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Sometimes a Cigar is Just a Cigar

July 11, 2019May 22, 2015 by Ben Hunt

Neurosis is the inability to tolerate ambiguity.
– Sigmund Freud (1886 – 1939)

To learn which questions are unanswerable, and not to answer them: this skill is most useful in times of stress and darkness.
– Ursula K. Le Guin, “The Left Hand of Darkness” (1969)

Is everything connected, so that events create resonances like ripples across a net? Or do things merely co-occur and we give meaning to these co-occurrences based on our belief system? Lieh-tzu’s answer: it’s all in how you think.
– “The Liezi”, ancient Taoist text attributed to Lie Yukou (c. 400 BC)

Deckard:	She’s a replicant, isn’t she?
Tyrell:	I’m impressed. How many questions does it usually take to spot them?
Deckard:	I don’t get it, Tyrell.
Tyrell:	How many questions?
Deckard:	Twenty, thirty, cross-referenced.
Tyrell:	It took more than a hundred for Rachael, didn’t it?
Deckard:	[realizing Rachael believes she’s human] She doesn’t know.
Tyrell:	She’s beginning to suspect, I think.
Deckard:	Suspect? How can it not know what it is?

– “Bladerunner” (1982)

I remember when I was a very little girl, our house caught on fire.
I’ll never forget the look on my father’s face as he gathered me up
In his arms and raced through the burning building out to the pavement.
I stood there shivering in my pajamas and watched the whole world go up in flames.
And when it was all over I said to myself.
“Is that all there is to a fire?”
– Jerry Lieber and Mike Stoller, “Is That All There Is?”, as recorded by Peggy Lee (1969)

I call our world Flatland, not because we call it so, but to make its nature clearer to you, my happy readers, who are privileged to live in Space.
– Edwin A. Abbott, “Flatland: A Romance of Many Dimensions” (1884)

Homey don’t play that game.

– Damon Wayans, “In Living Color” (1992)

There’s only one question that matters today in markets: why is the government bond market going up and down like a yo-yo? How is it possible that the deepest and most important securities in the world are currently displaying all the trading stability of a biotech stock?

As with all market questions of singular importance and vast attention, these are questions of meaning. We seek the why and we seek the cause because we are desperate to understand what it means. We are – all of us – convinced that this market behavior must mean something profound. Surely this insane quivering within the bond market means that we are on the cusp of a quantum shift in the market landscape. Surely this is the rumbling of a deep tectonic plate that presages a massive earthquake. Surely, as more than one Master of the Universe proclaimed at SALT the other week, the long-awaited bear market in government debt is nigh.

Maybe. Or maybe all those Masters of the Universe are just talking their book. I know … shocking.

We are all market neurotics today, in the Freudian sense of the word, incapable of handling ambiguity in Narrative after 5+ years of global coordination and cooperation among The Monetary Powers That Be, 5+ years of being told by a monolithic Voice of Command how we should think about every single data point that crosses our Bloomberg screen. This is the most hated bull market in history, precisely because we all believe that it is a creature of policy and Narrative, and when the Voices are silent or they say conflicting things, we start to freak out. We run from pillar to post, getting whipsawed at every turn. Importantly, the whipsawing is occurring in the securities that are most closely linked to policy and Narrative – government bonds – and that’s why I believe that what we’re experiencing is more akin to neurosis than some shift in market fundamentals.

Here’s my point: volatility ≠ instability. Or more precisely, a system can be volatile or unstable in a local sense but highly stable in a global sense.

Unfortunately, however, because we live in the local rather than the global … because every bit of our modern financial services system, particularly financial media, is by business necessity focused on the local rather than the global … we are as unaware of our true positioning in the world as Rachael in “Bladerunner”. Or Deckard, who sure seems like a replicant to me. From a local perspective these bond market gyrations make it seem as if we are totally unmoored and markets are on the brink of some life-altering change. From a global perspective, however, this is a tempest in a teacup.Or to paraphrase the late, great Peggy Lee, is that all there is to a bond market fire?

Okay, Ben, that’s quite a mouthful: “unstable in a local sense but highly stable in a global sense”. Translation, please?

The Rosetta Stone here is Information Theory, and to introduce that it’s probably easiest if I quote directly and extensively from one of my very earliest Epsilon Theory notes, “Through the Looking Glass”. I wrote this almost exactly 2 years ago, back when I only had a few hundred readers, so it should be fresh for 99% of the audience. It’s a lot to digest, but I promise that you won’t see markets in the same way once you finish. Information Theory is, in fact, the beating heart of Epsilon Theory. That said, one of the beautiful things about releasing content into the wild is that readers can do with it what they will. For the TLDR / Short Attention Span Theatre crowd, click here to skip to the chase on page 10.

***

Defining the strength of a signal as the degree to which it changes assessments of future states of the world dates back to Claude Shannon’s seminal work in 1948, and in a fundamental way back to the work of Thomas Bayes in the 1700’s. Here’s the central insight of this work: information is measured by how much it changes your mind. In fact, if a signal doesn’t make you see the world differently, then it has zero information. As a corollary, the more confident you are in a certain view of the world, the more new information is required to make you have the opposite view of the world and the less information is required to confirm your initial view. There’s no inherent “truth” to any signal, no need to make a distinction between (or even think of) this signal as having true information and that signal as having false information. Information is neither true nor false. It is only more or less useful in our decision-making, and that’s a function of how much it makes us see the world differently. As a result, the informational strength of any signal is relative. The same signal may make a big difference in my assessment of the future but a tiny difference in yours. In that case, we are hearing the same message, but it has a lot of information to me and very little to you.

Let’s say that you are thinking about Apple stock but you are totally up in the air about whether the stock is going up or down over whatever your investment horizon might be, say 1 year. Your initial estimation of the future price of Apple stock is a coin toss … 50% likelihood to be higher a year from now, 50% likelihood to be lower a year from now. So you do nothing. But you start reading analyst reports about Apple or you build a cash-flow model … whatever it is that you typically do to gather information about a potential investment decision.

The graph below shows how Information Theory would represent the amount of signal information (generically represented as bits) required to change your initial assessment of a 50% likelihood of Apple stock going up over the next year to a post-signaling assessment of some new percentage likelihood. These are logarithmic curves, so even relatively small amounts of information (a small fraction of a generic bit) will change your mind about Apple pretty significantly, but more and more information is required to move your assessment closer and closer to certainty (either a 0% or a 100% perceived likelihood of the stock going up).

Of course, your assessment of Apple is not a single event and does not take place at a single point in time. As an investor you are constantly updating your opinion about every potential investment decision, and you are constantly taking in new signals. Each new update becomes the starting point for the next, ad infinitum, and as a result all of your prior assessments become part of the current assessment and influence the informational impact of any new signal.

Let’s say that your initial signals regarding Apple were mildly positive, enough to give you a new view that the likelihood of Apple stock going up in the next year is 60%. The graph below shows how Information Theory represents the amount of information required to change your mind from here. The curves are still logarithmic, but because your starting point is different it now only requires 80% of the information as before to get you to 100% certainty that Apple stock will go up in the next year (0.8 generic bits versus 1.0 generic bits with a 50% starting estimation). Conversely, it requires almost 140% of the same negative information as before to move you to certainty that Apple stock is going down.

What these graphs are showing is the information surface of your non-strategic (i.e., without consideration of others) decision-making regarding Apple stock at any given point in time. Your current assessment is the lowest point on the curve, the bottom of the informational “trough”, and the height of each trough “wall” is proportional to the information required to move you to a new assessment of the future probabilities. The higher the wall, the more information required in any given signal to get you to change your mind in a big way about Apple.

Now let’s marry Information Theory with Game Theory. What does an information surface look like for strategic decision-making, where your estimations of the future state of the world are contingent on the decisions you think others will make, and where everyone knows that everyone is being strategic?

I’m assuming we’re all familiar with the basic play of the Prisoner’s Dilemma, and if you’re not just watch any episode of Law and Order. Two criminals are placed in separate rooms for questioning by the police, and while they are both better off if they both keep silent, each is individually much better off if he rats his partner out while the partner remains silent. Unfortunately, in this scenario the silent partner takes the fall all by himself, resulting in what is called the “sucker pay-off”. Because both players know that this pay-off structure exists (and are always told that it exists by the police), the logical behavior for each player is to rat out his buddy for fear of being the sucker.

Below on the left is a classic two-player Prisoner’s Dilemma game with cardinal expected utility pay-offs as per a customary 2×2 matrix representation. Both the Row player and the Column player have only two decision choices – Rat and Silence – with the joint pay-off structures shown as (Row , Column) and the equilibrium outcome (Rat , Rat) shaded in light blue.

The same equilibrium outcome is shown below on the right as an informational surface, where both the Row and the Column player face an expected utility hurdle of 5 units to move from a decision of Rat to a decision of Silence. For a move to occur, new information must change the current Rat pay-off and/or the potential Silence pay-off for either the Row or the Column player in order to eliminate or overcome the hurdle. The shape of the informational surface indicates the relative stability of the equilibrium as the depth of the equilibrium trough, or conversely the height of the informational walls that comprise the trough, is a direct representation of the informational content required to change the conditional pay-offs of the game and allow the ball (the initial decision point) to “roll” to a new equilibrium position. In this case we have a deep informational trough, reflecting the stability of the (Rat , Rat) equilibrium in a Prisoner’s Dilemma game.

Now let’s imagine that new information is presented to the Row player such that it improves the expected utility pay-off of a future (Silence, Rat) position from -10 to -6. Maybe he hears that prison isn’t all that bad so long as he’s not a Rat. As a result the informational hurdle required by the Row player to change decisions from Rat to Silence is reduced from +5 to +1.

The (Rat , Rat) outcome is still an equilibrium outcome because neither player believes that there is a higher pay-off associated with changing his mind, but this is a much less stable equilibrium from the Row player’s perspective (and thus for the overall game) than the original equilibrium.

With this less stable equilibrium framework, even relatively weak new information that changes the Row player’s assessment of the current position utility may be enough to move the decision outcome to a new equilibrium. Below, new information of 2 units changes the perceived utility of the current Rat decision for the Row player from -5 to -7. Maybe he hears from his lawyer that the Mob intends to break his legs if he stays a Rat. This is the equivalent of “pushing” the decision outcome over the +1 informational hurdle on the Row player’s side of the (Rat , Rat) trough, and it is reflected in both representations as a new equilibrium outcome of (Silence , Rat).

This new (Silence , Rat) outcome is an equilibrium because neither the Row player nor the Column player perceives a higher expected utility outcome by changing decisions. It is still a weak equilibrium because the informational hurdle to return to (Rat , Rat) is only 1 informational unit, but all the same it generates a new behavior by the Row player: instead of ratting out his partner, he now keeps his mouth shut.

The Column player never changed decisions, but moving from a (Rat , Rat) equilibrium to a (Silence , Rat) equilibrium in this two time-period example resulted in an increase of utility from -5 to +10 (and for the Row Player a decrease from -5 to -6). This change in utility pay-offs over time can be mapped as:

Replace the words “Column Utility” with “AAPL stock price” and you’ll see what I’m going for. The Column player bought the police interrogation at -5 and sold it at +10. By mapping horizontal movement on a game’s informational surface to utility outcomes over time we can link game theoretic market behavior to market price level changes.

Below are two generic examples of a symmetric informational structure for the S&P 500 and a new positive signal hitting the market. New signals will “push” any decision outcome in the direction of the new information. But only if the new signal is sufficiently large (whatever that means in the context of a specific game) will the decision outcome move to a new equilibrium and result in stable behavioral change.

In the first structure, there is enough informational strength to the signal to overcome the upside informational wall and push the market to a higher and stable price equilibrium. In the second structure, while the signal moves the market price higher briefly, there is not enough strength to the signal to change the minds of market participants to a degree that a new stable equilibrium behavior emerges.

All market behaviors – from “Risk-On/Risk-Off” to “climbing a wall of worry” to “buying the effin’ dip” to “going up on bad news” – can be described with this informational structure methodology.

For example, here’s how “going up on bad news” works. First, the market receives a negative Event signal – a poor Manufacturing ISM report, for example – that is bad enough to move the market down but not so terrible as to change everyone’s mind about what everyone knows that everyone knows about the health of the US economy and thus move the market index to a new, lower equilibrium level.

Following this negative event, however, the market then receives a set of public media signals – a Narrative – asserting that in response to this bad ISM number the Fed is more likely to launch additional easing measures. This Narrative signal is repeated widely enough and credibly enough that it changes Common Knowledge about future Fed policy and moves the market to a new, higher, and stable level.

So what is the current informational structure for the S&P500? Well, it looks something like this:

The market equilibrium today is like a marble sitting on a glass table. It is an extremely unstable equilibrium because the informational barriers that keep the marble from rolling a long way in either direction are as low as they have been in the past five years. Even a very weak signal is enough to push the marble a long way in one direction, only to have another weak signal push it right back. This is how you get big price movements “for no apparent reason”.

Why are the informational barriers to equilibrium shifts so low today? Because levels of Common Knowledge regarding future central bank policy decisions are so low today. The Narratives on both sides of the collective decision to buy or sell this market are extremely weak. What does everyone know that everyone knows about Abenomics? Very little. What does everyone know that everyone knows about Fed tapering? Very little. What does everyone know that everyone knows about the current state of global growth? Very little. I’m not saying that there’s a lack of communication on these subjects or that there’s a lack of opinion about these subjects or that there’s a lack of knowledge about these subjects. I’m saying that there’s a lack of Common Knowledge on these subjects, and that’s what determines the informational structure of a market.

***

I wrote all that right before the Fed’s Taper Tantrum in the summer of 2013, which can be understood using this Information Theory framework as a massive public relations effort by Bernanke et al to create a new Common Knowledge structure that would shape the informational contours of the market. The immediate signal of this initial effort at “communication policy” was a big red arrow pointing left, and almost all asset classes everywhere around the world took a dive as the strong signal sent the equilibrium marble skittering to the downside across the largely flat informational surface. But the longer term effect of communication policy was just as Bernanke hoped (and as he spoke about extensively in his farewell address as Fed Chair): it built an enormous Common Knowledge “wall” off to the downside left of the market informational surface – a Fed put based not on continued asset purchases, but on continued words of Narrative influence.

Those words form the Narrative of Central Bank Omnipotence, the overwhelming belief by market participants that central bankers in general, and the Fed in particular, determine market outcomes, and for the past two years this has been the only thing that matters in markets. I’ve been tracking and studying political Narratives for my entire professional career, close to 30 years now, and I’ve never seen anything like this. It’s a heck of a trick that Bernanke started and Draghi perfected and Yellen continues, and it’s the key, I think, to seeing recent bond market turbulence in the most useful perspective.

Everything I wrote about the informational surface of the equity market in early summer 2013 is exactly applicable to the informational surface of the bond market in early summer 2015. The bond market today is like a marble sitting on a glass table. There are very few informational structures or barriers to keep the price of US bonds from skittering this way or that, within a price range as expressed in yield terms of, say, 2.25% and 1.85% on the 10-year bond. This is what always happens when the Fed comes out and says that it’s increasingly “data dependent” …our local equilibria become much less stable when the Fed says that it hasn’t made up its collective mind about the pace or scale of monetary policy shifts.

With an informational structure like this, the 10-year bond could trade anywhere on this segment of the price line. Moreover, it takes a signal with precious little information to change people’s minds about whether the US 10-year should yield 1.90% today or 2.20% tomorrow. Precious little information means just that – precious little information – and it’s a classic mistake to infer grand theories or reach sweeping conclusions on the basis of precious little information. Don’t do that.

Because here’s the thing: the informational surface is only flat in this immediate vicinity of current bond prices. There are enormous Common Knowledge walls just off to the left and just off to the right of the price line segment shown above, Common Knowledge structures created by the entirely successful efforts by central bankers to mold investor behaviors and by the entirely unsuccessful efforts by central bankers to fix the real economy.

I really can’t emphasize this point too strongly – monetary policy since March 2009 has created a phenomenally stable global equilibrium in both markets and the real economy, an equilibrium that since the summer of 2013 no longer depends on massive asset purchases by the Fed.

Does the stability of the global equilibrium require someone to be making asset purchases, if not the Fed then the ECB or BOJ? To some degree I’m sure it does. But then I remember that Draghi’s mere words and an OMT program constructed out of whole cloth were sufficient to save the Euro in the summer of 2012. My strong sense is that the launching of central bank asset purchase programs may move the entire informational structure farther along to the right of the price line (higher prices, lower yields), and vice versa leftwards along the price line if the programs stop, but they don’t diminish the Common Knowledge structures themselves. Maybe the locally unstable price range of the US 10-year as expressed in yield terms goes to 2.75% – 2.35% if the ECB were to summarily stop its asset purchase program, but I still think you have an extremely stable global informational structure on either side of that new range, whatever it is. Among market participants today there is almost unanimity of belief that central bankers Will. Not. Allow. a global recession to occur, much less a deflationary equilibrium. But at the same time there is also almost unanimity of belief that central bankers Can. Not. Create. a global recovery, much less an inflationary equilibrium. That unanimity of belief establishes a global informational equilibrium of unparalleled strength and stability, or at least unparalleled in my experience.

And that leads me to my other main point: a highly stable equilibrium cuts both ways, for good and for bad. Another way of saying that you’re in a highly stable equilibrium is to say that you’re well and truly stuck. Yes, there are HUGE informational barriers to prevent economic behaviors that would create a recession in the US or horribly crush any major market or asset class. But by the same token, there are also HUGE informational barriers to prevent economic behaviors that would spark robust growth in the US or wildly elevate any major market or asset class. I’m not saying that the doomsday or heavenly scenarios are impossible. I’m saying that it would take an almost unimaginably large amount of new information to change people’s minds about what everyone knows that everyone knows about markets today, for either scenario to occur. Could happen. But I really don’t think that’s how you want to place your bets. My money is on the long grey slog of the Entropic Ending.

I know it sounds weird for me to say that we’re living in a deep, deep valley with giant mountains on both sides of us when it feels like we’re a marble sitting on a glass table, but that’s exactly the mixed metaphor that I think accurately describes our lives as investors here in the Golden Age of the Central Banker. I know it sounds weird to think that we could be living in that deep, deep valley and yet be completely oblivious to its existence, completely convinced that the narrow field of view foisted on us day in and day out by the business imperatives of the financial services industry, especially financial media, is the only possible field of view. But myopically focused on what we are told to focus on is exactly how we humans (and replicants, too, I suppose) tend to live out our lives. Shifting our perspective to take a more global view, whether that’s on the dimension of time or emotion or, yes, asset price levels, is probably the most difficult thing any of us can hope to achieve, and it will always be an imperfect shift at best. Yet it’s never been more important to make that effort, else we allow our innate search for meaning to be subverted by mass-mediated, faux-authentic signalers that profit from making us look over here rather than over there. And I’m not just talking about market signals. It’s EVERY expression of power in the modern age – financial, political, legal, medical, etc. – that suffers from this mass-mediated form of social control, this manipulation of the Common Knowledge game. The human animal is a social animal. We are biologically evolved over millions of years to infer meaning from social signals. We swim in a sea of socially constructed signals, and we can no more ignore the words of Yellen or CNBC or a Master of the Universe than an ant can ignore the pheromones of her queen. We can’t ignore the words. But we can recognize them for what they are. We can ask ourselves “Is that all there is?” and take a more global view.

Sometimes there’s significance in signs and portents. Sometimes there’s real meaning to be gleaned from careful study of localized phenomena, from the interpretation of immediate events to generate far-reaching conclusions. Then again, sometimes a cigar is just a cigar, and that’s how I’m thinking about recent gyrations in the bond market.

One final point, perhaps the most important one I’ve got, and it’s addressed to everyone who asks questions like “so, Ben, when do you think the Fed is going to raise rates?” or “so, Ben, where do you think the price of oil goes from here?” The answer: I don’t know and I don’t really care. Seriously. These are unanswerable, entirely over-determined-in-retrospect questions, and the worst possible thing you can do with an unanswerable, entirely over-determined-in-retrospect question is to try to answer it in deterministic fashion! The popular fetish with demanding an Answer with a capital A to this sort of question is a crystallization of the market neurosis that afflicts us in the Golden Age of the Central Banker, and it’s the quickest path I know to poor investing.

What I DO care about is Adaptive Investing. What I DO care about is understanding the informational structures of the market that determine the likely market price reaction to some new signal, whether that’s a Yellen speech, an earnings report, or technical trading data. Trying to predict what that signal is going to be or when that signal is going to come is a losing proposition. Sorry, but I don’t play that game. And neither should you. My god, we need more pundit predictions about the Fed or oil prices like we need an asteroid to crash into the Earth. What we need is an investment and allocation STRATEGYfor whatever comes down the pike, whenever it occurs. That’s exactly what an Information Theory perspective on markets can provide. Take another look at this informational surface.

This graph says nothing about when and what the Fed will do. It says everything about how to THINK about the bond market in a dynamic, non-myopic way, about how to prepare for probabilistic waves of new signals and how to react once they hit. There’s an entire investment and asset allocation strategy embedded in this graph, and I think it’s the most useful contribution I can make with Epsilon Theory, far more than adding one more voice to the cacophony of Fed “predictions” that drive our collective market neurosis. We are slowly being driven nuts by the paradoxes and ambiguities of the Golden Age of the Central Banker, a maddening time in the truest sense of the word, and I don’t begrudge anyone’s coping mechanisms or business models for dealing with this clinically insane market environment. I submit, however, that our mental health and financial health are best served by taking a strategic view of markets, a view that engages with the game without succumbing blindly to it. That and a regular dose of Epsilon Theory.

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The Talented Mr. Ripley

July 11, 2019April 27, 2015 by Ben Hunt

The more I practice, the luckier I get.
– Gary Player (b. 1935)

Luck is the residue of design.
– Branch Rickey (1881 – 1965)

I’ve found that you don’t need to wear a necktie if you can hit.
– Ted Williams (1918 – 2002)

They say that nobody is perfect. Then they say that practice makes perfect. I wish they’d make up their minds.
– Wilt Chamberlain (1936 – 1999)

It took me 17 years to get 3,000 hits in baseball. I did it in one afternoon on the golf course.
– Hank Aaron (b. 1934)

Talent is cheaper than table salt. What separates the talented individual from the successful one is a lot of hard work.
– Stephen King (b. 1947)

At one time I thought the most important thing was talent. I think now that – the young man or the young woman must possess or teach himself, train himself, in infinite patience, which is to try and to try and to try until it comes right. He must train himself in ruthless intolerance. That is, to throw away anything that is false no matter how much he might love that page or that paragraph. The most important thing is insight, that is … curiosity to wonder, to mull, and to muse why it is that man does what he does. And if you have that, then I don’t think the talent makes much difference, whether you’ve got that or not.
– William Faulkner (1897 – 1962)

Talent is its own expectation, Jim: you either live up to it or it waves a hankie, receding forever.
– David Foster Wallace, “Infinite Jest” (1996)

What is most vile and despicable about money is that it even confers talent. And it will do so until the end of the world.
– Fyodor Dostoyevsky (1821 – 1881)

Talent is a long patience, and originality an effort of will and intense observation.
– Gustave Flaubert (1821 – 1880)

There is nothing more deceptive than an obvious fact.
– Arthur Conan Doyle, “The Boscombe Valley Mystery” (1891)

Sheriff Metzger:	Mrs. Fletcher! Can I see you for a minute? [pause] Do me a favor, please, and tell me what goes on in this town!
Jessica Fletcher:	I’m sorry, but …
Sheriff Metzger:	I’ve been here one year, and this is my fifth murder. What is this, the death capital of Maine? On a per capita basis this place makes the South Bronx look like Sunny Brook farms!
Jessica Fletcher:	But I assure you, Sheriff …
Sheriff Metzger:	I mean, is that why Tupper quit? He couldn’t take it anymore? Somebody really should’ve warned me, Mrs. Fletcher. Now, perfect strangers coming to Cabot Cove to die? I mean look at this guy! You don’t know him, I don’t know him. He has no ID, we don’t know the first thing about this guy.

– “Murder, She Wrote: Mirror, Mirror, on the Wall: Part 1” (1989)

Dr. Yen Lo: His brain has not only been washed, as they say … It has been dry cleaned.
– “The Manchurian Candidate” (1962)

Dickie Greenleaf:	Everyone should have one talent. What’s yours?
Tom Ripley:	Forging signatures, telling lies … impersonating practically anybody.
Dickie Greenleaf:	That’s three. Nobody should have more than one talent.

– “The Talented Mr. Ripley” (1999)

My singular talent is seeing patterns that others don’t. That’s not a boast, but a fact, and frankly it’s been as much a source of alienation in my life as a source of success. As my father was fond of saying, “You know, Ben, if you’re two steps ahead it’s like you’re one step behind.” I can’t explain how I see the patterns – they just emerge from the fog if I stare long enough. It’s always been that way for me, for as far back as I have memories, and whether I’m 5 years old or 50 years old I’m always left with the same realization: I only see the pattern when I start asking the right question, when I allow myself to be, as Faulkner said, “ruthlessly intolerant” of anything that proves false under patient and curious observation.

For example, I think the wrong question for anyone watching “Murder, She Wrote” is: whodunit? The right question is: how does Jessica Fletcher get away with murder this time? Once you recognize that it’s a Bayesian certainty that the woman is a serial killer, that she controls the narrative of Cabot Cove (both figuratively as a crime novelist and literally as a crime investigator) and thus the behavior of everyone around her, you will discover a new appreciation for both the subliminal drivers of the show’s popularity as well as the acting genius of Angela Lansbury. Seriously, go back and watch the original “Manchurian Candidate” and focus on Lansbury. She’s a revelation.

Or take the Masters tournament earlier this month. I was lucky enough to attend Wednesday’s practice round, and I was sitting in a shady spot on the 10th green watching the players come by and try their luck at 15 foot putts. At first, like the other spectators, my question was: how are they such good putters? This was “the obvious fact,” to quote Sherlock Holmes, and I watched for any clues that I could adopt for my laughable game – a forward tilt of the wrist, a stance adjustment … anything, really. We all watched carefully and we all dutifully oohed and aahed when the ball occasionally dropped in the cup. But suddenly, a new pattern emerged from the fog, and I realized that we were all asking the wrong question. Instead, I started to ask myself, why are they such poor putters?

Now I realize that I just alienated at least half of the reading audience, but bear with me. I’m not saying that professional golfers are poor putters compared to you or me. Of course not. They are miracle workers compared to you or me. But it’s a stationary ball with a green topography that never changes. The speed of the greens is measured multiple times a day to the nth degree. These players have practiced putting for thousands of hours. They have superior eyesight, amazing muscular self-awareness, and precision equipment. And yet … after charting about 50 putts in the 12 – 15 foot range, the pattern of failure was unmistakable. These professional golfers were aiming at a Point A, but they would have sunk exactly as many putts if the cup had actually been located 6 inches to the right. Or 6 inches to the left. Or 12 inches back. Or 12 inches forward. The fact that a putt actually went in the hole from a distance of 12 – 15 feet was essentially a random event within a 15 x 30 inch oval, with distressingly fat probabilistic tails outside that oval. This from the finest golf players in the world. I saw Ben Crenshaw, a historically great putter who was playing in something like his 44th Masters and probably knows the 10th green better than any other living person, miss a long putt by 6 feet.

But here’s the thing. When a player took a second putt from the same location, or even close to the same location, his accuracy increased by well more than an order of magnitude. Suddenly the ball had eyes. So I went to the practice green, where I saw Jordan Spieth putt ball after ball from exactly the same location about 10 feet from the hole. He made 50 in a row before I got tired of watching. Now granted, Spieth is a wizard with the putter, a lot like Tiger was at the same age. See it; make it. But then I watched one of the no-name amateurs for a while, a guy who had no chance of making the cut, and it was exactly the same thing – putt after putt after putt rolled in from the same spot at a considerable distance.

The best golfers in the world are surprisingly poor aimers. Surprising to me, anyway. They are pretty miserable predictors of where a de novo putt is going to end up, even though we all believe that they are wonderful at this activity. But they are phenomenally successful and adaptive learners, even though we rarely focus on this activity.

I think the same pattern exists in other areas of the sports world. Take basketball free throws. I’d be willing to make a substantial bet that whatever a professional’s overall free throw shooting percentage might be – whether it’s DeAndre Jordan at 50% or Steph Curry at 90% – their shooting percentage on the second of two free throws is better at a statistically significant level than their shooting percentage on the first of two free throws. I have no idea where to access this data, but with the ubiquitous measurement of every sports function and sub-function I’m certain it must exist. Someone give Nate Silver or Zach Lowe a call!

I think the same pattern exists in the investing world, too. We are remarkably poor aimers and predictors of market outcomes, even though we collectively spend astronomical sums of money and time engaged in this activity, and even though we collectively ooh and aah over the professional who occasionally sinks one of these long putts. True story … in 2008 the long/short equity hedge fund that I co-managed was up nicely, and we were deluged by investors and allocators asking the wrong question: how did you have such a great year? At no point did anyone ask the right question: given your fundamental views and avowed process, why weren’t you up twice as much? Most investors, just like the spectators at Augusta, are asking the wrong questions … questions that conflate performance with talent, and questions that underestimate the role of process and learning in translating talent into performance.

I’m not saying that idiosyncratic talent doesn’t exist or that it isn’t connected to performance or that it can’t be identified. What I’m saying is that it’s as rare as Jordan Spieth. What I’m saying is that the talents that are most actionable in the investment world are not found in the predictions and the aiming of a single person. They are found within the learned and practiced behaviors that exist across a broad group of investment professionals. Jordan Spieth is a very talented putter and he works very hard at his craft. But there is no individual golf pro, not even Jordan Spieth, who I would trust with my life’s savings to make a single 15 foot putt. On the other hand, I would absolutely put my life’s savings on the line if I could invest in the process by which all golf pros practice their putting. I am far more interested in identifying the learned behaviors of a mass of investment professionals than I am in identifying a specific investment professional who might or might not be able to sink his next long putt.

What’s the biggest learned behavior of professionals in the investing world right now? Simple: QE works. Not for the real economy– I don’t know any professional investor who believes that the trillions of dollars in Fed balance sheet expansion has done very much at all for the real economy – but for the inflation of financial asset prices. This is what I’ve called the Narrative of Central Bank Omnipotence, the overwhelmingly powerful common knowledge that central bank policy determines market outcomes. The primary manifestation of this learned behavior today is to go long Europe financial assets … stocks, bonds, whatever. QE worked for US markets – that’s the lesson – and everyone who learned that lesson is applying it now in Europe. China, too. Here’s a great summary of this common knowledge position from a market Missionary, Deutsche Bank’s Chief International Economist Torsten Slok:

In my view, every asset allocation team in the world should have this chart hanging on their wall. Based on forward OIS curves the market expects the Fed to hike in March 2016 and the ECB to hike in December 2019. A year ago, the expectation was that the Fed and the ECB would both hike in November 2016. This discrepancy has significant relative value implications for FX, equities and rates. EURUSD should continue to go down and European equities will look attractive for many more years. Another consequence of this chart is that with ECB rates at zero for another five years, many European housing markets should continue to do well. The investment implication is clear: Expect that the benefits we have seen of QE in the US over the past 3 to 5 years will be playing out in Europe over the coming 3 to 5 years. – Torsten Slok, Deutsche Bank Chief International Economist, April 9, 2015

Just as a recap on how to play the Common Knowledge Game effectively, the goal here is to read Torsten’s note for its description and creation of common knowledge (information that everyone thinks that everyone has heard), not to evaluate it for Truth with a capital T. That’s the mistake many investors make when they read something like this … they start thinking about whether or not they personally agree with the Fed hike expectations embodied in forward OIS curves, or whether or not they personally agree with Torsten’s macroeconomic predictions on things like the European housing market, or whether or not they personally agree with the social value of the Fed or ECB policies that are impacting markets. In the Common Knowledge Game, fundamentals – whether they are of the stock-picking sort or the macroeconomic sort – don’t matter a whit, and your personal view of those fundamentals matters even less. The only thing that matters is whether or not the QE-works lesson has been absorbed by the learning process of investment professionals, and that’s driven by the lesson’s transformation into common knowledge by Missionaries like Torsten. From that perspective I don’t think there’s any doubt that what Torsten is saying is true, not with a capital T but with a little t, and that the long-Europe-because-of-ECB-QE trade has got a lot of behavioral life left to it.

One last point … I know that I’m a broken record in the fervency and persistence of my belief that Big Data is going to rock the foundations of the investment world, but this topic of talent, learning, and asking the right question is just too on-point for me to let it slide. I started this note with the alienating observation that I don’t believe that professional golfers are particularly good putters, certainly not in their ability to size up and sink a de novo putt from 15 feet or more. On the other hand, I am pretty certain that with a few months and a few million dollars, it’s possible to build a mobile robotic system with the appropriate sensors and mechanical tolerances that would sink pretty much every de novo putt it took from a distance of 15 feet. Or a robotic system that would hit 99% of its free throws. Machines are far more accurate aimers and more precise estimators of the environment than humans, and that’s a useful observation whether we’re talking about sports or investing.

But that’s not my point about Big Data. My point about Big Data is that such systems are ALSO better than humans at learning. They are ALSO better than humans at pattern recognition. I can remember when this wasn’t the case. As recently as 20 years ago you could read artificial intelligence textbooks that praised the computer’s ability to process information quickly with various backhanded compliments … yes, isn’t it amazing how wonderfully a computer can sort through a list, but of course only a human brain can perform tasks like facial recognition … yes, isn’t it amazing how many facts a computer can store in its memory chips, but of course only a human brain can truly learn those facts by placing them within the proper context. We have entire social systems – like sports and markets – that are designed to reward humans who are superior learners and pattern recognizers. Why in the world would we believe that clever and observant humans will continue to maintain their primacy in these fields when challenged by non-human intelligences that are, quite literally, god-like in their analytical talents and ruthless intolerance of what is false? At least in sports it’s illegal to have non-human participants … honestly, I can see a day where investing is reduced to sport, where we maintain human-only markets as part of a competitive entertainment system rather than as a fundamental economic endeavor. In some respects I think we’re already there.

I’ll close with a teaser. There’s still a path for humans to maintain an important role, even if it’s not a uniformly dominant role, within markets that we share with non-human intelligences. Humans are more likely than non-human intelligences to ask the right question within social systems, like markets, that are dominated by strategic interactions (i.e., games). That’s not because non-human intelligences are somehow thinking in an inferior fashion or aren’t asking questions at all. No, it’s because Big Data systems are giant Induction Machines, designed to ask ALL of the questions. The distinction between asking the right question and asking all of the questions is always interesting and occasionally vital, depending on the circumstances. More on this to come in future notes, and hopefully in a future investment strategy …

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It’s Still Not About the Nail

July 11, 2019April 14, 2015 by Ben Hunt

Reader reaction to the March 31 Epsilon Theory note, “It’s Not About the Nail”, was probably the strongest and most positive for any note to date. The message in a nutshell: financial advisors of all stripes and sizes would be well-served to do more than serve up old-school diversification platitudes in this Brave New World of a bull market that everyone hates, and the behavioral insights of regret minimization are an effective framework for making that adaptation.

This is a message that bears repeating, and thanks to Institutional Investor that’s what’s happening. A condensed version of “It’s Not About the Nail” can be found on the Institutional Investor website here, that piece will appear in the print magazine later this month in their “Unconventional Wisdom” column, and I’ve appended it below.

I think the reason this message strikes a chord is that it not only puts into words what a lot of people are feeling in an inchoate fashion, but also suggests a toolkit for improving the strained dialog between advisors and investors. It’s possible to take our tried and tested (but tired) notions of portfolio construction and energize them with the tools of game theory and behavioral economics, so that we get to the meaning of words like “diversification” and “de-risking”.

In the note I presented one way of thinking about all this in simple graphical terms, by taking the historical risk and reward of a portfolio or a subset of a portfolio and just seeing what the impact of a diversifying strategy would actually have been as seen in risk/reward space.

The goal here is to move the original portfolio (the gold ball) up and to the left into the green triangle that marries both the traditional meaning of diversification (maximization of reward per unit of risk) and the behavioral meaning of de-risking in a bull market (minimization of the risk of underperformance). There ARE strategies that accomplish this goal, but the trick is finding the strategies that do this for the actual portfolio you have today, not some hypothetical portfolio or index.

We’ve built a set of tools at Salient within our systematic strategies group to analyze the historical impact of a wide range of diversifying strategies from a wide range of asset managers on actual portfolios, and then to map the impact of various diversifying strategies in risk/reward space. It’s not rocket science, and I’m sure any number of Epsilon Theory readers could develop a similar toolkit, but we’ve found it to be a very useful process for not only evaluating, but also communicating how diversifying strategies can make an existing portfolio better for an investor’s needs. Sometimes Salient strategies show up well in this analysis; sometimes they don’t. If you’re familiar with the Progressive Car Insurance commercials with Flo, you get the idea.

If you’re an investment professional and/or financial advisor with a portfolio you’d like to have analyzed in this manner, reply to this email or drop me a note at [email protected] , and I’d be delighted to set it up for you.

As with all things Epsilon Theory-related, there’s no fee or obligation associated with this analysis. Thanks again to my partners and colleagues here at Salient for their commitment to releasing useful intellectual property into the wild. I think it’s a smart, non-myopic view of what it means to be an asset manager in the modern age, but a rare bird nonetheless.

All the best,
Ben

Institutional Investor – “Unconventional Wisdom”, April 5, 2015
Bull Session: How to Derisk in a Bull Market

There’s a massive disconnect between advisors and investors today, and it’s reflected in both declining investment activity as well as a general fatigue with the consultant-client conversation. Consultants continue to preach the faith of diversification, and their clients continue to genuflect in its general direction. But diversification as it’s currently preached is perhaps the most oversold concept in financial advisor-dom, and the sermon isn’t connecting. Fortunately, behavioral economics offers a fresh perspective on portfolio construction, one that lends itself to what we call Adaptive Investing.

Investors aren’t asking for diversification, which isn’t that surprising after six years of a bull market. Investors only ask for diversification after the fire, as a door-closing exercise when the horse has already left the burning barn. What’s surprising is that investors are asking for de-risking, similar in some respects to diversification but different in crucial ways. What’s also surprising is that investors are asking for de-risking rather than re-risking, which is what you’d typically expect at this stage of such a powerful bull market.

Why is this the most mistrusted bull market in recorded history? Because no one thinks it’s real. Everyone believes that it’s a by-product of outrageously extraordinary monetary policy actions rather than the by-product of fundamental economic growth and productivity — and what the Fed giveth, the Fed can taketh away.

This is a big problem for the Federal Reserve, as its efforts to force greater risk-taking in markets through large-scale asset purchases and quantitative easing have failed to take hold in investor hearts and minds. Yes, we’re fully invested, but just because we have to be. To paraphrase the old saying about beauty, risk-taking is only skin deep for today’s investor, but risk-aversion goes clear to the bone.

It’s also the root of our current adviser-investor malaise. How so? Because de-risking a bull market is a very different animal than de-risking a bear market. As seen through the lens of behavioral economics, de-risking is based on regret minimization (not risk–reward maximization like diversification), and the simple fact is that regret minimization is driven by peer comparisons in a bull market. In a bear market your primary regret — the thing you must avoid at all costs — is ruin, and that provokes a very direct physical reaction. You can’t sleep. And that’s why de-risking Rule No. 1 in a bear market is so simple: Sell until you can sleep at night. Go to cash.

In a bull market, your primary regret is looking or feeling stupid, and that provokes a very conflicted, very psychological reaction. You want to de-risk because you don’t understand this market, and you’re scared of what will happen when the policy ground shifts. But you’re equally scared of being tagged “a panicker” and missing “the greatest bull market of this or any other generation.” And so you do nothing. You avoid making a decision, which means you also avoid the consultant-client conversation. Ultimately everyone — advisor and investor alike — looks to blame someone else for their own feelings of unease. No one’s happy, even as the good times roll.

So what’s to be done? Is it possible to both de-risk a portfolio and satisfy the regret minimization calculus of a bull market?

In fact, our old friend diversification is the answer, but not in its traditional presentation as a cure-all bromide. Diversification can certainly de-risk a portfolio by turning down the volatility, and it’s well suited for a bull market because it can reduce volatility without reducing market exposure. The problem is that diversification can take a long time to prove itself, and that’s rarely acceptable to investors who are seeking the immediate portfolio impact of de-risking, whether it’s the bear market or bull market variety.

What we need are diversification strategies that can react quickly. That brings me back to adaptive investing, which has two relevant points for de-risking in a bull market.

First, your portfolio should include allocations to strategies that can go short. If you’re de-risking a bull market, you need to make money when you’re right, not just lose less money. Losing less money pays off over the long haul, but the path can be bumpy.

Second, your portfolio should include allocations to trend-following strategies, which keep you in assets that are working and get you out of those that aren’t. The market is always right, and that’s never been more true — or more difficult to remember — than now in the Golden Age of the Central Banker.

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It’s Not About the Nail

July 11, 2019March 31, 2015 by Ben Hunt

Do, or do not. There is no try.”

– Yoda, “Star Wars: Episode V – The Empire Strikes Back” (1980)

I see it all perfectly; there are two possible situations – one can either do this or that. My honest opinion and my friendly advice is this: do it or do not do it – you will regret both.
– Soren Kierkegaard, “Either/Or: A Fragment of Life” (1843)

The only victories which leave no regret are those which are gained over ignorance.
– Napoleon Bonaparte (1769 – 1821)

Maybe all one can do is hope to end up with the right regrets.
– Arthur Miller, “The Ride Down Mt. Morgan” (1991)

Of all the words of mice and men, the saddest are, “It might have been.”
– Kurt Vonnegut, “Cat’s Cradle” (1963)

One can’t reason away regret – it’s a bit like falling in love, fall into regret.
– Graham Greene, “The Human Factor” (1978)

I bet there’s rich folks eatin’

In a fancy dining car.

They’re probably drinkin’ coffee

And smokin’ big cigars.

Well I know I had it comin’.

I know I can’t be free.

But those people keep-a-movin’

And that’s what tortures me.

– Johnny Cash, “Folsom Prison Blues” (1955)

Regrets…I’ve had a few.

But then again, too few to mention.

– Paul Anka, Frank Sinatra “My Way” (1969)

The Moving Finger writes; and, having writ,
Moves on: nor all thy Piety nor Wit
Shall lure it back to cancel half a Line,
Nor all thy Tears wash out a Word of it.
– Omar Khayyam, “Rubaiyat” (1048 – 1141)

You can tell it any way you want but that’s the way it is. I should of done it and I didn’t. And some part of me has never quit wishin’ I could go back. And I can’t. I didn’t know you could steal your own life. And I didn’t know that it would bring you no more benefit than about anything else you might steal. I think I done the best with it I knew how but it still wasn’t mine. It never has been.”
– Cormac McCarthy, “No Country for Old Men” (2005)

Jesse:	Yeah, right, well, great. So listen, so here’s the deal. This is what we should do. You should get off the train with me here in Vienna, and come check out the capital.
Celine:	What?
Jesse:	Come on. It’ll be fun. Come on.
Celine:	What would we do?
Jesse:	Umm, I don’t know. All I know is I have to catch an Austrian Airlines flight tomorrow morning at 9:30 and I don’t really have enough money for a hotel, so I was just going to walk around, and it would be a lot more fun if you came with me. And if I turn out to be some kind of psycho, you know, you just get on the next train. Alright, alright. Think of it like this: jump ahead, ten, twenty years, okay, and you’re married. Only your marriage doesn’t have that same energy that it used to have, y’know. You start to blame your husband. You start to think about all those guys you’ve met in your life and what might have happened if you’d picked up with one of them, right? Well, I’m one of those guys. That’s me, y’know, so think of this as time travel, from then, to now, to find out what you’re missing out on. See, what this really could be is a gigantic favor to both you and your future husband to find out that you’re not missing out on anything. I’m just as big a loser as he is, totally unmotivated, totally boring, and, uh, you made the right choice, and you’re really happy.
Celine:	Let me get my bag.

– Richard Linklater, “Before Sunrise” (1995)

For it falls out
That what we have we prize not to the worth
Whiles we enjoy it, but being lacked and lost,
Why, then we rack the value, then we find
The virtue that possession would not show us
While it was ours.
– William Shakespeare, “Much Ado About Nothing” (1612)

When to the sessions of sweet silent thought
I summon up remembrance of things past,
I sigh the lack of many a thing I sought,
And with old woes new wail my dear time’s waste:
– William Shakespeare, “Sonnet 30” (1609)

No, I don’t have a gun.

– Nirvana, “Come As You Are” (1992)

I spend a lot of my time speaking with investors and financial advisors of all stripes and sizes, and here’s what I’m hearing, loud and clear. There’s a massive disconnect between advisors and investors today, and it’s reflected in both declining investment activity as well as a general fatigue with the advisor-investor conversation. I mean “advisor-investor conversation” in the broadest possible context, a context that should be recognizable to everyone reading this note. It’s the conversation of a financial advisor with an individual investor client. It’s the conversation of a consultant with an institutional investor client. It’s the conversation of a CIO with a Board of Directors. It’s the conversation of many of us with ourselves. The wariness and weariness associated with this conversation runs in both directions, by the way.

Advisors continue to preach the faith of diversification, and investors continue to genuflect in its general direction. But the sermon isn’t connecting. Investors continue to express their nervousness with the market and dissatisfaction with their portfolio performance, and advisors continue to nod their heads and say they understand. It reminds me of Jason Headley’s brilliant short film, “It’s Not About the Nail”, with the advisor reprising Headley’s role. Yes, the advisor is listening. But most find it impossible to get past what they believe is the obvious answer to the obvious problem. Got a headache? Take the nail out of your head. Nervous about the market? Diversify your portfolio. But there are headaches and then there are headaches. There is nervousness and then there is nervousness. It’s not about the nail, and the sooner advisors realize this, the sooner they will find a way to reconnect with their clients. Even if it’s just a conversation with yourself.

Investors aren’t asking for diversification, which isn’t that surprising after 6 years of a bull market. Investors never ask for diversification after 6 years of a bull market. They only ask for it after the Fall, as a door-closing exercise when the horse has already left the burning barn. What’s surprising is that investors are asking for de-risking, similar in some respects to diversification but different in crucial ways. What’s surprising is that investors are asking for de-risking rather than re-risking, which is what you’d typically expect at this stage of such a powerful bull market.

Investors are asking for de-risking because this is the most mistrusted bull market in recorded history, a market that seemingly everyone wants to fade rather than press. Why? Because no one thinks this market is real. Everyone believes that it’s a by-product of outrageously extraordinary monetary policy actions rather than the by-product of fundamental economic growth and productivity, and what the Fed giveth … the Fed can taketh away.

This is a big problem for the Fed, as their efforts to force greater risk-taking in markets through LSAP and QE (and thus more productive risk-taking, or at least inflation, in the real economy) have failed to take hold in investor hearts and minds. Yes, we’re fully invested, but only because we have to be. To paraphrase the old saying about beauty, risk-taking is only skin deep for today’s investor, but risk-aversion goes clear to the bone.

It’s also the root of our current advisor-investor malaise. De-risking a bull market is a very different animal than de-risking a bear market. And neither is the same as diversification.

Let’s take that second point first.

Here’s a simple representation of what diversification looks like, from a risk/reward perspective.

For illustrative purposes only.

The gold ball is whatever your portfolio looks like today from a historical risk/reward perspective, and the goal of diversification is to move your portfolio up and to the left of the risk/reward trade-off line that runs diagonally through the current portfolio position. Diversification is all about increasing the risk/reward balance, about getting more reward per unit of risk in your portfolio, and the goodness or poorness of your diversification effort is defined by how far you move your portfolio away from that diagonal line. In fact, as the graph below shows, each of the Good Diversification outcomes are equally good from a risk/reward balance perspective because they are equally distant from the original risk/reward balance line, and vice versa for the Poor Diversification outcomes.

For illustrative purposes only.

Diversification does NOT mean getting more reward out of your portfolio per se, which means that some Poor Diversification changes to your portfolio will outperform some Good Diversification changes to your portfolio over time (albeit with a much bumpier ride).

For illustrative purposes only.

It’s an absolute myth to say that any well-diversified portfolio will outperform all poorly diversified portfolios over time. But it’s an absolute truth to say that any well-diversified portfolio will outperform all poorly diversified portfolios over time on a risk-adjusted basis. If an investor is thinking predominantly in terms of risk and reward, then greater diversification is the slam-dunk portfolio recommendation. This is the central insight of Harry Markowitz and his modern portfolio theory contemporaries, and I’m sure I don’t need to belabor that for anyone reading this note.

The problem is that investors are not only risk/reward maximizers, they are also regret minimizers (see Epsilon Theory notes “Why Take a Chance” and “The Koan of Donald Rumsfeld” for more, or read anything by Daniel Kahneman). The meaning of “risk” must be understood as not only as the other side of the reward coin, but also as the co-pilot of behavioral regret. That’s a mixed metaphor, and it’s intentional. The human animal holds two very different meanings for risk in its brain simultaneously. One notion of risk, as part and parcel of expected investment returns and the path those returns are likely to take, is captured well by the concept of volatility and the toolkit of modern economic theory. The other, as part and parcel of the psychological utility associated with both realized and foregone investment returns, is captured well by the concepts of evolutionary biology and the toolkit of modern game theory.

The problem is that diversification can only be understood as an exercise in risk/reward maximization, has next to nothing to say about regret minimization, and thus fails to connect with investors who are consumed by concerns of regret minimization. This fundamental miscommunication is almost always present in any advisor-investor conversation, but it is particularly pernicious during periods of global debt deleveraging as we saw in the 1870’s, the 1930’s, and today. Why? Because the political consequences of that deleveraging create investment uncertainty in the technical, game theoretic sense, an uncertainty which is reflected in reduced investor confidence in the efficacy of fundamental market and macroeconomic factors to drive market outcomes. In other words, the rules of the investment game change when politicians attempt to maintain the status quo – i.e., their power – when caught in the hurricane of a global debt crisis. That’s what happened in the 1870’s. That’s what happened in the 1930’s. And it’s darn sure happening today. We all feel it. We all feel like we’ve entered some Brave New World where the old market moorings make little sense, and that’s what’s driving the acute anxiety expressed today by investors both large and small. Recommending old-school diversification techniques as a cure-all for this psychological pain isn’t necessarily wrong. It probably won’t do any harm. But it’s not doing anyone much good, either. It’s not about the nail.

On the other hand, the concept of de-risking has a lot of meaning within the context of regret minimization, which makes it a good framework for exploring a more psychologically satisfactory set of portfolio allocation recommendations. But to develop that framework, we need to ask what drives investment regret. And just as we talk about different notions of volatility-based portfolio constructions under different market regimes, so do we need to talk about different notions of regret-based portfolio constructions under different market regimes.

Okay, that last paragraph was a bit of a mouthful. Let me skip the academic-ese and get straight to the point. In a bear market, regret minimization is driven by existential concerns. In a bull market, regret minimization is driven by peer comparisons.

In a bear market your primary regret – the thing you must avoid at all costs – is ruin, and that provokes a very direct, very physical reaction. You can’t sleep. And that’s why Rule #1 of de-risking in a bear market is so simple: sell until you can sleep at night. Go to cash. Here’s what de-risking in a bear market looks like, as drawn in risk/reward space.

For illustrative purposes only.

Again, the gold ball is whatever your portfolio looks like today from a historical risk/reward perspective. De-risking means moving your portfolio to the left, i.e. a lower degree of risk. The question is how much reward you are forced to sacrifice for that move to the left. Perfect De-Risking sacrifices zero performance. Good luck with that if you are reducing your gross exposure. Average De-Risking is typically accomplished by selling down your portfolio in a pro rata fashion across all of your holdings, and that’s a simple, effective strategy. Good De-Risking and Poor De-Risking are the result of active choices in selling down some portion of your portfolio more than another portion of your portfolio, or – if you don’t want to go to cash – replacing something in your portfolio that’s relatively volatile with something that’s relatively less volatile.

In a bull market, on the other hand, your primary regret is looking or feeling stupid, and that provokes a very conflicted, very psychological reaction. You want to de-risk because you don’t understand this market, and you’re scared of what will happen when the policy ground shifts. But you’re equally scared of being tagged with the worst possible insults you can suffer in our business: “you’re a panicker” … “you missed the greatest bull market of this or any other generation”. Again, maybe this is a conversation you’re having with yourself (frankly, that’s the most difficult and conflicted conversation most of us will ever have). And so you do nothing. You avoid making a decision, which means you also avoid the advisor-investor conversation. Ultimately everyone, advisor and investor alike, looks to blame someone else for their own feelings of unease. No one’s happy, even as the good times roll.

So what’s to be done? Is it possible to both de-risk a portfolio and satisfy the regret minimization calculus of a bull market?

Through the lens of regret minimization, here’s what de-risking in a bull market looks like, again as depicted in risk/reward space:

For illustrative purposes only.

Essentially you’ve taken all of the bear market de-risking arrows and moved them 45 degrees clockwise. What would be Perfect De-Risking in a bear market is only perceived as average in a bull market, and many outcomes that would be considered Good Diversification in pure risk/reward terms are seen as Poor De-Risking. I submit that this latter condition, what I’ve marked with an asterisk in the graph above, is exactly what poisons so many advisor-investor conversations today. It’s a portfolio adjustment that’s up and to the left from the diagonal risk/reward balance line, so you’re getting better risk-adjusted returns and Good Diversification – but it’s utterly disappointing in a bull market as peer comparison regret minimization takes hold. It doesn’t even serve as a Good De-Risking outcome as it would in a bear market.

Now here’s the good news. There are diversification outcomes that overlap with the bull market Good De-Risking outcomes, as shown in the graph below. In fact, it’s ONLY diversification strategies that can get you into the bull market Good De-Risking area. That is, typical de-risking strategies look to cut exposure, not replace it with equivalent but uncorrelated exposure as diversification strategies do, and you’re highly unlikely to improve the reward profile of your portfolio (moving up vertically from the horizontal line going through the gold ball) by reducing gross exposure. The trick to satisfying investors in a bull market is to increase reward AND reduce volatility. I never said this was easy.

For illustrative purposes only.

The question is … what diversification strategies can move your portfolio into this promised land? Also (as if this weren’t a challenging enough task already), what diversification strategies can work quickly enough to satisfy a de-risking calculus? Diversification can take a long time to prove itself, and that’s rarely acceptable to investors who are seeking the immediate portfolio impact of de-risking, whether it’s the bear market or bull market variety.

What we need are diversification strategies that can act quickly. More to the point, we need strategies that can react quickly, all while maintaining a full head of steam with their gross exposure to non-correlated or negatively-correlated return streams. This is at the heart of what I’ve been calling Adaptive Investing.

Epsilon Theory isn’t the right venue to make specific investment recommendations. But I’ll make three general points.

First, I’d suggest looking at strategies that can go short. If you’re de-risking a bull market, you need to make money when you’re right, not just lose less money. Losing less money pays off over the long haul, but the long haul is problematic from a regret-based perspective, which tends to be quite path-sensitive. Short positions are, by definition, negatively correlated to the thing that they’re short. They have a lot more oomph than the non-correlated or weakly-correlated exposures that are at the heart of most old-school diversification strategies, and that’s really powerful in this framework. Of course, you’ve got to be right about your shorts for this to work, which is why I’m suggesting a look at strategies that CAN go short as an adaptation to changing circumstances, not necessarily strategies that ARE short as a matter of habit or requirement.

Second, and relatedly, I’d suggest looking at trend-following strategies, which keep you in assets that are working and get you out of assets that aren’t (or better yet, allow you to go short the assets that aren’t working). Trend-following strategies are inherently behaviorally-based, which is near and dear to the Epsilon Theory heart, and more importantly they embody the profound agnosticism that I think is absolutely critical to maintain when uncertainty rules the day and fundamental “rules” change on political whim. Trend-following strategies are driven by the maxim that the market is always right, and that’s never been more true – or more difficult to remember – than here in the Golden Age of the Central Banker.

Third, these graphs of portfolio adjustments in risk/reward space are not hypothetical exercises. Take the historical risk/reward of your current portfolio, or some portion of that portfolio such as the real assets allocation, and just see what the impact of including one or more liquid alternative strategies would be over the past few years. Check out what the impact on your portfolio would be since the Fed and the ECB embarked on divergent monetary policy courses late last summer, creating an entirely different macroeconomic regime. Seriously, it’s not a difficult exercise, and I think you’ll be surprised at what, for example, a relatively small trend-following allocation can do to de-risk a portfolio while still preserving the regret-based logic of managing a portfolio in a bull market. For both advisors and investors, this is the time to engage in a conversation about de-risking and diversification, properly understood as creatures of regret minimization as well as risk/reward maximization, rather than to avoid the conversation. As the old saying goes, risk happens fast. Well … so does regret.

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Ghost in the Machine, Part 1

July 11, 2019January 20, 2015 by Ben Hunt

The way out is through the door. Why is it that no one will use this method?
― Confucius (551 – 479 BC)

Tanzan and Ekido were once traveling together down a muddy road. A heavy rain was still falling. Coming around a bend, they met a lovely girl in a silk kimono and sash, unable to cross the intersection.
“Come on, girl,” said Tanzan at once. Lifting her in his arms, he carried her over the mud.
Ekido did not speak again until that night when they reached a lodging temple. Then he could no longer restrain himself. “We monks don’t go near females,” he told Tanzan, “especially not young and lovely ones. It is dangerous. Why did you do that?”
“I left the girl there,” said Tanzan. “Are you still carrying her?”
― Nyogen Senzaki, “Zen Flesh, Zen Bones: A Collection of Zen and Pre-Zen Writings” (1957)

In 1995, David Justice had a superior batting average to Derek Jeter (.253 to .250)
In 1996, David Justice had a superior batting average to Derek Jeter (.321 to .314)
In 1997, David Justice had a superior batting average to Derek Jeter (.329 to .291)
Yet from 1995 – 1997, Derek Jeter had a superior batting average to David Justice (.300 to .298)
― example of Simpson’s Paradox, aka The Yule-Simpson Effect (1951)

A student says, “Master, please hand me the knife,” and he hands the student the knife, blade first. “Please give me the other end,” the student says. And the master replies, “What would you do with the other end?”
― Alan W. Watts, “What Is Zen?” (2000)

Such in outline is the official theory. I shall often speak of it, with deliberate abusiveness, as “the dogma of the Ghost in the Machine.” I hope to prove that it is entirely false, and false not in detail but in principle. It is not merely an assemblage of particular mistakes. It is one big mistake and a mistake of a special kind. It is, namely, a category mistake.
― Gilbert Ryle (1900 – 1976)

The trouble with Oakland is that when you get there, there isn’t any there there.
― Gertrude Stein (1874 – 1946)

Dr. Malcolm: Yeah, yeah, but your scientists were so preoccupied with whether or not they could that they didn’t stop to think if they should.
― “Jurassic Park” (1993)

It’s a big enough umbrella
But it’s always me that ends up getting wet.
― The Police, “Every Little Thing She Does is Magic” (1981)

Everyone who lost money on the SNB’s decision to reverse course on their three and a half year policy to cap the exchange rate between the CHF and the Euro made a category error. And by everyone I mean everyone from Mrs. Watanabe trading forex from her living room in Tokyo to a CTA portfolio manager sitting in front of 6 Bloomberg monitors to a financial advisor answering a call from an angry client. It will take me a bit of verbiage to explain what I mean by a category error and why it’s such a powerful concept in logic and portfolio construction. But I think you’ll find it useful, not just for understanding what happened, but also (and more importantly) to protect yourself from it happening again. Because this won’t be the last time the markets will be buffeted by a forex storm here in the Golden Age of the Central Banker.

A year and a half ago, when I was just starting Epsilon Theory, I wrote a note called “The Tao of Portfolio Management.” It’s one of my less-downloaded notes, I think largely because its subject matter – problems of misunderstood logic and causality in portfolio construction – doesn’t exactly have the sexiness of a rant against Central Bank Narrative dominance, but it’s one of my personal favorites. That note was all about the ecological fallacy – a pervasive (but wrong-headed) human tendency to infer qualities about the individual from qualities of the group, and vice versa. Today I’ve got the chance to write once again about the logic of portfolio construction AND work in some of my favorite Zen quotes AND manage something of a Central Bank screed … a banner day!

I’ve titled this note “The Ghost in the Machine” because it starts with another pervasive (but wrong-headed) human tendency – the creation of a false dualism between mind and body. I know, I know … that sounds both really daunting and really boring, but bear with me. What I’m talking about is maybe the most important question of modern philosophy – is there a separate thing called “mind” or “consciousness” that humans possess, or is all of that just the artefact of a critical mass of neurons firing within our magnificent, but entirely physical, brains? I’m definitely in the “everything is explained by neurobiology” camp, which I’d say is probably the more widely accepted view (certainly the louder view) in academic philosophy today, but for most of the 19th and 20th centuries the dualist or Cartesian view was clearly dominant, and it was responsible for a vast edifice of thought, a beautiful cathedral of philosophical constructs that was … ultimately really disappointing and empty. It wasn’t until philosophers like Gilbert Ryle and Van Quine started questioning what Ryle called “the ghost in the machine” – this totally non-empirical but totally accepted belief that humans possessed some ghostly quality of mind that couldn’t be measured or observed but was responsible for driving the human machine – that the entire field of philosophy could be reconfigured and take a quantum leap forward by incorporating the insights of evolutionary biology, neurobiology, and linguistics.

Unfortunately, most economists and investors still believe in ghosts, and we are a long way from taking that same quantum leap. There is an edifice of mind that dominates modern economic practice… a beautiful cathedral where everything can be symbolized, where everything can be securitized, and where everything can be traded. We have come to treat these constructed symbols as the driver of the economic machine rather than as an incomplete reflection of the real world things and real world activities and real world humans that actually comprise the economy. We treat our investment symbols and thoughts as a reified end in themselves, and ultimately this beautiful edifice of symbols becomes a maze that traps us as investors, just as mid-20th century philosophers found themselves trapped within their gorgeous constructs of mind. We are like Ekido in the Zen koan of the muddy road, unable to stop carrying the pretty girl in our thoughts and trapped by that mental structure, long after the far more sensible monk Tanzan has carried the girl safely over the real world mud without consequence, symbolic or otherwise.

The answer to our overwrought edifice of mind is not complex. As Confucius wrote in The Analects, the door is right there in front of us. Exiting the maze and reducing uncompensated risk in our portfolios does not require an advanced degree in symbolic logic or some pretzel-like mathematical process. It requires only a ferocious commitment to call things by their proper names. That’s often not an easy task, of course, as the Missionaries of the Common Knowledge Game – politicians, central bankers, famous investors, famous economists, and famous journalists – are dead-set on giving things false names, knowing full well that we are hard-wired as social animals to respond in ant-like fashion to these communication pheromones. We are both evolved and trained to think in terms of symbols that often serve the purposes of others more than ourselves, to think of the handle rather than the blade when we ask for a knife. The meaning of a knife is the blade. The handle is not “the other end” of a knife; it is a separate thing with its own name and usefulness. The human animal conflates separate things constantly … maybe not a big deal in the kitchen, but a huge deal in our portfolios. Replace the word “knife” with “diversification” and you’ll get a sense of where I’m going with this.

Here’s what I mean by calling things by their proper names. The stock ticker “AAPL” or the currency ticker “CHF” are obviously symbols. Less obviously but more importantly, so are the shares of Apple stock and the quantities of Swiss francs that AAPL and CHF represent. Stocks and bonds and commodity futures and currencies are symbols, not real things at all, and we should never forget that. The most common category error that investors make (and “category error” is just a $10 phrase for calling something by the wrong name) is confusing the symbol for what it represents, and as a result we forget the meaning of the real world thing that’s been symbolized.

A share of stock in, say, Apple is a symbol. Of what? A limited liability fractional ownership position in the economic interests of Apple, particularly its free cash flows.

A futures contract in, say, copper is a symbol. Of what? A commitment to receive or deliver some amount of real-world copper at some price at some point in the future.

A bond issued by, say, Argentina is a symbol. Of what? A commitment by the Argentine government to repay some borrowed money over an agreed-upon period of time, plus interest.

A currency issued by, say, Switzerland is a symbol. Of what? Well, that’s an interesting question. There’s no real world commitment or ownership that a currency symbolizes, at least not in the same way that stocks, bonds, and commodity contracts symbolize an economic commitment or ownership stake. A currency symbolizes government permission. It is a license. It is an exclusive license (which makes it a requirement!) to use that currency as a medium for facilitating economic transactions within the borders of the issuing government, with terms that the government can impose or revoke at will for any reason at all. That’s it. There’s no economic claim or right inherent in a piece of money. As Gertrude Stein famously said of Oakland, there’s no there there.

Why is this examination of underlying real world meaning so important? It’s important because there is no positive long-term expected return from trading one country’s economic license for another country’s economic license. There is a positive long-term expected return from trading money for stock. There is a positive long-term expected return from trading money for bonds. There is a positive long-term expected return from trading money for commodities and other real assets. But there is no positive long-term expected return from trading money for money.

Unfortunately, we’ve been trained and encouraged – often under the linguistic rubric of “science” – to think of ANY new trading vehicle or security, particularly one that taps into as huge a market as foreign exchange, as a good thing for our portfolios. We are deluged with the usual narratives that alternatively seek to tempt us and embarrass us into participation. On an individual level we are told stories of savvy investors who look and act like we want to look and act, taking bold advantage of the technological wizardry (look! it’s a heat map! that changes color while I’m watching it!) and insanely great trade financing now at our fingertips in this, the best of all possible worlds. On an institutional level we are told stories of liquidity and non-correlation (what? you don’t understand what an efficient portfolio frontier is? and you call yourself a professional?), both good and necessary things, to be sure. But not sufficient things, at least not to cast the powerful magic that is diversification.

There are only a few sure things in investing. First, taxes and fees are bad. Second, compound growth is a beautiful thing. Third, portfolio diversification works. At Salient we spend a lot of time thinking about what makes diversification work more or less well for different types of investors, and if you’re interested in questions like “what’s the difference between de-risking and diversification?” I heartily recommend our latest white paper (“The Free Lunch Effect”) to you. One thing we don’t do at Salient is include currency trading within our systematic asset allocation or trend-following strategies. Why not? Because Rule #1 for tapping into the power of portfolio diversification is that you don’t include things that lack a long-term positive expected return. Just because we can trade currency pairs easily and efficiently doesn’t mean that we should trade currency pairs easily and efficiently, any more than cloning dinosaurs because they could was a good idea for the Jurassic Park guys. The point of adding things to your portfolio for diversification should be to create a more effective umbrella, not just a bigger umbrella. I like a big umbrella just as much as the next guy, but not if I’m going to get wet every time a forex storm whips up.

So if not for diversification, why do smart people engage in currency trading? There’s a good answer and a not-as-good answer to that question.

The good answer is that you have an alpha-driven (i.e. private information-driven) divergent view on the terms of the government license embedded within any modern currency. This is why Stanley Druckenmiller is an investing god, and it’s why anyone who put money with him before, during, and after he and George Soros “broke the Bank of England” in 1992 has been rewarded many times over.

The not-as-good answer is that you have identified a predictive pattern in the symbols themselves. I say that it’s not as good of an answer, but I’m not denying that there is meaning in the pattern of market symbols. On the contrary, I think there is real information regarding internal market behaviors to be found in the inductive study of symbolic patterns. This information is alpha, maybe the only consistent source of alpha left in the world today, and acting on these patterns is what good traders DO. But because it’s inductively derived, anyone else can find your special pattern, too. Or if they can’t, it’s because you’ve carved out a nice little parasitic niche for yourself that’s unlikely to scale well. More corrosively, the natural human tendency is to ascribe meaning to these patterns beyond the internal workings of the market, something that makes no more sense than to say that goose entrails have meaning beyond the internal workings of the goose. The meaning of the Swiss franc didn’t change just because you had a consistent pattern of market behavior around the EURCHF cross. Deviation in the expected value of the Swiss franc in Euro terms did not become normally distributed just because you can apply statistical methodology to the historical exchange rate data. I get so annoyed when I read things like “this wasn’t just the greatest shock in the history of forex, it was the greatest shock in the history of traded securities! a 30 standard deviation event!” Please. Stop it. Just because you can impose a normal distribution on the EURCHF cross doesn’t mean that you should. And if you’re making investment decisions because you think that this normal distribution and the internal market stability it implies is somehow “real” or has somehow changed the fundamental nature of what a currency IS … well, eventually that category error will wipe you out. Sorry, but it will.

I don’t mean to be snide about any of this (although sometimes I can’t help myself). The truth is that an aggregation of highly probabilistic entities will always surprise you, whether you’re building a baseball team or an investment portfolio. Portfolio construction – the aggregation of symbols and symbols of symbols, all of which are ultimately based on massive amounts of real world activities that may have vastly different meanings and underlying probabilistic natures – is a really difficult task under the best of circumstances for a social animal that evolved on the African savanna for an entirely different set of challenges. And these are not the best of circumstances. No, the rules always change as the Golden Age of the Central Banker begins to fade. The SNB decision was a wake-up call, whether or not you were directly impacted, to re-examine portfolios and investment behavior for category errors. We all have them. It’s only human. The question, as always, is whether we’re prepared to do anything about it.

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The Unbearable Over-Determination of Oil

July 11, 2019November 24, 2014 by Ben Hunt

Jett Rink: Everybody thought I had a duster. Y’all thought ol’ Spindletop Burke and Burnett was all the oil there was, didn’t ya? Well, I’m here to tell you that it ain’t, boy! It’s here, and there ain’t a dang thing you gonna do about it! My well came in big, so big, Bick and there’s more down there and there’s bigger wells. I’m rich, Bick. I’m a rich ‘un. I’m a rich boy. Me, I’m gonna have more money than you ever *thought* you could have – you and all the rest of you stinkin’ sons of … Benedicts!

Bick, you shoulda shot that fella a long time ago. Now he’s too rich to kill.
― “Giant” (1956)

Mussawi: Bob, what do you know about the torture methods used by the Chinese on the Falun Gong? Huh? Method number one. What’s your guess?

[pause]

Water dungeon. Did you guess water dungeon? Number two method? Number two, twisting arm and putting face in feces. Not interested in two? Number three. Number three is called ‘pulling nails from fingers’. What do you think, Bob? Number three sound good to you? The purpose is to get the monks or whatever to recant their beliefs. What if I had to get you to recant? That would be pretty difficult right? Because if you have no beliefs to recant then what? Then you’re f****d is what.

― “Syriana” (2005)

And therein lies the whole of man’s plight. Human time does not turn in a circle; it runs ahead in a straight line. That is why man cannot be happy: happiness is the longing for repetition.
― Milan Kundera, “The Unbearable Lightness of Being”

Everything we see hides another thing, we always want to see what is hidden by what we see, but it is impossible. Humans hide their secrets too well.

― Rene Magritte

9 Down Clue:	Market Leader
Answer:	T-H-E-F-E-D

– New York Times Crossword Puzzle, Saturday November 16

You know you’re in trouble when the Fed’s Narrative dominance of all things market-related shows up in the New York Times crossword puzzle, the Saturday uber-hard edition no less. It’s kinda funny, but then again it’s more sad than funny. Not a sign of a market top necessarily, but definitely a sign of a top in the overwhelming belief that central banks and their monetary policies determine market outcomes, what I call the Narrative of Central Bank Omnipotence.

There is a real world connected to markets, of course, a world of actual companies selling actual goods and services to actual people. And these real world attributes of good old fashioned economic supply and demand – the fundamentals, let’s call them – matter a great deal. Always have, always will. I don’t think they matter nearly as much during periods of global deleveraging and profound political fragmentation – an observation that holds true whether you’re talking about the 2010’s, the 1930’s, the 1870’s, or the 1470’s – but they do matter.

Unfortunately it’s not as simple as looking at some market outcome – the price of oil declining from $100/bbl to $70/bbl, say – and dividing up the outcome into some percentage of monetary policy-driven causes and some percentage of fundamental-driven causes. These market outcomes are always over-determined, which is a $10 word that means if you added up all of the likely causes and their likely percentage contribution to the outcome you would get a number way above 100%.Are recent oil price declines driven by the rising dollar (a monetary policy-driven cause) or by over-supply and global growth concerns (two fundamental-driven causes)? Answer: yes. I can make a case that either one of these “explanations” on its own can account for the entire $30 move. Put them together and I’ve “explained” the $30 move twice over. That’s not very satisfying or useful, of course, because it doesn’t help me anticipate what’s next. Should I be basing my risk assessment of global oil prices on an evaluation of monetary policy divergence and what this means for the US dollar? Or should I be basing my assessment on an evaluation of global supply and demand fundamentals? If both, how do I weight these competing explanations so that I don’t end up overweighting both, which (not to get too technical with this stuff) will have the effect of sharply increasing the volatility of my forward projections, even if I’m exactly right in the ratio of the relative contribution of the potential explanatory factors.

Here’s the short answer. I can’t. As a social animal in the financial services ecosystem I can’t avoid some overweighting of the explanatory factors. The longer answer is that I believe I can reduce the naïve overweighting by a rigorous focus on Narrative formation and dissemination, a process that I’ll describe below. But before we get to that let’s examine the consequences of an investment world where the overwhelming majority of market participants are not even thinking about mitigating the naïve overweighting of the various explanatory factors for oil price movements that are rolling through their heads, and where the entire financial services sector is designed to magnify this overweighting behavior.

What do I mean by that last bit? I mean that when there’s a large move in an important aspect of the market – and a $30 plunge in the price of oil certainly qualifies on that score! – it creates an overwhelming demand from global investors, from trillions of dollars of investment capital, for an answer to a single question: WHY? Anyone in the financial services world, from the smallest FA to the largest institutional allocator, must supply an answer to that question of Why, or else the capital that you advise or allocate for will start looking for a new advisor or allocator. The rarest answer in the financial services world is “I don’t know”, even though that’s almost always the most honest answer, because the business risk of “I don’t know” is overwhelming during large market moves. Global capital creates a multi-trillion dollar demand for The Answer, and financial service providers (or at least successful financial service providers) will always provide it.

When there’s a multi-trillion dollar market for The Answer, it should surprise no one that there is competition around the supply of The Answer. Many, many, many answers with a small-a will be supplied, each vying for contention for a slice of The Answer market. Not only is every advisor or allocator in the world today an answer-supplier in his or her own right, but also there are layers upon layers of answer supply and demand within the financial services world itself. The result is an artillery barrage of answers raining down on every market participant, including guys like me who have our own howitzers. ALL of us are caught in this barrage, and it’s LOUD.

All of us may be caught in the barrage, but very few of us have an independently grounded view of what’s going on in oil markets or a process for assimilating the answers. Unfortunately, without that independent grounding or process the sheer volume of the shouted answers becomes a form of torture.

The vast majority of market participants are like George Clooney’s CIA agent in Syriana – ungrounded and without personal conviction in the competition at hand. When Clooney is tortured, it’s only pain – pure, unadulterated, senseless pain – with no purpose or process. Clooney will say or do anything to avoid the pain, but there is nothing he can say or do that will assuage his torturer because he doesn’t have what his torturer wants. You can’t repudiate grounded beliefs under torture if you don’t have grounded beliefs to start with, and whatever belief you espouse under torture will never be a grounded belief. All you can do is shout out some new belief, some new Answer, each time you get another nail pulled off a finger … or, as we might say down in Houston, each time the price of oil goes down another $10/bbl.

Okay, Ben, interesting metaphors and all that, but what’s the investable implication of what you’re saying? Simply this: whatever volatility you think exists in future oil prices … you’re too low. There is a behavioral and market structure dynamic in play today that will amplify oil price volatility beyond whatever your combination of fundamental-driven or monetary policy-driven rationales might imply. The loudness of the artillery barrage of answers to the question of “Why is oil down” is itself a driver of increased volatility in the price of oil and energy sector stocks. And yes, this loudness (more formally, the degree and scope of competition in the answer-supply market) can be measured, which may be an interesting thing for traders to think about. Just sayin’.

Now please note that I do not mean volatility as the word is all too commonly used, as a synonym for “down”. This isn’t some self-fulfilling prophecy, where more people talking about why oil is down somehow pushes oil prices down further. That’s not it at all. What I’m saying is that when more people talk loudly and competitively about their particular Answer to why oil is down, ALL answers become more and more over-weighted. The price of oil becomes more and more over-determined. Events that seem to fit one of the Answers are trumpeted to the high heavens, and everyone rushes to buy or sell according to that event and that Answer. Until, of course, the next event comes along which fits another Answer and is in turn trumpeted on high and is in turn followed by a mad rush to buy or sell according to that event and that Answer. Risk On / Risk Off. Bigger and faster price movements up AND down. Greater than expected “error” from whatever alpha or beta model you’re using. That’s what I mean by volatility.

And the reverse is true, too. When fewer people talk loudly and competitively about their particular Answer to a pressing question of Why, I expect volatility to decline. It’s no accident, in my view, that US equity market volatility has declined with almost perfect inverse correlation to the advance in the Narrative of Central Bank Omnipotence. Today I am hard-pressed to find anyone who argues that equity markets are at current levels because economic fundamentals are so good, or more generally that market outcomes – good or bad – are driven by economic fundamentals. Instead it’s all central banks all the time. There is zero competition in the marketplace of Answers on this enormous question of Why, and I think that’s the driving force behind not only reduced volatility, but also – and far more importantly for the financial services sector – reduced market activity and reduced market interest.

What I’m describing here is another way of getting a handle on the Common Knowledge Game, which I’ve argued is the principal strategic interaction in markets where grounded beliefs are few and far between. I won’t belabor all that again, as you can read about it here and here. But whether you’re thinking in terms of Keynes’ Newspaper Beauty Contest or the Island of the Blue-Eyed Tribe or how a CIA agent responds to torture, it’s all the same dynamic. When you’re not sure of yourself and you’re trying to figure out what consensus view to adopt, as likely as not everyone else is trying to do the same thing. In these situations it’s Common Knowledge – public signals that we all believe that we all heard, aka Narratives – that largely determines each of our individual behavioral decisions.

I mentioned earlier that I believe it’s possible to mitigate these behavioral and structural impulses to overweight explanatory factors through a rigorous assessment of Narrative creation and dissemination, so I’ll turn to that now. To be clear … I don’t have The Answer for what drives oil prices. I have MY answer, which is a small-a answer because it adapts to Narrative shifts in the relative prominence of fundamental-driven factors and monetary policy driven factors. It’s also a small-a answer because it’s a self-consciously Bayesian effort at arriving at a useful assessment of what’s going on, not a Platonic effort at uncovering some eternal Truth with a capital-T. All it really means to say that you’re a Bayesian decision maker is that you ground yourself with some set of prior beliefs and then you update those beliefs with new information. Here, then, are my grounded beliefs, first on fundamentals and then on monetary policy.

On fundamentals … we have good models (good in the sense that they’ve been nicely predictive over the past several decades) for the relationship between global growth and oil prices. What all the models basically show is that US growth sets the floor and Chinese growth is the marginal driver above that floor, at least for the demand function. Without a US recession and/or a Chinese hard landing – neither of which are anywhere in sight – it’s really hard for oil to get very far below, say, $70/bbl and it’s almost impossible for the price to stay there for very long.

We also have good models for the relationship between oil supply and oil prices. Currently we have significant over-supply in the global energy markets, driven by two factors: the continued success of shale production efforts in the US (see the amazing chart below from Deutsche Bank’s Torsten Slok) and the mysteriously high production levels being maintained by Saudi Arabia.

I say mysteriously high because with 30% price declines Saudi Arabia has historically been rather quick to cut production, but they’ve been largely quiet of late. There’s a widespread belief (which I share) that there is geopolitical pressure on Saudi Arabia to maintain production levels in order to squeeze the economic vise on Russia and Iran. There are limits to this US geopolitical pressure, however, particularly with such a mistrusted Administration, and I think we’re now well past those limits.There’s also a somewhat less widespread belief (which I don’t share) that Saudi Arabia is content to maintain (or even increase) production in order to put more downward pressure on oil prices and force US shale production into unprofitable positions. While the proponents of this view are absolutely right that the threat of opening the production floodgates has always been the Saudi big stick used to maintain cartel discipline within OPEC, there’s just too much non-cartelized money, technology, and political capital invested in US shale production to slow it down in this way. It’s the Bick Benedict / Jett Rink problem from the classic movie Giant … if you’re Rock Hudson and you despise James Dean, you better get rid of him while he’s a dirt-poor wildcatter, because once he succeeds he’s too rich to kill.

Also, regardless of what happens in the short term with OPEC production targets, when you look at the production profiles of most major oil fields in the world today I think it’s very hard to see the current over-supply condition as anything but temporary, even with continued efficiency advances in the US shale fields (for a particularly apocalyptic view on all this, see the latest quarterly letter from GMO’s Jeremy Grantham). As with the global growth models, it’s really hard to get oil much below $70/bbl from a supply model perspective.

But then there’s monetary policy. For the past 30 years we’ve had general global coordination around a weaker dollar (which supports higher prices of assets, like oil, that are priced in dollars) and for the past 5 years we’ve had intensive global coordination to promote massive dollar liquidity (which also supports higher oil prices). Today that coordination has stopped, and the dollar is getting very strong very quickly as the Fed cuts back on dollar liquidity at the same time that other central banks continue to increase their own liquidity operations. As I hope that I’ve made clear in recent Epsilon Theory notes (here and here), I think that this monetary policy divergence is a very significant risk to markets, as there’s no direct martingale on how far monetary policy can diverge and how strong the dollar can get. As a result I think there’s a non-trivial chance that the price of oil could have a $30 or $40 handle at some point over the next 6 months, even though the global growth and supply/demand models would say that’s impossible. But I also think the likely duration of that heavily depressed price is pretty short. Why? Because the Fed and China will not take this lying down. They will respond to the stronger dollar and stronger yuan (China’s currency is effectively tied to the dollar) and they will prevail, which will push oil prices back close to what global growth says the price should be. The danger, of course, is that if they wait too long to respond (and they usually do), then the response will itself be highly damaging to global growth and market confidence and we’ll bounce back, but only after a near-recession in the US or a near-hard landing in China.

So now for the balancing act … is the price of oil today driven more by global growth and supply/demand factors or by monetary policy factors? I hope it doesn’t surprise anyone when I say that I think monetary policy dominates ALL markets today, including the global oil market. What’s the ratio? My personal, entirely subjective view is that oil prices over the past 3+ months have been driven by 3 parts monetary policy to 1 part fundamentals. How do I come up with this ratio? For the past 3+ months the oil Narrative has been dominated by public statements from influential answer-suppliers talking up the oil price dynamic of a rising dollar and monetary policy divergence. That’s the source of my subjective view of a 3:1 dominance for monetary policy-driven factors over fundamental-driven factors.

However – and this is the adaptive part where I play close attention to Narrative development and dissemination – the noise level surrounding this Thursday’s OPEC meeting is absolutely deafening. I mean, when the Sunday morning talking head shows are discussing OPEC and its influence on gasoline prices you know that something dramatic is happening with the Narrative. For at least this week and next the oil Narrative is going to be dominated by public statements from influential answer-suppliers talking up the oil price dynamic of OPEC decisions on fundamental global oil supply. For at least this week and next my personal, entirely subjective view of the ratio of explanatory factors is going to flip to 3 parts fundamentals to 1 part monetary policy. And since it’s hard to get the price of oil much lower than it is today on the fundamentals … well, you can draw your own conclusions about the risk/reward asymmetry over the next two weeks. Beyond that? I have no idea. I’ll just have to wait and see what happens to the Narrative.

I know this process probably sounds very reactive, as if I’m lacking all conviction about how the world works. Guilty as charged on the first count; innocent on the second. I don’t pretend that I have The Answer. I don’t pretend to have a crystal ball that tells me what OPEC is going to do this Thursday or when the next central banker will jawbone his currency down. I don’t know. Sorry. There are plenty of answer-suppliers out there who will be more than happy to tell you that they DO have that crystal ball, and if that’s what you need you’re wasting your time reading Epsilon Theory. I think that investing in a reactive manner – or as I like to call it, adaptive investing – is the best way to survive a profoundly uncertain world. That doesn’t mean that I don’t have strong ideas about how the world works, about how both monetary policy and fundamentals impact the price of oil. What it means is that it doesn’t matter what I think about the way the world works. The only thing that matters is what the market thinks about the way the world works, and in times like these the market will think whatever Common Knowledge says it should think.

It’s crucial to have strong views about how the world works, to have an independently grounded vision of the world, because otherwise I might start to think that whatever Common Knowledge is dominant at some given time … US dollar strength for the past 3+ months, OPEC impact on supply fundamentals for the next 2+ weeks … is The Answer for oil prices, forever and ever amen, and I will be whipsawed mercilessly when the Narrative shifts. And it will shift. But it’s equally crucial not to become a prisoner of my strong views about how the world works, or else at best I will miss the path that the market takes from here to there, and at worst I might be … wrong.

Here’s my Answer: there is no Answer. In a structurally unstable market, there is no stable deterministic model of discrete market-exogenous factors like global supply/demand and monetary policy to “explain” oil prices. Oil prices are systematically over-determined, particularly during times of pricing distress, and you’re kidding yourself if you think you can find the world’s secret eternal code that hides behind market outcomes. The market itself – the strategic interaction of social animals all trying to outsmart each other – is part and parcel of the code. Strategic interactions are not factors that you can plug into your model or regression analysis. They are emergent properties of a game … a game with rules and stable patterns of behavior, so it’s knowable and predictable, but not predictive in the same deterministic fashion that the econometric toolbox promises. For investors and allocators steeped in this predictive promise of econometrics, game theory will always seem like thin gruel, as postdictive rather than predictive. Fair enough. But rather than cling to my econometric toolkit and make market predictions that are less and less useful in this, the Golden Age of the Central Banker, I’d rather look at the market through the lens of game theory and Common Knowledge and Narrative so that I can adapt quickly to what IS rather than what I’d prefer it to be.

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Adaptive Investing: What’s Your Market DNA?

July 11, 2019January 5, 2014 by Ben Hunt

It is not the strongest or the most intelligent who will survive but those who can best manage change.
– Charles Darwin

We think we know that chimpanzees are higher animals and earthworms are lower, we think we’ve always known what that means, and we think evolution makes it even clearer. But it doesn’t. It is by no means clear that it means anything at all. Or if it means anything, it means so many different things to be misleading, even pernicious.

– Richard Dawkins. “The Greatest Show on Earth: The Evidence for Evolution”

In a sense, among higher animals adaptive fitness was no longer transmitted to the next generation by DNA at all. It was now carried by teaching. … For our own species, evolution occurs mostly through our behavior. We innovate new behavior to adapt.

– Michael Crichton, “The Lost World”

Historical fact: people stopped being human in 1913. That was the year Henry Ford put his cars on rollers and made his workers adopt the speed of the assembly line. At first, workers rebelled. They quit in droves, unable to accustom their bodies to the new pace of the age. Since then, however, the adaptation has been passed down: we’ve all inherited it to some degree, so that we plug right into joysticks and remotes, to repetitive motions of a hundred kinds.

– Jeffrey Eugenides, “Middlesex”

That’s evolution. Evolution’s always hard. Hard and bleak. No such thing as happy evolution.

– Haruki Murakami, “Hard-Boiled Wonderland and the End of the World”

It was therefore inevitable that the genetic code prescribing social behavior of modern humans is a chimera. One part prescribes traits that favor success of individuals within the group. The other part prescribes the traits that favor group success in competition with other groups.

– Edward O. Wilson, “The Social Conquest of Earth”

The illustration at the top of this note is taken from Charles Darwin’s so-called “B” notebook, where in mid-summer 1837 on page 36 he wrote the words “I think” followed by the first depiction of an evolutionary tree. The rest, as they say, is history, first with the publication of “The Voyage of the Beagle” in 1839, which made Darwin famous, and then with “On the Origin of Species” in 1859, which made him immortal. I think it’s fair to say that the theory of evolution is the most influential pillar of science since the development of Newtonian physics, topping even the theory of relativity developed by Einstein et al., and has done more to shape the modern human belief system around the Narrative of Science than anything since Galileo’s introduction of the idea of empirical tests and the scientific method in the 17th century.

I want to use evolutionary theory as a perspective for understanding human behavior within capital markets for a couple of reasons. First, I think it’s a more useful perspective than what economic theory has become … a cloistered, brittle theology that day after day becomes more abstract in its formation and more narrow in its application. I’m not saying that modern economic theory is wrong. I’m saying that it’s a beautiful, elegant mental construct – much like the medieval Christian construct of Heaven’s hierarchy with Seraphim, Cherubim, Ophanim, Thrones, etc. all in their proper sphere and convoluted yet logical relationship with each other. Both constructs are marvels of inspiration and genius, for sure, and yet they are useful to my life … how, exactly?

Gustave Doré, “Rosa Celeste, The Divine Comedy Canto XXXI”

Second, I want to use evolutionary theory because it is a Narrative with a great deal of power and meaning for anyone reading this note, enough power and meaning (I hope) to make a new vantage point on markets possible. The hardest thing in the world is to break free from the perspective imposed by an entrenched social construction while you’re immersed in it, and so much of history seems ludicrous to our modern eye in this respect. What do you mean the Italian State put Galileo on trial for saying the Earth goes around the sun, all evidence to the contrary? Boy, those guys must have been really stupid. Well … no, they were just as smart as we are. But they were immersed in an entrenched Biblical Narrative that defined their reality more than any amount of empirical evidence from astronomical observations ever could. Rather than argue against a mental construct of markets derived from the entrenched Narrative of Modern Economic Science, I’d rather argue for a mental construct of markets derived from the equally entrenched Narrative of Modern Evolutionary Science. Galileo didn’t have that option, as he was just getting the Narrative of Science off the ground. Fortunately, I do.¹

But as is often the case, the Scientific Narrative of our imagination and popular belief is somewhat at odds with the usefulness of the actual scientific toolkit. If you look again at Darwin’s drawing, it doesn’t look much like a tree in the botanical sense, or even what we tend to think of as an evolutionary tree, with a “primitive” species forming the trunk and “advanced” species forming the branches, such that the higher you go in the tree the more advanced the life-form must be. The truth, as Darwin wrote, is that “it is absurd to talk of one animal being higher than another”, and the popular conception of evolution-as-hierarchy is just plain wrong. No, what Darwin meant by an evolutionary tree is more like a map. There’s an element of time embedded in the map, with ancestors at the trunk and descendants as you move away from that trunk (hence the title of Darwin’s second-most famous book, “The Descent of Man”), but descendant species are not more advanced in nature, they are simply more suited to survival in their particular environment.

This, I think, is the first and most basic lesson of an evolutionary perspective properly applied: we are well served as investors to jettison the superiority complex that comes with living in the present and looking back on what naturally seems a benighted past. The notions of liberal progress and evolution-as-hierarchy are so deeply ingrained that we assume that whatever behaviors are new or modern, including modern investment management practices or modern investment strategies (or modern monetary policy), must be part and parcel of some advancement over what existed in the past. In truth there is no up-and-to-the-right arrow associated with evolution; there is no intelligent design pushing us “forward”. Modern behavioral adaptations are probably more complex than historical behaviors (adaptation tends towards specialization and complexity), but that’s a far cry from being inherently superior on some absolutist scale. All you can say about a successful behavioral adaptation is that it has made its adopters more suitable for their current environment, where suitability and success are defined in terms of the prevalence of the population of behavioral adopters, not the individual achievement of whatever goal the behavior is ostensibly supposed to address.

Using concepts like “suitability” and “population” and “adaptation” and “habitat” to describe human behaviors in market settings may seem like a trivial (or weird) distinction from the dominant mental constructs we use to understand The Market (itself a mental construct of a particular sort), but I hope to make the case over the next few months that it can make all the difference in the world.

Here’s a small example of what I mean. A fad diet that gains millions of converts is almost certainly a successful behavioral adaptation even if no one actually keeps off a single pound. If you want a more incendiary phrasing, replace “fad diet” with “routine mammograms” or “daily multivitamins” or, for you risk managers out there, “portfolio stress scenarios”. There’s a long list of modern behavioral adaptations that provide little or no direct benefit to their adopters, but are nevertheless useful in advancing the strength and numbers of the population of adopters through a dynamic based on biological or social signaling. I take a multivitamin every day, even though I think we can all agree that I am unlikely to develop a case of scurvy in its absence and that taking 30x the recommended daily allowance of thiamin is just silly. Why? Because I can say to my wife and my kids that I do. It makes them feel better about me. To them it’s shorthand for “I’m taking care of myself” and they treat me as more fit and powerful than if they think that I’m “not taking care of myself.” I am a slightly more successful husband and father because I take a multivitamin every day, as is every middle-aged American male who shares this behavioral trait with me. As a group, we do a little bit better in our family lives than the population of middle-aged American males who don’t. So if you’re a risk manager and you run a daily suite of portfolio stress scenarios, go right ahead. It is a perfectly rational thing to do even if you don’t think there is any direct benefit. But you’ll understand your own behavior better (and thus choose to embrace or reject that behavior with awareness) if you recognize portfolio stress scenarios for what they are … the equivalent of a bird species evolving an elaborate but functionally rather useless dance to demonstrate relative fitness to other members of the species.

Darwin’s evolutionary tree encapsulates these concepts of suitability, population, adaptation, and habitat. It is a depiction of adaptive radiation, one of the core principles of evolutionary theory and the source of a valuable toolkit for understanding markets. Adaptive radiation describes the creation of new species through the opportunistic spread of an old species into new habitats. Over time, adaptations that make the species more suitable for the new habitat are naturally selected, and as those adaptations grow in number and scope the population of the original species in the new habitat becomes increasingly differentiated from the population of the original species in another new habitat or the old habitat. Ultimately the populations are unrecognizable to each other from a breeding perspective (which is the only perspective that matters in natural selection terms), and you have new species in the various new habitats … but still sharing an ancestral genetic makeup and some sort of morphology or physical instantiation of that shared ancestral DNA.

Adaptive radiation is at the core of Darwin’s eureka moment on the Galapagos Islands, where he identified multiple species of finches, each inhabiting a different ecological or geographical niche.

Adaptive radiation of Galapagos finches (evolutionproject.wikispaces.com)

Darwin’s insight was to recognize that each separate species must have descended from a common ancestral finch, and that natural selection over hundreds of thousands of generations would drive preferential survival for those sub-populations that developed habitat-specific adaptations and eventually “create” the separate species.

This evolutionary process of adaptive radiation occurs everywhere life and habitat change meet, from a minor island chain to a small African lake to Earth itself. Here, for example, is the adaptive radiation pattern of forelimbs in mammals around the world.

Adaptive radiation of the mammalian forelimb (Jerry Crimson Mann)

How is the concept of adaptive radiation useful to our understanding of markets? Let’s start by taking seriously the notion that there are distinct populations of market participants, call them investor “species” if you like, developed over long periods of time through the adaptation of ancestral market attributes to provide improved suitability for specific market “habitats”. Obviously the morphology or physical instantiation of these attributes isn’t going to be a skeletal system as it was with the mammalian forelimb. It has to be something much more specific to the human animal, a creature with characteristics that throw traditional evolutionary theory for a loop.

First, we have a unique physical combination of enormous brains and non-specialized, grasping hands within an overall body size that is large enough to manipulate the environment and control fire (living on land in an oxygen-rich atmosphere helps quite a bit, too … sorry, dolphins). As a result we have the ability to create both physical constructs (inventions) and mental constructs (ideas) that accelerate our adaptation process exponentially beyond what is possible through natural biological selection alone. Homo sapiens broke out of Africa only 60,000 years ago! This is less than the blink of an eye in evolutionary terms, an almost comically short period of time for a species to not only spread globally, but to transform the entire world into a habitat of its own choosing. Science fiction authors are fond of the “terra-forming” trope, where an alien planet is made Earth-like through some application of massive, futuristic technologies. What they really mean is human-forming, and our own species history proves that it requires remarkably little time and remarkably little technology to accomplish that feat when you can take adaptation out of the realm of biological reproduction and place it into the realms of inventions and ideas.

Second, we are almost unique among mammals (it’s just us and naked mole rats … funny, but true) in that we are social animals. I mean this in the sense of what’s called “eusociality”, where populations of a species are organized by nests or colonies in which you find cooperative brood care, overlapping generations, and a division of labor between groups of individuals. Eusociality is the common thread between the most successful insect species on earth – the ants, the bees, and the termites – which is to say it is the common thread between the most successful life forms on Earth, period. But despite its sheer potency as an adaptation, eusociality is extremely rare outside of the insect world, as it requires a tremendously lucky deal of the DNA cards in terms of genetic pre-adaptations. The human animal was dealt just such a lucky hand, a straight flush in poker terms, and by combining the adaptive robustness and potency of eusociality with our individual inventiveness we are truly a uniquely powerful life-form. Basically we are huge mammalian termites with self-awareness and fire. The rest of the world never had a chance.

It’s this termite aspect of the human animal that is most at odds with our popular conception of who we are, as well as the aspect that is most relevant for an evolutionary perspective on markets. I don’t want to overplay the termite angle, because most of the time our big brains give us enough self-awareness to act as individuals rather than as drones to some hive dictat … as Jon Haidt writes, “humans are 90 percent chimp and 10 percent bee.” But that 10% is enough to confound modern economic theory and account for otherwise inexplicable behavior in markets.

To understand how this 10% bee-ness is relevant for markets, we need to focus on the way in which information pervades and flows through eusocial colonies. I believe that eusocial species are more successful than non-eusocial species because they are more information-rich, particularly in the information embedded within the colony hierarchy … its biologically-based collective norms and regimes. Various eusocial insect species have invented assembly lines, domesticated animals, irrigated farms, and built air-conditioned cities with millions of inhabitants. They all have complex caste systems with extraordinarily effective divisions of labor. There’s an enormous amount of information in these behaviors, all carried within the individual insect DNA but only expressed within the collective insect group.

Each individual ant or bee or termite may “know” what to do as an individual piece of the puzzle, but the only way to create the group expression of all this information is to act in a coordinated fashion, not as individuals. Acting as a coordinated group requires two things beyond the behavioral instruction book that every eusocial insect is born with – a language to transfer informational signals and a sensory/neural system that is constantly looking for and responding to these signals. Ants and bees and termites all have a complex language with a discernible grammar, and they are biologically evolved to respond to these language signals. But it’s the constancy of both the communication and the behavioral response that is the hallmark of every eusocial species and sets them apart from other group-oriented but non-eusocial species like a pack of wild dogs or a troop of chimps. Ants talk to each other all the time. They live in an atmosphere that is literally swimming with pheromone molecules conveying instructions and signals from other ants, and they can’t help themselves but to respond behaviorally to those signals. Sound familiar? How many human-generated or human-mediated signals hit you every day? For me it’s easily 4,000 to 5,000 and it’s probably a lot more than that once you start breaking down media and complex messages into their component signals. In fact, most days I don’t think I am ever separated from some sort of human-mediated signal for more than a few minutes. How many times did you check your email or Twitter feed today? Do you feel uncomfortable if you don’t respond to your spouse or child’s text message right away, even if it’s something trivial? Welcome to the world of the ant.

This is the eusocial aspect of the human animal, the 10% bee-ness that we are evolved to possess: we can no more ignore a speech by Ben Bernanke than a worker bee can ignore a pheromone from her queen. We are evolved not only to live in groups, but also to seek out and immerse ourselves in signals from other humans in our groups and, crucially, to respond to those signals in predictable, group-oriented ways. A Bernanke speech is a more complex signal than a queen bee pheromone, and our specific response to the Bernanke signal is not biologically hard-wired, but our hunger for human-mediated signals and our interpretation of those signals in the context of group dynamics IS biologically hard-wired. Language and communication are everything to the eusocial piece of the human animal, not just what is said, but who is saying it and how it is said. Thus language and communication are the human attributes we must examine to track adaptive radiation in the human context.

Actually, I don’t think that’s a terribly contentious statement, as even a cursory look at the human diaspora out of Africa and the subsequent behavioral adaptations of the human animal to their new geographies demonstrates both a classic adaptive radiation pattern and a tit-for-tat marriage with language development and evolution. Here, for example, is the Iranian language family tree, which I chose just for its obvious resemblance to Darwin’s notebook doodle and its explicit linkage of geographic habitat to language adaptation.

But here’s a more contentious statement: I think that there are meaningfully distinct market languages that are just as powerful in reflecting market participant populations undergoing adaptive radiation as “real” languages have been in reflecting global human populations undergoing adaptive radiation. If I’m right, the entire toolbox of linguistics and evolutionary biology opens up to us. If I’m wrong, we’re left with lots of nice metaphors but not much in the way of practical applications.

What are these languages? I think the granddaddy of them all is the language of Value, together with its grammar, Reversion to the Mean. To have an institutional market you must have market makers, so I would guess that the language of Liquidity was not far behind in development, as was the language of Growth, together with its grammar, Extrapolation. These are the three great proto-languages of the market (although the language of Liquidity is rapidly becoming a non-human tongue), and all market participants think and converse predominantly in one of them.

Can you think in more than one proto-language? I don’t believe so, any more than you can be both a dyed-in-the-wool Republican and Democrat at the same time. Can you speak more than one proto-language? Sure, in the same way that a lot of animals can both walk and swim. But if I had to bet on the winner of a 100-meter freestyle swim I’d put my money on the dolphin.

Aren’t there really dozens of distinct market languages out there? Absolutely, but I’d characterize them as genetic offshoots of the proto-languages, as the reflection of the adaptive radiation that has occurred as these ancestral investor “species” moved into new “habitats” and took on behavioral adaptations that made them more suitable for that environment. A value-oriented stock-picker today speaks an almost entirely different investment language than a value-oriented macro investor, and if you looked at them from a distance you might be fooled by the morphology, by the equivalent physical distinction between a big black ground finch and a tiny gray warbler finch. But if you pay attention to the grammar of their language, you’d see that they both interpret the world through a reversion-to-the-mean prism. This is their ancestral genetic code, and I believe that there are useful and practical applications that stem from making this connection, by observing that the population of value-oriented macro investors has more in common (from this perspective) with a population of stock-pickers than with growth-oriented macro investors.

Essentially I’m saying that every investor has a “market DNA” … not a genetic code that you’re born with, but a distinct collection of behavioral attributes that can be measured and summed up by the language you speak and think with to express your market behaviors. How did you come by this market DNA? The same way you absorb every other collection of behavioral attributes that makes you a member of whatever human tribes you belong to … your relatives’ attitudes towards money and risk when you were a child, your friends, your first job in financial services, a mentor, a successful friend or colleague, the books you’ve read and the TV shows that you watch … there’s no mystery to this, and no shortcut to creating or changing this identity, either. There’s a huge body of empirical work in political science about what’s called Party Identification, the way we identify with a political party at an early age and then tend to stick with that association through thick and thin for the rest of our lives. We create this stable political association out of lot fewer stimuli than we receive on money and investing. Why would the result be any different?

I included this quote by E.O. Wilson at the outset, but it’s so important for the concept of Adaptive Investing that it bears repeating:

– Edward O. Wilson, “The Social Conquest of Earth”

As market participants we are acting as both individuals and, whether we realize it or not, as members of a distinct group with a distinct language and a distinct set of behavioral adaptations to our particular market habitat. Our group is, in a very real sense, in competition with other groups for all the good things that a market can provide. Our market interactions are almost always with fellow members of our group. They are who we talk with, they are who we listen to, they are who we transact with. That last bit means that we are indeed competing with other individuals in our groups … there’s no denying that. But in meaningful ways we are also cooperating with other individuals within our investor “species”. As human animals we are biologically hard-wired to live through and for our groups as well as ourselves, and our market lives are no exception.

If your view of capital markets is solely through the lens of individual decision-making, of a buyer and a seller agreeing to a transaction regarding some security based on their individual utility functions, then you are only seeing a piece of the puzzle. Unfortunately, all of modern microeconomic theory – ALL of it – is based on assumptions of individual decision-making and optimization. Until we take context and populations seriously, until we recognize that economic behaviors are not simply optimization exercises against some exogenously assumed set of environmental constraints, until we understand that individual behavioral outcomes and decisions are, in part, driven by group dynamics and individual traits that only make sense in a group context … we are looking through a glass, darkly.

Whew! Okay, Ben, that’s a lot of words and imagery, but what’s the pay-off?

Here are a few brief examples of what it means to bring linguistic and evolutionary biology toolboxes – where the most advanced game theory and information theory of the past 20 years has been developed – to bear on market puzzles. I’ll unpack each in a future note, and there’s a lot more where this came from.

One of Jim Cramer’s favorite lines is “there’s always a bull market somewhere,” and this always used to annoy me as just another hucksterism. Now I think it’s a pretty good point. If your collection of investment behavioral adaptations is no longer working so well because your investment environment has changed … and here I’m looking at you, Mr. Value Investor … you can either change your collection of behaviors or you can move to a habitat that is more conducive to your attributes. The former is absolutely impossible for any non-self aware animal, and darn near impossible for even the most self-aware investor. A tiger can’t change his stripes, a seed-cracking finch can’t start eating insects, and a value investor can’t become a momentum day-trader. The latter – changing your habitat – is similarly impossible if you don’t have the means to get from one habitat to another. If you’re a snake on a tropical island and disaster wipes out your habitat … you will soon be a dead snake. If you’re a bird, on the other hand, hope is on the next island over. Will it be a struggle to find your way on what is probably a crowded new island? Sure, but that’s better than being a dead snake. I think that market participants often overestimate the value of their factual knowledge and personal experience within a particular market “habitat”, whether that’s an industry sector or asset class, when what’s really of importance is the fit between personal attributes and whatever habitat you’re in. A value investor can always learn new facts, but he can’t “learn” how to be a growth investor. The liquidity of capital gives you wings, and it’s probably a good idea to use them when you have to.

Still … it sure would be nice to know if the island you’re flying to is a new Eden where your investment attributes are highly suitable or if you’re flying into a new Hell, and this is where the linguistics toolbox can help. What we’re interested in measuring is HOW other market participants are talking about this new habitat, not WHAT they are saying. If you’re a value investor, you want to hear other value investors using value language and reversion-to-the-mean grammar in their description of the habitat, not growth investors using growth language and extrapolation grammar. It doesn’t really matter what your same-species investors are saying about the habitat (in fact, if they’re all saying wonderful things about the new habitat in your language, you’ve probably already missed the low-hanging fruit, whatever that means to your species). All you should care about is whether you’ve got a critical mass of fellow species members to interact with, and this is what an evolutionary perspective can reveal.

The same principle applies for single security analysis, particularly if you’re thinking about going short. I say this because shorts don’t work as the mirror image of longs. Longs tend to grind their way higher, as good news and story-supporting news is dribbled out more or less intentionally bit by bit. Shorts, on the other hand, work in punctuated fashion, as bad news comes out in an unanticipated rush. (Steve Strongin at Goldman Sachs wrote a tremendous article on this in April 2009, titled “Why Shorts Aren’t Longs: Stockpicker’s Reality Part IV”; it’s a great read for anyone interested in information flow and investing.) Put simply, shorts only work when the bull story breaks. Even so, if the story is not being told in the language that fits your market DNA, you’re going to have no idea whether to press the short or cover on the break. Moreover, you’re far more likely to have a sense of the catalyst that actually breaks the bull story if you’re in sync with the language of the prevalent conversation, which gives you a fighting chance to establish a position ahead of the break without getting killed by poor timing.

For example, let’s say that you shorted Twitter right after the IPO because you’re a value investor and you believe that the stock is just crazily priced on a value basis. The stock has gone against you significantly in recent weeks, but over the past few days it’s declined about 15%. Okay … what now? Do you press the short because you think maybe the story is broken, or do you thank your lucky stars for the brief reprieve in the onslaught and cover? You have no insight on this whatsoever because the bull story on Twitter has nothing to do with value and the recent price decline has nothing to do with value. Everything about the stock is being spoken with the grammar of extrapolation, which you don’t understand, and the dominant population around the stock is not your tribe. I know what I’d do with the position if I were you, but then I wouldn’t have put it on in the first place.

One last example, something using the biology toolkit … let’s say that you’re an allocator trying to evaluate several different strategies. Some present themselves as alpha-generating strategies, where the goal is uncorrelated absolute returns; others are smart (i.e. inexpensive) strategies for capturing broad market returns; others are some mix of the two. You can calculate Sharpe ratios, look at volatility and drawdowns, all the usual stuff, but you can’t shake the feeling that you are comparing apples and oranges here. Which of course, you are.

One new perspective on this age-old question is to look less at the external characteristics or morphology of the strategies and pay more attention to their market DNA, in particular to the grammar of the strategy language in theory and practice. This is a crucial aspect of diversification and risk management in portfolio construction that I think is often overlooked.

Or expressed in a more formal way – how suitable are the embedded utility functions in these investment strategies for the market environments they inhabit? What I mean by this is that adaptation means different things to a species at different stages in its relationship with its habitat. In the adaptive radiation stage, where the new species is just being “created”, the trick is keeping the sub-population together long enough for natural selection to do its work and the adaptations to “take”. There is no substitute for a high growth rate in this opportunistic phase. On the other hand, once you have a well-established species the adaptive focus shifts from high growth to maintaining its established position in the face of unknown shocks to its habitat. Suitability in this core phase of a species lifecycle is a function of adaptations that confer robustness on the population.

I believe that there are strong corollaries between an alpha-generation investment strategy and an opportunistic phase sub-population moving into a new habitat, as well as between a broad market return strategy and a core phase population maintaining its position within an existing habitat. The former lend themselves to behaviors that prioritize growth rates; the latter to behaviors that prioritize robustness. There’s a large body of work on both types of behaviors in biology and economics, and I’m pretty giddy about the opportunity to synthesize this with a game theoretic toolkit. Ultimately, I think, a biological perspective holds the key for constructing an exciting new way of understanding risk and reward in portfolio construction, a perspective that avoids the one-size-fits-all utility model that pervades politics and the treat-utility-as-exogenous assumption that pervades economics. Constructing that new perspective on investment risk and reward is the ultimate goal of the Adaptive Investing project, and I’ll be building this in plain sight and in real time at Epsilon Theory. Like evolution itself I’m sure there will be false starts and dead ends aplenty, but with your participation I’m confident we can come up with a set of behavioral adaptations that will make the Epsilon Theory sub-population more suitable for our unstable markets and our unstable world.

Endnote

¹ I am a well-trained and reasonably competent social scientist with a lot of years in academia and a lot of years of “field work” in capital markets. But I’m not trained as an evolutionary biologist. It’s not my area of professional expertise and I don’t claim that it is. If you’re a natural selection purist like Steven Pinker (whose work I actually really admire), I’m sure it will seem as if I am using the concept of evolution in a simplistic, metaphorical fashion, which will probably drive you nuts. I mean, I never talk about genes, I rarely talk about natural selection, and clearly I’m in some sort of thrall to E.O. Wilson. To which I’d reply … yes, on all counts (particularly the bit about Wilson, as we Alabama boys have to stick together).

My goal is to understand individual and group/population dynamics in capital markets. There’s a lot of funky stuff happening in markets today that is poorly explained (and that’s being generous) by economic theory, and there are concepts and tools in evolutionary biology that simply do not exist in economics or political science. That’s useful, and I am certain that one doesn’t need to be a card-carrying evolutionary biologist to find real value in the evolutionary science toolkit for these purposes. So just to be clear, I don’t pretend to have anything interesting to say on group selection vs. kin selection as an explanation of altruism, punctuated equilibria versus whatever the latest neo-Darwinian synthesis might be, or some other such academic dust- up, and I have zero interest in engaging in those debates. I don’t have to embrace everything that Wilson claims about group selection (a lot of which I find to be quite a stretch, particularly his normative conclusions) to find value in his perspective for explaining the behavioral adaptations of various investor “species” or the “adaptive radiation” of various investment strategies.

Is this exercise more metaphor than science? Absolutely. But I’m way past the academic conceit of looking down my nose at metaphor and analogy. Evolutionary theory as metaphor has helped me make sense of my little corner of the human experience, and that’s what I’m trying to share.

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