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 Fundamentals Are Sound

Cobb: What do you want?
Saito: Inception. Is it possible?
Arthur: Of course not.
Saito:  If you can steal an idea, why can’t you plant one there instead?
Arthur: Okay, this is me, planting an idea in your mind. I say: don’t think about elephants. What are you thinking about?
Saito: Elephants?
Arthur: Right, but it’s not your idea. The dreamer can always remember the genesis of the idea. True inspiration is impossible to fake.
Cobb: No, it’s not.
— Inception (2010)

Cobb is right. It’s not impossible. When we are deep in our element as analysts of economies and issuers, we are supremely confident. We know the critical assumptions in our portfolios, models and projections cold. But when we apply ourselves to assessing what others’ views may be, with understanding what is ‘priced in’, we begin to doubt. Deeper into the hole, where we grapple with what other price-setters are treating as the consensus of yet other investors, our models break. More importantly, our confidence evaporates. Our vulnerability to those stories explodes. So how do you feel about your positioning today?

— Randall Munroe, “Night Sky”, XKCD

The dream of retreat to a world where we can win by understanding what’s really happening underneath the hood is a siren call. We remember the first time we figured out how to identify potentially unpriced optionality in a business model. When we absolutely pegged that fatally flawed assumption in the new management team’s cost reduction plan that no one else saw. You know. The good ol’ days.

There are brief flashes in which central bank or inflation narratives, fiscal policy angles, next-thing rotation pitches from the sell-side and “cash coming off the sidelines” think pieces seem to fade to the background and we see daylight again. And sure enough, it’s another head fake. That long-awaited rotation back to value unwinds after two or three sessions, and we start grumbling about “algos” and passive investors and volatility-targeted strategies and extravagant tech multiples and cryptocurrency excesses and are there mountain lions around here?

Arthur: So, once we’ve made the plant, how do we go out? Hope you have something more elegant in mind than shooting me in the head.
Cobb: A kick.
Ariadne: What’s a kick?
Eames: This, Ariadne, would be a kick.
— Inception (2010)

It’s easy, if a bit heartbreaking at times, to move on from a fundamental investment thesis. Most good ones have a list of sell disciplines describing exactly how they fail, anyway. It’s slightly tougher to change our perspectives on how other investors are likely to behave. But once we acknowledge that everybody knows that everybody knows something, it is almost impossible to know what sort of evidence we can rely on to reject it. That has a lot of important implications, but one more than any other: Narratives tend to influence prices far, far longer than we expect.


“I don’t know half of you half as well as I should like; and I like less than half of you half as well as you deserve.”

This was unexpected and rather difficult. There was some scattered clapping, but most of them were trying to work it out and see if it came out to a compliment.

— J.R.R. Tolkien, The Lord of the Rings, Speech from Bilbo’s 111th Birthday Party

From time to time I speak to and run seminars with students at colleges in Texas, usually with business school students or participants in student-run investment funds. Like any instructor, I have a go-to challenge question. It is a question to spark inquiry, to raise a skeptical eye to the priors with which we approach many of the fundamental questions of investing. It’s also an asshole question. Because, like most instructors, I am an asshole.

“What”, I ask the students, “is the most important single driver of today’s price of ExxonMobil stock?”

It’s the worst kind of question, because I’m obviously asking it for the sole purpose of telling everyone they’re wrong. Still, it’s fun to watch the arguments between very bright students. “Value” is always among the first two or three responses. “Well, what do you mean by value?” I prod, usually yielding a response about multiples. “Value may influence your returns going forward, but a multiple IS the price, so that can’t be it,” a student usually responds, before the discussion descends into bickering and debate over fundamental data which may drive pricing. Earnings? EBITDA? Cash Flow? Oil Price? No, future expectations for oil prices!

It’s yesterday’s price, I tell them.

It feels like a throwaway, the sort of dad joke enjoyed only by middle-aged professionals in tweed playing at being a professor. But for investors trained by schools, banks or long-only shops in the various churches of fundamental stock-picking, it is a necessary and important reminder. Most approaches to security analysis inherently view each day as a tabula rasa. We wake up and decide to evaluate all available information about companies and their securities, determine that the appropriate price either has or hasn’t changed and send our updated limits to the desk. Except that isn’t how this works at all. Like almost anything else in public and political spheres, prices are always determined around the margin.

Consider the tax cut debate the U.S. just endured, and the language used by politicians and media to discuss the issue. Each tax plan is presented as either a cut or a hike, and good or evil on that basis (or on how said cut or hike disproportionately favors one class or another). Did you hear a single analyst discuss what absolute level for a particular income category would generate the most revenue? What would be the fairest on either an objective or subjective basis? Stimulate the most consumption or investment? A politician who never said a word about a static 20% tax rate might be furious with the idea of taking it from 15% to 16%, for example. This is true across every kind of policy issue, and across budget issues for every corporation and household in America. We rarely, if ever, discuss and debate policy issues or investment decisions on an absolute, aggregated basis. Our evaluations are always, always, always on the margin.

This is doubly true for financial markets, where these marginal determinations are made daily. That means that exogenously influenced, random and economically sensible drivers of variations in prices, and, most importantly, the narratives built around them, all become part of the accepted structure of a security’s price going into the next trading day. Strong efficient-markets hypothesis adherents would say that this is wrong, and that any trading not reflective of currently available information would be quickly stamped out and the price returned to an appropriate representation of all available facts (whatever those are). Strong EMH adherents are also too busy being served negative calorie donuts glazed with a 1937 Chateau D’Yquem reduction from a polished unicorn’s horn, so be grateful that the rest of us can have a serious conversation about investing in peace.

That said, the basic idea isn’t wrong, is it? Over enough time, securities prices can diverge enough from the price of comparable investments in ways that influence enough investors to abandon the idea that the accumulated information contained in yesterday’s price is right. EMH assumes that this happens insanely quickly, and the rest of us sane people recognize that it takes some time. In fact, I’d say the world today largely falls into three camps: (1) rare EMH holdovers in academia, (2) kinda-sorta efficient market folks that believe information just propagates slowly, and sentiment…er..something something Brownian motion, and (3) those who believe that prices reflect a shifting mix of fundamental financial data, investor preferences, objective functions and attempts to guess the preferences and objective functions of others.

Some would characterize these differences as a simple question of time horizon.

But are they?

Dick Thaler’s Party Trick

If you’ve ever had a professional dinner with Dick Thaler (maybe personal dinners with him go this way too, but I have never been invited), you’ve probably heard him give his telling of the Keynesian Beauty Contest that Ben has written about several times.

In Keynes’s version of the contest, you win by correctly picking the woman from a series of pictures in a newspaper that you think will be voted as the most beautiful by everyone participating. First-degree thinking, in Keynes’s parlance, is to pick the woman you believe is the most beautiful. Second-degree thinking is picking the woman that you believe the other participants will believe is the most beautiful. Degrees above that require thinking less about beauty or what others will think is beautiful, and more about what the contestants are likely to think about one another. There is no neat solution to this illustration, of course, because we don’t really know what others find beautiful. We are even less certain about what others will believe about their peers’ ability to judge beauty. This uncertainty makes it particularly apt as an analogy to the practice of investment management, but Thaler’s version has the added feature of applying simple mathematics in the place of subjective determinations. That’s useful because it allows us to quantify consistent behavioral tendencies in the game.

Thaler’s version is a little different, and goes something like this:

Everyone at the table must pick a number between 0 and 100. The winner will be the person who chooses the number that is closest to 2/3 of the average.

0th Degree 50.00
1st Degree 33.33
2nd Degree 22.22
3rd Degree 14.81
4th Degree 9.88
5th Degree 6.58
6th Degree 4.39
7th Degree 2.93
8th Degree 1.95
9th Degree 1.30
10th Degree 0.87
11th Degree 0.58
12th Degree 0.39
13th Degree 0.26
14th Degree 0.17
15th Degree 0.11
16th Degree 0.08
17th Degree 0.05
18th Degree 0.03
19th Degree 0.02
20th Degree 0.02
21st Degree 0.01
22nd Degree 0.01
23rd Degree 0.00

Because there are multiple calculations that a person might ignore or fail at, I’m taking some liberty of interpretation, but I think the first-degree answer to this question is 33. The player will realize that he has no information to guide his first step within the 0-to-100 range, so he concludes that the average of 50 is the only sensible place to start. We’ll give him credit for realizing that he must be 2/3 of that number, and thus arrives at 33.

Unlike Keynes’s contest, Thaler’s also has a ‘real’ solution. You’ve seen it replicated (albeit in a flawed format that isn’t Pareto-optimal) in the movie A Beautiful Mind. You know, the bar scene with the blonde? Also, why is every example of game theory a creepy story about old male economists picking beautiful women? Anyway, Thaler’s problem has a single solution that is a Nash Equilibrium: zero. If everyone can calculate 33, then surely they’ll figure out 22, 15, 10, and all the way down. By the time you’re playing 23rd-Degree Dinner with Dick, you’ve already gotten down to two digits of zero. A computer would tell you this instantly. But then, a computer would also assume that all the people playing understood AND remembered limits from their first week of calculus. There’s no shame if you don’t. I mean, there is, but it’s politer to say that there isn’t.

When we have played this game with clients, audiences, classrooms and colleagues, my experience is that the winning guess consistently falls between 15 and 22, usually closer to 22. I expect, but don’t know, that Thaler would give you a similar value.

What does this mean? Or at the least, what does it imply?

First, it should be obvious that every sufficiently large iteration of this game will include some people who don’t understand it at all. Some won’t have a natural grasp of expected value and won’t start from 50, but from some other number they expect will be popular. These people will tend to increase the average winning point total somewhat, since they aren’t following the averaging and iterative mathematical process that forces all the numbers downward. If you want some real-world examples of what this person looks like, Google “Bitcoin Price Target.”

The second group of participants — usually a small group — are those who understand the basic principles of the problem but think that everyone else is a moron who doesn’t. They bet on 33. These are your first-degree thinkers. This is basically every graduate of every business school in the world until he has to manage an actual P&L for the first time.

The third group of participants — usually larger than the second — understand the math all too well, and assume that everyone else can, too. They provide the real solution of zero, or if they have a modicum of wisdom to pair with that beautiful brain and neckbeard combo, add a couple points to catch the stragglers who are too slow to catch on. They drag down the winning score. Ben wrote about these people earlier this week in Too Clever by Half. They’re the coyotes.

The bulk of participants, however, answer between 22 and 33. They understand that the principle is to recognize that you want to be 2/3 of the answer everyone will guess. Since the most basic answer without getting into guessing others’ behavior is 33, they go one layer deeper and judge it to be sufficient. This is second-degree Keynes. In this way, Keynes’s example is much more like financial markets, because it incorporates compounding uncertainty at every level. We know what we think. We have a pretty good guess at what others think. But building a mental model of what others think others will think is an order of magnitude more challenging, because it requires perspective not only on the underlying — a woman’s beauty — but on others’ prejudices and biases about the other judges!

Playing a third-degree game is too daunting a task to consider for most, and so curiously, even in the mathematically deterministic version of the game that has a Nash equilibrial ‘correct’ answer, the takeaway is the same as in the beauty contest: you usually win by guessing that others are playing a mix of one to two degrees of the Common Knowledge Game. Some people buy and sell on fundamentals, and some on how they think people will react to them.

But as Ben discussed in The Three-Body Problem, we think that this is changing. We think it has changed. We think that the violent expansion of communications policy by global central banks and the accompanying expansion of always-on media has meant more participants shifting to third-degree thinking. The reason we talk about Narrative so much is that we find it a useful meta-expression of and proxy for exactly the kind of mental model a third-degree participant must construct. When we refer to Narrative, we mean it as an expression of what everyone knows that everyone knows.

If you accept that Narrative is exerting greater influence on asset prices, you will lose if you play the traditional strategy. You will lose if you assume that others are playing one- or two-degree strategies.

The Fundamentals are Sound

So what did everybody know that everybody knows over the last couple weeks? And when you looked at the game unfolding, what strategy were you playing?

I’ve written about the silliness of trying to ascribe specific causes to market action, but I’m willing to stand on this as probably, approximately correct. Let me tell you what I think happened. Then let me tell you what I think other people think happened. And if you’ll bear with me, let me tell you what I think markets will ultimately decide everybody knows that everybody knows happened.

I think that there was already an emerging Inflation Narrative coming into 2018, although not much actual inflation to show for it. Ben has written credibly about this on several occasions. Torsten Slok at Deutsche Bank put out a nice chart highlighting breakevens leading into the events of last week (don’t get too cynical about the forced perspective of sell-side axis ninjas, please).

Source: Deutsche Bank 2018

I think that a roaring start for risk assets in early January gave tactical allocators, macro shops and hedge funds an opportunity to bank early returns (and incentive fees) by taking off risk. I say “think,” but “know” would be nearer the truth. I have the receipts, as it were.

I think these funds thought that the emerging Inflation Narrative warranted pulling back some of that risk not just in risky assets but across their book, including in rates (sovereign debt). I think this accelerated and compounded confidence in the Inflation Narrative.

I think that many market participants thought that the focal point of the event through the end of January was not inflationary expectations, but frothiness of equity markets. I think they thought this because that is where their focus had been as a result of the remarkable returns of 2017 and 2018 and the length of time since the last S&P decline of any significance. I think media bears this out, but it’s story, not fact.

I think that the resulting spike in volatility on February 2nd and into February 5th confirmed and exacerbated what most people thought about the proximate cause of the correction. As a result, the weight of market behaviors shifted from response to a rate shock or rise in inflationary expectations to a classic risk-off trade.

I think that with the relaxation in volatility since the events of late January into February 5th many investors think that the event was an equity and volatility event. A moment of irrational pessimism brought on by blow-ups in vol-selling and vol-targeting.

I think that more large institutional allocators today than at any point since the early 1980s know that their peers know that inflation, if and when it comes, will fundamentally change how they must build, allocate and manage portfolios.

I think that instead of focusing on this, other investors are comforting themselves with an age-old mantra: “The Fundamentals are Sound.”

“The Fundamentals are Sound” on the U.S. economy. On stocks. This was just a correction that we needed after things got a little frothy. It was short-term sentiment. It was risk parity and vol-targeting funds driving markets lower for no reason after a jump in vol. If you loved the Dow at 26,000, you ought to really love it now.

“The Fundamentals are Sound” on cryptocurrencies. The price action doesn’t matter. It’s the technology that matters. As long as you research and understand the technology and what it has the potential to do to overcome overcentralized, centrally planned banking and transactional systems, you won’t lose. All the smartest people, all the people who have really done their research on this technology, the people who get it, are not sweating these price moves.

Amazing. Every word of what I just said is wrong.

Well, it isn’t that the statement isn’t factual. It may be.

It’s that we have no idea if and when it is going to matter. You can argue all you want that it’s a random walk to a known destination, but as the walk gets longer, that distinction becomes less meaningful.

Sure, it serves a useful purpose to use this language with some clients, in that it keeps them from taking rash actions to change their asset allocation without a real basis for doing so. If you’re a financial advisor and telling your client this fact helps to keep them from dumping all of their risky assets, then you have my blessing and more. But we must be honest with ourselves. If we believe that “Fundamentals are Sound” is necessarily a relevant statement after a correction like this, we must acknowledge that it also carries two embedded assumptions that are so extreme that it’s worth taking a step back to truly unpack them.

  1. It requires us to believe that yesterday’s price was the right one.
  2. It requires us to believe that non-fundamental influences on price (second-degree or third-degree issues) have not changed either, or that they will revert soon.

The silliness of the first ought to be self-explanatory. The “Fundamentals are Sound” relative to what? Relative to how they manifested in prices yesterday? Last week? How they would have manifested over the last 30 years? Absolute pronouncements of appropriate valuation and marginal thinking about price changes are a risky combination.

Understanding the second is a bit nearer to my purpose here. After events like this, it is appropriate to ask: do I think that the decision-making processes of other investors have changed? Do I think that those investors’ views of other investors’ positioning and decision-making has changed? Furthermore, do I think that any of the broad Narratives reflective of how investors are responding to one another have changed, or that they have strengthened or weakened?

Now, my confidence about the mechanics I’m describing here is high, but I don’t judge my ability to evaluate using these mechanics to be higher than any of yours. In fact, many of you are probably shrewder investors than I. But I think a lot of investors will be coming out of the last two weeks saying that nothing has changed, or focusing on how long it will take to bounce back from a couple weeks of fear-driven market behavior. I think that may be a mistake. Why?

Because it takes much longer to unwind third-degree thinking. Narratives last.

Think about the Keynes game again. Imagine that I drew a feature on one of the men or women from the beauty contest to make them most distinctive, and perhaps more polarizing. Let’s say a diamond nose stud, or a face tattoo. How long does it take you to figure out how your first-degree thinking about the game changes? Second? Third? How much more data would you need to conclude that there was a change, and how would that differ for thinking at each degree? How many more events to give you insight into responses? There’s a reason Narrative-driven markets last far longer than we expect them to. Time passes more slowly in a dream-within-a-dream than it does in a single dream alone.

Again, I think investors who look at risky or speculative assets and say, “I like this just as much, and I don’t really see why it should have gone down this much,” may well be right. I think that they’d be justified in having some expectation that volatility will fall, and that some of the correction would be recaptured over coming weeks and months as people forgot why they felt the need to go risk-off for three days in February.

But I think it’s not the Friday and Monday sell-offs and whether they were “justified” that will end up mattering. It’s what happened the week before that we should be paying attention to.

If the events of that week did anything, it was to further convince me that market participants have bought into the Inflation Narrative — even well in advance of strong data on actual inflation. So while I don’t have any valuable short-term positioning thoughts (and I never will, so don’t ask), I think that the surprising strength and persistence of this Narrative — and Narratives in general — has real implications for us as asset allocators and alpha-seekers. Even alpha-seekers in the Craftsmanship Alpha mode.

We all talk a big game about diversification, and rightfully so. Look, I wrote a piece that called it the second most important thing in investing. But how big a part do TIPS (Treasury Inflation Protection Securities) play in your portfolios? Commodities? Other real assets? Many of these have been such abominable relative investment opportunities over the last 35 years that they frequently aren’t even considered as asset classes. In some generous cases they’re called alternatives or diversifiers, but few investors today consider them in the same context as stocks and bonds.

As the Inflation Narrative heats up, I believe asset allocators will have to seriously evaluate the extent to which this tacit assumption is still appropriate. They will have to grapple with whether nominal bonds have the same crisis risk aversion and diversification characteristics that they have over the last couple decades. But here’s the rub. They will have to do so in a prospective, long-term way that may not have the benefit of a recent high-confidence in-sample and out-of-sample period for their backtests. Are you ready to tell your committees that you think sovereign bonds may not be the same safe asset in certain types of major equity drawdowns? Are you ready to suggest what to do about that? Are you prepared to stake your career on it?

It’s not uncharted territory. There is nothing new under the sun, after all. But it’s territory that few of us have trod during our careers. And if you’re staring at the ground, trying to convince yourself that it’s solid before every step, you may be missing where we’re headed.

We have to be humble, too. If you’ve been talking about an emerging Inflation Narrative for a few months, we know enough about behavioral biases to recognize that you’ll start seeing ‘evidence’ of it everywhere you look. But that’s kind of how Narrative works in the first place, y’all. In the end, we don’t have all the answers, but we do think we know how to think about these questions.

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