methods like those Swensen used
to fashion “the Yale model” back in the day when fashioning investment policies in
2019 would be a mistake of potentially Snodgrassian proportions.
Strike that: there’s nothing wrong with making
data as distinct from tradition or intuition king in the policy-making process,
as Swensen did as a novice CIO or as Rickey and Roth did for the Truman-era
Dodgers, so long as one uses the best
Having bemoaned above the tendency of finance
types to opine on all manner of things without articulating clearly the metrics
and time horizon underlying such judgments, I’ll walk that talk here by noting
that “best” as I’ve just used it
means data germane to the deceptively difficult task of enhancing the real or
inflation-adjusted value of invested capital over the next 35 years.
Because I haven’t a clue how materially societal and technological
changes will affect the future duration of generational cycles; and the 35 year
investment horizon that the estimable Dr. Hunt has referenced in Pricing Power (Part 1 and Part
2) strikes me as an
attractively precise substitute for what I really have in mind: a mindset
compelling fiduciaries deploying capital today to weigh the interests of future
beneficiaries of such capital at least as heavily as the current generation of
Clearly, not all readers are aiming to enhance real wealth over such an
extended horizon, even with small portions of their investable wealth. Just as clearly, many endowed charities are, with the typical publicly supported
non-profit impliedly seeking annualized real returns in the range of 4-5%:
ongoing enhancements to real wealth needed to offset such orgs’ customary
endowment spend rates of 4-5%.
What to Do? Where in the world can today’s investors deploy capital with
reasonable assurance of earning annualized real returns of 5% or more over long
and potentially indefinite holding periods? Just as no wonk worth
listening to on monetary matters should critique the Fed’s evolving policies without
stating clearly the metrics and time horizon he or she is using to gauge such
policies’ success, no hired gun worth canvassing on the real return
quandary just referenced should address it without first pushing the ultimate
owners of any such capital to articulate with reasonable clarity the types and
degrees of risk they’re able and willing to tolerate. That said, I’m skeptical any strategies
the typical investment committee at work today would readily endorse will do
the trick, least of all US-focused PE of the sort Swensen funded aggressively
and adeptly when most institutions would not and could not.
Indeed, even as Yale wannabes continue ignoring data Swensen himself cited in Pioneering Portfolio Management respecting PE funds’ ugly tendency to underperform comparably leveraged investments in marketable stocks, stewards of long-term capital outside as well as within the endowment arena are generally ignoring readily available data pointing them toward plausible solutions to the real return quandary raised above. I alluded to such data in the still unanswered! question with which this note opened and will discuss them and the investment pros who’ve brought them to my attention in Part 2 of this note. As will be seen, like the astute allocators on which this post has focused — Swensen and Rickey — the pros in question seem to take special delight in hittin’ ‘em where they ain’t.
Hittin’ ‘Em Where They Ain’t – Part 2: Addition by Subtraction
 Born in 1896, Hornsby was a player, player-manager,
or off-field exec in pro baseball from 1915 until shortly before his death
during the 1962-63 offseason. Having
notched 2,930 fewer MLB hits than Hornsby — generally regarded as the best
right-handed hitter in MLB history — I’m hardly one to critique anything he did
or didn’t do. That said, Hornsby
might have enjoyed offseasons more if he’d permitted himself to read or watch
movies. He refused to do either during
his 23 seasons as an active player (1915 – 1937), convinced that doing so would
harm his eyesight. FWIW, Hornsby didn’t
smoke or drink either. He did gamble,
however, compulsively and lucklessly enough (on horse races) to
necessitate his working for pay during the entirety of his 25 years as an
 Hope springs eternal in Sandi,
however, especially for Padres fans with multi-year time horizons: taking a
page from the team that won the most recent World Series using a strategy
discussed at length below, the Padres have built what is widely viewed as the top
farm system in pro baseball as the 2019 season approaches. If the immediate past serves as reliable
prologue to the future — a concededly shaky premise in baseball no less than
investing, as also discussed below — the Padres will be world champs within a
half-decade, that being the approximate interval between the Red Sox’s zenith
in annual talent rankings of MLB farm systems earlier this decade and the
team’s most recent World Series win (in 2018).
Readers seeking more info on Volcker’s role in Nixon’s abandonment of the gold
standard in 1971 could do worse than start with the brief history of this
decision published by an organization that, like this author, thinks Volcker subsequently
did a superb job as Fed chair. The
Hoover Institution’s brief piece on the topic is available here.
I’m also planning to write about a pro whose guts and smarts would’ve made him
a Hall of Famer if certain team owners hadn’t been so short-sighted and
selfish: Fay Vincent, Commissioner of Baseball for a depressingly brief three
years ending in September 1992.
 Lowenfish’s Branch Rickey: Baseball’s Ferocious Gentleman (2007) remains the best of the multiple Rickey biographies published to date IMO. No full length biography of Swensen has yet appeared, but much has been written about David’s distinctive personality and methods, including the prior note in this series; a 2017 talk given by this writer (available upon request via firstname.lastname@example.org); and, most importantly and authoritatively, in Swensen’s pathbreaking book on institutional funds management and annual reports published by Swensen’s office available here.
Of the many books about the impact of computer-based analytics on pro baseball,
the one I’ve found most illuminating is Travis Sawchik’s Big Data Baseball: Math,
Miracles, and the End of a 20-Year Losing Streak, published
initially in 2015. With help from
another brilliant baseball wonk (Ben Lindbergh), Sawchik has completed a second
book on the steadily rising level of play in pro baseball (off and on the
field) that’ll be released in June 2019 — The
MVP Machine: How Baseball’s New Nonconformists Are Using Data to Build Better
Players. Perhaps because I’m more intimately familiar
with the use and abuse of data science in finance than in baseball, I haven’t
identified any books on quantitative methods for investing that I deem must-reads. If I had to point ET faithful to a single
such book while also honoring the principle that it’s better to teach hungry
folks to fish than to hand them fishes, it’d be Benoit Mandelbrot’s 2006
Misbehavior of Markets: A Fractal View of Financial Turbulence. FWIW,
I try to read every word written by my friend and quant jock extraordinaire Mark Kritzman; a
compilation of Mark’s remarkably voluminous writings is available here.
Revenue-sharing protocols generally enable MLB franchises with aggregate big
league payrolls beneath the threshold for MLB’s “luxury tax” ($206 million for
2019) to operate in the black even if their big league teams post losing
records and miss the playoffs year after year.
How long this not unhappy condition for many team owners (MLB’s
equivalent of closet indexing by active money managers?!) can or will last is
an open question to be explored in future notes. As will be seen, tensions between team owners
on the one hand and an arguably overmatched players union on the other are
mounting in a manner redolent of the widening gyre in American politics on
which Ben Hunt has shed useful light in Things Fall
Apart. Whether America’s
next national elections on November 3, 2020 will produce a day of reckoning for
certain politicians or political views remains unclear. But it’s virtually certain that a day of
reckoning — and perhaps the first work stoppage in MLB since 1995 — will be
upon us by this time in 2022, given the 2021 expiry of MLB’s current and
increasingly outmoded Collective Bargaining Agreement (CBA).
This seemingly odd handle for the use of quantitative tools in baseball
analytics derives from the leading association of such tools’ users: the
Society of American Baseball Research (SABR), founded in — where else? — Cooperstown,
NY in 1971.
Yale’s six fiscal years ending June 30, 2003 — an interval embodying a wild
ride for investors as a group — Yale’s endowment outperformed a 60/40
stock/bond mix by an eye-popping annualized margin of 12.3%: 14.3% per annum for
Swensen’s bulldogs vs. 2.0% per annum for puritans maintaining a 60/40 mix of
the S&P 500 and a broad US bond index (BBAgg). Crucially for institutions pondering during
the early Aughts whether they wanted to “be like Yale,” Swensen trounced the
60/40 bogey during both bull and
bear markets for stocks: 23.1% vs. 6.1% annualized returns in the three years
ending June 30, 2000 followed by 7.0% vs. -2.7% annualized in the three years
ending June 30, 2003.
Sports fans who deem football superior to baseball due to football’s seemingly zippier pace should note that
the average NFL game takes roughly the same amount of time to play as the
average MLB game (a tad over three hours) but with roughly one-third less ball-in-play time on average in the NFL than in MLB
(12 vs. 18 minutes/game).
MLB will surely and rightly stage similar events in 2034 marking the centennial
of the birth of the greatest Latino player in MLB history: Roberto Clemente
(1934 – 1972). A fun and well-researched
account of how the Rickey-led Pirates “stole” Clemente from the Dodgers during
the 1954-55 MLB offseason is available here.
 Though He Who Must Be Not Named can plausibly
lay claim to having made the worst error in MLB history (in Game 6 of the 1986
World Series), Fred Snodgrass of the then-New York Giants is viewed by most baseball
historians as having committed the worst such gaffe: a dropped fly ball in the
final game of the 1912 Series — won ultimately by the team that lost the Series in ’86!
Unlike publicly supported .orgs and .edus that engage routinely in fundraising
and are generally free to adopt whatever endowment spending rates (and
corresponding return goals) they wish, private grantmaking
foundations are subject to minimum
payout requirements dictated by Congress. These strictures cause such
foundations to distribute mandatorily an average of about 5% of
their wealth each year.
Le vrai est trop simple, il faut y arriver toujours par le compliqué.
The truth is too simple: one must always get there by a complicated route.
Letter from George Sand to Armand Barbés (1867)
We kicked off this series with a bold objective: learning how to live full of both scientific skepticism and the wonder of discovery. With clear eyes and full hearts. We will do this best, I wrote, by identifying and rooting out sources of bias and systematic error wherever we find them in our thinking and research.
This installment was going to be about how we permit the intrusion of bias into the very questions we ask. I was halfway through writing it when I realized that there was still more we needed to talk about first. Because whether our answers become biased in our writing down of questions, in our thinking very hard about the answer, or in our writing down that answer, the sources of the systematic errors which cripple our thinking are themselves often predictable and consistent.
on a journey of discovery about the nature of discovery, you and I, and we need
to make a detour.
though, or you’ll miss the turn.
A little more than an hour after you leave Austin, your GPS will tell you to turn right. A split-second later, your brain will retort, ‘There is no way that rough, barely two lane, curbless road with a double-wide on the corner is ‘Main Street.’ Sorry, brain. It is…or, was. It’s a small town. It’s also Saturday, which means that the cattle auction is taking place at the livestock commission. If you hear mooing, you will know you went too far. The beef you’re looking for is of a different sort, and once you have righted yourself on Main Street, you aren’t likely to miss it. Even at 7:45 AM – yes, sorry, did I mention that it’s basically open for four hours on Saturday morning? – the double-parked cars and the line of weary travelers bearing Buc-ee’s growlers full of coffee shall be a sign unto you.
have long since come to expect that our best regional cuisine will often come
from humble, out-of-the-way places. There’s a reason the Michael Scott bit
about Sbarro’s in The Office goes over so well. The hipster meme – “Oh, it’s a
weird, out of the way little place – you probably haven’t heard of it” – is
already five years stale at this point. We’re all in on the joke now. So if I
told you that the best cut of smoked meat in the world is beef brisket, and
that the best beef brisket in the world comes from a little place in Lexington,
Texas that’s only open on Saturday mornings, you probably wouldn’t bat an eye. Especially
since it has now been at the top of the Texas Monthly list for more than a
I’m telling you, everything about Snow’s BBQ is wrong.
starters, it really is just a one-day-a-week operation. It is extraordinary
enough (and popular enough) that it could do a bustling business on most days
like the joints in Austin or Lockhart. But despite the fixed cost-related
challenges of a Saturday-only approach, they haven’t made the switch. The owner
of the place is a former prison guard and rodeo clown whose day job for most of
the time he has owned Snow’s was at a coal mine. The pitmaster is an 83-year
old former butcher who works most of the week in maintenance at the high school
down in Giddings.
All that makes for a good story. But that’s not what’s wrong. It’s the way they BBQ here. CorrectBBQ is about indirect heat. Tootsie Tomanetz cooks almost everything over direct heat, and I think if she had her way, would still be doing it on briskets, too. CorrectBBQ is about low and slow. Tootsie Tomanetz cooks several cuts – including a really excellent sausage – at much higher temperatures than the typical joint. CorrectBBQ is about sourcing bespoke prime-grade or American wagyu beef from idyllic ranches in Montana. Tootsie Tomanetz buys her beef from a butcher in Taylor called O’Brien Meats that doesn’t even have a website. Correct BBQ is about washing the meat in a constant billow of smoke. Tootsie Tomanetz’s fires are heavy on hot coals and light on fresh logs – a much less smoky fire. Correct BBQ doesn’t rely on shortcuts like the Texas Crutch. Tootsie Tomanetz has been wrapping her briskets in foil for years. Oh, and by the way – Correct BBQ is a guy thing. I guess no one told Tootsie about that one either.
it sounds like Correct BBQ is a
religion, that’s because it is.
Thin Red Line
you want to understand the religion of Correct
BBQ, there is no greater symbol of it than that the pale red strip at the
bottom of this slice of brisket.
That little strip of color is called a smoke ring, and it is a fundamental part of the lore of Correct BBQ. Restaurants around the US frequently tout it as an indication of properly smoked meats. The largest national body governing competition BBQ standards, the Kansas City Barbeque Society, included it for many years among its formal judging criteria. Despite its removal some years ago, many judges still swear by it, or at a minimum acknowledge the subconscious effect it has. Like this one. And this one. Even though most competitions today don’t formally recognize it as part of the judging standard, it remains an obsession of most aspiring and backyard cooks.
The most common reason given for celebration of the smoke ring is a tautological one: It is the hallmark of Correct BBQ. Perhaps one layer below a pure tautology, the smoke ring ‘is believed to show that you have done a good job and properly low and slow smoked the meat in question.’ In other words, the smoke ring is accepted by many as post hoc evidence of proper technique, and two aspects of the technique in particular: cooking meat slowly over low temperatures, and cooking it over a smoky wood fire. It is a beautiful bit of lore that adds romance and an air of artistry to an otherwise (literally) visceral activity. This pink flesh is the result of a lazy fire tended dutifully, with billowing smoke slowly washing over a well-seasoned cut of meat over a period of hours. As such romantic lore tends to be, the smoke ring was for many years ingrained as common knowledge among aficionados – a thing that everybody knew that everybody knew. It was the answer from the gods to him who performed the ritual properly and with a pure heart.
only it were true.
smoke ring is not ‘smoke penetrating the meat.’ It is not even evidence of a
significant quantity of smoke. It is the result of a chemical reaction between
nitric oxide and myoglobin, the main non-water substance inside the ‘juices’ in
a piece of meat. The size of a smoke ring in a piece of meat is determined
entirely by the quantity of these gases that come in contact with that myoglobin
before it hits about 170 degrees. The presence of those gases has only a
limited relationship with the quantity of ‘smoke’ produced by the cooking fire.
You can produce comparable quantities of those gases with plain old charcoal
briquets. If you’re pressed for time, sprinkle that brisket with curing salts
containing sodium nitrite and throw it in the microwave. You’ll be the lucky
owner of a disgusting hunk of gross with an exquisitely deep salmon smoke ring.
the preference for low-and-slow cooking is a methodological abstraction of the
scientific process of collagen denaturation and breakdown. It works, but not because
of some direct relationship between flavor and the speed of cooking, but
because the technique strikes a balance between maintaining high enough internal
temperatures for long enough to effectively facilitate beneficial chemical
processes in intramuscular collagen on the one hand, and minimizing excessive
drying and evaporation on the meat’s exterior on the other. For many cuts, each
of these processes can be achieved through a higher temperature cook and a
longer period of insulated resting of the prepared meat.
Likewise, the disdain many had for techniques like the Texas Crutch – wrapping a brisket during part of its cooking process – was based on a belief that it replaced smoking with steaming (which is not entirely incorrect), and that it sped up the cooking in a non-traditional way that would harm the product (which is nonsense). We now know, of course, that wrapping a piece of meat reduces the process of evaporative cooling and results in moister, more flavorful BBQ.
evaluation of food is a subjective, human thing. But that is the point.
In any field for which the interpretation or objective function – the thing
we’ve solving for – isn’t quantifiable or even knowable, any tangible method feels
like a godsend. Won’t someone just tell
me what to do? But that method will always be an abstraction from the thing
we seek. When these abstractions become ritual, the risk is that our process of
discovering facts about that topic will be guided by its relationship to the
abstraction, to the religious myths that we memorize and pass along to others.
is all made more difficult by the fact that there may be good reasons for parts
of the ritual. I still personally have much better luck, for example, cooking
most things at a very low temperature over a very long period. The point is
that the ritual of Correct BBQ
stifled the exploration of newer, better ways to prepare it. People made BBQ to
most closely resemble what they expected from the ritual. In algorithmic terms,
we were stuck in a local optimum and needed enough crazy-ass ideas to succeed
to have any hope of achieving movement in our literal and figurative
posteriors. Sure, there were always exceptions and independent thinkers. But it
has really only been in the last two or three decades that people like Tootsie Tomanetz
who didn’t give a damn what anyone else thought have come into the mainstream. It
isn’t that Tootsie, or Aaron Franklin or any of the other demigods of Texas BBQ
aren’t respecters of tradition. These are post oak-only, salt-and-pepper
purists, after all. It’s that their experiments weren’t guided by hewing to the
rituals of Correct BBQ for the sake
of those rituals.
Snow’s BBQ IS Tannu Tuva, y’all. Not literally, I mean, although
it is a pain in the ass to get there.
I mean that it is proof that some of the world’s greatest joys come from unearthing
beauty that remains beautiful even when
we discover what it really is. Tannu Tuva wasn’t something that Richard Feynman
feared would become less beautiful or magical through its discovery any more
than beautiful food would cease to be art because we understand the science
behind its flavors, textures and aromas. Knowing only adds.
I have a friend who’s an artist, and he sometimes takes a view which I don’t agree with. He’ll hold up a flower and say, “Look how beautiful it is,” and I’ll agree. But then he’ll say, “I, as an artist, can see how beautiful a flower is. But you, as a scientist, take it all apart and it becomes dull.” I think he’s kind of nutty. … There are all kinds of interesting questions that come from a knowledge of science, which only adds to the excitement and mystery and awe of a flower. It only adds. I don’t understand how it subtracts.
What Do You Care What Other People Think, by Richard Feynman (1988)
Knowing only adds, that is, unless what we most desire is the sanctity of the ritual. But ritual isn’t the only potential enemy of a worthy process of discovery. We must also grapple with the way in which systematic errors and bias creep into our analysis when relevant facts ARE knowable, when some of them ARE measurable…and when they appear to clearlysupport our theories and priors. As it happens, the field that made Feynman famous not only gives us perhaps the greatest simultaneous source of skepticism and wonder in all of physics, it also deals with exactly this problem. And it just so happens to be about a different kind of thin red line.
Another Thin Red Line (or Two)
What you see below is a stylized illustration of the visible light portion of hydrogen’s emission spectrum.
OK, I admit that I escalated quickly from a discussion of coagulated meat juices, so let’s keep it simple. These are the colors of light emitted when a hydrogen atom moves from a high energy state to a lower one. This was a big deal in the late 19th and early 20th centuries, not just because we were trying to understand electromagnetism, but because observing electromagnetic effects (like, say, light) allowed us to test different theories about sub-atomic particles. It was a beautiful dance between experimental and theoretical physics, between deductive and inductive research methods. In 1916, Niels Bohr built a model that described electrons orbiting the nucleus of an atom at various discrete distances. It wasn’t the first model that gave the atom the solar system treatment, but it was the first that seemed to provide a mechanism explaining the spectrographic image we see above. In other words, Bohr sought a physical description of what rules electrons could be following that could also explain why a change in the energy state of that electron would emit that particular frequency of red light.
He knew at the time that his model wasn’t completely right. While we could observe the effects of what we would later explain using quantum mechanics, we lacked the math and the models to explain those effects. And so the Bohr model relied on quantization heuristics, which is a smarter-sounding way of saying, “Let’s bolt some stuff onto the model we used to use to solve this problem so that it spits out the solution we can observe.” You can think of it like the old up-converters they used to sell for pre-HD cable boxes and DVD players, or the auto-tune on a Selena Gomez record. I’m making it sound more dishonest than it is in service of a joke – a lot of things are figured out by finding out what lies in the gap between our current model and our current observations.
even with Bohr’s quantization heuristic (which defined a discrete list of
possible stable states for electrons), the model wasn’t quite right. That’s
because while it looks like each of
the emitted frequencies is a single line, and while the Bohr model creates a
workable physical explanation for that measurement in a hydrogen atom, that
isn’t exactly what a spectrograph would measure. If you could look more closely
– much more closely – you’d see that there is a fine structure to that red line. In other words, there are two red lines there. The Bohr model didn’t
account for this, and not for lack of trying. Enter Arnold Sommerfeld.
Sommerfeld built on Bohr’s model in a few ways. The most obvious change modified Bohr’s framework to one in which the orbits at different energy states were elliptical. Without going into a rabbit hole discussion of angular momentum and phase integrals, the important fact is that Sommerfeld developed a closed form solution that was exactly right in predicting the two red lines for the relativistic hydrogen atom. His was precisely the formula that Paul Dirac would propose for this calculation under full quantum mechanics some twelve years later, and Sommerfeld did so with no understanding of the features of quantum mechanics that were responsible for the fine structure! As L.C. Biedenharn put it in one of many pieces summarizing and exploring the affair, “Sommerfeld’s methods were heuristic (Bohr quantization rules), outdated by two revolutions (Heisenberg-Schroedinger nonrelativistic quantum mechanics and Dirac’s relativistic quantum mechanics) and his methods obviously had no place at all for the electron spin, let alone the four components of the Dirac electron.”
this wasn’t magical enough, Sommerfeld’s method also left us with the gift of a
new dimensionless physical constant for
our Standard Model of particle physics, which is a fancy way of saying that we
discovered a number that is really important but which isn’t really a
measurement or unit of anything. It’s just a number that reflects a fundamental
property of the universe. The fine-structure
constant, as it is called, can be measured and observed just about
everywhere, but cannot be mechanistically explained as a governing rule or
1/137, give or take. Sommerfeld calculated it as the ratio of the velocity of
an electron in the first circular orbit of the Bohr model to the speed of
light. It’s also the square of the ratio of the elementary charge to the Planck
charge. It’s part of the function describing the probability than an electron
will emit or absorb a photon. It manifests in the relationship between the
energy of a particular photon and the energy level at which two electrons
overcome electrostatic repulsion. Or, as Feynman put it:
…[it] has been a mystery ever since it was discovered more than fifty years ago, and all good theoretical physicists put this number up on their wall and worry about it. Immediately you would like to know where this number for a coupling comes from: is it related to p or perhaps to the base of natural logarithms? Nobody knows. It’s one of the greatest damn mysteries of physics: a magic number that comes to us with no understanding by man. You might say the “hand of God” wrote that number, and “we don’t know how He pushed his pencil.” We know what kind of a dance to do experimentally to measure this number very accurately, but we don’t know what kind of dance to do on the computer to make this number come out, without putting it in secretly!
QED: The Strange Theory of Light and Matter, by Richard Feynman (1985)
fine-structure constant is Tannu Tuva, too – a miracle in its discovery, mysterious
in its origin, but also measurable. Knowable. Observable. And no less miraculous
or mysterious for all that. But it IS the kind of thing you put on your wall
and worry about. Not just about the Athena-springing-from-the-head-of-Zeus feeling
you get from a number that just happens to be a fundamental identity of the
universe. There’s also something
unnerving about a property that can be correctly predicted from an abstracted model.
in physics, that unnerving prospect is the exception which proves the rule. After
all, it’s not as if physicists stopped trying to better understand quantum
mechanics, particle physics and electromagnetism just because Arnold Sommerfeld
had figured out what must be happening inside a hydrogen atom. It’s a good
the social sciences, rather less thankfully, the exception IS the rule. Every model we build which seeks to predict
some event that is a function of human behavior is nearly always inductively overdetermined
and deductively underdetermined. What I mean by that is that investors,
journalists, policy wonks and other social scientists can never be as certain as
a physicist that our model or analysis reflects a true feature of the world,
but we will nearly always have enough observational data to demonstrate to us
that it does. We have so many degrees of freedom, so many variables to
consider, that with enough data we can usually construct a dozen workable
models for why that atom produces those two frequencies of red light. Evidence
of this peril is everywhere. It lies in every investment strategy backtest,
every interpretation of a politically charged video presented as fact, in every
macroeconomic model, and in every perfectly detailed economic report given by a
central banker under the aegis of immunizing communications policy.
credible observer with any measure of experience with the statistical rigor of
financial, economic, sociological, psychological and political research will
inevitably come to one conclusion: no matter how much we would pretend that it
is something else, the vast majority of our research in these fields is
heuristic and nothing more. When we treat these data-backed heuristics as part
of whatever the equivalent of the Standard Model is in our fields, bias and
systematic error will very often be our reward.
Red Badge of Bias
I believe these two forces – Ritual and Heuristic – are the most constant threats to clear eyes and full hearts throughout our processes of discovery.
Ritual isn’t inherently bad. There are deep parts of us which respond to its pull, and our lives would be emptier if we rejected it fully. We have written about many of the worthy uses of narrative in Holy Theatre, such as the ones brought to bear in the Civil Rights movement or in the Second World War. Yet we must still be mindful of how Ritual steers our questions, our thinking and our answers into right-thinking patterns and convention. It is the source of the monocultural newsroom and the risk-averse investment committee and countless research projects which begin from unproven, unexamined priors. The tyranny of Ritual is its presumption that its priors are self-evident, as morally unworthy of challenge.
Heuristic is also not inherently bad. For example, I believe in functioning markets as spontaneously organized entities that will nearly always defeat a deductive approach to understanding their value. Similarly, there are many non-falsifiable principles whose survival for millennia ought not to be discarded lightly. Where Heuristic imperils our research is in the the post hoc rationalization of our deductive frameworks on a pseudo-empirical basis. Doing so not only directly introduces the risk of systematic error should our inductive process have missed some key latent variable (as it so often does), but it also indirectly shuts off avenues of inquiry and analysis. It is a force of laziness and overconfidence, typified by the belief that once we have ‘proven’ that something is likely under some set of statistical parameters, we are absolved from trying to disprove it further. The tyranny of Heuristic is its presumption that our priors have been proven, and are in no further need of updating.
For a successful technology, reality must take precedence over public relations, for nature cannot be fooled.
The Rogers Commission Report (1986)
With apologies to Mr. Feynman, we will need to expand this idea. For a successful news organization, for a successful investor, for a successful technology, reality must not only take precedence over public relations, but over both Ritual and Heuristic. The only way that it is possible for this to happen is through ruthless governance of the priors which influence which topics we take up, which stories we research, and which factors and markets we examine.
And that – following this little detour we’ve taken together – is exactly where we will go in Part 3.