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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Too Clever By Half


The smartest animals on my farm aren’t my bees (although they possess the genius of the algorithm). It’s not the horses or the goats or even the dogs. The barn cat is pretty smart, but only in fairly limited circumstances, and the house cats are useless. Obviously it’s not the sheep or the chickens. Nope, the smartest animals on my farm aren’t really on my farm at all. They’re the coyotes who live in the woods.

My favorite example? We have a really big invisible fence for the dogs … covers about five acres. Yes, my farm is a great place to be a dog. For those of you who aren’t familiar with the technology of the invisible fence, it’s a buried wire that transmits a signal to a receiver placed on your dog’s collar. When the dog gets close to the wire, the receiver starts to beep, and when the dog gets all the way to the “fence” boundary, the receiver generates a small electric zap. I know, I know … it’s negative reinforcement and it’s a shock collar and all that. Don’t care. It’s fantastic for us and our dogs. But whether it’s a smart dog like Maggie the German Shepherd or a … shall we say … “special” dog like Sam the Sheltie, after a few weeks (Maggie) or a few hours (Sam) they will forget where the fence exists if they stop wearing the collar.

Not so the coyotes.

The coyotes know *exactly* where the invisible fence begins and ends, without the benefit of *ever* wearing a shock collar. How do I know? Because they intentionally leave their scat on their side of the invisible fence, creating a demilitarized zone as precise and as well-observed as anything on the Korean peninsula. Occasionally a coyote will try to test our dogs by leaving its scat juuusst over the line on our side of the DMZ. Our dogs, of course, just blithely ignore the provocation, not even knowing that they’re being challenged. My dogs are the Roadrunner in some real-life Looney Tunes competition with Wile E. Coyote, super-genius. The coyotes are scheming; my dogs have no idea what scheming is.

I feel bad for the real-life coyotes in exactly the same way that 7-year-old me felt bad for Wile E. Coyote and 30-year-old me felt bad for The Brain (not a coyote, of course, but still). They put SO MUCH EFFORT into their plans and machinations for taking over the world, and it all comes to naught in a world of Roadrunners, Pinkys, and dogs like my Sam the Sheltie.
I see myself in the coyotes. So do most people reading this note, I bet.

For the canonical compilation of all Pinky and the Brain “pondering” quotes, see Richard Watanabe’s magisterial site.

The truth is that domestication makes any animal dumb. You name the species — dogs, cats, cows, horses, sheep, pigs — human selection on “tameness” for thousands of years accumulates a wide array of traits, including floppier ears, shorter snouts, hair color variability and the like, most likely based on more basic inherited alterations in certain stem cell and stress hormone production patterns (see Domesticated: Evolution in a Man-Made World, by Richard Francis, for a great read on all this). Different species show these external traits to different degrees. But the trait that ALL domesticated species demonstrate relative to their wild species is a smaller brain. I’d bet it’s happening with humans, too, but that’s just an observation for another day.

Unfortunately, coyotes are too smart for their own good. They are, to use the wonderful Brit phrase, too clever by half. They are, to use a post-modern, TV reality show lingo, not good in the meta-game. And the meta-game has turned against the coyotes with a vengeance.

Case in point — in our pre-farm life, where we had a yard like any other yard and were part of a neighborhood like any other neighborhood, we still had run-ins with coyotes. There were three or four of them roaming around one fall, coming in from the local nature preserve, and it became something of an issue in our small town. Warnings went out on mom chat groups not to let your small children play outside alone, much less your small dog or cat (yes, this was back in the day when it was not a blatant act of animal cruelty in Fairfield County, Connecticut to let your house cat go outside when it wished). Fortunately, clear instructions were provided through various channels as to how to protect your family.

Don’t yell at the coyotes. Half fill an empty coffee can with loose change and shake it at them. This will frighten them and they will run off.

Again, this is Fairfield County, Connecticut, where even owning a BB gun is enough to earn a lifetime ban from any play dates for your kids. It’s a far cry from growing up in Alabama like me or Texas like my wife, but when in Rome …

A few afternoons later the coyotes came wandering around our yard. We had (very) small kids at the time. So my wife dutifully brought out the coffee can she had prepared, and rushed out into the yard to confront the coyotes, shaking the coffee can like a madwoman. At which point the lead coyote, a female we think, sloooowly looked up and just stared at my wife. It wasn’t scared. It wasn’t frightened. It recognized immediately that there was absolutely zero danger posed by this human female gesticulating wildly and making a bizarre clanking sound with her hands. The message from that coyote’s stare was clear — is that all you got? Really? Almost derisively, the lead coyote sloooowly turned around and sauntered back towards the woods, leading the others away.

It was an alpha move. Smart, cool, totally in command. I’m leaving because I want to, at my own speed, and only because you’re annoying me with that ridiculous noise, not because I’m scared.

It was also a really dumb move for the meta-game.

What’s the meta-game? It’s the game of games. It’s the larger social game where this little game of aggression and dominance with my wife played out. The meta-game for coyotes is how to stay alive in pockets of dense woods while surrounded by increasingly domesticated humans who are increasingly fearful of anything and everything that is actually untamed and natural. A strategy of Skirmish and scheming feints and counter-feints is something that coyotes are really good at. They will “win” every time they play this individual mini-game with domesticated dogs and domesticated humans shaking coffee cans half-filled with coins. But it is a suicidal strategy for the meta-game. As in literally suicidal. As in you will be killed by the animal control officer who HATES the idea of taking you out but is REQUIRED to do it because there’s an angry posse of families who just moved into town from the city and are AGHAST at the notion that they share these woods with creatures that actually have fangs and claws.

The smartest play for coyotes in the meta-game is never to Skirmish with humans. Never. And if you find yourself in a Skirmish-with-Humans game, then the smart play is to act scared, to run away at top speed from a jangling coffee can. But no, coyotes are too clever by half, plenty smart enough to understand and master the reality of their immediate situation, but nowhere near smart enough to understand or withstand the reality of their larger situation. It’s their nature to play the scheming mini-game. They can’t help themselves. And that’s why the coyotes always lose. It’s always the meta-game that gets you.

Okay, Ben, entertaining as ever, but where are you going with all this?

Almost there. Before I pull this charming discussion of too clever by half coyotes back into the real world of markets, there’s one other (supposedly) clever, non-domesticated animal I need to introduce into this story. That’s the raccoon.

Coyotes have a roguish charm and bring something interesting to the world with their independence and scheming. Raccoons are simply criminals. And they’re not that smart. I’d put our barn cat up against a raccoon any day on any sort of cognitive test. We think raccoons are clever because they have those anthropomorphic paws and those cute little masks and even a Marvel superhero with its own toy line, but please. Raccoons are takers, not schemers. They’re killers, often for the sheer hell of it. Raccoons steal and kill way beyond what they need, and they do so in a totally wanton, non-clever way. I hate raccoons.

When they push their scheming and stealing too far, coyotes and raccoons ALWAYS end up getting killed by the farmer — regretfully in the case of coyotes, remorselessly in the case of raccoons. It’s not a cute Looney Tunes death, either. There’s no little puff of smoke and immediate reincarnation for these Wile E. Coyotes and Rocket Raccoons. Just blood and sadness.

That’s true on the farm and it’s true in the real world, too. And that’s how we pull this allegory together.

Every truly disruptive discovery or innovation in history is the work of coyotes. It’s always the non-domesticated schemers who come up with the Idea That Changes Things. We all know the type. Many of the readers of this note ARE the type.

Financial innovation is no exception. And this is Reason #1 why financial innovation ALWAYS ends in tears, because coyotes are too clever by half. They figure out a brilliant way to win at the mini-game that they’re immersed in, and they ignore the meta-game. Eventually the meta-game blows up on them, and they’re toast.

Reason #2? Financial innovation, more than any other sort of innovation, attracts the raccoons — con men and hucksters at best, outright thieves at worst. They infest financial innovation. And they can’t control themselves, so they always push it too far. They’re never content with stealing a little. Or even a lot. No, raccoons want it ALL.

Example, please.

Financial innovation is always and in all ways one of two things — a new way of securitizing something or a new way of leveraging something.

Securitization is a ten-dollar word that means associating something in the real world (a cash flow from a debt, an ownership interest in a company, a deed on a property, a distributed ledger mathematical calculation, etc.) with a piece of paper that can be bought and sold separately from that real world thing.

Leverage is a ten-dollar word that means borrowed money.

That’s it. There’s nothing new under the sun. Finding new ways to trade things (securitization) or new ways to borrow money on things (leverage) is what financial innovation is all about, and there are vast riches awaiting the clever coyotes who can come up with a useful scheme on either.

The biggest market disasters happen when both leverage and securitization get mixed up with the same clever scheme, as when new ways of leveraging and securitizing U.S. residential mortgages were developed in 2001, resulting in the creation of a $10 trillion asset class that utterly collapsed during the Great Financial Crisis. There were a lot of coyotes involved in so gargantuan an Idea That Changes Things, but most illustrative for these purposes is the Gaussian Copula formula published by David Li in 2000, the “technology” which allowed the securitization of pretty much any mortgage portfolio (prior to this most securitization was limited to “conforming” mortgages securitized by Fannie Mae and other government-sponsored mortgage agencies) and also the leveraging of those securities through tranching (splitting up the security into still more securities, each of which can be used as collateral for more borrowing, particularly those tranches with higher credit ratings). I wrote a bit about the Gaussian Copula in “Magical Thinking”, and if you want to learn more you can’t do better than  Felix Salmon’s 2009 Wired magazine article — “The Formula That Broke Wall Street” — still my all-time favorite piece of financial market journalism.

The formula doesn’t look like much, does it? But this little equation made billions of dollars in profits for Wall Street through hundreds of clever coyote schemes. More than a few raccoons got involved along the way. And then it broke the world in 2008.

It’s what I’ll call “coyote-math”. The math behind blockchain and Bitcoin the Gaussian Copula and non-agency residential mortgage-backed securities (RMBS) is undeniable. It is a mathematical certainty that these securities “work”. Unless, of course, you have a government-led chilling effect on exchanges and network transactions a nationwide decline in U.S. home prices, in which case Bitcoin non-agency RMBS doesn’t work at all.

So what will does the aftermath of this classic example of financial innovation gone awry look like?

Blockchain The Gaussian Copula is still around. These things don’t get un-invented, and it’s still a very useful piece of code for certain applications. The truth about blockchain the Gaussian Copula is that it’s an Idea That Changes Things In a Modest Way, not an Idea That Changes Everything. It’s a modern algorithmic twist on letters of credit portfolio risk, and there are a few interesting uses for that. Just a few, but that’s okay. That’s still important. Just not as important as HODLers Wall Street thought it was.

As for the primary financial application that blockchain the Gaussian Copula spawned, Bitcoin non-agency RMBS is still around, too. The securitization of distributed ledger calculations non-conforming mortgages is something that market participants still want and still trade. It will NEVER be a $10 trillion asset class again, because the inherent flaws of this security have been well revealed. Turns out that Bitcoin a AAA-rated tranche of Alt-A mortgages wasn’t the store of value that coyote-math “proved” it was, to the detriment of individual institutional investors who put a significant portion of their portfolio into these securities, and to the ruin of those who used leverage to acquire these securities.

Many of the coyotes involved with this classic example of financial innovation gone awry are (professionally) dead. At the very least careers were permanently derailed, and entire coyote institutions, like Bear Stearns, were taken out into the street and shot in the head by animal control officers were merged into healthier financial institutions by government regulators as an example to other coyote institutions as a necessary measure for systemic stability. I miss Bear Stearns. The world is a poorer place for Bear Stearns not being in it.

Surprisingly few of the raccoons involved are (professionally) dead. In fact, more than a few of the financial hucksters involved with the run-up to the Great Financial Crisis are back to their old tricks with cryptocurrencies whatever the latest coyote innovation might be. This makes me VERY angry, and probably colors my view on blockchain financial innovation more generally. I wouldn’t miss the raccoons for a second if the animal control officers took them out, but somehow they never do.

And that brings me to what is personally the most frustrating aspect of all this. The inevitable result of financial innovation gone awry, which it ALWAYS does, is that it ALWAYS ends up empowering the State. And not just empowering the State, but empowering the State in a specific way, where it becomes harder and harder to be a non-domesticated, clever coyote, even as the non-clever, criminal raccoons flourish.

That’s not an accident. The State doesn’t really care about the raccoons, precisely because they’re NOT clever. The State — particularly the Nudging State — cares very much about co-opting an Idea That Changes Things, whether it changes things in a modest way or massively. It cares very much about coyote population control.

When coyotes play the Skirmish game, that’s all the excuse the State needs to come swooping in. And that’s exactly what is happening with Bitcoin what happened with non-agency RMBS.

What’s the alternative to playing Skirmish in the meta-game?

It’s this: to be an arborist.

It’s this: to be as wise as serpents and as harmless as doves.

Coyotes can change the world. Coyotes WILL change the world. But not if they misplay the meta-game. Not if they hang out with raccoons. Not if they fetishize ANY financial instrument as an intrinsic aspect of a commitment to liberty and justice for all. Because it’s not.

Render unto Caesar the things that are Caesar’s. Wise words 2,000 years ago. Wise words today.

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