To lose one parent, Mr. Worthing, may be regarded as a misfortune; to lose both looks like carelessness.
– Oscar Wilde, “The Importance of Being Earnest”
Behold yon miserable creature. That Point is a Being like ourselves, but confined to the non-dimensional Gulf. He is himself his own World, his own Universe; of any other than himself he can form no conception; he knows not Length, nor Breadth, nor Height, for he has had no experience of them; he has no cognizance even of the number Two.
– Edwin A. Abbott, “Flatland: A Romance of Many Dimensions”
There are only patterns, patterns on top of patterns, patterns that affect other patterns. Patterns hidden by patterns. Patterns within patterns. .. What we call chaos is just patterns we haven’t recognized. What we call random is just patterns we can’t decipher. What we can’t understand we call nonsense. What we can’t read we call gibberish.
– Chuck Palahniuk, “Survivor”
The FOMC will conclude a two-day meeting on Wednesday afternoon. There’s no press conference after this meeting, no opportunity for Bernanke (in his last FOMC meeting) to provide additional “communication policy”, no opportunity for Yellen to signal her personal take on the weak December jobs report and the Emerging Markets carnage of the past week. Whatever the formal statement says is all the market will get, until, of course, Jon Hilsenrath weighs in with a WSJ article to tell us what the FOMC really meant to say.
From a game theory perspective, whether or not the Fed continues the taper with an additional $10 billion in cuts to the monthly bond purchase program is a really big deal. Not because it’s the consensus outcome if you poll economists (consensus actually means very little for how the market plays the Common Knowledge game), and certainly not because of any fundamental economic implications of purchasing “only” $65 billion in securities per month rather than the current $75 billion. No, the importance of an additional $10 billion monthly taper is simply that it will be the second $10 billion cut in a row. It sets a pattern. It turns a point into a line. It creates what game theorists call a “focal point”, which exerts an extremely strong gravitational pull on common knowledge construction.
Tom Schelling, who won a Nobel prize for his work and is, for my money, one of the two all-time best thinkers about real-life applications of game theory (I’ll talk about the other, Bill Riker, in this Sunday’s note) wrote extensively about the idea of a focal point, particularly in his must-read book “The Strategy of Conflict.” As Schelling describes, a focal point IS common knowledge – it is the belief that we have about what the other party believes, and vice versa – and it will almost always be the equilibrium outcome of a free-form strategic decision, particularly if we cannot communicate directly with the other party. In one of Schelling’s examples, you’ve agreed to meet a friend at noon in New York City, but you forgot to agree on a place to meet. What happens? You both end up at the clock in Grand Central Station right at noon. Each of you thought of the clock as what your friend would think of as a meeting place and, recursively, what your friend would think of what you would think of what your friend thought. The clock is a focal point. A focal point, however created, reduces ambiguity and uncertainty in our decision-making. Usually that’s a good thing, but sometimes – as the Fed will discover if they stick to $10 billion in additional tapering – it’s not.
From a game theory perspective, the Fed is much better off increasing the taper by $5 billion or $7 billion … even a larger amount than their last meeting, say $12 billion … than sticking with the same $10 billion figure. This is how the Fed can best maintain useful ambiguity in their communication policy, what they have referred to as “data dependence” and is what Schelling calls “the threat that leaves something to chance”. If you’re long the market in any way, shape, or form … if you are relying on the notion that “the Fed has got my back” in your investments … this sort of ambiguity is exactly what you want to see in the FOMC statement. At this point in the lifecycle of the Narrative of Central Bank Omnipotence, clarity and predictability are entirely counterproductive.
I know it sounds weird to put so much weight on a second identical number, but the human animal will not see a second $10 billion as “just a number”. The human animal has been biologically evolved for millions of years and culturally trained for tens of thousands of years as a pattern recognizer extraordinaire. We simply can’t help ourselves. Like it or not, a second $10 billion cut will be seen as the establishment of a pattern, and that’s a problem. Why? Because once you identify a pattern you will extrapolate a continuation of the pattern … this is what humans DO in their strategic decisions … and you will start to see opinion leaders attaching a final number to the size of QE3. It’s a big impressive number, to be sure, but it’s not open-ended. It’s not infinity. It’s a limit. It’s a clear signal (much clearer than the single data point from last meeting) that the Fed is reducing the pace of asset purchases and headed to zero.
Once these final-size-of-QE3 stories start to appear, everyone associated with the Fed, from the Chair to the Governors to the media mouthpieces, will bend over backwards to say that tapering is not tightening, that they are not putting on the brakes but only taking their collective foot off the accelerator. This is a misreading of game dynamics and the forward-looking creation of mutual expectations. In a game of Chicken, where you and James Dean are racing your cars towards the cliff, you win (and James Dean knows you’ve won) when he takes his foot off the accelerator. Once that happens, the game is over. Putting on the brakes is the final move, but it’s not the moment where the game is won or lost! In technical terms, it’s the second derivative of behavior (acceleration/deceleration) that makes all the difference in game-playing, not the first derivative (velocity).
There’s a long note laying out this James Dean game dynamic on the here if you’re interested in reading more.
Well, Dick, it’s got a good beat and you can dance to it.
– standard response to Dick Clark’s “how do you rate this song” question
Dancing is a vertical expression of a horizontal desire.
– Robert Frost
I know nothing, except what everyone knows – if there when Grace dances, I should dance.
– W.H. Auden
Those who dance are considered insane by those who cannot hear the music.
– George Carlin, stealing a line from Friedrich Nietzsche
As long as the music is playing, you’ve got to get up and dance. We’re still dancing.
– Chuck Prince, former Citigroup CEO, summer of 2007, before the Deluge
I don’t set trends. I just find out what they are and exploit them.
– Dick Clark
In 1949, Yale anthropologist George Murdock spearheaded the establishment of an inter-university research organization to continue his life’s work: the cataloguing of what he called cultural universals, the social behaviors that exist in every human society across time and geography. That institution – the Human Relations Area Files (HRAF) – is still going strong today, supporting all sorts of social science research by providing a fully-indexed electronic collection of cultural anthropological studies. The goal is to find patterns or commonalities in human social behavior, and it all stems from Murdock’s List: his compilation of the 67 universal social behaviors of the human animal. Every now and then someone publishes an updated version of Murdock’s List (either directly, like Donald Brown in his 1991 book, ”Human Universals”, or indirectly, like Steven Pinker in his 2002 book “The Blank Slate”), but it’s hard to improve on the original. It’s a fascinating list, with items such as “propitiation of supernatural beings”, “eschatology”, and “kinship nomenclature” right alongside “joking”, “hair styles”, and “mealtimes”. Pretty much everything we do in life is instantly recognizable as an item on Murdock’s List, and what isn’t just needs a little tweak in perception to fit one category or another.
I like looking at human behaviors through the lens of Murdock’s list for the same reason I like looking through the lens of evolutionary theory: behaviors that seem illogical or just plain stupid through our standard lenses of small-l liberalism or modern economic theory take on a new appearance with a change in perspective. In “Adaptive Investing” I discussed how non-economic behaviors such as routine mammograms and daily multivitamins (and portfolio risk scenario tests) make sense from an evolutionary perspective as a behavioral adaptation to demonstrate fitness, much like the dance of the Blue-Footed Booby or the ceremonial fight of the Oryx Gazelle, but they also make sense from a Murdock’s List perspective as a “propitiation of supernatural beings”, where we attempt to appease the great modern god Cancer (or in the case of risk scenario tests, the great ancient god Luck) with a ritualized sacrifice of our time and money.
One of Murdock’s 67 cultural universals is dancing. You find dance in every human society that ever existed (more so than music), and it will exist in every human society in the future. Why? Because it is part of our eusocial nature, part of the 10% bee-ness than makes up the human animal. Like the bee, we dance both to communicate and as a hard-wired response to signals from fellow members of our species. It’s not a language that we hear or generate in the same way that we speak English, but it has a grammar and a vocabulary nonetheless. Because it so primal, dance has an urgency that modern spoken languages do not, and I say that as an individual to whom dancing is very much a foreign language.
Interestingly enough, mathematics is not on Murdock’s List. Mathematics is an entirely formal language, about as far away in human terms as one can get from the language of dance (and yes, there have been efforts to create formal linguistic representations of dance, none of which have caught on). The unfortunate fact is that it’s very hard to represent human social behaviors in formal linguistic terms. That’s true whether the social behavior occurs in an artistic or cultural setting, like dancing, or whether it occurs in a market setting, like the “dancing” that Chuck Prince was referring to in 2007 when Citi was still underwriting and securitizing Alt-A and sub-prime mortgages as fast as humanly possible. But just because it’s really hard to describe a group dynamic like dancing with the same symbols that describe a capital asset pricing model doesn’t mean that dancing (or “dancing”) lacks a language and a grammar. You just need to develop an ear for it, and that’s where game theory can help.
Game theory is a bridge between hot-blooded social languages like dancing and cold-blooded formal languages like mathematics. Game theory is an abstraction of dynamic social interactions. Because it’s an abstraction, game theory usefully adopts some of the formal grammar of mathematics, which remains the most efficient way to represent theory regardless of what the theory is about. But game theory has no meaning or usefulness outside of a social setting. Like the tango, game theory takes two. Also like the tango, game theory is all about movement, the fluid movement of separate individuals who are bound up with each other in a system of mutual expectations and individual goals. Put it all together and game theory uses some basic mathematical concepts to organize our thinking about dynamic and strategic behaviors that have their origins in our social animal brains and Murdock’s List. It’s a powerful tool kit.
Some people have an intuitive ability to “speak” game theory fluently. These are geniuses like Dick Clark who can translate between the language of the social animal and the language of the self-aware brain effortlessly, and make an enormous fortune in the process. Clark recognized the trends, nuances, and idioms of popular culture just as surely as he recognized the economic formulas behind radio and television syndication. Was he a brilliant artist? Nope. Couldn’t dance, sing, or act. But he spoke the language of performers and somehow figured out how to communicate that primal grammar to Middle America in a way that felt “safe”. It seems weird today, as we are immersed in a popular culture of youth, but “youth culture” (a phrase coined by Paul Anka in reference to Dick Clark) didn’t exist before American Bandstand. As much as anyone over the past 50 years, from the Beatles to Elvis Presley to any performer you want to name … Dick Clark was responsible for the modern landscape of how the languages of music and dance are communicated in a commercially lucrative fashion. His secret (other than a bizarrely youthful face)? Clark understood the Common Knowledge Game.
Clark didn’t poll America to determine their taste in music. He told them their taste in music … not directly, but by creating common knowledge – ideas that a crowd believes that the crowd believes. With the American Bandstand group dance staging and scripted questions, Clark allowed the TV audience to see a crowd of attractive young people act as if the music were popular. This is all it takes. Clark didn’t have to force his preferred choice of popular culture on his audience like some centrally-planned Ministry of Culture. The TV audience chose it all on their own, thinking all along it was their choice! This is the power of the Emperor’s New Clothes. This is the power of the sitcom laugh track and the live studio audience. This is the power of public coronations and executions. This is the power of Tahrir Square and Tiananmen Square. This is the power of the crowd seeing the crowd, and it is the most potent force in the social world.
It’s certainly the most potent force in the social world of markets, and every Central Banker today is playing the Common Knowledge Game just as hard as Dick Clark ever did.
Here’s last Thursday’s (Jan. 9) WSJ headline teaser at 9 am ET after the ECB press conference:
European Central Bank President Mario Draghi used unexpectedly strong language to stress that the central bank will remain accommodative for as long as necessary.
How is this the Common Knowledge Game? Since August 2012 we have watched the markets dance to Draghi’s tune. If you don’t know by now that Draghi’s words move the market crowd, then you’re an idiot. But you’re not an idiot. And neither is any one of the hundreds of thousands of people reading the WSJ headline. And neither is Draghi. We are told by the WSJ that Draghi’s words today have a good beat and you can dance to it. So we do. We dance, just like we’ve been trained to do by watching this show 30 times before.
As a result, Italy and Spain’s equity and credit markets outperformed Germany’s by a mile after Draghi’s signal … which was exactly the intended effect (Spain is now borrowing money at the cheapest rate in the euro era!) and exactly why it is so difficult to be a macro Value investor today. All of your fundamental indicators that show (correctly) that Italy and Spain are ridiculously overvalued at current prices relative to, say, Germany don’t matter in the least. Or rather, they matter, but they evaporate like dew when the Draghi sun shines at a press conference. Note to Jeremy Grantham: it costs Draghi nothing to use “unexpectedly strong language” to keep this game going for a looonnng time.
Here’s last Friday’s (Jan. 10) WSJ headline teaser at 9 am ET after the disappointing jobs report: “Weak jobs report complicates Fed plans.” Seems innocuous enough, right? Nope, this is a market roiler, especially for the most sensitive assets to the Narrative of Central Bank Omnipotence … assets like gold.
Gold rocked last Friday, on deflationary news. Huh? I know that gold bugs will tell you how great gold can be in a deflationary environment, but come on, that only makes sense if you’re talking about end-of-the-world deflation. The jobs report last Friday was run-of-the-mill, plain vanilla disappointing growth news. Not end-of-the-world news, not even negative growth news … just disappointing growth news. This should be bad for gold prices, not good, and Friday’s price action made no sense through the lens of traditional economic theory. But it made perfect sense through the lenses of history and game theory, where the meaning of gold has shifted from an alternative store of value to insurance against Central Bank policy error.
Of course, this sort of challenge to the Narrative of Central Bank Omnipotence could not go unaddressed, and sure enough by 7 pm last Friday you had a WSJ article by none other than Jon Hilsenrath, the Common Knowledge spokesman for the Fed, titled “Fed Unlikely to Alter Course After Jobs Report.” Over the weekend and on Monday you had at least three Fed Governors come out with similar statements, that there was no confusion or complication imposed by the jobs report. Nothing to see here folks, move along. None of these Powers That Be are taking issue with whether or not the Friday jobs report was bad news … the only thing that matters is how this news impacts the common knowledge structure that generates their power to control market outcomes. That’s the threat that must be squelched. This is what Bernanke meant when he talked about using communications as a policy tool, and this is what Yellen (and Draghi and Abe and everyone else in the club) will continue to do … use public statements to play the Common Knowledge Game and drive market outcomes by proxy.
I can sleep well at night if you get nothing else out of Epsilon Theory beyond the recognition that a) you are being played, and b) there are rules and logic to how you are being played. But I’d also like to demonstrate that c) it’s entirely rational to play along (to a point), and d) you can be a player, too.
It can be entirely rational to act as if the Emperor is wearing a beautiful set of clothes. In fact, when you’re caught in a Common Knowledge Game others will look at you askance if you act publicly according to the evidence of your own eyes rather than the evidence of the crowd watching the crowd. But you need to recognize that’s what you’re doing. It’s critically important to avoid internalizing your behavior, falling into what Kant called a “dogmatic slumber”, believing in your heart of hearts that the Emperor truly looks marvelous. The tragedy of 1984 is not that Big Brother rules Oceania, but that in the end, Winston loves Big Brother and gives himself over to collective solipsism. The fright of Invasion of the Body Snatchers is not the cat-and-mouse with alien pod people, but that in the end, Donald Sutherland becomes a pod person and outs the human survivors.
Other than the minor detail of losing your free will, why is it so important to avoid becoming a pod person? Why is it a bad idea solely from the perspective of being an effective investor? Because the tango is an unpredictable dance. Because your best move in ANY game is not pre-ordained or even fully under your control. Your best move depends not only on Know Thyself, advice that Socrates gave almost 3,000 years ago and is still the smartest, deepest thing that anyone has ever said, but also on Watch the Other, the sensitivity that all social animals possess to look for and pick up on minute changes in the signals that our hive-mates emit.
The moment you give yourself over to the Dick Clarks of the world who create common knowledge, the moment you abdicate your keenly evolved human abilities of self-awareness and other-evaluation … that’s the moment you put yourself at the most risk. Because the game will change. Even if the external conditions of the world today are exactly the same as the external conditions of the world yesterday, a change in the internal conditions of the other game-players, whether it’s a queen bee like Draghi or a set of worker bees like us, can change your best move.
This is the insight that game theory provides, an insight that econometrics (which only looks at external conditions) can’t – how social dynamics and group interactions impact market behaviors. Game theory predicts that gold prices will go up on ANY news – even deflationary news – IF that news creates a worker bee perception that the queen bees are rattled by the news. And vice versa, gold will go down on ANY news – even inflationary news – IF that news improves the perception that global central banks are large and in charge … the Narrative of Central Bank Omnipotence. It’s not the news itself, which is what an econometric perspective would say, but how that news impacts the belief structures that comprise the game. It’s not the card that’s dealt (the news), but how that card fits the hand that your poker opponent is representing. An ace of spades is good news for your opponent in the abstract, but it might be terrible news if he’s representing a heart flush. Game theory is all about playing the player, not the cards. That’s not a replacement for understanding the fundamentals and the math of drawing this card or that, but it sure is a complementary skill set. If you want to win.
Well, it’s funny that people, when they say that this is evidence of the Almighty, always quote beautiful things. They always quote orchids and hummingbirds and butterflies and roses. But I always have to think, too, of a little boy sitting on the banks of a river in West Africa who has a worm boring through his eyeball, turning him blind before he’s five years old. And I reply and say, “Well, presumably the God you speak about created the worm as well,” and now, I find that baffling to credit a merciful God with that action. And therefore it seems to me safer to show things that I know to be truth, truthful and factual, and allow people to make up their own minds about the moralities of this thing, or indeed the theology of this thing.
– David Attenborough
You still don’t understand what you’re dealing with, do you? Perfect organism. Its structural perfection is matched only by its hostility.
You admire it.
I admire its purity. A survivor…unclouded by conscience, remorse, or delusions of morality.
Look, I am…I’ve heard enough of this, and I’m asking you to pull the plug. [Ripley goes to disconnect Ash, who interrupts]
I can’t lie to you about your chances, but…you have my sympathies.
– Alien (1979)
From an evolutionary perspective, the parasite is a beautiful creature. Instead of possessing a set of adaptations that make it suitable for thriving within a “natural” habitat – an ocean, a forest, a tundra, a jungle, etc. – the parasite typically finds its habitat within an organism itself. Parasites twist the core evolutionary process of adaptive radiation in a new direction, finding opportunities for new niches and species differentiation within host species that emerge over time in new geographies, not the new geographies themselves. To a parasite, the world IS an oyster. Given the amazing diversity of life on Earth, using life-forms as habitats presents a phenomenal opportunity for parasitic adaptive radiation and thus, evolutionary success. Almost every multi-cellular life-form on the planet serves as a host for one or more parasites, and as a result parasites account for more biodiversity and sheer numbers than non-parasitic life. In many respects, the parasite is an evolutionary apex.
Why do parasites get such bad press? Most of them are not what zookeepers would call “charismatic vertebrates”, but instead tend to be viruses or squishy worms with nasty looking (from a human perspective) and voraciously-presented mouths. That’s a problem for any public relations campaign. More importantly, parasites do not behave according to what game theorists call a “nice” or cooperative strategy. These are not win-win relationships, where there’s some sort of symbiotic benefit shared between the two organisms, some sort of reciprocal value provided by the tapeworm to whatever warm-blooded intestinal tract it happens to inhabit. No, the very definition of a parasite is that it is harmful to its host, with a one-way transfer of resources. Parasites are squatters, not tenants. They are thieves, not buyers.
But they don’t steal a lot. Not usually, anyway, as examples of Alien-esque life-forms that kill their hosts in some burst of gore are few and far between. Almost all parasites are better off keeping their hosts alive for as long as possible, so it would seem natural for any individual parasite to take just enough from its individual host to live well without killing off the host. And this is, in fact, the case – few parasites kill their hosts – but it’s the why behind this fact, the evolutionary dynamic behind this fact, that I want to examine.
An individually successful hookworm is not thinking “Gee, I better slow down a little bit here. Wouldn’t want to damage my host too much.” That hookworm acts exactly as it is programmed to act … to eat and reproduce as much as it is hookworm-ly possible to eat and reproduce. An evolutionary perspective requires us to look at the population of hookworms in relationship to its habitat – the population of host animals – to figure out the evolutionarily stable strategy (or ESS as it’s known) for hookworms. We will never figure out the ESS by looking at an individual hookworm and an individual host, because you can’t just extrapolate from what’s good or bad for that individual relationship, no matter how much of a long-term view you take for that individual hookworm and its descendants.
From a population perspective, a parasite species is trying to balance growth with robustness in the context of its life-form habitat in exactly the same way that a non-parasite species is trying to balance growth and robustness in the context of its geographical habitat. Both grow by consuming resources. If growth outstrips resource supply, that’s a problem, because the offspring population is going to starve and die off. This is the population dynamic that is most closely associated with the work of Thomas Malthus, who despaired of any animal (including the human animal) escaping this deterministic pattern of population growth outpacing resource availability, punctuated by enormous population die-offs in order to restore the balance between resource supply and demand. In the human context, innovation in our tools and our mental constructs has allowed us to increase our species population essentially unchecked by Malthusian logic since the 14th century and the Black Death, with only a small hiccup from pandemic and global war in the early 20th century. In the non-human context, any respite from resource-depletion die-offs must come from the glacially slow process of natural selection and the evolution of adaptations that push a species into a more robust, less volatile relationship with its environment. This is an ESS.
What’s interesting (to me, anyway) is that a parasite species tends to have more options in the development of its ESS than a non-parasite species. A parasite is not geographically “grounded” like a non-parasite. Because its habitat is another population of life-forms, the population of parasites can more easily “choose” how to allocate its resource consumption. Maybe the parasite species is better off if it concentrates on a few individuals within the host population and really loads up on those unlucky targets, depleting all of their resources and killing them in the process, but leaving a critical mass of healthy hosts unharmed so that they can reproduce and provide juicy targets in the future. Maybe the parasite species is better off by getting smaller and less noticeable or impactful on the host species. Maybe the parasite species is better off if it moves from host species to host species within its lifecycle, so that no single host species is damaged too severely even if the individual parasites run rampant during their stay. These are strategic options at the population level that are much more difficult to develop or evolve within species that have a specific geography for a habitat. Not impossible … maybe you can rotate from one resource-rich patch of your geography to another and then back again (migration) … but more difficult. A resource habitat created by life-form populations is just more fungible than a resource habitat created by a singular geography, and that’s a really big deal for an ESS.
This flexibility (and hence evolutionary speed) in creating an ESS is a big reason why parasites dominate the world. Like humans, they’re pretty good at getting around the gloomy future that Malthus predicted. Not by inventing the printing press, fossil fuel energy sources, and liberal ideas of social organization, but by quickly evolving a wide range of behavioral adaptations that are extremely effective at balancing resources and growth. Here’s what these parasite ESS’s have in common: they make the parasite population invisible to the host population. The relationship between individual parasite and individual host may also be invisible, but it also might be a violent struggle to the death or somewhere in between … evolution doesn’t care about individuals. Evolution has to be understood at the group level, and the evolutionary beauty of the parasite is its amazing suitability and fitness – at the group level – for using life itself as a habitat.
Now why do I care so much about parasites and their evolutionarily stable strategies? Because the most effective alpha-generating investment strategies are parasites. An alpha-generating strategy of the type I’m describing uses the market itself as its habitat. It’s not an investment strategy based on the fundamentals of this company or that company – the equivalent of a geographic habitat – but on the behaviors of market participants who are living their investment lives in that fundamentally-derived habitat. A parasitic strategy isn’t the only way to generate alpha – you can also be better suited for a particular investment environment (think warm-blooded animal versus cold-blooded animal as you go into an Ice Age) and generate alpha that way – but I believe that the investment strategies with the largest and most consistent “edge” are, in a very real sense, parasites.
What do these parasitic strategies look like? Their number is legion. They exist in every nook and cranny of every public market in the world, and they feed off the behaviors of non-economic or differently-economic market participants. A giant pension fund isn’t engaged in commodity markets because it has an opinion on the contango curve of oil futures; it’s trying to find a diversifying asset class for a massive portfolio that needs inflation protection. If you’re an experienced trader in that market and you see signs of the giant pension fund lumbering through the brush … well, you’re in the wrong business if you can’t skin a few dimes here. This is what good traders DO, and the really good ones have devised effective processes and strategies that comprise a strategy, so that it’s not just a one-off trade but an expression of a consistent informational edge. These strategies are inherently niche-oriented, and they do not scale very well, any more than any single parasite species can scale beyond the size of its host species. But the informational edge is real, which means that the alpha generation is real, and that’s a beautiful thing even if the outward form is as ugly as a hookworm.
Why does a parasitic strategy have a bigger informational edge than a non-parasitic strategy? Because market participant behaviors are far more consistent over time than the economic fundamentals of companies or countries. I can predict with 100x more confidence what a giant pension fund is trying to achieve with its market activities than what S&P 500 earnings will actually be next year. World events and market outcomes are utterly unpredictable, especially in a global environment of economic deleveraging, massive monetary policy experimentation, and political fissures the size of the Grand Canyon within and between countries. Human nature, though, is as constant as the northern star.
How does a parasitic strategy with an informational edge persist? Why isn’t it arbitraged (or regulated) away? First, remember that we’re talking about the group level, not the individual. Certainly it’s possible to have competition between individual parasitic strategies that split the economic resources taken from the host. But at the group level, just like their biological cousins, effective parasitic investment strategies are largely invisible to their hosts. As Baudelaire said way before Kevin Spacey did in The Usual Suspects, the greatest trick the devil ever pulled was convincing the world he didn’t exist.
What’s the pay-off for thinking about alpha-generation investment strategies through this evolutionary perspective? Two big pay-offs, I think.
First, one of the trickiest puzzles of effective allocation and risk management for anyone who invests in actively managed funds is trying to figure out the capacity limits of those strategies. This typically isn’t something you worry about with a strategy that is focused on capturing broad market returns or one that uses big liquid securities like S&P e-mini’s to express its portfolio, but it’s a significant concern with funds that claim to have some sort of informational or process edge (alpha generation potential) and express that edge with single-name securities or any sort of liquidity-challenged instrument. There are very powerful formulas in the evolutionary biology toolkit for figuring out both the optimal population size of a parasite species relative to its host as well as the optimal amount of resources that the parasite population should take from the host. This is at the heart of figuring out what behaviors, including size, are evolutionarily stable for the parasite, and it is directly applicable to alpha-oriented investment strategies with parasitic qualities. Instead of taking a manager’s word on investment capacity or making some rough guess based on the AUM of other managers (which is basically the state of the art today), these ESS tools should allow us to project investment capacity directly for many alpha-generation strategies.
Second, it shows how one might create an advanced multi-strat investment platform, one that uses the Adaptive Investing perspective to identify the alpha-generation strategies with the most effective ESS’s, as well as the optimal capacity and allocation characteristics for the market “habitat” in which these strategies operate. Unlike the individual strategies, which inherently scale poorly, a multi-strat structure scales easily, limited only by the number of individual strategies brought under the operational umbrella. Would this sort of investment platform have something of an image problem, intentionally seeking out and unafraid to characterize certain investment strategies as parasites? Maybe. But somehow I think there are plenty of others out there who, like me, can see the evolutionary beauty of these strategies and are not afraid to call them by their proper name. I hope you’ll join me in this exploration.
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:
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”
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.
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.