Investing with Icarus

The wind blows where it wishes, and you hear the sound of it, but cannot tell where it comes from and where it goes.

The Bible, John 3:8

As Narrative abstractions — cartoons — become our short-hand for things that used to have meaning, our models become more and more untethered from the reality they seek to reproduce. When wind becomes the thing-that-makes-the-leaves-move, then wind becomes a bear rubbing his back on the bark.

He that breaks a thing to find out what it is has left the path of wisdom.

The Lord of the Rings, J.R.R. Tolkien

Pursuing better returns by uncovering absolute truths about the companies and governments we invest in is not a serious enterprise in the face of markets rife with Narrative abstractions. It is a smiley-faced lie, a right-sounding idea that doesn’t work, and which we know doesn’t work. Selling the idea that it does to clients is the territory of the raccoon and the coyote. We can pursue it, or we can do the right things for ourselves and our clients. But not both.

Disneyland is presented as imaginary in order to make us believe that the rest is real, whereas all of Los Angeles and the America that surrounds it are no longer real, but belong to the hyperreal order and to the order of simulation. It is no longer a question of a false representation of reality (ideology) but of concealing the fact that the real is no longer real…

Simulacra and Simulation, Jean Baudrillard (1981)

How does Wall Street maintain the respectability of dishonest businesses? By declaring victory over straw men — active management is dead! Hedge funds lost the Buffett bet, beta won! Risk parity / vol-targeting / AI funds / quant funds are to blame! If you must sell that L.A. is real, you must create Disneyland.

“All right,” said Susan. “I’m not stupid. You’re saying humans need… fantasies to make life bearable.”

REALLY? AS IF IT WAS SOME KIND OF PINK PILL? NO. HUMANS NEED FANTASY TO BE HUMAN. TO BE THE PLACE WHERE THE FALLING ANGELS MEETS THE RISING APE.

“Tooth fairies? Hogfathers? Little—”

YES. AS PRACTICE. YOU HAVE TO START OUT LEARNING TO BELIEVE THE LITTLE LIES.

“So we can believe the big ones?”

YES. JUSTICE. MERCY. DUTY. THAT SORT OF THING.

“They’re not the same at all!”

YOU THINK SO? THEN TAKE THE UNIVERSE AND GRIND IT DOWN TO THE FINEST POWDER AND SIEVE IT THROUGH THE FINEST SIEVE AND THEN SHOW ME ONE ATOM OF JUSTICE, ONE MOLECULE OF MERCY. AND YET — Death waved a hand. AND YET YOU ACT AS IF THERE IS SOME IDEAL ORDER IN THE WORLD, AS IF THERE IS SOME…SOME RIGHTNESS IN THE UNIVERSE BY WHICH IT MAY BE JUDGED.

“Yes, but people have got to believe that, or what’s the point—”

MY POINT EXACTLY.

Hogfather, Terry Pratchett (1997)

So long as the government requires financial markets to act as a utility, and so long as it makes more sense for big tech companies to hire evangelists than CEOs — until the farmer comes out with his gun – we have only a few choices:

  1. We can be raccoons: We can recognize the overwhelming influence of abstractions and continue to sell products and ideas that don’t.
  2. We can be coyotes: We can recognize the overwhelming influence of abstractions and DESIGN new products and ideas that don’t.
  3. We can be victims: We can let the raccoons and coyotes run rampant over the farm.
  4. We can insulate: We can push back from the table and try to do the things that aren’t abstractions. Real things. Physical things. Things that put spendable currency in our accounts.
  5. We can engage: We can do our best to think about how to change our investment strategies and processes to respond to abstraction-driven markets.

These aren’t mutually exclusive, although only two are worthwhile. Ben’s DNA is long vol, so he wrote about how to insulate. My DNA is short vol. This note is first in a series on how to engage.

Speaking of DNA, there are few fields of study I find as thrilling as the intersection of anthropology and genetic geneaology. What I mean by that is how people lived, died and moved, and how their cultures and lineages moved with them. Yes, if kicking off notes with the old King James didn’t give you enough of a hint, I’m a big hit at parties.

Some of the appeal of genetic anthropology comes from the simple pleasures it offers, like the satisfaction of watching white supremacist idiots discover that they are mutts just like the rest of us.

The second appeal is the grand scale of ancestry and human movement, even over cosmologically infintestimal periods of time. This appeal is timeless. For example, in a legend common to three of the world’s great religions, God promises to multiply Abraham’s descendants as the stars of the heaven and as the sand on the seashore. It’s a pretty attractive promise, but temper your excitement — it was a reward for being a hair’s breadth away from murdering his son. The promises are poetic, of course, but the scope of the two is surprisingly different.

There are somewhere around 100 billion to one trillion stars in the Milky Way, an estimate which would vary based on how you estimated the galaxy’s total mass through the gravity it exerted and based on what you assumed was the average type of star. We’ve discovered a Wolf-Rayet star in the Magellanic Cloud with mass perhaps 300 times that of our sun, for example. It is so much larger than our sun that its surface would reach almost a third of the current distance to Mercury. Icarus wouldn’t stand a chance. On the other hand, we’ve discovered a red dwarf only 19 light-years away with less than 10% of the mass of the sun. But the 100 billion to one trillion range is a fair estimate. Earth has already seen 100 billion human lives. It will (hopefully) see its trillionth at some point between the year 2500 and 3000, if y’all could stop killing each other. Still, if you’re willing to ignore that we can see stars from other galaxies, too, I think we can prematurely give this one to Abraham.

As for the sand, there are about seven or eight quintillion grains on the earth. There’s just no way, even if Elon manages to get us off this planet before the next mass extinction event.

Interestingly, if you look backward, that isn’t quite true. When it comes to lineage, exponential math doesn’t always work going forward. One couple dies without any offspring, while another has a dozen children. But it always works going backward. Everyone has two parents and four grandparents. Based on most of those traditions holding that Abraham lived around 2,000 BC, we can estimate that the average living person has about 1.5 quindecillion ancestors from that time. Given that there were only about 72 million people alive at the time, that means that each of those individuals, on average, shows up in your family tree about 20 duodecillion times. That’s a 20 with 39 zeros. Congratulations! Math is amazing, and you are inbred.

The third appeal is that the really interesting findings are new. Very new. Anthropologists, of course, have theorized about the propagation and spread of cultures through comparative review of ancient art, tools, jewelry, burial sites and artifacts for centuries. Linguists can lean on anthropological techniques, but can also compare similar or derived grammar, vocabulary, and the like to identify how languages originated and spread. Maybe even some sense of where they came from. DNA has been used to develop and cultivate theories about human migrations and the spread of cultures for a shorter time, but in earnest starting in the late 1990s into the early 2000s. These studies have principally relied on the DNA of living individuals. Scientists examine current populations and theorize how ancient populations would have had to migrate to create the current distribution of various genetic admixtures — archetypes of varying compositions that can be generalized, like “Near Eastern Farmers.”

But in the last five years, the real excitement has been in the enrichment and analysis of ancient DNA. That means that, instead of just looking at modern populations and developing models to predict how they may have gotten there, we instead may look at the actual DNA of people who lived and died in some place in the distant past. We don’t have to guess how people moved and where they came from based on second-hand sources, like the DNA of people living in the same place thousands of years later, or on the pottery that they left behind.

We can know the truth.

Desperate for Wind

The allure of a fundamental truth is powerful. It’s the draw of science, and it’s a good thing. Understanding the true physical properties of materials and substances, for example, is the foundation of just about every good thing in our world. I mean, except for justice, mercy, duty, that sort of thing. We have the food we eat because those who went before discovered human chemical and enzymatic processes for digestion, and learned the mineral, chemical, water and solar needs for the plants that would be digestible. We have the devices we carry in our pockets because many thousands of researchers, designers and other scientists discovered the electrical conductivity of copper, the thermal conductivity of aluminum, the fracture toughness of various types of glass and a million other things.

I grew up around this kind of thinking. My dad worked for the Dow Chemical Company for some 40 years. Most of that time he spent as a maintenance engineer, an expert in predicting and accounting for the potential failure of devices and equipment used in the production (mostly) of polyethylene. His professional life’s work was perfecting the process of root-cause analysis. There may not be anyone in the world who knows more about how and why a furnace in a light hydrocarbons facility might fail. It may sound hyperspecialized, but that kind of laser-focused search for truth is something I took and take a lot of pride in.

Investors are hungry for that kind of clarity about markets. But it doesn’t exist. In The Myth of Market In-Itself, I wrote about investors’ vain obsession with finding root causes in media, economic news and Ks and Qs. Ben recently wrote about it pseudo-pseudonymously as Neb Tnuh, mourning the conversion of Real Things into cartoons, crude abstractions that investors are forced to treat like the authentic article:

Do I invest on the basis of reality, meaning the fact that wage inflation is, in fact, picking up in a remarkably steady fashion in the real economy? Or do I invest on the basis of Narrative abstractions that I can anticipate being presented and represented to markets at regularly scheduled moments of theater? Because the investment strategy for the one is almost diametrically opposed to the investment strategy for the other.

Like many Epsilon Theory readers, I am Neb Tnuh. Like Neb, I want to evaluate businesses and governments again. I want to understand their business models, evaluate their prospects against their competitors and subtitutes, quantify the return I can expect and the return I ought to demand for the risk, and seek out investment opportunities where the former exceeds the latter. I want this. But like everything else in life, wanting something to be possible doesn’t make it so.

It also doesn’t make it noble. Arch-raccoon James Altucher fancies himself Neb Tnuh, too:

“But business is just a vehicle for transforming the ideas in your head into something real, something tangible, that actually improves the lives of others. To create something unique and beautiful and valuable is very hard. It’s very special to do. It doesn’t happen fast.”
― James Altucher

And sure, there are ways to pull away from the table. There are ways to be short abstractions, like Neb recommends. Before he wrote The Icarus Moment, he wrote Hobson’s Choice, which described some of the few ways that all the Neb Tnuhs out there can reject the false choice between investing on the basis of a reality that is decoupled from risk and return, or not investing at all. These are strategies to insulate against Narrative abstractions, and I think they should be larger parts of almost every investor’s portfolio. Am I being explicit and actionable enough here? I’m talking about more real assets.

But a strategy which only insulates isn’t practical. It’s not practical for asset owners with boards, or actuarial returns, or a need to hit traditional benchmarks. It’s not practical for individuals who may not have the luxury, wealth or flexibility to, oh, I don’t know, buy an airport or 3,000 acres of northern red oak forests in Georgia. It probably isn’t desirable either. First, that level of underdiversification implies an extreme difference in return expectation, and I’m not going to leave that free lunch on the table. Neither should you. Second, the raison d’etre of turning the market into a utility, of propagating central bank missionaries and evangelist CEOs is the belief that those behaviors are at least somewhat predictable. If we’re not applying that in some measure to the rest of our portfolios, we’ve probably left something else on the table.

And so, unless we would be victims of the coyotes and raccoons who would sell us their own panaceas to this investing environment, we must engage with Narrative-driven markets. But it is hard. It is hard because the nature of abstractions is to require far more information — which usually means more time, too — to change their state. Think about when you’re explaining some complicated analogy to someone and they get confused (did you like my meta joke?). How much longer does it take you to get your conversation back on track? Think about the Keynsian Newspaper Beauty Contest. When you’re playing at the third or fourth level, how much more difficult is it to hold the pattern of what you’re evaluating in your mind, and how much more difficult is it to change that pattern to respond to new information once you’ve approximated it with some other thing, some heuristic or placeholder?

When an asset’s price, volatility behavior or direction is being driven by agreed-upon abstractions, so too is the required information to change its state far greater than usual. Missionaries explain away bad news, or create a new pro forma metric. Media members promote the new spin on the story. Supplicants call on confirmation bias to interpret it based on their existing thesis. And the contrarians who could move the price have all gone to the Hamptons for the decade. Notice how volatility spikes briefly and then disappears?

The question on whether to engage, or to try your luck with strategies that presume a strong, efficient link between economic facts and asset prices, is a question of timing. Unless your investment horizon — by which I mean the horizon over which your trade can go profoundly against you without your getting fired (if you’re a professional) or changing your mind (whether or not you’re a professional) — is more than 10 years, I simply don’t think you can have any confidence that your fundamental analysis has anything more than even odds. Sorry. And in case you were wondering, the answer is no. I don’t care who you are. You do not have a 10+ year horizon to survive being told by Mr. Market you were wrong without being fired or putting yourself under extreme pressure to change your mind.

Investing in a Time of Icarus

But we have already written about a lot of this. You know that Ben and I have said that many of these strategies just aren’t going to work the way that they used to, or when we’re looking for low-hanging fruit, that they haven’t worked the way that we all expected them to. You know that we think this is largely the result of markets and economies becoming utilities, Narrative replacing economic sensibility, and governments and oligarchs stepping into their own as missionaries for that utility and the Narratives that support it.

But what do we do? What do we do differently?

I’ve written about part of the answer fairly plainly in the Things that Matter and the Things that Don’t Matter series from 2017. There is a finite, definable list of investment principles which matter all the time, even in an Icarus Moment. Ben has written about the second element, which is to insulate.

For those who want to engage and continue the search for alpha, the answer depends.

First, it depends on the definition of alpha. When I say alpha, I mean any asset class-level decision that causes a portfolio to deviate from either the most diversified possible portfolio or a market cap-weighted portfolio of all global financial assets. I also mean any security-level decision that causes a portfolio to deviate from the broadest possible market-cap weighted benchmark for that asset class. It’s a simple definition that doesn’t get pedantic about whether a systematic active strategy is really a kind of “beta.” Sure it is. Or no, it’s not. It’s a stupid debate. I don’t care.

Second, it depends on the type of investment strategy you are using. It also depends on your methodology for implementing that strategy. Incorporating both of these requires some kind of framework to discuss.

Here’s what we’ll do: the dimensions I will use for the framework will be different from style boxes, and they’ll be different from categories used by many hedge fund index providers or asset allocators. I will define the categories instead by how I think they interact with an Icarus Moment, or a Three-Body Market — with a market in which asset price movements are heavily influenced by Narratives over an extended period of time.

The first dimension of those categories is what basis on which the strategy seeks to predict future asset prices (by which I include relative future asset prices). I roughly split strategy types into three categories: Economic Models, Behavioral Models and Idiosyncratic Models. Economic Models, in my definition, seek to predict future asset prices principally on the basis of actual and projected economic data about an economy, a financial market or an issuer, whether it’s a company or a government. Behavioral Models may incorporate some elements of Economic Models, but are principally driven by suppositions and beliefs about the behaviors of other market participants rather than the underlying companies. Idiosyncratic Models include various strategies which may even seek to exert direct influence on the future price of an asset.

For the second dimension of the framework, I think it is useful to separate investment strategies which are Systematic from those which are Discretionary. By Systematic Strategies, I refer to alpha-seeking strategies that reflect more-or-less static, if potentially emergent, beliefs about how prices are determined by certain characteristics or states, and whether those characteristics or states are directly related to economic data or more clearly influenced by observable investor behaviors.  The second category, Discretionary Strategies, refers to those in which there may be a process associated with similar beliefs, but in which the decision is made based on the judgment of a human portfolio manager. There are frequently observer effects in any investment strategy (i.e. where the act of observing something changes it), but particularly so in Narrative-driven markets. The systematic/discretionary dimension is important to understanding how this can manifest.

Those two dimensions give us six broad categories, which I have filled in with general descriptions of strategies that I think fall into each. There are things I haven’t captured here, but not many. Of active traditional and non-traditional investment strategies in public markets, I’m comfortable that this captures more than 80%. Close enough for government work.

Over the next few months, I will write a piece covering each of these six categories. My aim with this exercise is three-fold. For those who elect to both insulate and engage:

  • I want to tell you the strategies that I don’t think will work.
  • I want to tell allocators / asset owners how I think the evaluation of the strategies that may work should change.
  • I want to tell asset managers how I think they should consider adapting their strategies so that they still work in this environment.

If you think that I have bad news for the strategies on the left third of the table, thank you for paying attention. If you’re looking for a prize at the bottom, there is none.

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The Icarus Moment

A juvenile red-tailed hawk took up residence near our farmhouse soon after we moved onto the property, now eight years ago. The girls named him Indiana Jones, which is a wonderful name for a hawk, and his daily kreeeeeees thrill me every time I hear them. Red-tailed hawks are also known as chickenhawks, but we’ve never had a problem with Indiana in that regard, as he seems more than content to pillage our fields for ground squirrels, voles and the occasional snake. I am particularly happy for his attacks on the local vole population, as we lost a young apple tree to voles a few years back (they will eat the tender bark all the way around the thin trunk, “ringing” the tree and killing it). We don’t know if Indiana has been successful in finding a mate in one of the past few breeding seasons. We hope so. It’s a solitary life being a red-tailed hawk, all alone in your instinctive mastery of flight and field.

Tyger Tyger, burning bright,
In the forests of the night;
What immortal hand or eye,
Could frame thy fearful symmetry?

[Four stanzas later …]

Tyger Tyger burning bright,
In the forests of the night:
What immortal hand or eye,
Dare frame thy fearful symmetry?
William Blake (1757 – 1827)

It’s the single word change in the first and last stanza of Blake’s most famous poem, the shift from Could to Dare, that moves me as much as Indiana’s kreeeeeees. It’s at the heart of all of Blake’s work, this notion that not only is it a difficult thing to frame/model the symmetry/pattern of Nature as found in a raptor’s swooping flight or a tiger’s slouchy walk, but that it is a dangerous thing, too!

Of course, that’s exactly what we humans do all the freakin’ time.

Here are some amazing William Blake paintings on this theme.

Blake’s famous quote was “Art is the Tree of Life. Science is the Tree of Death.”, so I suppose it’s no great surprise that Isaac Newton was one of the main villains in Blake’s philosophy, which saw science — particularly fundamental science focused on divining the “laws” of nature — as part and parcel of an inherently repressive political regime hell-bent (literally) on imposing a stultifying order and uniformity on mankind. The old man in “The Ancient of Days” isn’t the God of Genesis bringing form to the Void, but a god of mostly evil — Urizen by name — using that same compass of Newton’s to measure the Void and begin the repressive march of Science with a capital S. And then there’s my personal fave … Blake’s doltish Adam, hypnotized by the Snake as he asserts our most potent means of control — the power of names, aka the power of abstraction, aka the power of symbolic representation, aka the power of Narrative.

William Blake is the OG Epsilon Theory

Okay, Ben, thanks for the art history lesson. But what’s the point? These ETFs aren’t going to trade themselves, you know.

Yeah, I know. And that’s actually pretty close to the point I’m going to make. But it’s bigger than that, too, and to get there I need to make one more observation about red-tailed hawks, science and social history.

There is nothing abstract about a red-tailed hawk and its mastery of flight. There is no active contemplation and scenario modeling required for Indiana to glide on a thermal, spot a chipmunk sliding through the tall grass, and dive Stuka-like to rend his breakfast with beak and talon. It’s beautiful, sure, in a deadly sort of way familiar to anyone who observes markets or politics for a living. It’s a mystery that a part of my brain would desperately like to solve, double sure. But most of all … it’s REAL. It’s utterly authentic and true. Not only to Indiana and the chipmunk, but to me the Observer, too.

There is no separation from what Indiana IS and what Indiana DOES.

Marx called the separation from what one is and what one does “alienation”, and he applied it (of course) to his notion of class identity and class struggle, such that in capitalist societies a worker was separated from the meaning of his labor. When you’re a cog in a machine, moving widgets around on an assembly line, there’s no connection to the finished product. You ARE a human but you DO as a machine. That’s alienation, and it’s a heartbreaker.

Now Marx being Marx, naturally he thought of this notion of alienation as it applied to the terrible but inevitable seizure of the means of production by the capitalist class from the working class (to be followed by the capitalist class eating itself, but that’s another story). And that’s fine. But the concept of alienation goes much farther than that. Alienation applies just as much to Team Elite and us awful capitalists as it does to the “working class”. More so.

Meaning what? Meaning that I’ll tell you the story of Neb Tnuh, investor and citizen, and you tell me if it sounds familiar.

Neb has a hard time talking with real people these days. Neb just doesn’t … connect … with people the way he used to. He doesn’t have much to say. He mumbles a lot. He imagines long and involved conversations with people in his head, but that’s where they stay. In his head. He gets lost in his own thoughts. Hmm, “lost” isn’t quite right. Trapped is more like it. Trapped in a maze of social abstractions, both in markets and in politics, blared at him from all sides, without pause or relief.

Sartre famously said that hell is other people. For Neb, hell is other people who want to talk about markets or politics. It’s not that Neb is so certain that he has the answer for what’s going on, for why his Twitter feed is a dumpster fire, for why the markets seem like a bad joke and why politics seem like “Black Mirror” re-runs. No, Neb is positive that he doesn’t have an answer, that he’s definitely not in on the joke. But he would rather carve out an eye with a rusty spoon than wrestle with civilians who want to tell him why Trump is so awful or why Trump is so great, why Bitcoin is going to $100,000 or why Bitcoin is going to zero, why the “fundamentals are sound” or why the fundamentals are sound EXCEPT for this one issue which will bring the whole house of cards tumbling down ANY DAY NOW, why the Fed is the source of all evil in the world or why the NRA is the source of all evil in the world or why the Democrats / Republicans are the source of all evil in the world, why Amazon is going to take over the world or why Amazon … actually, no one ever takes the other side of that argument, which is kinda interesting to Neb.

So obviously Neb is a real barrel of laughs at parties, which he shuns like the plague today even though he remembers that he used to like parties. The circle of real people that he actively feels comfortable being around has shrunk and shrunk and shrunk until he can count them on his fingers. And unless they are in the trenches of this mental war of abstracted social constructs, Neb increasingly has a hard time connecting even with them. He increasingly talks past and through the people who are the most important to him, like his wife and daughters. They’re not on this abstracted battleground (thank god!), but as the war takes up more and more mental space there’s just not enough room for much else.

On the flip side of that coin, it’s easier and easier for Neb to talk with complete strangers on social media platforms, precisely because these entities (some human, some not) are entirely abstracted. He doesn’t even have to work very hard at “naming” the strangers as Adam named the beasts, because they depict themselves as symbolic representations of this tribe or that. It’s all so easy for Neb to lose himself in this ocean of social abstraction and Turing tests, because he’s fluent in the symbolic languages of mathematics, history and pop culture. And so he swims in that ocean, compulsively even, until he’s forgotten whether or not there was ever a shore.

Neb Tnuh is profoundly alienated.

Who Neb Tnuh IS — a free man in a real world — is almost totally separated from what Neb Tnuh DOES — abstracted other-regarding behaviors for abstracted others — both as an investor and as a citizen.

What’s driving Neb’s alienation? It’s what William Blake warned about. It’s the abstraction of the real world and real human activities into mental constructs, which are then established as “the real things” that we must interact with in order to succeed. It’s Magical Thinking, which is ALWAYS used in service to a political structure of social control.

But it’s worse than Blake imagined. Driven by a global policy response to the Great Financial Crisis and by the universal spread of new media technologies, the scope and scale of abstraction in service to political ends has evolved to levels unparalleled in human history. Yeah, this time is different.

The simple abstraction of nature is something that’s been alienating the Neb Tnuhs of the world since Archimedes was drawing figures in the sand and got a Roman sword in the gut for his troubles. What’s different today is that the abstractions themselves have become abstracted farther and farther away from their ostensible real-world source, such that the abstractions have become — and I’m using this word in its technical sense — cartoons. We’ve “progressed” from abstracting the principles of flight from red-tailed hawks to abstracting the principles of social influence from the abstracted principles of red-tailed hawks. We model the model in order to instill fear or greed or pleasure or patriotism. Constantly. Everywhere.

Today we abstract social behaviors, not Newtonian physics.

Today we abstract at scale through digitization.

THIS is the true Triumph of Abstraction. It’s the Triumph of the Cartoon.

I’ll give you two examples. These cartoons will seem like small examples, tiny things. But they’re not. Hundreds of billions of dollars of wealth has been created (and lost) because of the first of these cartoons, as recently as the other Friday. A Presidential election was impacted by the second cartoon. And it’s not the Presidential election you’re thinking of. Although that one, too.

Example 1 — In the beginning, there was a desire to model the employment patterns of the U.S. economy to help policymakers figure out what was actually going on. So in 1884 (!) Congress established the Bureau of Labor Statistics (BLS) to do some counting and abstracting, and since 1915 (!) the BLS has been surveying employers to estimate how many Americans are working and how much they’re being paid. On the first Friday of every month, the BLS releases its report on the real-world employment patterns in the U.S. for the prior month. This data is an abstraction, to be sure, full of seasonal adjustments and model estimations, but it is a first level abstraction. This is not the cartoon.

One of the standard calculations that the BLS reports is the percentage change on a year-over-year basis in how much workers are being paid. Usually this wage growth report takes a backseat to the more famous “jobs report” of how many jobs were added or subtracted from the U.S. economy in the prior month and the even more famous “unemployment report” (which is actually based on an entirely different survey) of the percentage of Americans who were actively looking for work but were unable to find jobs. But when everyone and his cousin is either worried about wage inflation or hoping for wage increases, then the wage growth “number” takes on enormous importance. It’s the depiction and the narrative around the BLS wage growth calculation that is the cartoon. And that cartoon is everything for markets today.

On Friday, February 2, the BLS reported a January wage growth number of 2.9%, far “hotter” than consensus estimates and widely taken as evidence that (finally) inflationary pressures were showing up in wages. The following week markets sold off as hard as they have in years, in large part because it seemed that central bankers were now terribly “behind the curve” when it comes to inflation, and that they would be forced to tighten faster and more dramatically than “promised” via prior forward guidance.

On Friday, March 9, the BLS reported a February wage growth number of 2.6%, well below consensus estimates and widely taken as evidence that — together with the massive increase in jobs — we were actually in a “Goldilocks” investment world that was neither running too hot to force the Fed’s hand nor too cold to slow down expectations of real-world growth and expansion. What a difference a month makes! All major market indices had glorious days, with the NASDAQ setting a new all-time high.

What if I told you that both of these wage growth numbers were misleading abstractions of what they claimed to be?

What if I told you that you’ve been whipsawed by a cartoon, and you’re going to be whipsawed again?

Here’s what I’m talking about, and if you want to double-check the math or the numbers it’s all available on the BLS website. For historical data, this is a good place to start.

The most basic way to look at wages for a monthly report would be to count up how much all workers got paid in that prior month. But that doesn’t work for a month-to-month comparison because different months have meaningfully different numbers of days. Unless you’re getting paid on a monthly or twice-monthly basis, then you’re going to be making less in February than you are in January. So the BLS uses the work week as their basic apples-to-apples comparison basis.

On this most basic abstraction of wages, annual wage growth for January (the Feb. 2 announcement) was 2.8% and annual wage growth for February (the Mar. 9 announcement) was 2.9%.

Wait, what? That’s not at all what we were told. It’s not quite as hot for January, and it’s clearly not Goldilocks for February. What’s going on here?

As far back as I can trace the theater of BLS reports — and that’s how one should think about these market data reports, as theatrical productions consciously designed to impact behavior — the “number” that’s reported isn’t the apples-to-apples comparison of weekly wages. Instead, it’s hourly wages. Why? Because back in 1915 this is how most people got paid. The abstracted idea of hourly wages connects with people more than the abstracted idea of weekly wages. It’s a more effective tool for eliciting a behavioral response, so that’s why our theatrical effort focuses on it every month.

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 last year. That additional layer of abstraction is the average length of the work week.

Now this data estimation changes very little from month to month. Unlike the difference in work days from month to month, which can be meaningful and is incredibly easy to measure, the difference in work hours from week to week is an immaterial and almost certainly statistically spurious estimation. Here are the average number of hours in the work week since 2012.

Since 2012, the average length of the work week has been as low as 34.3 hours and as high as 34.6 hours. For more than SIX YEARS, the maximum deviation from the mean has been less than NINE MINUTES, less than ONE-HALF OF ONE PERCENT of the total work week. This is the flattest line you will ever see in any time series, and any month-to-month deviation from the mean is almost certainly a spurious statistical estimation. Meaning that the month-to-month differences in the average work week are so far inside your margin of error for this sampling and estimation process that you can have ZERO confidence that you are abstracting anything real. This is as bogus of an abstraction as you will ever see.

And yet it makes all the difference in the world for hourly wage calculations!

Why was the February wage growth number reported on March 9th as 2.6% rather than 2.9%?

Because the average work week in February 2018 was randomly estimated as being six minutes longer than it was a year ago.

Everything you read about what the March 9th wage growth number meant for your portfolio — the entire Goldilocks narrative of a “contained” wage inflation number combined with strong job growth — is based on a statistically spurious result. Everything. It’s all made up. None of it is real.

And yet, on the basis of the Goldilocks narrative, which was the all-day headline of the Wall Street Journal and the talking point of every Missionary on CNBC that Friday, the S&P 500 was up more than 1.7% on the day. That’s $415 BILLION of market wealth created in the S&P 500 alone, in one day, from a cartoon representation of annualized wage growth in the U.S. economy.

Now here’s the kicker. Unless the average work week in March randomly declines 12 minutes versus the February average work week, it’s all going to happen again on April 6th. Why? Because the March 2017 work week was 34.3 hours long. So even if weekly pay increases by more than 3% in March, which is like the Maginot Line of wage inflation numbers, when the curtain rises at 8:30 AM ET on April 6th, we will be told by the theater performers that the wage inflation “number” is still a very manageable 2.6% or something like that. And in the immortal words of Monty Python, there will be much rejoicing.

But by the same token, at some point this year we will have a perfectly random 12 or 18 minute estimated decline in the average work week, and the 2017 comp will be a month with a randomly high average work week. On that first Friday of that fateful month, we will have a “shockingly” high wage inflation number, “proving” that the Fed is way behind the curve, with breathless coverage of swooning markets on CNBC. In the immortal words of Monty Python, there will much gnashing of teeth as the Killer Bunny emerges from its cave.

It’s the Triumph of the Cartoon, and as an investor it puts me at war with myself. Do I invest on the basis of reality, meaning the fact that wage inflation is, in fact, picking up in a remarkably steady fashion in the real economy? Or do I invest on the basis of Narrative abstractions that I can anticipate being presented and represented to markets at regularly scheduled moments of theater? Because the investment strategy for the one is almost diametrically opposed to the investment strategy for the other.

I’ll probably do the latter. I’ll probably act on the basis of abstracted and doubly abstracted cartoons of reality because that’s what I think everyone else is going to react to (the Common Knowledge Game), rather than act on the basis of what I truly believe is happening in the real world.

And that’s where the alienation comes from.

But that’s just my alienation as an investor. I am equally if not more alienated as a citizen.

Example 2 — Sticking with the labor statistics genre of abstraction in the service of Narrative creation, let’s turn to the weekly theater of new unemployment claims, presented every Thursday morning at 8:30 AM. This is, historically speaking, a decidedly uninteresting and low prestige data series, to the degree that the Bureau of Labor Statistics does not compile the data and abstracted reports themselves, but have handed it off to a lonely backwater the Employment and Training Administration of the Labor Department.

Starting with the Great Recession, however, interest in all macro data reports soared to new heights, and as the only weekly U.S. government report of any note whatsoever, CNBC began to build a regular feature around the new unemployment claims report in mid-2009. Over the next three or four years, anyone who was actively involved in markets would know whether or not the weekly initial unemployment data had surprised to the upside (bad news, as that meant that more people than expected had filed for unemployment claims for the first time) or surprised to the downside (good news, as fewer people than expected had filed). These reports were presented as a Big Deal, and markets moved markedly up and markedly down on the news. Not for more than a day or a half day, typically, but they moved.

Almost always, the number surprised to the downside (good news) as “green shoots” of recovery spread across our great nation from 2009 through November 2012, when — oh wait! — we had a Presidential election. In truth, these abstracted reports, purporting to give an accurate snapshot of weekly developments in the real-world employment situation in the U.S., were a joke over this time period. They were a constructed cartoon.

The chart below is a frequency distribution (also called a histogram) of the errors made in the reporting of weekly unemployment claims from September 30, 2009 through the November 2012 election.

Frequency Distribution of Weekly Unemployment Data Reporting Errors
September 30, 2009 – November 2012 Election (n=162)

Source: Employment and Training Administration. For illustrative purposes only.

What you’re seeing here is the percentage of weekly reports that showed an error in the original reporting versus the initial revisions posted one week later (there are then final revisions posted two or more weeks later). The bars to the right of the red line are positive revisions, meaning that the revised reports showed more people than originally reported filing for unemployment. In other words, the original report made a “good news!” mistake by under-reporting the true number of first-time unemployment claimants.

In a bias-free world, you would have errors equally on one the left side of the red line as on the right side of the red line, and they would form some sort of normal distribution (a bell curve) centered on that red line of zero revisions. Obviously enough, these revisions are anything but normally distributed. They are bizarrely and incontrovertibly skewed enormously to the “good news!” bias side of all this. I mean … I could give you p-tests and other calculations of statistical significance, but this picture is worth a thousand words. There is a greater chance that the sun will go nova tonight and destroy the Earth in a paroxysm of incinerating plasma than for these errors in initial jobless claims to be the work of chance alone.

And I know what you’re thinking, because I thought the same thing when I first compiled this data for a 2013 Epsilon Theory note (“Heeeere Comes Lucky!”). Maybe these reports have always been so jaded, so wrong, so cartoonish in their bias. But no.

Here’s the histogram of the errors made in the reporting of weekly unemployment claims during the Bush Administration from September 30, 2005 through the November 2008 election. Same time frame, same number of observations. Totally different pattern.

Frequency Distribution of Weekly Unemployment Data Reporting Errors
September 30, 2005 – November 2008 Election (n=163)

Source: Employment and Training Administration. For illustrative purposes only.

There are a few weeks with slight over-reporting of unemployment claims and a few more weeks of more pronounced under-reporting of unemployment claims, but by and large this is a picture of a reasonably accurate and only slightly biased data report. Compared to the same time period in the first Obama term, there is no comparison.

Here are the aggregate numbers that underpin these graphs.

In the first Obama term, original Labor Department reports understated initial jobless claims by 858,000 people relative to initial revisions. Compared to final revisions, the original estimates look even worse, understating jobless claims by 884,000.

In the second Bush term, original Labor Department reports understated jobless claims by 292,000 relative to initial revisions. Compared to final revisions, the original Bush-era reports understated jobless claims by only 5,000 people.

Were there more initial jobless claims in the Obama time period than in the Bush time period? Yes, but only approximately 25% more. The total errors versus initial revisions, on the other hand, increased almost 300% over the comparable time periods, the total errors versus final revisions increased more than 18,000% over the comparable time periods, and the skew towards under-reporting actual claims (not just the number of wrongly reported claims but the degree of wrongness) is even more pronounced.

These are the facts.

So I want to be very careful in what I say next.

What I am NOT saying is that there was a conscious conspiracy to skew the employment Narrative of the real economy in a good news direction. The reported abstraction of initial unemployment claims is constructed from a compilation of abstractions from each individual state, and in the disarray of state government post-Great Financial Crisis, no doubt these first level abstractions were chronically late and poorly estimated, requiring significant revisions in subsequent weeks.

What I AM saying is that this systematic error was clearly visible and known to the BLS, which is staffed with very smart people, and they could have fixed it if they had wanted to. The BLS adjusts raw data all the time, and there are obvious statistical adjustments that could be applied to this obvious systematic error. But the BLS chose not to fix it, or rather they chose to allow the Employment and Training Adminstration to continue making these egregious errors.

Until after the election.

On September 12, 2013, reported weekly unemployment claims were shockingly low — only 292,000 Americans had filed for initial unemployment benefits in the prior week, the lowest number in more than seven years and a decline of more than 30,000 applicants from the prior week. Huzzah! This economy is finally starting to hum! As it turns out, however, the low number was because neither Nevada nor California had filed their data with the Labor Department on time. As it further turns out, the Employment and Training Administration knew that the number was way off for this reason, but published it anyway without explanation. As it further turns out, the Labor Department informed a few reporters of the mistake in an embargoed fashion, which meant that the “news” of the embedded error in the filing was dribbled out by private news agencies after the official release.

The problem with all this for the Labor Department wasn’t the ridiculous process that drove a ridiculous error. After all, this had been the practice for years. The problem for the Labor Department was that their act of theater was now publicly revealed as an act of theater. The multi-level data abstraction was revealed as a constructed cartoon. So the Labor Department asked Keith Hall, a former BLS commissioner, and “several” unnamed economists (i.e., current BLS commissioners) to tell the Wall Street Journal that the methodology and bureaucratic oversight of the Employment and Training Adminstration had to be improved. And it was. I guess.

The kicker, of course, is that this cartoon Narrative regarding real-world employment patterns had a significant impact on the 2012 election. That’s not my view. That’s the view of Obama’s Chief Strategist for both Presidential campaigns, David Axelrod. Take a look at what he says about the unemployment rate in a panel discussion organized by his Institute of Politics: Campaign Strategists: 2012 Explained. It’s a long video, but for anyone interested in U.S. politics it’s a must-see. Why did Obama win in November? Because the unemployment rate went down in the months leading up to the election. The economy got better, as evidenced and interpreted by the unemployment rate, and that swung a lot of undecided voters. Per David Axelrod, that’s what won the election.

Now did the weekly initial claims data play a big role in shaping that cartoon interpretation of the U.S. economy going into the November 2012 elections? I dunno. This particular act of theater was more widely distributed on CNBC than on CNN, so it didn’t get the sort of audience of, say, the unemployment “number” itself. But it wasn’t useless, either.

Let’s just say that I think a lot of people owe Jack Welch an apology.

To be clear, this is neither a Democrat nor Republican thing. It’s an us thing.

I mean … “emails”? Are you freakin’ kidding me? Cartoons aren’t just created to mobilize positive sentiment and supportive social behaviors (although that’s pretty much all we see in capital markets, because it’s a positive-sum game, not zero-sum like politics). The negative cartoon-ification of Hillary Clinton was both the most vicious and the most effective gambit in the last 100 years of American politics. To be sure, The Clintons™ brought soooo much of this on themselves. If there’s ever been a political candidate more ripe to be transformed into a negative cartoon than Hillary Clinton, I am unaware of who that might be. But where Donald Trump embraces and actively creates his obvious cartoonishness, Hillary Clinton had her cartoon imposed on her unwillingly, to disastrous result. Today’s key to political and economic success is controlling your own cartoon. Yes, this is why Trump won.

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.

So where does this end?

You hear a lot of people talk about an inevitable Minsky Moment, where financial system instability is revealed in an Emperor’s New Clothes instant, and the whole central bank-led house of cards comes tumbling down. I’m a big fan of Hyman Minsky, but I don’t believe that a Minsky Moment is nigh, for the most part because Minsky saw central banks as the solution to financial instability, not the cause. I wrote about my views on the Minsky Moment here, back in 2014.

But I do think we are close to what I want to call an Icarus Moment.

The myth of Icarus is one of the Old Stories, meaning that its narrative power spans geography, culture and time. The Greeks alone had at least two Icarus narratives, both the younger myth that we all know and the older myth of Phaeton driving the chariot of the sun to his death.

What is an Icarus Moment?

It’s the price we pay for our hubris in modeling Nature past the point where our human brains and human bodies can handle the strain of our application of those models. It’s our forfeit for daring to frame the fearful symmetry of a jungle cat. It’s flying too close to the sun. It’s the destructive consequences of overweening pride in our pursuit of greater and greater abstraction that drives greater and greater alienation at greater and greater scale.

An Icarus Moment is a Fall.

It’s the Fall of Rome and the Fall of Troy. It’s the Fall of Man. It’s the Fall of the Mississippi Company and the South Sea Company. It’s the Fall of Enron and the Fall of Corzine. It’s the Fall of Residential Mortgage-Backed Securities. It’s the Fall of every too-clever-by-half coyote in the history of man, both in politics and in markets.

It’s the Fall of Donald Trump. It’s the Fall of Bitcoin. It’s the Fall of the Euro. It’s the Fall of Pax Americana. It’s the Fall of Central Bank Omnipotence. Hubristic conceits one and all, now operating as cartoons of their former selves.

Why do I think we’re near an Icarus Moment?

Three reasons.

First, it’s the overwhelming dominance of abstraction and symbolic representation in our social lives, in turn leading to bewildered and profound alienation.

Our politics are now completely consumed by trope and fiat news, such that our identities as Democrats or Republicans no longer have recognizable meaning. The Donald Trump cartoon of the Mad King? The Russia/China cartoon of the Foreign Peril? The Bezos/Gates/Buffett cartoon of the Oligarch? The Bitcoin/Silicon Valley cartoon of the New? The CNN/Fox/CNBC cartoon of the Circus? Tropes all, combined and recombined in engaging fashion as if written for a Hollywood script (which is itself a trope). Who we ARE as citizens and voters is no longer reflected in what we DO as citizens and voters, and that’s the very essence of alienation.

Our markets are now completely consumed by factors and narratives, such that our identities as value investors or growth investors no longer have recognizable meaning. Value investing and growth investing, which have been the dominant ideologies of markets for the past 70 years or so, are no longer meaningful processes where research into individual real-world companies has any usefulness whatsoever. Instead, they have been abstracted into “factors”, into a modeled quality of a modeled quality of a real-world company. We no longer invest to own a fractional share of a corporation’s cash flows and opportunities (an individual stock). We no longer invest to own an abstraction of that fractional ownership share across multiple companies (an index). Today we invest to own an abstraction of a quality of the abstraction of fractional ownership shares across multiple companies (a factor). And even these factors are muted to the point of triviality by the algorithmically unpredictable shifts of the Three-Body Problem. My guess is that 80% of investment research and management jobs in the financial services sector add zero value today and will be gone in less than 20 years.

Second, it’s the return of hubris as the ancient Greeks conceived it, an aggressive pride where the strong delight in attempts to shame the weak. You see it constantly from our White House. You see it constantly on Twitter and throughout social media. You see it whenever rapacious, know-nothing narcissism is celebrated as leadership even as civility, expertise and service are mocked as cuckery. Which is to say you see it everywhere.

Pride goeth before destruction, and a haughty spirit before a Fall.

Yeah, I know I sound like a grumpy grandpa when I write something like this. Yeah, I know that this is a Bible quote. It’s also THE plot of every Greek tragedy. You think we’re wiser than Aeschylus, than Sophocles, than Euripides? You think we’re smarter than Socrates, than Plato, than Aristotle? You think our politicians have got anything on Cleon, on Alcibiades? Bollocks. This is the human condition, people! There is NOTHING new under the sun when it comes to human behavior, and this is how the story of aggressive pride ALWAYS ends. We’ve transformed Pride from the deadliest of the Seven Deadly Sins into the foremost of Virtues, particularly in our children and our celebrities, and that’s the biggest tragedy of any age.

Third, from a game theoretic perspective, we are transforming all of our cooperative games into competitive games. I’ve written about this in two Epsilon Theory notes — “The Silver Age of the Central Banker” and “Virtue Signaling, or … Why Clinton is in Trouble” — so I won’t repeat all that here. The basic idea, though, is that most games we play as a nation in the international arena or as political parties in the domestic arena have multiple equilibria, multiple balancing points that are as good as it gets for the players and where it is irrational to take actions that would break away from those balancing points. On two occasions — after the Revolutionary War for domestic games and after World War II for international games — political leaders in the United States established/enforced an equilibrium that is largely cooperative at the meta-game level (I’m using cooperative in the non-technical sense of the word), to the benefit of ALL players. What we are doing now is unilaterally and intentionally breaking those equilibrium positions — in both international and domestic games — to “drop down” to competitive equilibria where ALL players are worse off. Why? Because it makes for an effective political cartoon. We’re tough! We’re fighters! We’re winners! Again, bollocks.

But because these competitive equilibria are, in fact, equilibria, they stick. They stick until you have an enormously destructive event — an Icarus Moment — that breaks this equilibrium and creates “room” for a dominant player to reestablish the cooperative “regime”. Or not. Sometimes, as it was for Groucho, the Icarus Moment is an all-encompassing war. Sometimes, as it was for Karl, the Icarus Moment is a lot of medium-sized wars and domestic conflicts. Sometimes, as it was for Augustine, the Icarus Moment is a slow-motion dissipation of the City of Man, where the Oligarchs and the Generals hollowed out the greatest country in the world for a century in a long series of little Icarus Moments until some second-rate foreign power finally put out the lights in the West for a millennium.

So what do we do about all this?

As investors, I think we must take a profoundly agnostic perspective on capital markets. That means that we don’t trust anything we hear or read. That means we ask WHY we are being told something with as much or more attention as we ask WHAT we are being told. That means that we don’t trust our own biases. That means that we recognize our long-standing investment processes to identify value or growth as a bias, not as some eternal investment truth.

The bottom line here is that we all have to make the same alienated decision as Neb Tnuh. Recognizing that we are being played, do we embrace the game-playing and focus on the Narrative ebbs and flows for our investment decisions? Or do we push away from the casino table that our doubly and triply abstracted markets have become, in favor of securities that are at least closer to real-world economic activities? We can’t isolate ourselves from abstracted markets and an Icarus Moment. But we can insulate ourselves. Exactly two years ago I wrote a long note on exactly this, called “Hobson’s Choice”. It’s held up pretty well, I think.

Oh yeah, one more thing. When an Icarus Moment happens, you want to be long volatility.

As citizens, I think our actions depend on where we are in life. For me, now in the autumn of life (early autumn, one hopes!), it’s a matter of reconnecting to the real world of real people and real animals. It’s a matter of repairing the damage — and it IS damage — that alienation creates. That’s why I have a farm. That’s why I write Epsilon Theory. It’s therapy.

More broadly, though, here’s the principle I want to live by: don’t be Daedalus.

Don’t become so consumed with your own powers of abstraction and ability to create weapons and labyrinths that you end up in a prison yourself. Don’t be the guy who straps those wings onto Icarus and sees his son fall to his death. The game ain’t worth the candle.

Or in terms of a recent note: don’t be a coyote who ignores the meta-game.

For my children, for anyone in the spring and summer of life, it’s a different principle: don’t be Icarus.

Don’t confuse a knowledge of Science and its languages of abstraction for wisdom. Wisdom comes from an ability to think critically about abstraction and its uses and misuses for political and economic power. Anyone can learn a language, like mathematics. Anyone can apply that language to abstracted questions of social behavior, like economics. Everyone is so focused on STEM. Everyone is tripping over themselves to hire physicists or math majors. Not me. I want to hire comparative literature majors. I want to hire history majors. Why? Because it’s training in how to think about the WHY and not just the WHAT; because it’s training in the universal language of symbolic representation, which is words and story, not math.

Or in terms of a recent note: don’t believe the coyote-math.

Long volatility and short abstraction

That’s my algorithm for living in the Cartoon Age, both as an investor and as a citizen.

It’s a lonely perch, because it doesn’t scale. You’ll never get rich and you’ll never get elected President being long volatility and short abstraction. But it’s real. It’s my personal equilibrium.

Everyone sees a hawk and wishes they could fly. But that’s not the hawk’s great secret.

The great secret is living such that Being and Doing are as one.

And we can all do that.

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What is it, really?

Hygiene Inspector: If I may begin at the beginning? First, there is the cherry fondue. Now this…is extremely nasty. But we can’t prosecute you for that.
Mister Milton, Owner and Proprietor of Whizzo Chocolate Company: Agreed.
Inspector: Next, we have Number 4: Crunchy Frog. Am I right in thinking there’s a real frog in ‘ere?
Milton: Yes, a little one.
Inspector: Is it cooked?
Milton (confused): …No?
Milton: We use only the finest baby frogs, dew-picked and flown from Iraq, cleansed in the finest quality spring water, lightly killed, and sealed in a succulent Swiss, quintuple smooth, full cream, treble milk chocolate envelope, and lovingly frosted with glucose.
Inspector: That’s as may be, but it’s still a frog!
Milton: What else would it be?
Inspector: Well don’t you even take the bones out?
Milton: If we took the bones out, it wouldn’t be crunchy, would it?
Inspector: Constable Parrot ‘et one of those!
Milton: It says “Crunchy Frog” quite clearly.
Inspector: Well, never mind that. We have to protect the public. People aren’t going to think there’s a real frog in chocolate. The superintendent thought it was an almond whirl! They’re bound to think it’s some kind of mock frog.
Milton (offended): Mock frog? We use no artificial preservatives or additives of any kind!
Inspector: Nevertheless, I advise you in the future to replace the words “Crunchy Frog” with the legend “Crunchy Raw Unboned Real Dead Frog” if you want to avoid prosecution.
Milton: What about our sales?
— Monty Python Live at the Hollywood Bowl, “Crunchy Frog” sketch (1982)

It has been pointed out to us that we write rather a lot about philosophy and psychology for a website/blog/newsletter about investing.

Is this surprising? This should not be surprising. All of us are in the business of prediction. Thankfully, not all of it is explicit prediction, like saying that we think that the price of Walmart stock will be $120 in three years, or that Tesla will be bankrupt in four years. Most of it is implicit prediction, like the way that investing money in something risky implies all sorts of things about the returns we expect from it. Predictions all the same. And any activity like this relies on developing confidence in some basis for creating (or assuming) those predictions.

Philosophy, and specifically epistemology, asks how we can know the things we need to make those predictions. Are conditions, traits, features of the thing we’re predicting observable? Are their responses observable? With what confidence may we infer traits from similar things we have observed? Further, may we reason how those traits might interact with other things to allow prediction? Psychology asks how accurate those human observations might be. It asks what evolutionary processes may have colored or influenced what we know, and what we think we know. It posits heuristics that might substitute for empirically-driven reasoning, whether helpfully or harmfully. Furthermore, in a field like investing that is responsible for making predictions about human behavior itself, psychology is recursively relevant, in that it studies both the tool of the observer and the observed.

Psychology and philosophy are critical tools for the investor. But in addition to being particularly ripe fields for bullshit, they also suffer from one of the same tendencies that plagues investors: people get so hung up on terminology and conventions that they start saying and doing dumb things. As always, the shrewd investor avoids that behavior himself and for his clients and capitalizes on it in others.

The Tyranny of Terminology

Of course, that gasbag introduction was just a way to tell you that I got into a little debate about Jordan Peterson.

If you don’t know much about him, Peterson is a professor of psychology at the University of Toronto, a cultural commentator and a bit of a rabble-rouser. As a psychologist and academic, he is heavily cited and as far as I can tell (which is not very far, but judging by citations alone), well-thought-of in his field. As a cultural commentator, he is thoughtful and incisive as a proponent of self-control, advocate of free speech, and opponent of what he characterizes as Neo-Marxism and Postmodernism, especially in the American university. As a scientific historian of philosophy? Well, this is where things get a little more controversial.

You see, the piece I was discussing with a very thoughtful senior staffer at a large U.S. university endowment (don’t tell my salespeople I’m getting into philosophical debates with clients and prospects, please and thank you) made the argument that Peterson was the wrong choice for a public conservative intellectual. The argument, if I may summarize, finds fault with him because (1) he attracts an audience of mostly young white males, (2) the traits he ascribes to Postmodernism are cherry-picked and not entirely correctly as derived from the history of the movement, and (3) he uses the terms “Neo-Marxist” and “Postmodern” seemingly interchangeably despite the different heritage and intellectual evolution of the terms and associated philosophical movements. The piece is a rousing little number, and almost enough to make you want to sit through that whole documentary on Jacques Derrida. (No, not really. Good Lord.)

Guess what? All the claims are pretty much true. Guess what else? None of them matter. I’ll get back to why, but first, I want to talk about another very current example.

You may have seen that Steven Pinker, cognitive pyschologist scientist at Harvard, published a new book called Enlightenment Now. Now, the reality is that the book doesn’t really undertake much discussion of the specifics of schools of enlightenment thought per se, but rather tells the story of human progress over the last 200 years. It makes the argument that these improvements are vastly underestimated and underappreciated. It also connects those achievements to specific influences of science and reason, sometimes very compellingly and sometimes somewhat less so. It is an encouraging and energizing read, even where its contentions are less well supported. I, for one, think there’s rather a lot in the 20th century alone that a purely scientific approach to curing society’s ills has to answer for. But much of the criticism has little to say about that, instead grousing that the science and reason the book discusses aren’t really about THE Enlightenment, but about principles of the Scottish Enlightenment specifically, and even then only about a subset of principles that Pinker particularly likes. After all, Marx was just a natural extension of the French Enlightenment!

Are you detecting a pattern here?

There are a lot of different kinds of talk about Enlightenment Principles right now. Ben and I write about them a lot. Ben wrote about them back in 2016 in Magical Thinking, and later in Virtue Signaling, or…why Clinton is in Trouble. I wrote about them in short last year in Gandalf, GZA and Granovetter. The remarkable new web publication Quillette provides a platform for writers who are thinking about them. The Heterodox Academy is building a strong core of support for them in universities. Pinker is talking about them. Chomsky has been speaking about them for decades. Hitchens, too, before he passed. In his own way, Taleb is talking about them (although he’d dislike the company I’ve chosen for him thus far). Peterson won’t shut up about them. Many of these same people — and some others — are simultaneously issuing criticisms of what is purported to be a diametrically opposed philosophy. In the early 2000s, the scandalous moniker applied was “Cultural Marxism.” Today this opposition is usually generalized into references to “Neo-Marxism” and “Postmodernism.”

But here’s the biggest shocker. Get out the fainting couch: they’re not all saying the exact same thing.

These are thinkers focused on many different areas, and so there are all sorts of topics where they disagree, sometimes vehemently. All would say that they believe in logic, truth and rationality, I think, but would define those things very differently. Most of the folks in the list above, for example, believe in a rationalism that inherently excludes faith. They are among the most prominent atheists of our time. They typically adhere to empiricism and the scientific method as the primary — even sole — method for transforming observations about the world into predictions. For two of them, Taleb and Peterson, rational thought means also incorporating evolved heuristics, intuition, instinct and long-surviving human traditions. This is not fringe stuff, but the logical conclusion of any serious consideration of Hayek and spontaneous order. It also means particular sensitivity to scientific techniques that end up equating absence of evidence with evidence of absence. All this means when you see many of the above names together, it’s…not always friendly. Like, stuff you can’t really walk back. Even among the two primary authors of this blog there are differences in how we see these things. I haven’t talked to Ben about it, but if I gave him the list of the above, I’d guess he’d hitch his wagon to Hitchens. Me? I’m probably closer to Taleb or Peterson.

What I doubt you’d find much of from this group is navel-gazing about terminology on the issue of postmodernism. While Voxsplainers and science historians quibble (very justifiably in the latter case) about whether there is a “discrete, well-defined thing called the Enlightenment” or whether it is fair to use “Postmodernism” in reference to a movement to esteem individual experience as peer or superior to free inquiry and free expression, the rest of us know exactly what people are talking about when they talk about this issue.

Don’t believe me? Fine. Go Full Cosmo and ask people you know these four questions:

Should governments and other important institutions abridge or allow (e.g., through Heckler’s Veto) the abridgement of some speech to protect people from speech which we think may be harmful to society, especially to historically oppressed groups?

Should we restrict the examination or evaluation of certain topics, especially when allowing them would prop up harmful social structures (especially power and class structures)?

Should we be skeptical that certain features and traits of the material, cosmological and biological world can ever be objectively true or important, considering the biased social lenses through which they are observed?

When making predictions about the world, should we consider personal experience and truths as equal or superior to whatever is uncovered through rational evaluation of the empirical merit or survival of a fact, idea or principle?

If you don’t think there’s a real thing happening in academia, in the public sphere, in politics and in creative media between those with three or four responses on opposite ends of the spectrum, I don’t know what to tell you. But I do know that this intuitive, arbitrary, subjective scale that I made up right just now is going to do a lot better job telling you about what people are referring to as a conflict between “Enlightenment” and “Postmodernism” than any etymologically thorough review of the terms themselves. How do I know this? Because it asks the question we should all ask any time that we see prediction or analysis oriented around terminology, categories, benchmarks, titles and jargon:

“Yes, but what is it, really?”

What is it, really?

There isn’t a question I can think of that an investor ought to ask more often, especially when it comes to any interaction they have with a representative of a financial services company trying to sell them something. And as Ben has written, all financial innovation is either finding a new way to sell something (securitization) or a new way to borrow money on things (leverage). The name of the thing being sold isn’t always a very good representation of what the thing is, sometimes for innocent reasons, and sometimes because crunchy, raw, unboned, real, dead frog doesn’t sound very appetizing.

Now, obviously the origin of most investment terminology, conventions, and even jargon IS innocent. Usually their purpose is to reduce complicated or large sets of data or principles to like dimensions. This is pretty helpful for communication and analysis. If we were constantly redefining the generally accepted conventions for a concept like “U.S. Large Cap Stocks”, for example, we would find it difficult to do a great many things with much efficiency. Economic constructs like sectors and common investment styles also have their appeal for this reason.

The problems, however, come in one of two flavors: first, as terminology becomes convention within an industry, we get further and further removed from a fundamental understanding of what the thing actually is. When we talk about U.S. Large Cap Stocks as a sort of monolithic entity unto itself, we forget that there is a lot going on underneath the hood. Sectors are changing. Companies, even entire industries are born and dying. New IPOs, companies slipping out into small cap land, companies bought out by private equity. We forget the nature of our fractional ownership, and the limited mechanical reasons why a stock’s price might rise and fall. The nature of what you own at any given time and the underlying risks attached to it really does change rather a lot, and that’s without getting into the massive sentiment-driven influences on price variation.

One of my favorite analogues to this is the ubiquitous reference to the “Top 1%” of wage earners. The concept is interesting and useful as a simplifying term, but like an asset class, it is by no means a static construction. Consider, for example, that more than 10% of wage-earners will, at some point in their lives, be among the Top 1%! Perhaps more impressively, more than 50% of Americans will at some point be in the Top 10%. Consider the impact that this has on a wide range of policies considered and rhetoric used — not invalidating, to be sure, but relevant.

The second class of problems stemming from the long-term path from terminology into convention is the inevitable realization by market participants that they can — and once enough people do, that they must — game the system. That’s where the coyotes and raccoons come in, but also your garden-variety professionals justifiably worried about career risk. But all of these folks hope you’re hungry for some delicious Crunchy Frog.

Fight Fiercely, Harvard!

What do I mean? Well, sometimes it’s obvious. Let’s consider the curious case of the Harvard Endowment.

A week ago, multiple media outlets reported that alumni from the Class of 1969 (“an artist, a clergyman, and two professors” one article reports, but disappointingly does not finish the joke) wrote incoming Harvard University President Lawrence Bacow to encourage him to force HMC to move half of the $37.1 billion endowment out of “hedge funds” and into ETFs tracking the S&P 500. The reason? This passive management strategy would have worked better over the last several years, and would have saved a bunch of money in fees.

It goes without saying that the alumni recommendation is just really, really terrible. Like, Fergie-singing-the-anthem terrible. It’s terrible because it would arbitrarily change the risk posture of the endowment by a massive amount. It’s terrible because it would shift what has historically been a well-diversified portfolio into a woefully underdiversified portfolio with extraordinarily concentrated exposure to the performance of common stock in large U.S. companies. It’s terrible because the confluence of those two changes would massively increase the drawdowns of the endowment, its risk of ruin, and potentially impact the long-term strategic planning and aims of the greatest research university on the planet.

But mostly, it’s terrible because the proposal isn’t passive at all. Not even a little bit. It’s a massively active roll of the dice on a single market! While alumni, executives and investors bicker over whether the portfolio ought to be “passively managed”, the origin of the term and the nonsense they’re proposing couldn’t be more at odds.

Now, you may be saying, “It’s a silly alumni letter. Most people get this.” No, they really don’t. Remember, the goofy letter was covered throughout the financial media, and they are the same media who triumphantly report the annual difference in return between literally anything and the S&P 500, regardless whether it is the return on a completely different type of security or vehicle with vastly different risk and diversification characteristics. This is how most of the world thinks about investing. This is how the damned Center for Economic Policy and Research thinks about investing, for God’s sake. People who are otherwise very smart think they’re making an intelligent point about fees when they’re really making a dumb point about asset allocation — about quantity and sources of risk. Even the aforementioned Steven Pinker contracted Gell-Mann Amnesia and retweeted an article attributing the Buffett bet between S&P 500 and hedge funds to a question of cost rather than the dominating risk differences between the two.

How do we cut through terminology confusion on an issue like this?

We ask: “What is it, really?”

If you’re being sold a portfolio based on principles of “passive management”, does your advisor or manager mean “low-cost”, does he mean “not making active bets against a global market portfolio”, or both (or, y’know, neither)? If it’s a low-cost story, what is it, really? Does it have a low headline fee, but with expensive underlying implementation using swaps or external funds that don’t get included in the stated fee?  Does it have a low headline fee that your advisor is layering high additional costs on top of? What is the asset allocation you’re being sold on? Is it implicitly making an active bet against a global portfolio of financial assets? Is it the right amount of risk? Is it taking sufficient advantage of the benefits of diversification?

If you’re being asked by a client or prospect about “passive management” or “indexing”, are you sure they’re asking you about low-cost investing? Are you sure they care whether the portfolio is avoiding making bets against market cap-weighted indices? Are you sure they care whether you’re in-line with some measure of a global market portfolio? Or are they asking you why you weren’t invested 100% in the S&P 500?

Because whatever the “real” definition of passive management, we all know that we all know that this is almost always what people mean.

Deeper down the Rabbit Hole

The fact that people really mean, “why don’t you just buy the S&P 500” when they say, “why don’t you just invest passively” tells us something else about most investors. When it comes to what they buy and what they own, and especially when it comes to conventions that manifest in indexes and benchmarks, they frequently haven’t given much thought to what it really is.

Try this yourself, with your boards, your financial advisor, or with your clients. Ask them, “What is it, really, that you invest in when you buy a stock?”

I’ve done it, so I’ll give you a preview: you’ll get a huge range of answers, usually relating to “ownership” of companies or businesses. So what is an investment in a stock, really? It is a fractional, juniormost claim on the cash flow of a company, usually denominated in the currency of the country where it has its headquarters, the price of which at any given moment is determined by the investor out there who is willing to pay you the most for it — and nothing else. It has no “intrinsic value”, no “fundamental” characteristic that can be evaluated without knowing how a hundred million others will value and perceive it. It is a risky and inherently speculative investment.

In my experience, this is not what most investors mean when they say to their advisor, “just buy me a portfolio of stocks.” What they really mean is “I want to own things I understand.” They believe that investments in businesses are simple and straightforward. Unfortunately, while the businesses and how they make money may seem perfectly sensible on the surface, the forces influencing the returns from ownership of a common stock are anything but simple and straightforward. Sure, diversification helps a lot, and there are decades of relevant data to help us build some confidence about some range of likely outcomes. There are also theories of varying quality about rational behavior in that spontaneous order we call a market. But what you really own is something whose value may confound any attempt at analysis or linkage to economic fundamentals over your entire investment horizon.

Think this is just a misunderstanding of individual investors? Think again. This is a systematic problem. Consider, for example, that every Series 7-trained professional — by which I mean most of your brokers and financial advisors — is told that alternative investments tend to be “riskier” than traditional investments. In isolated cases this is true, and it’s certainly true that there are strategies by which the complexity of so-called alternative strategies introduces new dimensions of risk — usually as a way for financial intermediaries to confuse people into paying them more. But by and large, it’s an unequivocally false statement. Still, the dimension of complexity vs. perceived simplicity dominates how investors think about risk, even though the relationship is rarely strong. Don’t believe me? Ask a client, or better yet, your financial advisor to rank the following in terms of their riskiness: (1) $100 invested in an S&P 500 index fund, (2) $100 invested in centrally cleared financial futures contracts on German bunds, (3) $100 invested in fully collateralized, centrally cleared credit default swaps on U.S. IG credit. My guess is that nearly all individual investors, a majority of financial media members and a plurality of financial professionals would put #1 somewhere other than the top of the risk list. And it’s Not. Even. Close.

As it intersects with familiarity bias/availability heuristics (i.e., we are biased in our analysis toward things that we think that we know), the tyranny of terminology becomes less insidious and more obvious in its influence. Terms like stocks, bonds, commodities or real estate have readily ascertainable meanings and definitions but mean something very different when they come out of the mouths of most investors. They mean familiarity or foreignness.  Whether we are individuals working with advisors or advisors ourselves, we must understand that when most investors say risk, they mean complexity. When most investors say simple — or something they think of as simple — they mean “low risk.” These are dangerous misconceptions.

Crunchy Frogs

And friends, any time there’s a dangerous misconception, there’s someone in the financial services industry poised to weaponize it. Plenty of Crunchy Frogs to go around, you see.

In every sub-field of money management, the name of the game is benchmark arbitrage. It’s a game played in three parts: risk layering, benchmark selection and multi-benchmarking.  In each case, the affinity investors have for the comfort of indices makes them susceptible to marketing and fee schemes that have the potential to cause them harm.

Risk layering is the oldest of the three games. I wrote about it last year in I am Spartacus. The basic premise here is to select a benchmark that will feel attractive, familiar and conventional, and then to take additional risk on top of it to either (1) earn a better fee for the return generated by that risk or (2) generate better-looking performance to improve marketing potential. This IS the business model of private equity buyout funds, who since the massive fund raises and valuation increases of the mid-2000s, now take your cash, buy a company at a premium, layer on debt and sell it a few years down the line without having really done much of anything else. They’re not alone. Keying on the intellectual attraction of an “absolute return hurdle”, many so-called hedged and market neutral funds take on credit, equity and other risks beyond what exists in the benchmark, happily collecting incentive fees on garden-variety sources of return. Long-only funds do this too, of course. Most actively managed funds tend to buy higher beta, higher volatility stocks, and nearly all are smaller capitalization than the benchmark they are measured against.

Benchmark selection is often just a variant of risk-layering, but where the fund manager tries to control both the measurement and the measuring stick. Think of this like “venue-shopping” in the criminal justice world. Have you hired an international manager benchmarked to the MSCI EAFE Index? They do this. I don’t know who you hired, but they do this. They always have 5-10% in emerging markets stocks, don’t they?  There’s a reason they didn’t select the MSCI World ex-US benchmark, folks.

As for multi-benchmarking, well…I hate to tell you, but if you have ever hired a money manager, a financial advisor or even an in-house investment team, you’ve seen this one, even if you didn’t notice it. It’s very simple: you pick two benchmarks, and then you make sure you’re always positioned between them. And that’s it. Sometimes one of the benchmarks is a peer benchmark (e.g., Morningstar, Lipper, eVestment peer group, Wilshire TUCS, Cambridge for the alts folks), or sometimes it’s a “style” benchmark (e.g., Value, Growth, High Dividend, Quality, Low Vol, etc.). But the objective is to always be able to point to something that you’re outperforming. A lot of this is well-intentioned and human, and there’s often a good reason to do it. But if you’re not looking out for it, it can confound.

And that’s kinda the point.

We can’t avoid convention, or the taxonomy that emerges naturally from an industry like ours. Nor should we want to. It helps us have conversations with each other. It helps us focus on Things that Matter instead of getting bogged down in details. But if we are to be successful, we must recognize the influence it has on us, our clients, our advisors and other investors. My advice?

Try to understand what your clients really think their investments are. Know what they really mean when they ask why you are or aren’t doing something.

Know what your advisors and managers think something is. Ask questions. Don’t assume based on terminology, and don’t be steamrolled by jargon.

Know what the things you own actually are, and build a risk management program to ensure that the baser temptations of people in this industry don’t cost you or your clients money.

As we delve further into alpha in a “Three-Body Market”, this last point will come up a lot. You can’t seek alpha if you don’t really know how to measure it. Except for the Postmodernists. Y’all can still tell us how it makes you feel.

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Good Job!

Every dog needs a job. It’s how they make sense of their place in the pack. It’s the key to a Good Dog.

You don’t have to tell dogs what their job is. They tell you. Maggie the German Shepherd? Her job is to protect. Sam the Sheltie? His job is to herd. Not sheep, of course, because that would be too useful. Nope, just squirrels. Turns out it’s not easy to herd squirrels, but that doesn’t stop our “special” dog from giving it his all, every day, rain or shine. Eco the Golden Retriever, pictured above? His job was to love, which he did with grace and abandon for 12 years. Rest in peace, old friend. You were a Good Dog, and I miss you.

A dog knows perfectly well when she’s done a Good Job. You can see it in her gait, in her tail, in her ears … everything about the way she carries herself says, “yep, I done good. did you see how good I done? ‘cause I done good.” Conversely, a dog also knows when she hasn’t performed up to snuff. The hangdog look is a real thing. A dog knows honor and a dog knows shame, and there is no more important example that any animal can set for us poor benighted humans.

Why? Well, this is the money quote from Sheep Logic:

Because with no sense of shame there is no sense of honor. There is no mercy. There is no charity. There is no forgiveness. There is no loyalty. There is no courage. There is no service. There are no ties that bind us as citizens, as fellow pack members seeking to achieve something bigger and more important than our ability to graze on as much grass as we can. Something bigger like, you know, liberty and justice for all.

Unlike dogs, humans have a hard time knowing whether or not they’ve done a Good Job. We consistently overestimate our competence at tasks, and when we fail, we evince befuddlement — as if we’re looking for the Restore Saved Game function — rather than remorse or apology. We humans are more Yogi Bear than Lassie.

It’s a widespread behavioral phenomenon at every age and demographic category. But it’s endemic in the young.

I think our notions of what it means to do a Good Job are so stunted for three reasons.

We’ve trivialized honor.

We’ve personalized shame.

We’ve redefined pride.

We trivialize honor through our constant celebration of mere engagement as some sort of actual achievement. We give ourselves and our children these faux “Certificates of Achievement” in one form or another all the time, and once you start looking for them you will see them everywhere.

This is how the Nudging State and the Nudging Oligarchy bring us into the fold. This is how they neg us.

This is how our children become Industrially Necessary Eggs.

We personalize shame by attaching it to identity rather than to behavior. Shame over behavior is ephemeral and corrective. Shame over identity is existential and utterly self-destructive.

The personalization of shame is a merciless goal of the Nudging Oligarchy because we will pay any price to “fix” ourselves. And our children are their primary targets.

Wait, your body isn’t “perfect” like a Victoria’s Secret model? What a shame. But don’t worry, we can help you with that.

We redefine pride when we confuse it for participation and belonging, when we treat it as the opposite of shame rather than what it really is — the foremost of the Seven Deadly Sins.

Like honor and shame, pride has been reattached from behavior to identity by the Nudging State and the Nudging Oligarchy. Like honor and shame, our children are their primary targets.

As Hieronymus Bosch knew well, the demon holding up the mirror of Pride isn’t a fable. The demon is us.

We’ve turned honor into a cheap candy, shame into an existential identity crisis, and pride into a virtue.

  • No wonder hospital admissions for suicidal teenagers have doubled over the past ten years.
  • No wonder our girls cut themselves and our boys shoot themselves.
  • No wonder my Twitter timeline is, day in and day out, a dumpster fire.
  • No wonder our 2016 election was a Sophie’s Choice.

By the way, the right answer to a Sophie’s Choice is NO. The right answer to an impossible dilemma is simply this: Homey don’t play that game.

Whee! I bet you’re a real hoot at cocktail parties, Ben. But can we come back to Planet Earth now?

Yeah, sorry about that. Actually, sorry not sorry. But in any event we’ve got to answer this question:

So what DOES it mean to do a Good Job?

Here’s what it means to any self-respecting dog. Which is to say, here’s what it means to all dogs:

You know what your job is.

The job is in service to the pack.

You do the job better than the average dog.

That’s it. That’s the Good Dog’s definition of a Good Job. Like all old wisdom, it’s deceptively simple. Like all old wisdom, it’s applicable across time and endeavor. This is an algorithm, by the way.

I’ll discuss two applications of the Good Dog’s definition of a Good Job in this essay: professional sports and professional investing. In both fields, there’s a LOT of money at stake with answering our question du jour — what does it mean to do a good job? — and in both fields there’s a clear notion of what “the pack” represents — the team in professional sports and the portfolio in professional investing. Given these similarities, it surprises me that there’s not a commonly held language to address the issue.

I think that professional sports is actually more advanced in their language on this than professional investing, or at least more cohesive, so I’ll start there. This is particularly true in the major professional sport most similar to professional investing in terms of its research methodology and sheer number of observable score/price events — baseball.

The modern methodology of baseball analysis goes by the name sabermetrics, coined by the Godfather of modern baseball statistics, Bill James, and named after the Society for American Baseball Research. I’m not sure if my dad started getting the Bill James Abstract in 1980 or 1981, but it was definitely before James hit the (well-deserved) big time in the mid-80s. In his own way, I’d say that Bill James has been the most influential data scientist in the world over the past 40 years. Certainly he’s had a huge impact on my career. Many others who work with data for a living, like Nate Silver, say the same thing.

The central question that Bill James set out to answer in the late 1970s is the Good Job question: You say that Ted Williams was a great baseball player. How do you know? Compared to who? What does that statement even mean? What’s the relationship between the greatness of Ted Williams and the performance of the Boston Red Sox?

These are exactly the questions that investors should be asking about active asset management, too.

There’s an enormous body of work developed in the sabermetric community to answer the Good Job question, but here I want to focus on one specific thread — the idea of Wins Above Replacement (WAR). It’s an approach largely credited to Keith Woolner (he calls it Value Over Replacement Player, or VORP), although as with all great concepts there are plenty of parents and plenty of variations on this theme.

Here’s what WAR seeks to measure: if you were replaced with an average player for your specific position, how many fewer games would your team win?

This is a perfect application of the Good Dog’s definition of a Good Job, all in convenient algorithm form!

  1. You know what your job is. We compare shortstops to shortstops, left fielders to left fielders, relief pitchers to relief pitchers. We take into account all aspects of the job, including defense.
  2. The job is in service to the pack. We measure players in terms of how they contribute to winning games for the team. We care about individual statistics only as they relate to team outcomes, not as ends in themselves.
  3. You do the job better than the average dog. You and your major league peers are, by definition, above average. We have the performance data for easily available replacement players (minor league call-ups, mostly), and we’re going to use that as your performance benchmark.

WAR is the Good Job algorithm for baseball. Today, WAR and its variants are the foundation for almost every economic decision that general managers make, from drafts to trades to contracts, in how they structure their team. Not just in baseball, but in every professional team sport.

So what’s the equivalent of WAR for investing?

Well, there’s no snappy acronym in investing, so I’m going to make one up.

Let’s call it PAR — Performance Above Replacement.

In WAR we want to compare the offensive and defensive stats of a professional position player, like a left fielder, to a readily available replacement position player, like a AAA call-up.

In PAR we want to compare the offensive and defensive stats of a professional active manager, like a long/short equity hedge fund manager, to a readily available replacement manager, like an ETF.

What do I mean by offensive and defensive stats? I mean making a distinction between the investment manager’s performance when the market is up and when the market is down. Makes sense, right? There are bull market managers and there are bear market managers and there’s a lot of muddy area in-between. Let’s measure how active managers perform across this crucial dimension for your portfolio so that we don’t miss some skill that might otherwise get lost in the shuffle. This is particularly important for long/short equity and global macro investors because they’re constantly changing their gross and net exposures, and it is the driving force behind the most commonly uttered phrase of active managers trying to explain how they do a Good Job: “We capture x% of the upside in our market but only y% of the downside!” where, of course, x is greater than y. If you haven’t heard (or used) that line 5 bazillion times in your investing career, then … lucky you. In more technical terms (and I’m sorry to do this, but I promise you there will be a payoff), these active managers are saying: “I am doing a Good Job because my performance demonstrates convexity.”

The concept of convexity is at the heart of Performance Above Replacement.

Convexity? Woof … that’s a ten-dollar word if there ever was one.

Let’s say you’ve got an area of your portfolio — call it your “tactical overlay” portion of the portfolio — where you’d like to give active management a shot. You’ve identified an active manager who runs a long/short global macro fund, you’ve decided that this is potentially a “real” diversifying strategy, and now you want to look at the manager’s PAR. Since this manager plays in the Everything sandbox, you’re going to use a global 60/40 investable index (or better yet a global risk parity strategy … yes, I went there) as the “replacement player”, and you’re going to separate out how the manager performs in up markets versus down markets, using the S&P 500 for that distinction because that’s your benchmark.

Here are some stylized absolute return profiles on the left, and the corresponding relative return profile on the right. I’m simplifying things here by drawing straight lines instead of what would be a smattering of point observations (monthly performance numbers, for example), but you can use a linear regression to create the lines. Actually you’re running two linear regressions, one for the manager’s offensive stats (performance when the S&P 500 is up, in green) and one for the manager’s defensive stats (performance when the S&P 500 is down, in red). The blue line is the performance of the replacement strategy (a global 60/40 or risk parity fund). Both funds cross the y-axis slightly below zero (more so for the active manager) to reflect the management fees and expenses associated with the funds.

When you “normalize” the active manager’s performance versus the replacement strategy and the S&P 500, which is what the right-hand graph is doing, you see that this manager nicely outperforms the replacement strategy in difficult markets without underperforming nearly so much when markets are rocking, creating a shallow V-shape or upward bend to the performance line. THIS is convexity.

This manager clearly has positive PAR, meaning that she improves the performance of your portfolio versus what you would have done with a passive replacement strategy, once you take into account both offensive and defensive stats. This manager is like a talented defensive catcher (i.e., a position where it’s important to play good defense) who is a so-so offensive player. That’s a classic player type, and there are plenty of teams who would find a spot on their roster for that.

There are dozens of different tools and well-known performance analytic statistics (Sortino ratio, Jensen’s alpha, upside/downside capture) that will do some variant of this PAR calculation for you, and they’re all designed to capture different aspects of convexity. This sort of exercise is the mother’s milk of consulting gigs, and every consultant in the world would look at this data and tell you that this manager is doing a Good Job.

Pretty exciting, right? Here’s a methodology that clearly works in professional sports and can be directly brought over to professional investing. It’s empirically driven and mathematically sound.

But it doesn’t work.

Or at least it doesn’t work anymore. Like so many other aspects of our investing lives, these mathematically sound and empirically driven efforts to answer the Good Job question for active management have collapsed under the chaotic gravitational pull of The Three-Body Problem.

In exactly the same way that Quality has been absolutely useless as an investment factor for the past eight and a half years, so have our traditional measurements of active manager skill.

The orange line in the chart below is the S&P 500 Index from 1998 to today. The white line and blue-shaded area is the HFRX Global Hedge Fund Index divided by the S&P 500 Index. It represents the relative underperformance or outperformance of hedge funds versus the S&P 500, and today we are at all-time underperformance lows. There is no convexity here! At least not in the aggregate. It skipped town in March 2009, just as the Central Bank Brigade rode in to save the day.

Managers who used to “capture” more upside than downside don’t. Managers who used to demonstrate convexity in their results don’t. They still have lots of stories to tell you about how they manage gross and net exposure, lots of stories to tell you about volatility and risk management, and lots of stories to tell you about thematic opportunities. Most still express a great deal of pride in their investment process.

I’m not saying that these “proprietary processes” will never work again. I’m not saying that they’re not working now. I’m saying that if they’re working, they’re working very very faintly. So faintly that you have to believe in the story to stay the course, because it’s sure not in the aggregate results. I’m saying that the processes and the skills and the performance convexity of professional active investors are swamped by the gravitational pull of $20 TRILLION of central bank balance sheets, as are the traditional tools we’ve used to measure all that. Because that’s the point of the Three-Body Problem – any algorithmic understanding of the system will fail to predict what’s next.

So what’s to be done? Do we just give up trying to answer the Good Job question? If our evaluative tools for active managers are non-predictive, do we just throw ourselves onto the waves of the S&P 500 and hope for the best? Because that’s what a lot of investors are doing, including giant pension funds who should know better, even though doing so is an active management decision of the first order!

Here’s the thing. Yes, It’s more difficult than ever to answer the Good Job question regarding active investment management. It’s also never been more important.

Because while I have no way to predict what’s next in the Three-Body System, I can tell you with absolute certainty that there IS a next, and it will NOT look like now.

Because you ARE the active manager when you select this passively managed fund over that passively managed fund, and you are not as good of an active manager as you think you are.

As wonderful as it would be for investors to style themselves as baseball general managers, poring over advanced performance statistics to pick this or that great fund manager in some sabermetric nirvana, that’s just not in the cards. We have to find a better way, a way to answer the Good Job question in a Three-Body system. Because we’re not getting away from active management even if we wanted to.

Our answer, I think, is to go back to first principles, to go back to the code of the Good Dog. The answer, I think, is in convexity, but not in the mathematical over-scientificized cartoon of the word.

The answer, I think, is in convexity as a philosophy.

Convexity as a philosophy is about identifying what you are particularly good at, and then executing on THAT. It’s the key to unlocking a much more stable notion of identity — a Good Dog’s notion of identity. Good Dogs know what they’re good at, and I don’t need to calculate a Sortino ratio to know if they’re doing a Good Job.

We can do the same with our evaluation of active managers. We can tell when an active manager is doing a Good Job. We can see it in her demeanor, we can see it in her temperament, we can see it in her bravery, both personally and professionally. Every Good Dog is a Brave Dog. It’s the same with investment managers. We can see it in her humility — the virtuous opposite of sinful pride. We can see it in her sense of shame when a behavior is not up to snuff. Not identity, behavior. There’s no shame in identity. Ever.

There’s a sine qua non for adopting convexity as a philosophy in evaluating active managers, and it’s as simple as it is difficult: courage, both personally and professionally. We’ve got to be Brave Dogs, too.

To be clear, the behavioral attributes associated with a Good Dog’s notion of a Good Job are a necessary condition for approving an active manager, not a sufficient condition. Sam the Sheltie does a Good Job, too, but I wouldn’t exactly recommend an accomplished squirrel herder as a must-have addition to your farm. Even Maggie the German Shepherd, who does a Good Job of protecting the farm and is a player everyone would want on their team, has “regimes” where her above-replacement performance vanishes. I’ll put it this way … she apparently dislikes chickens almost as much as I do, such that if you’re a fox and you want to chow down on a free range hen or two, picnic-style in the middle of a grassy field while Maggie sits there and watches you eat … well, come on over. And that gets me to the second sine qua non of adopting convexity as a philosophy in our manager selection — we must have the process and the fortitude to scale our active risk allocations up and down based on what is working, including the ability to take risk completely away from our managers. Maggie is a VERY Good Dog. But when the chickens are loose her risk allocation here at the farm goes to zero. We find protection somewhere else.

Convexity as a philosophy is also at the heart of how we improve ourselves and our children as citizens.

Always be yourself. Unless you can be Batman. Then always be Batman.

It’s maybe the funniest movie line I know. Why is this funny? Because we have made a political and social fetish out of identity, out of the New Commandment to ALWAYS BE YOURSELF. Unless you can be Batman.

At the same time, we’ve attached pride and shame to identity, rather than to behavior where they belong, training ourselves and our children to be absurdly self-assured and prideful, and yet existentially ashamed all at the same time. ALWAYS BE YOURSELF is the most powerful story we tell ourselves. And the most dangerous if attached to pride and shame wrongly understood.

We can tell ourselves a new story. A story, dear Brutus, where the fault is not in our stars, but in ourselves. As is the achievement. As is the honor.

Find your pack. Here and here and here are some ideas on how to do that. And then do a Good Job with your service to the pack, no matter how big, no matter how small. You’ll figure it out.

Every dog needs a job to make sense of its place in the world. So does every human.

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Is Volatility Back?

On this special episode of the Epsilon Theory podcast, we share an excerpt from a conference call we recorded on February 13 discussing our thoughts on the market selloff earlier in the month. You’ll hear from Christopher Guptill, co-CEO and chief investment officer at Broadmark Asset Management and Dr. Ben Hunt, author of Epsilon Theory.


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