The Road to Tannu Tuva, Pt. 2

Source: Texas Monthly, Credit Wyatt McSpadden

Le vrai est trop simple, il faut y arriver toujours par le compliqué.

The truth is too simple: one must always get there by a complicated route.

Letter from George Sand to Armand Barbés (1867)

We kicked off this series with a bold objective: learning how to live full of both scientific skepticism and the wonder of discovery. With clear eyes and full hearts. We will do this best, I wrote, by identifying and rooting out sources of bias and systematic error wherever we find them in our thinking and research.

This installment was going to be about how we permit the intrusion of bias into the very questions we ask. I was halfway through writing it when I realized that there was still more we needed to talk about first. Because whether our answers become biased in our writing down of questions, in our thinking very hard about the answer, or in our writing down that answer, the sources of the systematic errors which cripple our thinking are themselves often predictable and consistent.

We’re on a journey of discovery about the nature of discovery, you and I, and we need to make a detour.

Careful, though, or you’ll miss the turn.

A little more than an hour after you leave Austin, your GPS will tell you to turn right. A split-second later, your brain will retort, ‘There is no way that rough, barely two lane, curbless road with a double-wide on the corner is ‘Main Street.’ Sorry, brain. It is…or, was. It’s a small town. It’s also Saturday, which means that the cattle auction is taking place at the livestock commission. If you hear mooing, you will know you went too far. The beef you’re looking for is of a different sort, and once you have righted yourself on Main Street, you aren’t likely to miss it. Even at 7:45 AM – yes, sorry, did I mention that it’s basically open for four hours on Saturday morning? – the double-parked cars and the line of weary travelers bearing Buc-ee’s growlers full of coffee shall be a sign unto you.

We have long since come to expect that our best regional cuisine will often come from humble, out-of-the-way places. There’s a reason the Michael Scott bit about Sbarro’s in The Office goes over so well. The hipster meme – “Oh, it’s a weird, out of the way little place – you probably haven’t heard of it” – is already five years stale at this point. We’re all in on the joke now. So if I told you that the best cut of smoked meat in the world is beef brisket, and that the best beef brisket in the world comes from a little place in Lexington, Texas that’s only open on Saturday mornings, you probably wouldn’t bat an eye. Especially since it has now been at the top of the Texas Monthly list for more than a decade.

But I’m telling you, everything about Snow’s BBQ is wrong.

For starters, it really is just a one-day-a-week operation. It is extraordinary enough (and popular enough) that it could do a bustling business on most days like the joints in Austin or Lockhart. But despite the fixed cost-related challenges of a Saturday-only approach, they haven’t made the switch. The owner of the place is a former prison guard and rodeo clown whose day job for most of the time he has owned Snow’s was at a coal mine. The pitmaster is an 83-year old former butcher who works most of the week in maintenance at the high school down in Giddings.

All that makes for a good story. But that’s not what’s wrong. It’s the way they BBQ here. Correct BBQ is about indirect heat. Tootsie Tomanetz cooks almost everything over direct heat, and I think if she had her way, would still be doing it on briskets, too. Correct BBQ is about low and slow. Tootsie Tomanetz cooks several cuts – including a really excellent sausage – at much higher temperatures than the typical joint. Correct BBQ is about sourcing bespoke prime-grade or American wagyu beef from idyllic ranches in Montana. Tootsie Tomanetz buys her beef from a butcher in Taylor called O’Brien Meats that doesn’t even have a website. Correct BBQ is about washing the meat in a constant billow of smoke. Tootsie Tomanetz’s fires are heavy on hot coals and light on fresh logs – a much less smoky fire. Correct BBQ doesn’t rely on shortcuts like the Texas Crutch. Tootsie Tomanetz has been wrapping her briskets in foil for years. Oh, and by the way – Correct BBQ is a guy thing. I guess no one told Tootsie about that one either.

If it sounds like Correct BBQ is a religion, that’s because it is.

One Thin Red Line

If you want to understand the religion of Correct BBQ, there is no greater symbol of it than that the pale red strip at the bottom of this slice of brisket.

That little strip of color is called a smoke ring, and it is a fundamental part of the lore of Correct BBQ. Restaurants around the US frequently tout it as an indication of properly smoked meats. The largest national body governing competition BBQ standards, the Kansas City Barbeque Society, included it for many years among its formal judging criteria. Despite its removal some years ago, many judges still swear by it, or at a minimum acknowledge the subconscious effect it has. Like this one. And this one. Even though most competitions today don’t formally recognize it as part of the judging standard, it remains an obsession of most aspiring and backyard cooks.

The most common reason given for celebration of the smoke ring is a tautological one: It is the hallmark of Correct BBQ. Perhaps one layer below a pure tautology, the smoke ring ‘is believed to show that you have done a good job and properly low and slow smoked the meat in question.’ In other words, the smoke ring is accepted by many as post hoc evidence of proper technique, and two aspects of the technique in particular: cooking meat slowly over low temperatures, and cooking it over a smoky wood fire. It is a beautiful bit of lore that adds romance and an air of artistry to an otherwise (literally) visceral activity. This pink flesh is the result of a lazy fire tended dutifully, with billowing smoke slowly washing over a well-seasoned cut of meat over a period of hours. As such romantic lore tends to be, the smoke ring was for many years ingrained as common knowledge among aficionados – a thing that everybody knew that everybody knew. It was the answer from the gods to him who performed the ritual properly and with a pure heart.

If only it were true.

The smoke ring is not ‘smoke penetrating the meat.’ It is not even evidence of a significant quantity of smoke. It is the result of a chemical reaction between nitric oxide and myoglobin, the main non-water substance inside the ‘juices’ in a piece of meat. The size of a smoke ring in a piece of meat is determined entirely by the quantity of these gases that come in contact with that myoglobin before it hits about 170 degrees. The presence of those gases has only a limited relationship with the quantity of ‘smoke’ produced by the cooking fire. You can produce comparable quantities of those gases with plain old charcoal briquets. If you’re pressed for time, sprinkle that brisket with curing salts containing sodium nitrite and throw it in the microwave. You’ll be the lucky owner of a disgusting hunk of gross with an exquisitely deep salmon smoke ring.

Even the preference for low-and-slow cooking is a methodological abstraction of the scientific process of collagen denaturation and breakdown. It works, but not because of some direct relationship between flavor and the speed of cooking, but because the technique strikes a balance between maintaining high enough internal temperatures for long enough to effectively facilitate beneficial chemical processes in intramuscular collagen on the one hand, and minimizing excessive drying and evaporation on the meat’s exterior on the other. For many cuts, each of these processes can be achieved through a higher temperature cook and a longer period of insulated resting of the prepared meat.

Likewise, the disdain many had for techniques like the Texas Crutch – wrapping a brisket during part of its cooking process – was based on a belief that it replaced smoking with steaming (which is not entirely incorrect), and that it sped up the cooking in a non-traditional way that would harm the product (which is nonsense). We now know, of course, that wrapping a piece of meat reduces the process of evaporative cooling and results in moister, more flavorful BBQ.

The evaluation of food is a subjective, human thing. But that is the point. In any field for which the interpretation or objective function – the thing we’ve solving for – isn’t quantifiable or even knowable, any tangible method feels like a godsend. Won’t someone just tell me what to do? But that method will always be an abstraction from the thing we seek. When these abstractions become ritual, the risk is that our process of discovering facts about that topic will be guided by its relationship to the abstraction, to the religious myths that we memorize and pass along to others.  

This is all made more difficult by the fact that there may be good reasons for parts of the ritual. I still personally have much better luck, for example, cooking most things at a very low temperature over a very long period. The point is that the ritual of Correct BBQ stifled the exploration of newer, better ways to prepare it. People made BBQ to most closely resemble what they expected from the ritual. In algorithmic terms, we were stuck in a local optimum and needed enough crazy-ass ideas to succeed to have any hope of achieving movement in our literal and figurative posteriors. Sure, there were always exceptions and independent thinkers. But it has really only been in the last two or three decades that people like Tootsie Tomanetz who didn’t give a damn what anyone else thought have come into the mainstream. It isn’t that Tootsie, or Aaron Franklin or any of the other demigods of Texas BBQ aren’t respecters of tradition. These are post oak-only, salt-and-pepper purists, after all. It’s that their experiments weren’t guided by hewing to the rituals of Correct BBQ for the sake of those rituals.

Snow’s BBQ IS Tannu Tuva, y’all. Not literally, I mean, although it is a pain in the ass to get there. I mean that it is proof that some of the world’s greatest joys come from unearthing beauty that remains beautiful even when we discover what it really is. Tannu Tuva wasn’t something that Richard Feynman feared would become less beautiful or magical through its discovery any more than beautiful food would cease to be art because we understand the science behind its flavors, textures and aromas. Knowing only adds.

I have a friend who’s an artist, and he sometimes takes a view which I don’t agree with. He’ll hold up a flower and say, “Look how beautiful it is,” and I’ll agree. But then he’ll say, “I, as an artist, can see how beautiful a flower is. But you, as a scientist, take it all apart and it becomes dull.” I think he’s kind of nutty. … There are all kinds of interesting questions that come from a knowledge of science, which only adds to the excitement and mystery and awe of a flower. It only adds. I don’t understand how it subtracts.

What Do You Care What Other People Think, by Richard Feynman (1988)

Knowing only adds, that is, unless what we most desire is the sanctity of the ritual. But ritual isn’t the only potential enemy of a worthy process of discovery. We must also grapple with the way in which systematic errors and bias creep into our analysis when relevant facts ARE knowable, when some of them ARE measurable…and when they appear to clearly support our theories and priors. As it happens, the field that made Feynman famous not only gives us perhaps the greatest simultaneous source of skepticism and wonder in all of physics, it also deals with exactly this problem. And it just so happens to be about a different kind of thin red line.

Another Thin Red Line (or Two)

What you see below is a stylized illustration of the visible light portion of hydrogen’s emission spectrum.

Source: Auxiliary Hypotheses Blog

OK, I admit that I escalated quickly from a discussion of coagulated meat juices, so let’s keep it simple. These are the colors of light emitted when a hydrogen atom moves from a high energy state to a lower one. This was a big deal in the late 19th and early 20th centuries, not just because we were trying to understand electromagnetism, but because observing electromagnetic effects (like, say, light) allowed us to test different theories about sub-atomic particles. It was a beautiful dance between experimental and theoretical physics, between deductive and inductive research methods. In 1916, Niels Bohr built a model that described electrons orbiting the nucleus of an atom at various discrete distances. It wasn’t the first model that gave the atom the solar system treatment, but it was the first that seemed to provide a mechanism explaining the spectrographic image we see above. In other words, Bohr sought a physical description of what rules electrons could be following that could also explain why a change in the energy state of that electron would emit that particular frequency of red light.

He knew at the time that his model wasn’t completely right. While we could observe the effects of what we would later explain using quantum mechanics, we lacked the math and the models to explain those effects. And so the Bohr model relied on quantization heuristics, which is a smarter-sounding way of saying, “Let’s bolt some stuff onto the model we used to use to solve this problem so that it spits out the solution we can observe.” You can think of it like the old up-converters they used to sell for pre-HD cable boxes and DVD players, or the auto-tune on a Selena Gomez record. I’m making it sound more dishonest than it is in service of a joke – a lot of things are figured out by finding out what lies in the gap between our current model and our current observations.

Still, even with Bohr’s quantization heuristic (which defined a discrete list of possible stable states for electrons), the model wasn’t quite right. That’s because while it looks like each of the emitted frequencies is a single line, and while the Bohr model creates a workable physical explanation for that measurement in a hydrogen atom, that isn’t exactly what a spectrograph would measure. If you could look more closely – much more closely – you’d see that there is a fine structure to that red line. In other words, there are two red lines there. The Bohr model didn’t account for this, and not for lack of trying. Enter Arnold Sommerfeld.

Sommerfeld built on Bohr’s model in a few ways. The most obvious change modified Bohr’s framework to one in which the orbits at different energy states were elliptical. Without going into a rabbit hole discussion of angular momentum and phase integrals, the important fact is that Sommerfeld developed a closed form solution that was exactly right in predicting the two red lines for the relativistic hydrogen atom. His was precisely the formula that Paul Dirac would propose for this calculation under full quantum mechanics some twelve years later, and Sommerfeld did so with no understanding of the features of quantum mechanics that were responsible for the fine structure! As L.C. Biedenharn put it in one of many pieces summarizing and exploring the affair, “Sommerfeld’s methods were heuristic (Bohr quantization rules), outdated by two revolutions (Heisenberg-Schroedinger nonrelativistic quantum mechanics and Dirac’s relativistic quantum mechanics) and his methods obviously had no place at all for the electron spin, let alone the four components of the Dirac electron.”

If this wasn’t magical enough, Sommerfeld’s method also left us with the gift of a new dimensionless physical constant for our Standard Model of particle physics, which is a fancy way of saying that we discovered a number that is really important but which isn’t really a measurement or unit of anything. It’s just a number that reflects a fundamental property of the universe. The fine-structure constant, as it is called, can be measured and observed just about everywhere, but cannot be mechanistically explained as a governing rule or force.

It’s 1/137, give or take. Sommerfeld calculated it as the ratio of the velocity of an electron in the first circular orbit of the Bohr model to the speed of light. It’s also the square of the ratio of the elementary charge to the Planck charge. It’s part of the function describing the probability than an electron will emit or absorb a photon. It manifests in the relationship between the energy of a particular photon and the energy level at which two electrons overcome electrostatic repulsion. Or, as Feynman put it:

…[it] has been a mystery ever since it was discovered more than fifty years ago, and all good theoretical physicists put this number up on their wall and worry about it. Immediately you would like to know where this number for a coupling comes from: is it related to p or perhaps to the base of natural logarithms?  Nobody knows. It’s one of the greatest damn mysteries of physics: a magic number that comes to us with no understanding by man. You might say the “hand of God” wrote that number, and “we don’t know how He pushed his pencil.” We know what kind of a dance to do experimentally to measure this number very accurately, but we don’t know what kind of dance to do on the computer to make this number come out, without putting it in secretly!

QED: The Strange Theory of Light and Matter, by Richard Feynman (1985)

The fine-structure constant is Tannu Tuva, too – a miracle in its discovery, mysterious in its origin, but also measurable. Knowable. Observable. And no less miraculous or mysterious for all that. But it IS the kind of thing you put on your wall and worry about. Not just about the Athena-springing-from-the-head-of-Zeus feeling you get from a number that just happens to be a fundamental identity of the universe. There’s also something unnerving about a property that can be correctly predicted from an abstracted model.

Thankfully, in physics, that unnerving prospect is the exception which proves the rule. After all, it’s not as if physicists stopped trying to better understand quantum mechanics, particle physics and electromagnetism just because Arnold Sommerfeld had figured out what must be happening inside a hydrogen atom. It’s a good thing, too.

In the social sciences, rather less thankfully, the exception IS the rule. Every model we build which seeks to predict some event that is a function of human behavior is nearly always inductively overdetermined and deductively underdetermined. What I mean by that is that investors, journalists, policy wonks and other social scientists can never be as certain as a physicist that our model or analysis reflects a true feature of the world, but we will nearly always have enough observational data to demonstrate to us that it does. We have so many degrees of freedom, so many variables to consider, that with enough data we can usually construct a dozen workable models for why that atom produces those two frequencies of red light. Evidence of this peril is everywhere. It lies in every investment strategy backtest, every interpretation of a politically charged video presented as fact, in every macroeconomic model, and in every perfectly detailed economic report given by a central banker under the aegis of immunizing communications policy.

The credible observer with any measure of experience with the statistical rigor of financial, economic, sociological, psychological and political research will inevitably come to one conclusion: no matter how much we would pretend that it is something else, the vast majority of our research in these fields is heuristic and nothing more. When we treat these data-backed heuristics as part of whatever the equivalent of the Standard Model is in our fields, bias and systematic error will very often be our reward.

The Red Badge of Bias

I believe these two forces – Ritual and Heuristic – are the most constant threats to clear eyes and full hearts throughout our processes of discovery.

Ritual isn’t inherently bad. There are deep parts of us which respond to its pull, and our lives would be emptier if we rejected it fully. We have written about many of the worthy uses of narrative in Holy Theatre, such as the ones brought to bear in the Civil Rights movement or in the Second World War.  Yet we must still be mindful of how Ritual steers our questions, our thinking and our answers into right-thinking patterns and convention. It is the source of the monocultural newsroom and the risk-averse investment committee and countless research projects which begin from unproven, unexamined priors. The tyranny of Ritual is its presumption that its priors are self-evident, as morally unworthy of challenge.

Heuristic is also not inherently bad. For example, I believe in functioning markets as spontaneously organized entities that will nearly always defeat a deductive approach to understanding their value. Similarly, there are many non-falsifiable principles whose survival for millennia ought not to be discarded lightly. Where Heuristic imperils our research is in the the post hoc rationalization of our deductive frameworks on a pseudo-empirical basis. Doing so not only directly introduces the risk of systematic error should our inductive process have missed some key latent variable (as it so often does), but it also indirectly shuts off avenues of inquiry and analysis. It is a force of laziness and overconfidence, typified by the belief that once we have ‘proven’ that something is likely under some set of statistical parameters, we are absolved from trying to disprove it further. The tyranny of Heuristic is its presumption that our priors have been proven, and are in no further need of updating.

For a successful technology, reality must take precedence over public relations, for nature cannot be fooled.

The Rogers Commission Report (1986)

With apologies to Mr. Feynman, we will need to expand this idea. For a successful news organization, for a successful investor, for a successful technology, reality must not only take precedence over public relations, but over both Ritual and Heuristic. The only way that it is possible for this to happen is through ruthless governance of the priors which influence which topics we take up, which stories we research, and which factors and markets we examine.

And that – following this little detour we’ve taken together – is exactly where we will go in Part 3.

For more about Snow’s and Tootsie, the Texas Monthly Profile and more recent NY Times feature come highly recommended.


The Road to Tannu Tuva, Pt. 1

Source: Atlas Obscura’s lovely atlas to this location,

There is a large, flat rock set into the gentle rise of a hill in a strange land called Tannu Tuva. Someone has carved a symbol into its face like some kind of ancient rune. But it is not an ancient rune. It was drawn there just this year by a man called Ralph Leighton. Likewise, Tannu Tuva is not some place out of fantasy. It is a Russian state that today is called the Tuvan Republic.

Those are the facts, anyway, but none of them is true. Not really.

In every way that matters, the stylized engraving of fermion scattering you see above, a famous illustration from the field of quantum electrodynamics called a Feynman Diagram, is an ancient rune. Even carved just months ago, it is at once both a mechanism for lucid communication and an esoteric symbol of one of the most mystical features of our natural world. Tannu Tuva, too, was and is a very real place. Yet it is also very much a place out of a fantasy, a conscious representation by a small group of scientists to the power of leaving the door to the unknown ajar, to the adventure of discovery, and to the commitment to overcoming barriers thought to be impossible.

You’ve heard of the man who first drew that diagram. You may have read much of his story. His name was Richard Feynman, and he is a genius. Or at least, he was until his death, 30 years ago last February.

Mathematician Mark Kac was also a genius. A Polish mathematician, Kac worked with Feynman at Cornell in the 1940s after Feynman left the Manhattan Project. Kac had arrived in New York after finishing his studies in Lwów in 1937. It was a near thing. His parents and his brother were murdered by Nazis in Krzemieniec in 1942. Each of Kac and Feynman pursued his own genius, Richard in theoretical physics and Mark in mathematics. But their mutual respect led to a significant joint achievement: The Feynman-Kac Formula.

The Feynman-Kac Formula may not be familiar to you. Among other things, it allows for some stochastic problems to be solved using a deterministic framework. In other words, it allows us to use formulas to solve a certain class of problems that would otherwise require us to simulate the system to reach a result. While it can’t be used, lamentably, to solve a Three-Body Problem, it is the kind of mathematical approach that permits us to solve some similar problems without resorting to number crunching on iterative calculations and simulations.

If you work in finance, have studied for the CFA or went to business school, you have probably unwittingly used the FeynmanKac Formula in what investors consider to be an important partial differential equation: pricing a stock option. Yes, by far the most famous application of the joint work of this mathematics wizard and physics genius is the Black-Scholes formula. Something tells me that being used primarily as a memorization test by second-year banking analysts to intimidate college seniors in Goldman Sachs interviews was not the fate Richard and Mark might have had in mind for their achievement. Their collaboration is still intriguing, not least because it gave us Kac’s description of what it was that made Richard Feynman so unusual.

In science, as well as in other fields of human endeavor, there are two kinds of geniuses: the “ordinary” and the “magicians.” An ordinary genius is a fellow that you and I would be just as good as, if we were only many times better. There is no mystery as to how his mind works. Once we understand what he has done, we feel certain that we, too, could have done it. It is different with the magicians. They are, to use mathematical jargon, in the orthogonal complement of where we are and the working of their minds is for all intents and purposes incomprehensible. Even after we understand what they have done, the process by which they have done it is completely dark. They seldom, if ever, have students because they cannot be emulated and it must be terribly frustrating for a brilliant young mind to cope with the mysterious ways in which the magician’s mind works. Richard Feynman is a magician of the highest caliber.

Enigmas of Chance: An Autobiography, by Mark Kac (1985)

Kac’s characterization of Feynman as the magician kind of genius is consistent with the observations made about Feynman by many others. Oppenheimer commented specifically on his unparalleled and unique relationship with both the theoretical and experimental physicists on the Manhattan Project, for example.  Al Seckel’s stories about Feynman famously included references to his interactions with Stephen Hawking. In one such story, Feynman dismissed Hawking’s ability to perform path integration in his head, since it was “much more interesting to come up with the technique like I did.” Creativity, not technical mechanics, was the secret to Feynman’s genius. His genius was a difference in kind, not in magnitude.

Another Feynman peer and contemporary during his years at Caltech was a physicist (and genius) named Murray Gell-Mann. He is most famous for his Nobel Prize-winning role in the development of our understanding of elementary particles. He is also famous, especially in our little publication, for his role in describing Gell-Mann Amnesia. Popularized by Michael Crichton, of all people, Gell-Mann Amnesia describes our ability to read with disbelief the poor quality of conclusions in a newspaper or magazine story about a topic we know very well, after which we turn the page to take in reports on other fields of expertise and nod along happily.

Gell-Mann had a productive but challenging relationship with Feynman. As a charming read published by the Atlantic in 2000 put it: “Dick and Murray, as everyone soon called them, became inseparable. Strolling Caltech’s immaculately landscaped campus or dueling at the chalkboard over some calculations, the two scientists discussed physics for hours.”  But the two were often at odds in matters of style and personality. They also approached the conventions of science – when you write up your findings, how early in your process you publicize your theories, how you publish – so differently that their partnership may have fallen short of what it could have been. At the least, it fell short of what many hoped. Gell-Mann, at once both confounded by Feynman’s form of genius and irritated by what he perceived as affectations of false-humility, playfully described Richard’s approach to science:

You write down the problem.

You think very hard.

Then you write down the answer.

It was a joke, and best told, as it was originally to Sidney Coleman and then to James Gleick in Genius: The Life and Science of Richard Feynman, with closed eyes and knuckles pressed to forehead, pretending to think very hard. 

And yet.

There is a simple truth in this logical process that is faithful to, if obviously a comically oversimplified version of, what science means. It also happens to be the process whereby human ingenuity is transformed into tangible output in almost every other technical and social field. The technical prowess of ordinary geniuses in Kac’s terminology, and the act of thinking very hard in Gell-Mann’s, are important to any science. They are necessary conditions for science to have really found out anything. Necessary but insufficient. The transmission mechanism which begins with our world and the people in it, and ends with some tangible or intellectual product that influences that world, requires two more things:

Someone to write down the problem.

Someone to write down the answer.

These are roles that exist not only in physics, medicine, mathematics and other natural sciences or practical derivations thereof, but in any field which relies upon the discovery of truths about the world, predictions about the implications of those truths, and the evaluation of the credibility of those predictions. By right, that ought to (and does) include the social sciences – political science, economics, sociology, anthropology, language and history. It also includes the critical field of journalism, and yes, the business of investing and capital management.

When Kac spoke of Feynman as a magician, he was speaking in large part of his creative capacity to visualize problems in a different way.  Much of Feynman’s reputation was built on his Nobel Prize-winning work with Tomonaga and Schwinger on quantum electrodynamics, but even more was built on Feynman’s illustrations that framed the analysis of those dynamics. He had a picture in his mind of what was happening in nature, and he constructed a language which not only helped to communicate those details, but which itself served to prod the discovery of the mathematics to describe it. A lifelong scientist whose conscious dabbling in visual art and music took place too late to amount to much beyond personal pleasure, Feynman’s greatest work was nonetheless a heavily symbolic creation of both art and language.

Yes. Feynman was a magician of the highest caliber.

The magician’s role – to be able to conceive the right questions to ask and right ways to ask them – is critical to every science, to investing and to journalism. It is also innately subjective. The reasons should be intuitive. We research what we think is important, what we think is interesting, and perhaps most importantly, what we think will pay the bills. The result is perilous for even the most well-meaning researcher. From the very beginning of each process of writing down our questions, our work is saddled with bias. The questions we ask, the stories we assign, the avenues of research we pursue and the investments we elect to evaluate are all heavily influenced by both external directives and our own judgments based on internal priors.

At each other stage of the research process – from analysis to interpretation – temptation is everpresent. We will naturally be more inclined to test theories which, if proven, fit with our other theories. We will naturally be more inclined to believe results which support a theory we favor. We will more easily see disqualifying flaws in data which do not support our theories, beliefs or priors. We will be tempted to inject non-falsifiable judgments and opinions we feel confident are self-evident into the gap between our findings and their implications.

We can never wholly avoid the injection of bias into our research. We can only adopt processes which seek to ruthlessly rip it out by root and stem.

When we, our colleagues and our peers are hell-bent on the falsification of every idea spawned by the questions we pose, and on expunging underdetermined explanations for some fact or theory about the world, we slowly erode the influence of that bias. What remains from that process is science. The true scientist, whether he be journalist, investor, physicist, mathematician or sociologist, does not stop research and challenge when he calculates a feature of some thing that is adequately explanatory. He stops when he and all the resources around him that can be marshaled can find no other way to destroy his idea.   

When the scientist, journalist or investor does not aggressively seek out the falsification of his ideas and the questions which led to them, a strange thing happens: The magician becomes a missionary for his priors. What remains from his process is not science. What remains are facts tenuously grafted onto a premise he rather fancied. What remains is scientism – the meme of science!

It is for this reason, I think, that Feynman’s most unique trait may be his commitment to the absolute scientific necessity of doubt. No simple Pollyannaish visionary charmed by the magic of discovery, Feynman was also a missionary of another variety. In his case, however, his mission was to promote the vitality of doubt. Richard was talking about scientism and the meme of science! before almost anyone. He called it “cargo cult science.”

There is one feature I notice that is generally missing in cargo cult science. … It’s a kind of scientific integrity, a principle of scientific thought that corresponds to a kind of utter honesty — a kind of leaning over backwards. For example, if you’re doing an experiment, you should report everything that you think might make it invalid — not only what you think is right about it; other causes that could possibly explain your results; and things you thought of that you’ve eliminated by some other experiment, and how they worked — to make sure the other fellow can tell they have been eliminated.

Details that could throw doubt on your interpretation must be given, if you know them. You must do the best you can — if you know anything at all wrong, or possibly wrong — to explain it. If you make a theory, for example, and advertise it, or put it out, then you must also put down all the facts that disagree with it, as well as those that agree with it. There is also a more subtle problem. When you have put a lot of ideas together to make an elaborate theory, you want to make sure, when explaining what it fits, that those things it fits are not just the things that gave you the idea for the theory; but that the finished theory makes something else come out right, in addition. In summary, the idea is to try to give all of the information to help others to judge the value of your contribution; not just the information that leads to judgement in one particular direction or another.

Surely You’re Joking, Mr. Feynman (1985)

In a world awash with narrative, it is precious and rare to know that a thing is what we say it is and not a glorified reflection of our priors and predispositions. It is even more rare, however, to come upon a process for taking in information as an investor or citizen that is capable of achieving that standard. Most investment processes – even many systematic strategies – are utterly incapable of achieving it. Most journalistic standards fall well short, too. Even many of our sciences, you will be unsurprised to discover, have empowered a great many shoddy analyses to exist through a combination of indifference and a lack of scientific integrity.  

Over the next three editions of this Notes from the Road series, I will draw a map of how I think we can sharpen our awareness of the science! meme at work. I will explore our engagement as investors, consumers of news and evaluators of findings from the natural and social sciences. I will also draw a map of how we can do better as primary actors in our own research processes. Because I think that that Richard would find some delight in a dead serious treatment of Murray Gell-Mann’s tongue-in-cheek description of the Feynman Method, that will be our model. Three notes to follow this one, each discussing the ways in which the science! meme creeps into each phase of an otherwise legitimate fact-finding undertaking – in the questions we ask, the analysis we undertake, and the stories we tell about it.

The next note, Part 2, will examine how what questions we ask and how we ask them influence the quality and direction of underexamined research in multiple fields. This will be the start on our Road to Tannu Tuva. But it is important that you know it isn’t just a road of rigor.

“Okay, then what ever happened to Tannu Tuva?”

“Tannu what?” I said. “I never heard of it.”

“When I was a kid,” Richard continued, “I used to collect stamps. There were some wonderful triangular and diamond-shaped stamps that came from a place called ‘Tannu Tuva.’ ”

… I straightened up in my chair a bit and said, “Sir, there is no such country.’

“Sure there is,” said Richard. “In the 1930s it was a purple splotch on the map near Outer Mongolia, and I’ve never heard anything about it ever since.”

Had I stopped and thought a moment, I would have realized that Richard’s favorite trick was to say something unbelievable that turns out to be true. Instead, I tightened the noose that had just been placed around my neck: “The only countries near Outer Mongolia are China and the Soviet Union, I said, boldly. “I can show you on the map.”

We opened…a map of Asia.

“See?” I said. “There’s nothing here but the USSR, Mongolia, and China.  This ‘Tannu Tuva’ must have been somewhere else.”

“Oh, look!” said Carl. “Tuvinskaya ASSR. It’s bordered on the south by the Tannu-Ola Mountains.”

Sure enough, occupying a notch northwest of Mongolia was a territory that could well once have had the name Tannu Tuva. I thought, I’ve been had by a stamp collector again!

“Look at this,” remarked Richard. “The capital is spelled K-Y-Z-Y-L.”

“That’s crazy,” I said. “There’s not a legitimate vowel anywhere!”

“We must go there”, said Gweneth

“Yeah!” exclaimed Richard. “A place that’s spelled K-Y-Z-Y-L has just got to be interesting!”

Tuva or Bust! Richard Feynman’s Last Journey, by Ralph Leighton

The Road to Tannu Tuva is the realization that the rigor of doubt and uncertainty on the one hand, and the joy of discovery on the other, need not be strangers. Far more than that, it is the realization that they are and ought to be considered one and the same.

Although truth be told, around these parts we have a different expression for this idea:

Clear Eyes. Full Hearts.


Draft Day


Did the Cowboys secure a Greg Bell among the five players they received from the Vikings? If so, where is he? That’s the disappointing aspect of this deal – no substance among those five players…those stealin’, dealin’ Vikings didn’t miss a trick…it’s a textbook example of how the strong fleece the weak in a blockbuster trade. All they had to do was find somebody dumb enough to fall for it.

Randy Galloway, The Dallas Morning News (October 14, 1989)

The media, and the public all made precisely the same mistake: They figured that I was so shorthanded that I’d have to keep all the old Minnesota players…bringing them in was essentially a formality. I wanted the draft picks.

Jimmy Johnson, Turning the Thing Around – My Life in Football (1993)

You live in Texas now. You love the game of football. You just don’t know it yet.

Friday Night Lights, Season 5, Episode 1 (“Expectations”) (2010)

When I traveled to Ireland this summer, I went almost five days at one point with zero human contact. I found the cure for an associated momentary bout of homesickness in the most unlikely place imaginable: Friday Night Lights on Irish satellite television. Not the decent movie from 2004. I’m talking about the last great network television drama. The source of the line from Ben’s recent note Clear Eyes, Full Hearts, Can’t Lose. It’s a show that I can’t imagine a European audience would really have understood, so steeped as it is in the special rituals of small-town football in the rural USA. But maybe they would. After all, even I didn’t grow up loving football. After years of living in Texas, I would come to. I just didn’t know it yet.

There is something magical about walking through a small town in America on a Friday night between Labor Day and Christmas. Empty streets, other than the odd through-traveler. Darkened storefronts, the third or fourth reverberation of a snare drum in the distance. It’s too far to hear trumpets, cheerleaders or whistles, but the bass of the marching band’s sousaphones carries. Every once in a while, if you stay long enough, you’ll hear the swell of the crowd in the distance, a universal roar that all sports fans would know and appreciate.  The picture at the top of this note is from a typical Friday night in my hometown in Texas.

For some reason, in football anyway, the legends of these games always seem to come from towns like this. It’s easy to come up with cynical explanations – that small towns elevate gifted young men and women into legends because there isn’t that much else going on. I choose to see it a different way. I think these towns are uniquely willing to invest themselves in celebrating and exhorting their neighbors. Sure, some of us might prefer it if they channeled that encouragement to more productive passions than just football, but I still believe that the spirit that creates legends is a marvelous one.

And oh, we had legends in Texas. We had Eric Dickerson. Born and bred in little Sealy, an hour and change west of Houston, he did things with a football no man his size should have been able to do. Big, fast, shifty and smooth, he may still be the most underrated to ever play the game. We had Adrian Peterson, whose father was serving an eight-year prison sentence, who saw his brother die in a car accident when he was seven years old. All Day, they called him, because that’s exactly how he ran. Inventive, agile, fast, with an impossibly strong grip, A.D. was Eric Dickerson 2.0. Most of all, we had Earl Campbell. He grew up dirt poor, the seventh son of a man who worked on a rose farm outside of Tyler, Texas. He was the hardest-hitting running back that ever held a football, but he didn’t lift weights. I think he may have done more to turn Texas off to the evils of segregation than any man alive. Earl Campbell wasn’t content to beat you. He wanted to destroy you.

There will be no Earl Campbell 2.0.

Georgia had Herschel Walker. If YouTube had existed in 1979, he would have broken it. He was the Georgia state champion in shot put, 100-yard dash and 220-yard dash. He rushed for 3,167 yards his senior year. If you’re not familiar with these totals, this is the rough equivalent of the statistics you would produce if you got the ball every play and just never got tackled. He was the top recruit in the nation when he agreed to play for his in-state Bulldogs in 1980.

After impressive freshman and sophomore seasons, and a Heisman winning junior year, Walker had a choice. He could stay in college for another year and enter the NFL draft. Alternatively, he could leave school right then and there and join the USFL, a new league which didn’t require him to complete college. It would also allow him to sign with any team he wanted. And Herschel Walker wanted to sign with the New Jersey Generals.

It was an incredibly lucrative contract for the time. It paid Walker a $1.5 million signing bonus and a little over $1 million a year for three years. By comparison, the most highly paid running back in the NFL at the time was future Chicago Bears Hall of Famer Walter Payton, who made around $700,000. The NCAA was furious. The NFL was furious. Team owners were furious. Herschel Walker was rich.

Signing Herschel Walker was part of an increasingly aggressive strategy by the USFL. It would become even more aggressive in 1984 with the purchase of the New Jersey Generals by a young man named Donald Trump. Trump – now Herschel’s boss – wanted to force the NFL to absorb the USFL in the way many other sports leagues had done with their competitors in the past. If successful, it would instantly multiply the value of his investment. He moved the USFL to primetime in the fall to compete directly with the NFL, and he led an anti-trust lawsuit against the league, seeking $1.7 billion in damages. After years of expensive litigation, the USFL won its suit, but was awarded nominal damages of only $1. Cash poor from its aggressive strategy, it would soon fold, more or less in line with the end of Walker’s 3-year contract.

The Dallas Cowboys were shrewd and saw the pending failure of the USFL on the horizon. At the urging of Gil Brandt (the most important guy in NFL history you probably haven’t heard of) they used a 5th round draft pick in 1985 as a flyer to reserve Walker’s rights, just in case he had no choice but to enter the NFL. It paid off, and he almost immediately became a very productive player. The problem is that an NFL roster carries 53 men. One productive running back, even one as otherworldly as Herschel Walker, couldn’t turn a lousy Cowboys team into a good one. (Also pictured: Saquon Barkley and the 2018 New York Giants)

Walker continued to be productive, but the Cowboys kept getting worse. In 1987, they won seven out of fifteen games. In 1988, they won only three out of sixteen. In February 1989, the Cowboys were sold for $140 million to oil man and Shakey’s Pizza franchisee (no, really, look it up) Jerry Jones. Jones wasted no time in putting Tom Landry, the only coach the Cowboys had ever known, out to pasture. In his place, Jones hired his former Arkansas Razorbacks teammate Jimmy Johnson, who was by then the successful head football coach at the University of Miami.

The Cowboys got off to a rough start in Jerry and Jimmy’s first season. By mid-October they were 0-5, and had lost those five games by a combined score of 146-54. This was a very bad team, and it wasn’t going to get better soon. They needed to rebuild, which meant trading players for as much value as they possibly could. The problem was that, while Jimmy’s first draft only months before would ultimately produce a Hall of Famer and a few other extraordinary talents, they really only had two proven bargaining chips in any trade: wide receiver Michael Irvin and running back Herschel Walker. As the story goes, it was Oakland Raiders owner Al Davis who talked Jimmy out of trading Irvin. But Walker? Well, the offers that Jimmy got for Walker were too good to pass up – although he was the only one who seemed to know it at the time.

Dallas ultimately traded Walker for five players and three draft picks: one first round, one second round and one sixth round pick. Not bad. But the agreement also stipulated that if the five players were not on the Dallas roster because they were cut or traded, the compensation would revert to additional draft picks. It’s a detail that escaped the notice of most sports media, but it was what Jimmy had in mind all along. He had every intention of simply securing the alternate draft pick compensation for these players. And that’s exactly what he did.

In the end, Dallas ended up with three first round picks, three second round picks, a third round pick and a sixth round pick from Minnesota. They used those picks to draft players who would go on to play critical roles in Dallas’s three Super Bowl victories in 1993, 1994 and 1996. Johnson had changed the NFL forever. He had written a script. He had created a Path to the Super Bowl, and everyone was now on notice that it ran through the NFL Draft.

Imitation, Flattery, Etc.

The Vikings were brutally skewered for their lopsided trade, although they remained a successful team throughout much of the 1990s, with a better than average track record of getting into the playoffs. But Walker didn’t win them any championships. Jimmy had caused the value of draft picks to skyrocket, which meant that no one was going to win a trade like that again. Still, many teams tried to follow the path that Jimmy’s Cowboys had charted.

In 1994, the Colts traded quarterback Jeff George to the Falcons for multiple top picks. The 2000 New York Jets traded Keyshawn Johnson for multiple top picks. The 2002 New Orleans Saints dealt Ricky Williams for multiple picks from the Dolphins, just a couple years after they had traded their entire draft to the Washington Redskins for the rights to the same Ricky Williams. Not all of the draft capital-driven strategies involved trades of players. Some stockpiled picks through combinations of tanking (i.e. trading away any talent with an understanding that it would result in losing and higher draft status) and trading away of very high picks in the first round for multiple later picks (teams are often willing to trade several first and second round picks for one of the few very top picks in the first round). The 2012 Rams traded their #2 overall pick for a huge number of picks from the Redskins and other teams. And the Cleveland Browns have been pursuing a…perhaps accidental tanking strategy for the last decade, stockpiling pick after pick to take the best possible players from college ranks.

It hasn’t worked.

Oh, sure, the Colts’ trade allowed them to select Marvin Harrison, who was part of the team that would go on to win the Super Bowl a decade later. The Broncos won, but they won with a quarterback they signed as a free agent, not the guy they picked with their first round bounty, who is now a 31-year old leftfielder for the…<checks notes>…Binghamton Rumble Ponies. The current LA Rams team looks very potent and might prove the exception, too – except that the players selected with their bevy of picks are almost all gone, outside of an above average defensive tackle. The teams who pursued Jimmy Johnson’s path to the Super Bowl over the last two decades haven’t found the promised land.

In fact, of the teams which have reached the promised land in the last several years, most have been much more aggressive acquirers of veteran players with draft picks rather than the other way around. The Philadelphia Eagles managed to mortgage their future, at least how most pundits described it, to select a talented young quarterback. He promptly got injured, only for their backup to lead them through the playoffs and into history. The team with the best record in the NFL, the LA Rams team mentioned above, has been more influenced by a recent trade in which they disposed of a massive number of draft picks to select their current quarterback, Jared Goff. And the New England Patriots have been the New England Patriots.

So why did the Stockpile Top Picks and Win strategy stop working? Is it broken? Did it just become a crowded trade that will mean-revert? Was it ever a legitimate strategy to begin with? And why, if it doesn’t really work, are teams like the Oakland Raiders still pursuing it with gusto?

The Problem with Process

We are obsessed with process at Epsilon Theory. We think it is a necessary – if usually insufficient – condition to almost any worthwhile analysis of investments or politics. But just like you, we are faced with two basic problems when we evaluate the processes of both general managers and portfolio managers:

  • We are wired to associate outcomes with the biggest single visible variance from norms. We struggle when forced to accommodate multiple influences, and invariably fail to identify hidden influences.
  • Even when we have good data to evaluate the relationship between a process and outcomes, the stories we hear about why a process was being pursued in the first place are almost always after the fact.

In other words, to continue the theme of the Notes from the Road series, the path of events matters, but the path of our exposure to information matters, too.

When teams evaluated the Cowboys dynasty from the 1990s, the biggest single visible variance was the process which led to the Herschel Walker trade and its impact on the drafts between 1990 and 1992. In reality, however, the Cowboys success was dependent on a much wider range of variables. The quality of their selections in 1989 – before the Herschel trade – ended up being among the best in NFL history. Troy Aikman, Daryl Johnston, Tony Tolbert and Mark Stepnoski became roster cornerstones. Even the player they jumped ahead of Oakland to select in the second round (after which they traded him for Johnston and others), Steve Wisniewski, went on to play at a high level for 13 years. A few years later, Al Davis would get revenge on Jerry Jones by jumping in front of him to draft an offensive lineman, this time out of Iowa State. That guy is now a strategist at Schwab and one of the funniest guys in financial services (you can follow him on Twitter @77cyko).

That wasn’t all. The Cowboys spent money – a lot of money – on players like Deion Sanders. They dominated the weird few years of Plan B free agency. The players they selected in the 1991 draft would go on to play 1,222 combined games in the NFL. They were successful on all 9 of their picks in the first 5 rounds in 1992, even borderline Hall of Fame receiver Jimmy Smith, whom they traded to the Jaguars. And then, in 1994, they took a small school lineman out of Sonoma State, who just happened to turn into the best offensive guard in the history of the NFL.

A million things had to go right for the Cowboys. But our desire to simplify processes causes us to see the path to the Super Bowl as the result of their biggest single visible variance: the Herschel Walker trade.

This is problematic for us as portfolio managers and allocators, not just because of this natural tendency, but because the people trying to sell us ideas aren’t stupid either. They know we need a hook. They’re waiting for us to ask about their edge. Hell, we even ask them the question in a way that is designed to deliver the biggest single visible variance: “what is the thing which most differentiates you from your peers?” They will always have an answer, and it will usually take a sexy, compelling form. A model, a quirk in the process, a database, a proprietary computational technique, a risk management framework. And it’s never that, or at least, it’s never just that. Want to know why Buffett hasn’t spawned a thousand mini-Buffetts? Because everyone tries to define some biggest single visible variance, or a 5-point listicle of his principles, and none of them is right. None of them is sufficiently explanatory[1]. Not even close.

Part of why our explanations are so flawed, however, gets back to the second problem with process evaluation. When we hire managers, we are almost always evaluating historical decisions on the basis of a process that is being described to us after the fact. I cannot tell you how many funds, strategy recommendations and third-party writeups I have seen which accept a fund manager’s description of a process, then compare it to historical positions and performance to establish whether the manager has adhered to a consistent process. Well, yeah, it has, because they wrote the story about the process they’re describing after they made those decisions. Most overhauls of a team’s roster don’t take place because of some master vision for maximizing value. Not really, anyway. They happen because there’s a new coach or general manager who wants the players to be players that he picked. Then, if it works, five years later we get a version of the master plan. In the few cases where there really was a master vision from the very beginning, we usually stupidly run them out of town before it gets a chance to work.

We face uncertainty not only in our measurements of the nexus between process and outcome, but between philosophy and process. It’s a system with every bit of a three-body level of complexity.

The Process Process

Some of these things are hard-wired. There’s nothing I can tell you that will change how your eye will be drawn to the biggest single visible variance. But if you are in the business of hiring fund managers, evaluating models or allocating to investment strategies, I have some advice for improving your process for evaluating process:

  • Make distinct your processes for evaluating the nexus between process and decisions on the one hand, and process and outcome on the other. Because we are always tempted to ‘talk stocks’ and ‘talk markets’, you will always be drawn into a discussion connecting selected decisions and their outcomes. Even the bad ones will end in humblebrags. Try to keep these discussions isolated. When you’re evaluating consistency with process, don’t introduce or allow the strategist/manager to introduce outcome into the discussion.
  • Don’t stop asking about process and philosophy once you hire/invest. It is common practice to set it and forget it on these fundamental questions, and to shift the ongoing diligence process to decisions and outcome. Don’t. Continually record how people describe what they believe they are doing, note how and when it changes, and evaluate their decisions against both.
  • Engage new employees in reunderwriting old investments. It’s a rare practice – and resource intensive, so not feasible for all – but onboarding new employees by asking them to reunderwrite certain existing investments before they are familiar with them is an extremely valuable way to detect incrementalism in our own thinking, to evaluate independently whether process stories have changed, and to inculcate the new employees with your best practices and philosophies.
  • Follow along first. Most allocators do this, but usually for the wrong reasons (waiting for another manager to stumble, or this manager to do really well). If you hire managers, funds or strategists, tracking their decisions after you’ve memorialized some assumptions and beliefs about them – even if you don’t have money invested – is extremely useful. Sure, there may be times where access to an idea means taking some risk on pursuing it with less hard data and more intuition, but as a general rule, following at least one or two strategies with the same vigor and process as those you have invested is useful. 
  • Don’t throw away all your priors at once. There ARE big shifts and events that can change everything about portfolio construction. Ben and I have written frequently recently about one we’re concerned about. But false positives are far more common. It’s not new, but for liquid markets strategies, I have had a lot of success deploying CUSUM – a standardized quality control technique that Britt Harris taught me and many others in Austin – as a tool for evaluating the information conveyed by performance. When it’s integrated into a “multiple alarm” framework, it can effectively highlight when a performance event is significant earlier than rolling measures, while still ensuring that big single events aren’t driving the boat. You can read more about these techniques here, but I’m also happy to walk you through their implementation. The math is trivial, but it is cumbersome in Excel. 

Even if you’re not in the business of selecting strategies and hiring managers, it is worthwhile to remember: Anyone who provides a simple, single reason for something you know is complicated, is probably either stupid, lying or selling you something. These traits are not, alas, mutually exclusive.

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[1] I mean, other than a beta, leverage and luck explanation, but that’s closer to being proof of what I’m saying that any kind of refutation.

Special thanks to reader Hodges for a helpful correction to Herschel’s history!


Notes From the Road: Roadkill

Get well soon balloon

Most species do their own evolving, making it up as they go along, which is the way Nature intended. And this is all very natural and organic and in tune with mysterious cycles of the cosmos, which believes that there’s nothing like millions of years of really frustrating trial and error to give a species moral fiber and, in some cases, backbone.

This is probably fine from the species’ point of view, but from the perspective of the actual individuals involved it can be a real pig, or at least a small pink root-eating reptile that might one day evolve into a real pig.

— Reaper Man by Terry Pratchett (1991)

This is Part 2 of the multi-part Notes from the Road series, introduced with Bayes and the Boreen. The Series explores how popular, otherwise adaptive methods we use to develop theories about political and financial markets based on priors and lived experience can subject us to unexpected new risks. The series tells the story of a range of journeys in history, sports, the arts and nature to illustrate the sources of those risks.

If, as Ben has written, memes are self-sustaining ideas that live in the human brain, I think there’s one that may predate all of the rest: Only the strong survive!

It’s a dumb meme about how we think evolution works that has spread, ironically, because of the way evolution actually works. Despite growth in scientific literacy, the popular conception of evolution continues to celebrate the idea that better/stronger/smarter things will prosper, and worse/weaker/dumber things will fail. The reality is much less sexy. Evolution is the process whereby nature necessarily favors traits which improve the ability of an organism to suvive until it reproduces. The idea that we are successful because of objectively superior traits – because only the strong survive! – is an idea perfectly adapted to the human ego. But on almost no dimension would we have judged our mammal ancestors superior to the dinosaurs they outlasted. But outlast they did, because – by sheer luck – their traits were better adapted to a post-Chicxulub state of the world.

That last observation is an important one. When we consider evolution as it truly is, we still usually focus on the organism, or in an Epsilon Theory context, the idea or the investment strategy in isolation. An individual organism mutates a new trait, which either makes it more or less well-adapted to the current environment. If more, then over time the trait is more likely to propagate. If less, then organisms carrying the trait will probably die along with it.  But for all the value that there is in constant improvement of our processes and philosophies in similar ways, the survival of a species or idea isn’t just a function of its own changing traits – it’s a function of the changing states of the world and the people in it.

For our investment principles and strategies, like any organism, observing that evolution is both a function of the traits of our ideas AND changes in the state of the world reveals two types of risks to our models and frameworks for understanding it:

  • Type 1 – The False Positive: We think and act like our principles are based on immutable laws of nature. They aren’t, and we get a rude shock when the world changes.
  • Type 2The False Negative: We believe that principles others believe are immutable laws are only representative of some temporary state of the world. We try to predict the change in the world, and it never happens. We waste returns, fees and client goodwill in the process.

Evolution is a painful journey for the individual. There’s not much solace in our failures becoming Harvard Business School case studies that help the species – or other investors. We must find some kind of middle ground between allowing ourselves to become speedbumps to a change in the state of the world on the one hand, or victims to the coyotes who would tell us “This Time It’s Different” about every bit of normal variability in the world on the other. We have to find that middle ground in our non-investing lives, too. Which of our heuristics and principles for evaluating life decisions are objectively true, or are at least true enough? Which are adaptations to our past environments and experiences, and will those be relevant to our new situation? When we make big life decisions, are the priors we rely on, well…reliable?  In the end, we muddle through, and more often than not, make it up as we go along.

Incidentally, that’s exactly what I’m doing. Next week, it’ll be 27 hours with a 2- and 3-year old in a blue pickup on the 1,712 miles of Dwight D. Eisenhower’s asphalt dream between old home and new. In honor of this journey, since we’re talking about growth, evolution and risk, and since I’m moving up to a part of the country where I won’t be able to talk about this sort of thing in polite company any more, I figure it’s as good a time as any to write about roadkill. And that’s saying something, because it’s always a good time to write about roadkill.

Full disclosure. If you’ve read this far, you’ve read the word ‘roadkill’ five times: once in Ben’s email, once at the top of this essay, twice in the prior paragraph and once in this sentence. You clicked on it, and I kind of feel like you’re already in for at least a penny here. But if you were squeamish about Ben’s disgusting tick infestation picture from a couple months ago, this one may not be for you.

Profiles in Roadkill: Dasypus Novemcinctus

Now that we’ve gotten all that out of the way, we can start talking vehicular critterslaughter. Allow me to introduce you to someone special.  This handsome fellow on the left is a nine-banded armadillo – one of the three state mammals of Texas, because unlike the boring-ass state you live in, Texas gets THREE state mammals. Take that, James Madison and your exquisitely reasoned Federalist Paper 62. Armadillos are remarkable little creatures who followed an unusual and narrow genetic path that has produced some of the strangest land mammals alive today. In addition to its signature armor plating, the armadillo reproduces from an egg which separates into four parts after fertilization. That means that nearly all litters consist of 4 identical creatures of the same sex. What’s more, the implantation of that fertilized egg is typically delayed by the mother by several months to better align with the spring season. Very handy, that.

The armadillo can inflate its intestines to float. It can hold its breath for six minutes to submerge. And that armor really is as tough as we think it is. Tough enough to defeat a .38 revolver. Like its closest cousins, the anteater and tree sloth, the armadillo is a marvel of specialized adaptations. One of evolution’s many weird, slimy miracles.

Also, when an armadillo sees headlights, it gets so terrified that it jumps straight up in the air and gets slammed by a car that would otherwise have passed right over it.

Profiles in Roadkill: Odocoileus virginianus

The armadillo, however, probably isn’t the animal most people (outside of Texas, anyway) think of when they think of victims of automobile-related critter flattenings. In honor of the trek we will take through the beautiful and too-unfairly-maligned state of Mississippi (which is also probably better than your state since it has two state land mammals), it is time we recognize the famousest of roadkill, the white-tailed deer. So common is the sad sight of one of these beautiful creatures along US highways that it causes the otherwise stonehearted, rage-filled American motorist to descend into our country’s unique style of gallows humor. Get well soon, gross deer. Get well soon.

Like the armadillo, evolution has gifted the white-tailed deer with extreme traits that are well-adapted to the challenges it faced during its emergence as a species. First, it is a remarkable jumper. While deer fences tend to be around eight feet tall, the average individual can actually jump somewhat higher than that, in some cases as much as 12 or even 15 feet. Somewhat less when it needs to jump forward and not just up.

Second, probably because of the adaptive benefits of a better field of vision for spotting predators, deer’s eyes are positioned closer to the sides of their head than the front. That means that deer, like many other prey animals, sacrifice binocular vision and depth perception to, you know, get eaten less by things behind them and to their sides. The downside is that it is more difficult for deer to judge distance and the depth of objects in front of them. Incidentally, in addition to being particularly stupid, this is one of the reasons why white-tails don’t always jump over fences they almost certainly could – poor depth perception means that they can’t be sure if they’re going to clear it.

Third, whether because of the need to manage temperatures and heat, to avoid predators, or other reasons they keep to themselves, thank you very much, white-tailed deer are crepuscular, which means they are most active in the twilight hours of dawn and dusk. That adaptation means that their vision is attuned to modest levels of light.

Like the armadillo, the combination of these natural talents has done wonders for making white-tailed deer one of the most successful and widely distributed mammal species in the world.

It also means that when a deer leaps into a road, it spots your distant car in its remarkable peripheral vision, turns its head, is blinded by your headlights because of the attunement of the rods in its eyes to take in more light, and because of its lousy visual acuity and depth perception, can’t make out the closing distance of your vehicle until it’s too late, at which time it leans upon its remarkable leaping abilities so that it can take out your windshield because screw you AND your Volvo.

Profiles in Roadkill: Sciurus carolinensis

Although the deer is the most iconic roadkill animal, it’s not the most common. The most common is the state mammal of one of the most beautiful states in our fair union, but one that admittedly only manages to have a single state mammal, so take my kind words about its trees, mountains and coastlines for the damning faint praise that they are. It’s your time to shine, Interstate 85 and North Carolina.

The 1993 data from an ongoing survey of roadkill (weirdly created for schools as a testing ground for teaching the scientific method) reported just over 750 squirrels in its sample. If anyone is curious, there were only 308 raccoons and 4 coyotes. The noble possum comes in second, at 348. Squirrels are the undisputed kings of roadkill, and yes, the extremely disappointing state mammal of the State of North Carolina. By the way, this really IS disappointing, because North Carolina could have selected one of its many legitimately interesting and endangered/threatened species, like the Carolina Northern Flying Squirrel. The state is also one of the last homes east of the Mississippi for the Townsend’s big-eared bat, which adapted a whispered form of echolocation that probably serves as a countermeasure to the active sonar jamming skills of its primary prey – moths.

Now, obviously some of the reason so many squirrels become double-thumps in the road is because – despite my efforts as a kid with a BB-gun – there are a lot of squirrels. But that’s kind of the point. There are a lot of squirrels because squirrels are a very successful species. Part of why they are a very successful species is because they are very successful at avoiding predation, mostly by hawks and other birds with a taste for tree-rat.  Part of the reason they are so successful at avoiding predation is that they adapted an instinctive tendency to run in seemingly random zig-zag motions that involve unpredictable changes in both speed and direction. Very good defense against a hawk flying at high speed toward a fixed point.

Not so much against a speeding teenager driving his mom’s Yukon.

All three of these animals are incredibly successful and still growing their geographic footprint. All three are incredibly well-adapted to the challenges that they faced over the course of their evolution. All three are well-prepared for the challenges they face in most of their daily lives. All three get dead real quick when their evolutionary strengths are transformed into circumstantial weaknesses.

Part of the reason I wrote this, the second note in this series, was to make you look at that hilarious and morbid roadside pizza party deer. That and to pursue some tortured analogy to compare you, dear reader, to roadkill. But there’s an important investment lesson here, too: Survival is the only way we measure the success of an adaptation, and the species that treats past adaptations as timeless and universal – as laws of physics – will go extinct.  

The trick is in knowing what, among all the things we do as investors, reflects timeless and universal principles, and what reflects our adaptation to states of the world which will change. It’s not always easy to tell the difference.

Timeless and Universal Principles

For my part, I think timeless and universal principles of investing must be either tautologies or generalized reflections of human behavior. Heuristics which are based on states of the world (e.g. I like this asset class because it is cheap, I favor this sector because of its growth characteristics, I’m concerned about this country because of higher-than-usual geopolitical risk) don’t really fit. Philosophies which are driven by views on the superiority of certain constructs (e.g. asset classes, instruments, etc.) are similarly ephemeral. I think there are really four timeless and universal principles, and we’ve written about each before:

  1. Over very long periods, you will generally be paid based on the risks an average investor (including all of his liquidity sensitivities, his investment horizons, etc.) would be taking if he made that investment [1]. – Whom Fortune Favors
  2. We must be supremely confident that we have information about the returns on various investments to justify decisions which reduce the diversity of our sources of return.You Still Have Made a Choice
  3. Humans have evolved to demonstrate preferences for certain types of investments and returns. Those preferences – and the fact that other humans will shrewdly seek to exploit those preferences – will influence returns.The Myth of Market In Itself
  4. Taxes, fees and transaction costs will reduce returns.Wall Street’s Merry Pranks

I think it’s a good framework. You may not, in which case you should replace it with what you think these rules are. Or y’know, by sending me an email telling me how stupid I am. Both are fine. But identifying these rules means acknowledging that all of our other philosophies are either successful adaptations OR new things we’re trying out because we are guessing they will be better suited for some future state of the world. After all, if we’re going to update our Bayesian estimates, we’ve got to have some kind of experiment.

It isn’t hard to identify beliefs and strategies that look well-adapted over the last decade, by which I mean investment strategies whose reputations have survived. Structurally owning more assets in U.S. financial markets looks well-adapted during this age of the world. So has owning more stocks in technology companies. Believing that there is no need for an investor to have a financial adviser seems like a very well-adapted trait. Aversion to any strategies which try to pick which securities will outperform. Keeping things simple with a 60/40 portfolio of stocks and bonds. Leveraged strategies. Aversion to, skepticism about and usually derisive attitudes towards hedge funds. Those of us who saw what worked in 2009 and 2010 and stuck with it as the new normal probably have a pretty confident assessment of some of our adaptations. More than a few of us and our clients have adopted some of the above as heuristics – our rules of thumb around which we generalize our investment beliefs into process.

What does treating well-adapted-looking traits like permanent states of the world look like? Below is one innocuous-looking example from social media marketing. I’ve removed any author’s name to protect the innocent.

There are good principles in here. But look at these more closely to see temporarily well-adapted traits creep in. A decade of dominance from US stock markets and low volatility has created a world of investors who now think that saying “keep things simple” and “avoid excessive diversification”, which are smart-sounding dog whistles for “just buy US large cap ETFs”, is timeless and universal advice. It’s not. And it’s going to get a lot of investors hurt.

Unfortunately, the memeability of common sense! advice like this is is exactly how an adapted trait evolves into a species-defining characteristic. Survival and reproduction. And then extinction.

Identifying the line between timeless principles and adaptations gets even harder over very long periods. 30 years. 50 years. Owning more bonds than our timeless principles might otherwise recommend. Relying on those same bonds to be diversifying against stocks. Knowing that commodities are not really investable, that real assets should just be a personal asset. Trusting that risky assets will always generate positive returns over a long enough horizon. As periods get longer, our confidence that our heuristics are not situational adaptations, but timeless and universal principles, grows.

All of this is Roadkill thinking. Oh, we may not get run over right away. It may never happen – during our investment lifetimes, anyway. We may go quietly in our sleep like so many armadillos, convinced that we adapted to survive cars just because we never got run over. But believing that the strategies we developed are timeless and universal strategies just because they’ve worked for us during our careers so far, or because they have worked for others for what feels like a very long period of time, is Roadkill thinking.

This first kind of Roadkill thinking is of the Type 1 error variety I mentioned earlier – false positives when identifying timeless and universal truths about markets.

Type 2 errors in Roadkill thinking are usually the more pernicious. It’s easy to think that the solution to our fears that an investment environment may be changing is to be creative, to throw a bunch of ideas at the wall, because that’s what we think adaptation looks like. And it is, in a way. But while adaptation through (mostly) random mutation works at the species level, at the individual level, it is literally murder. If our adaptive strategy is trying to time the turn in value or the market top, we will probably fail individually. If our adaptive strategy is to hold a quarter of our portfolio in cryptocurrencies to insulate us against what’s next, we will probably fail individually. If our adaptive strategy is to drain the swamp by…sorry, lost my train of thought, there. And sure, our failures will inform and improve the odds of success of other investors at large. A fat lot of good that does us. There’s a reason why coyotes with no skin in the game are so drawn to fields where they can promise disruption, new ideas, and high risk/high reward opportunities: because they share in all the upside of the aggregate while subjecting us to the risk of individual ruin along the way.

What does matter is that pursuit of these strategies often comes at the explicit or implicit expense of the ideas that really are permanent. We have finite dollars and finite attention, and our attempts to do something about environments that confuse us are usually distractions. In the same way that we’re probably all Coyotes from time to time, I think we’ve got a lot of Roadkill in us, too. I certainly do, anyway. There’s no extricating it from our nature, but as with so many things, simply acknowledging it goes a long way toward being mindful of its influence:

  1. Roadkill doesn’t know what its timeless and universal investment principles are.
  2. Roadkill doesn’t discern between temporarily effective adaptations and timeless principles.
  3. Roadkill randomly tries new adaptations even when they violate timeless and universal principles.

If we would not be Roadkill – or worse, food for coyotes – we would do well to subject our priors to constant challenge. What assumptions are we making about our investments, intentionally or unintentionally? What priors are built into our portfolio construction and investment selection methodologies? Are they always true, or maybe artifacts of an environment or industry convention?

For my part, were I sitting on an investment committee during a period of slowing in population growth, after a sustained long-term rally in multiple types of risk assets, following an extended period of falling interest rates, in the face of historically significant household and government debt, with increasing abstraction sitting between valuations and value, I would hold very loosely to all but my core principles. During every regular review, I would subject my conventions – sectors, style definitions, benchmarks, asset class definitions, risk measurement methodologies, and the like – to scrutiny.

More to the point, when we write about Narrative, we write in part because we believe that Common Knowledge about investment strategies and investable assets is part of what makes them work. This is our theory, and not a fact, but I think that Narrative analysis can inform earlier, less individually risky attempts at adaptation as environments change. Big if true. And I think it is.

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We had a little fun at North Carolina’s expense, but it’s a wonderful state and a wonderful place with a lot of people that are hurting – and will be hurting – for a long time. From my experience with Hurricane Harvey in Houston, there are few organizations that do as much good as the United Way. If you can, consider giving now to the United Way of Coastal Carolina. Or if you want to make amends for laughing at the balloon deer, the Outer Banks SPCA and the Dare County Animal Shelter will be in desperate need of help over the next few weeks.

[1] This is, incidentally, why I am not one of those who thinks that volatility is a terrible ex ante way of thinking about risk. If price sensitivity matters to individual investors – and it does – it matters to how the return investors will demand for taking that risk, even if that perception is completely irrational and they should be thinking about “permanent impairments to capital” or some other phrase that has survived because it sounds clever in marketing materials. My experience with investor behavior also tells me that unrealized returns often become realized when they’re big, negative numbers.


Notes from the Road: Bayes and the Boreen


I believe in American exceptionalism. Unironically. Still.

Millions of men and women over many centuries uprooted themselves from established lives of plenty and poverty alike. They bought passage or sold a portion of their futures for passage under indentures. They crossed the perilous Atlantic – and later, the Pacific – to start new lives as strangers in a strange land. Others were stripped of their freedom and sent here against their will. When they or their descendants were finally freed, a generation of millions were forced to start new lives among those who had enslaved them, who had thought them less than human.

Read moreNotes from the Road: Bayes and the Boreen