We’ve had a heckuva busy year at Epsilon Theory, so to ring out 2017 I thought it might be helpful to distribute a master list of our publications over the past 12 months. We’re long essay writers trying to make our way in a TLDR world, so even the most avid follower may well need a map!
It’s also a good opportunity to give thanks where thanks are due.
First, a heartfelt thank you to my partners at Salient for contributing a ton of resources to make Epsilon Theory happen, never once asking me to sell product, and allowing me the leeway to speak my mind with a strong voice that would make a less courageous firm blanch. Epsilon Theory isn’t charity, and it’s the smart move for a firm playing the long game, but no less rare for all that.
Second, an equally heartfelt thank you to the hundreds of thousands of readers who have contributed their most precious resource – their time and attention – to the Epsilon Theory effort. We live in a world that is simultaneously shattered and connected, where we are relentlessly encouraged to mistrust our fellow citizens IRL but to engage with complete strangers on social media. It’s an atomized and polarized existence, which works really well for the Nudging State and the Nudging Oligarchy, less well for everyone else. The lasting impact of Epsilon Theory won’t be in what we publish, but in how we’re able to bring together truth-seekers of all stripes and persuasions, because it’s your engagement with the ideas presented here that will change the world. I know that sounds corny, but it’s happening.
Now on to the 2017 publishing map.
Our big initiative for this year was to publish two coherent sets of long-form notes, one by yours truly and one by my partner Rusty Guinn.
My series of essays is called Notes From the Field. As many long-time readers know, I’m originally from Alabama but now live out in the wilds of Fairfield County, Connecticut, on a “farm” of 44 acres. I put that word in quotations because although we have horses and sheep and goats and chickens and bees, my grandfather – who owned a pre-electrification, pre-refrigeration, pre-pasteurization dairy farm in the 1930s – would surely enjoy a good belly laugh at my calling this a farm. Still, I’ve learned a few things over the years from the farm and its animals, and they’ve helped me to become a better investor.
Notes From the Field: The eponymous note has two essays: “Fingernail Clean”, introducing the concept of the Industrially Necessary Egg – something we take for granted as proper and “natural” when it’s anything but, and “Structure is a Cruel Master”, introducing the genius of both humans and bees – our ability to build complex societies with simple algorithms.
Horsepower: The horse and horse collar revolutionized European agriculture in the 10th and 11th centuries, a revolution that lives on in words like “horsepower” and changed the course of human civilization. Today we are struggling with a productivity devolution, not revolution, and there is nothing more important for our investments and our politics and our future than understanding its causes and remedies.
The Arborist: We are overrun with Oriental Bittersweet, privet, and kudzu — or as I like to call them, monetary policy, the regulatory state, and fiat news — invasive species that crowd out the small-l liberal virtues of free markets and free elections. What to do about it? Well, that’s citizenship, and I’ve got some ideas.
Always Go To the Funeral: Going to the funeral is part of the personal obligation that we have to others, obligation that doesn’t fit neatly or at all into our bizarro world of crystalized self-interest, where scale and mass distribution are ends in themselves, where the supercilious State knows what’s best for you and your family, where communication policy and fiat news shout down authenticity, where rapacious, know-nothing narcissism is celebrated as leadership even as civility, expertise, and service are mocked as cuckery. Going to the funeral is at the heart of playing the meta-game – the game behind the game – of social systems like markets and elections, and it’s something we all need to understand so that we’re not played for fools.
Sheep Logic: We think we are wolves, living by the logic of the pack. In truth we are sheep, living by the logic of the flock. In both markets and politics, our human intelligences are being trained to be sheep intelligences. Why? Because that’s how you transform capital markets into a political utility, which is just about the greatest gift status quo political institutions can imagine.
Clever Hans: You don’t break a wild horse by crushing its spirit. You nudge it into willingly surrendering its autonomy. Because once you’re trained to welcome the saddle, you’re going to take the bit. We are Clever Hans, dutifully hanging on every word or signal from the Nudging Fed and the Nudging Street as we stomp out our investment behavior.
Pecking Order: The pecking order is a social system designed to preserve economic inequality: inequality of food for chickens, inequality of wealth for humans. We are trained and told by Team Elite that the pecking order is not a real and brutal thing in the human species, but this is a lie. It is an intentional lie, formed by two powerful Narratives: trickle-down monetary policy and massive consumer debt financing.
The Three-Body Problem: What if I told you that the dominant strategies for human investing are, without exception, algorithms and derivatives? I don’t mean computer-driven investing, I mean good old-fashioned human investing … stock-picking and the like. And what if I told you that these algorithms and derivatives might all be broken today?
Rusty’s series of essays, Things that Matter (and Things that Don’t), connects to mine with his just published The Three-Body Portfolio. It’s a wonderful piece on its own (I can’t believe I didn’t think of the Soylent Green reference – Epsilon is people!) and is a great segue to his 2017 serial opus. In chronological order:
With A Man Must Have a Code, Rusty begins the conversation about why we think that all investors ought to have a consistent way of approaching their major investment decisions.
In I am Spartacus, Rusty writes that the passive-active debate doesn’t matter, and that the premise itself is fraudulent.
In What a Good-Looking Question, Rusty writes that trying to pick stocks doesn’t matter, and is largely a waste of time for the majority of investors.
In Break the Wheel, Rusty argues that fund picking doesn’t matter either, and he takes on the cyclical, mean-reverting patterns by which we evaluate fund managers.
In And they Did Live by Watchfires, Rusty highlights how whatever skill we think we have in timing and trading (which is probably none) doesn’t matter anyway.
In Chili P is My Signature, Rusty writes that the typical half-hearted tilts, even to legitimate factors like value and momentum, don’t matter either.
In Whom Fortune Favors (Part 2 here), Rusty writes that quantity of risk matters more than anything else (and that most investors probably aren’t taking enough).
In You Still Have Made a Choice, Rusty writes that maximizing the benefits of diversification matters more than the vast majority of views we may have on one market over another.
In The Myth of Market In-Itself (Part 2 here), Rusty writes that investor behavior matters, and he spends a lot of electrons on the idea that returns are always a reflection of human behavior and emotion.
In Wall Street’s Merry Pranks, Rusty acknowledges that costs matter, but he emphasizes that trading costs, taxes and indirect costs from bad buy/sell behaviors nearly always matter more than the far more frequently maligned advisory and fund management expenses.
Bernard: If knowledge isn’t self-knowledge, it isn’t doing much, mate. Is the universe expanding? Is it contracting? Is it standing on one leg and singing ‘When Father Painted the Parlour’? Leave me out. I can expand my universe without you.
‘She walks in beauty, like the night of cloudless climes and starry skies, and all that’s best of dark and bright meet in her aspect and her eyes.”
—Arcadia, Tom Stoppard
It is a romantic thought, that we might divorce our personal universe from the universe around us. For us investors, maybe that means to hide in a room building an elegant model to work out the true value of a thing. I mean, by itself it’s a complete waste of time…but so romantic!
To make a prairie it takes a clover and one bee, One clover, and a bee. And revery. The revery alone will do, If bees are few. — “To make a prairie”, Emily Dickinson
Since I’m bogarting Ben’s title, I might as well steal his best literary reference, too. The market isn’t necessarily tied to ‘fundamentals’ any more than a prairie is to bees. Revery alone will do, and sometimes it will do for a very, very, very long time.
A true German can’t abide the French, But he’ll gladly drink their wine. — Faust, Johann Wolfgang von Goethe
You don’t have to be French to drink their wine, y’all. Being part of the Epsilon Theory pack doesn’t mean buying into narratives. It means understanding that in a market, if it matters to someone, it should matter to everyone. And narratives matter to a whole lot of someones.
Epsilon Theory started from a pretty simple idea. Ben observed that no financial or econometric model can ever fully explain the returns or volatility of financial markets. I don’t think he’ll be too mad if I point out that this wasn’t a particularly novel observation. After all, every statistical model in the world has an error term that basically accounts for this — epsilon.
β + α + ε
Said less vaguely, epsilon is the way in which — as people — investors respond to both financial and non-financial stimuli in various non-random ways. It is an observation that a not insignificant portion of the systematic (i.e. not diversifiable) risk and return in your portfolio is completely divorced from the risks faced by economies and businesses. It is a feature only of the markets and the people who comprise them.
Some regard changing perceptions, sentiment and shifting narratives as a source of short-term volatility in securities prices, and little more. Indeed, that is the implication of the old Benjamin Graham trope I disputed in The Myth of Market In-Itself — that the market is a short-run voting machine, but a long-run weighing machine. Sure, sentiment may matter in the short run, but eventually truth will out! I did a fair job, I think, of identifying my issues with that point of view, but as per usual, it was Ben that really got to the heart of the issue. In his latest note, he characterizes the occasional sharp rise in unpredictability of market outcomes — not to be mistaken for volatility — as the result of a Three-Body Problem. You do yourself a disservice if you haven’t read the piece, and probably a greater disservice if you haven’t read the Liu Cixin book of the same title recommended in it. But in short, a three-body problem refers to a system that is solvable not through elegant algorithm, but only through brute-force computation. There is no closed-form solution to predict the future locations of a set of three planetary bodies in a vacuum like, say, the Earth, the sun and the moon.
In most environments, where the purpose of markets is to efficiently and accurately price risk of various uses of capital, those markets tend to behave more or less like two-body systems. The interaction of Planet A (which we’ll call ‘fundamental data’) and Planet B (which we’ll call ‘prices’) is generally predictable. Oh sure, there’s volatility. Remember, not everyone agrees on the starting point and velocity of Planet A — at least, not since Reg FD, anyway. Information takes time to propagate. But we also know that Planet C (let’s call it ‘epsilon’) is sitting out there somewhere. Yet it’s far enough away that its gravity can’t do more than induce short- and medium term distortions in the relationship between A and B. If you knew the truth about the starting positions and velocities of Planet A and Planet B, however, you could develop a formula that would tell you within a pretty fair margin where prices would be down the line.
In this typical state of the world, being a better investor has meant getting better at uncovering the truth about Planet A so that you can predict Planet B’s future location. It’s no wonder that a generation of investors grew up learning about traditional security analysis, the only way investment management is taught in every business school in the world.
Still, everyone from the most well-respected market commentators to the staunchest Graham and Dodd-quoting undergrad recognizes the existence of markets in which Planet C — epsilon — contributes its gravity to the system. Among those periods in which our ability to make predictions on the basis of relationships between fundamental data and securities prices is especially poor, are those we know as bubbles and manias. William Bernstein characterizes these periods as those typified by the “flood of new investors who swallow plausible stories in place of doing the hard math.” He goes on to quote Templeton, admonishing investors, “The four most expensive words in the English language are ‘This time it’s different.’”
Well, guess what? Roll your eyes at the expression to your heart’s content, but I’m telling you what Ben has been telling you for years now:
This Time It’s Different.
It’s not different because people really got it right this time (in ways they missed every other time) about some new technology that’s going to Change The World! Electric cars, cryptocurrency, AI and automation, these may all be fabulous things, and they may well prove to be game-changers for productivity and returns on capital down the line, but if you think any of those things explain current valuations, you’re nuts. You’re also wrong.
It’s different because financial markets are no longer a mechanism for price discovery and the pricing of risk of capital allocation decisions.
Markets have been made into a utility. More to the point, they have been made into a political utility, a tool for ensuring wealth and stability of our political structures. The easing tools we dabbled in to stabilize prior business cycles were brought to bear instead as tools for propping up and expanding financial asset prices. Beyond the direct marginal price impact of the easing itself, central bankers tailored communications policies to create Pavlovian responses to every narrative. Our President tweets about the policy implications when the S&P 500 hits new highs, for God’s sake. This isn’t a secret, y’all. The singular intent of every central banker in the world is to keep the prices of financial assets from going down, and the singular intent of every government that puts those central bankers in power is to ensure that they do so, in order to retain social stability. Sure, there’s a dual mandate. But the mandates aren’t employment and price stability. They’re (1) expanding financial asset prices and (2) effectively marketing the idea of corresponding wealth effects to the public.
Markets have also rapidly become a social utility, an inextricable part of every contract between governments and the governed. Underfunded pensions and undersized boomer 401(k) accounts mean that ownership of risky assets is not a choice driven by diversification or relative return expectations, but by the fact that it is the only asset they can buy that has any potential of meeting the returns they would need to be adequately funded. Let’s say that you are running a state pension plan that is 65% funded. Your legislature is telling you that no help is coming from the state budget. You and every member of your agency will be fired if you even suggest cutting benefits, if you even have that authority. Your consultant or internal staff just did their new mean reversion-based capital markets return projections, and higher valuations mean projected returns on everything are lower. What’s worse, your funded status assumes returns that are higher than anything on their sheet. You are being presented with a Hobson’s Choice — behind Door #1, you get fired, and behind Door #2, you lever up your stock exposure with an increased private equity allocation. This a brutal position to be in.
And sure, like most markets with bubble-like characteristics, this one has become a utility for psychic value as well. Investors buy Bitcoin on the narrative-driven belief that it is an ‘investment’ in the technology, a way to participate in shifting the economy toward privately negotiated and settled transactions. It isn’t. We’ve all seen the absurd stock charts of companies who did nothing more than add “blockchain” to their names. We’ve observed TSLA, NFLX and CRM continue to trade on earnings reports that provide zero incremental data on business direction or momentum but heroic narratives that the sell side dutifully push out to the masses looking for good stories. If you must own risky assets and those assets don’t have growth, then revery alone will do, if bees are few.
It may comfort us to say that “The market has been divorced from fundamentals for so long, but eventually it must swing back.” And it will. The point of this note, and the point of The Three Body-Problem isn’t to say that it won’t. Planet C will drift away again, and outcomes will look more like what economic and business fundamentals would predict. More like our historical analysis of what drives good, high quality investments. But too many investors are comforting themselves with the stories of the 1990s, of the Nifty Fifty, and the idea that non-fundamentally-driven markets mean return to sanity after five to ten years. But they don’t have to. And because of the utilitization of markets, because of the exit of passive-oriented investors from the price-setting margin of markets, it’s possible that they won’t for a very long time.
This Three-Body Problem isn’t going anywhere for a while.
The Three-Body Portfolio
When I began this Code series at the beginning of 2017, I kicked it off with A Man Must Have a Code, a conversation about why we think that all investors ought to have a consistent way of approaching their major investment decisions. I posited that a code ought to consist of a concise list of Things that Matter, Things that Don’t Matter and Things that Don’t Always Matter (But Do Now). And so my notes have focused on investing principles that I think of as generalized solutions. These are things that I believe are true in both Two-Body and Three-Body Markets:
In I am Spartacus, I wrote that the passive-active debate doesn’t matter, and that the premise itself is fraudulent.
In What a Good-Looking Question, I wrote that trying to pick stocks doesn’t matter, and is largely a waste of time for the majority of investors.
In Break the Wheel, I argued that fund picking doesn’t matter either, and took on the cyclical, mean-reverting patterns by which we evaluate fund managers.
In Chili P is My Signature, I wrote that the typical half-hearted tilts, even to legitimate factors like value and momentum, don’t matter either.
In Whom Fortune Favors (Part 2 here), I wrote that quantity of risk matters more than anything else (and that most investors probably aren’t taking enough).
In You Still Have Made a Choice, I wrote that maximizing the benefits of diversification matters more than the vast majority of views we may have on one market over another.
In The Myth of Market In-Itself (Part 2 here), I wrote that investor behavior matters, and spent a lot of electrons on the idea that returns are always a reflection of human behavior and emotion.
In Wall Street’s Merry Pranks, I acknowledged that costs matter, but emphasized that trading costs, taxes and indirect costs from bad buy/sell behaviors nearly always matter more than the far more frequently maligned advisory and fund management expenses.
In all of these, you’ve gotten a healthy dose of emphasis on getting beta — how we get exposure to financial markets — right. But you’ve seen precious little on alpha — uncorrelated sources of non-systematic, incremental return. Where we dealt with the usual ways in which investors seek out alpha, I have been critical. Maybe even derisive. Sorry, not sorry. There’s a reason:
Even in normal environments, alpha is hard.
Alpha is hard because it’s hard to measure. It’s hard to know if what we’re doing is actually something that adds value, or if we’re being fooled by randomness. We may even just be layering on some other systematic factor, or beta, that is just compensating us for taking additional risk. Every couple of years, someone rediscovers that bond managers tend to “have more persistent alpha”, and a couple of weeks later, someone rediscovers that bond managers just layer on more corporate credit risk than the benchmark. Every couple years, stock-picking strategies go back into vogue — it’s a stock-pickers’ market, they say! Fundamentals matter again! No, they don’t. You’re structurally smaller cap and loaded up on higher volatility names, and when those factors work you feel smart.
Alpha is hard because randomness is an insanely powerful force in the universe and within our industry. Any time I hear a fund manager or financial advisor say, “Look, a 10-year track record like that doesn’t just happen by accident,” every part of me wants to scream, “Yes, it bloody well does, and if there’s anything true and good about mathematics at all, it will happen by accident ALL THE TIME.” I’m not saying that Warren Buffett’s success is an accident, but I am absolutely saying that with as many investors as there are, it is improbable that history would not create Warren Buffett’s track record. We are all looking for a way to increase returns that doesn’t involve taking more risk, and once we’ve gotten all we can out of diversification, believing in alpha is our only choice.
In a three-body market where epsilon exerts its gravity, alpha is not just hard. Finding it emphasizes entirely different types of data and analysis. The whole point of recognizing an increasingly chaotic system is that our confidence in the causal relationships over time and between assets at a point in time drops significantly. Given that tools relying on temporal and cross-asset relationships are the ones we most often use to evaluate investment strategies, it puts us in a bit of a pickle! Sure, there are some exogenous strategies like high-frequency trading that are pretty effective across environments for mechanical reasons. But many of the “time-tested” strategies that work in Two-Body Markets can stop working for a very long time, and the “new” strategies we identify in our in-sample periods can start looking like hot garbage the second we drop them out-of-sample. The search for alpha in this kind of environment — even when it occasionally bears fruit — is time-consuming, expensive, and often leads to unintended risk, cost and diversification decisions that more than offset any positive that they generate. We get a stock pick right, but it is dwarfed by sector effects. We pick the right country to invest in, but get killed on currency. For many investors – for most investors — this means that trying to beat “the market” on an intra-asset class level or at on an inter-asset class level through tactical asset allocation should not be part of their playbook. For these people, I hope the Code to this point is a useful tool. Thanks for reading.
But for those who know they won’t be content with that very adequate outcome, I’ll do my best to talk about alpha strategies that I think can work in a Three-Body Market. That means identifying the likelihood of success of various analytical security and asset class selection strategies. It also means giving you my perspective on what edge (ugh, I know) would even conceivably look like in a fund manager. As we close the door on 2017, I also close my series on The Things That Matter and The Things that Don’t Matter. As we open the door on 2018, look forward to a new series on the Things that Don’t Always Matter (But Do Now).
Together, I think they’ll provide a pretty good roadmap for the Three-Body Portfolio. But I mean, even if they don’t, at worst you’ll get to read horror stories of terrible fund managers, so what have you really got to lose?
From Texas, my best wishes for a prosperous New Year to you and yours.
 I know some will pipe in that this is just part of beta. This is mathematically true in that systematic sources of risk are what we mean when we say ‘betas’, but anyone reading this who pretends not to understand that what we’re talking about is a specific component of systematic risk that tends to be understated in favor of econometric and financial variables is a filthy pedant.
 Actually, he tweets about the Dow hitting new highs, because of course he refers to the Dow.
That space and time are only forms of sensible intuition, and hence are only conditions of the existence of things as phenomena; that, moreover, we have no conceptions of the understanding, and, consequently, no elements for the cognition of things, except in so far as a corresponding intuition can be given to these conceptions; that, accordingly, we can have no cognition of an object, as a thing in itself, but only as an object of sensible intuition, that is, as phenomenon — all this is proved in the analytical part of the Critique; and from this the limitation of all possible speculative cognition to the mere objects of experience, follows as a necessary result.
— Immanuel Kant, The Critique of Pure Reason (1781)
I know, diving right into 18th-century German metaphysics is a real crowd-pleaser. But this is just a bunch of fancy words to say that we can never know the fundamental truth of a thing independently from our perceptions and experience. It’s the realization that makes Kant probably the most indispensable of the great thinkers. Doubly so for Epsilon Theory. We desperately want to believe that with enough information and analysis, we can know the true value of something. There is an almost mythological belief in the market as the mechanism through which we uncover that truth. The rest of the world will realize that we are right, and then we will make money. But the ‘true value’ of a thing — the market in-itself — isn’t something we can know. We observe value only through price, a measure based on our collective subjective experience.
Is there any hiding of the character of an apple-tree or of a geranium, or of an ore, or of a horse, or of a man? A man is known by the books he reads, by the company he keeps, by the praise he gives, by his dress, by his tastes, by his distastes, by the stories he tells, by his gait, by the motion of his eye, by the look of his house, of his chamber; for nothing on earth is solitary, but everything hath affinities infinite.
— Journals of Ralph Waldo Emerson, June 7, 1860
Still, just because there isn’t a knowable intrinsic value to an investment, no investment in-itself, it doesn’t mean we can’t know anything about it. The people who form the market and apply their sensible tuition to these things have affinities infinite. Some of those affinities can be observed or inferred. This is the soul of the Narrative Machine writ large.
Run a BBW Tumblr blog and forget the password
I may be speaking too soon but this is a disaster
Like old people in modern sneakers
I saw Book of Mormon with a congregation of true believers
— milo, “In Gaol”, a toothpaste suburb (2014)
As investors, it is very tempting to get so caught up in our own tribe of investing — our style, our philosophy — that we sit in a state of constant bemusement of other investors, sure that everyone is going to come around to our point of view on the value of something eventually. That congregation of true believers we can’t believe are watching a parody of their beliefs can stick around for a long, long time, folks. Over a sufficiently long period, being wrong about value but right about price can become indistinguishable from being right about value.
Empathy, evidently, existed only within the human community, whereas intelligence to some degree could be found throughout every phylum and order including the arachnida.
— Philip K. Dick, Do Androids Dream of Electric Sheep (1968)
I’ll admit it. At any given time around our Houston office, there are four TVs tuned to CNBC. Don’t ask me why. Or at least don’t expect a satisfactory answer.
If pressed, I would tell you that it’s important to know what a voice that speaks through thousands of televisions in similar offices around the world is saying, even if it’s a meal of empty calories. After all, Epsilon Theory is about stories. Stories, those who tell them, and those who, in listening, respond. Some of those stories are powerful myths, timeless and universal, others virtuously or nefariously cultivated for a singular place in space and time. And some of them — including most of what you hear on financial television — are vapid and worthless.
A story linking six months of a presidency to the returns of a stock market at the same time. A story linking August returns to calendar years that end with the number 7. A story that “stocks slipped on the news” of a development in investigations of Russian collusion with no evidence of relationship other than that the two things happened on the same day. Oh look, oil fell on “profit-taking.” Linking a down day in U.S. markets to one of a million macro factors that moved that day. We say the stock moved “on this news” or “on that news” when, if we’re really being honest with ourselves and each other, we know that all of these stories are stupid and wrong. Deep down we know that we have no earthly clue why our investments go up and down every day, much less moment to moment, and we’re just grasping for answers. Stories. And boy, are people ready to give us some.
It’s a problem. And it’s a problem we can’t ignore, because our investment decisions communicate views about our expectations even if we don’t intend it. We don’t get to say that “it’s OK” not to understand what moves markets, because every day we are all making bets that say we do. Sure, we have all sorts of explanations for why investments should rise in value. We should be paid for taking risk. We should own something valuable if it continues to grow its earnings. We should be able to trust the fact that risky investable assets have produced positive returns over almost any long-term horizon for the last several centuries.
But the distinction between understanding why we ought to be paid for owning something and understanding how that manifests itself in changes in securities prices is not just academic. It is fundamental, and it sits squarely in Epsilon Theory’s wheelhouse. In the same way that Ben bastardized Gresham’s Law, I’m going to steal from Friedman:
Investment returns are always and everywhere a behavioral phenomenon.
That’s why Investor Behavior is #3 on our list of Things that Matter.
Knowledge and Information
I know we all know this, but from time to time it bears repeating: until it defaults, matures or is called, the price of every security in the world is ultimately driven by two — and only two — things:
Who is willing to pay the most to buy the thing, and
Who is willing to accept the least to sell the thing.
That’s it. A lot of applied behavioral economics IS flawed and less rigorous than it ought to be, but at the risk of giving Taleb the vapors, any argument for how prices are determined and, thus, how returns are generated that ignores investor behavior isn’t just weak. It’s objectively wrong.
Now, while there really aren’t any strong-form efficient market guys out there with skin in the game (i.e., outside of academia) anymore, there are still a lot who think about markets as being generally efficient, by which they mean that the market generally does a good job of pricing available information. This is actually a pretty fair point of view. To believe otherwise is to take a dim view of the value of markets as a mechanism for expressing the aggregated will of individuals. That ain’t me. I was and will always be a Hayekian at heart. Since we’ve decided it’s now acceptable to terminate employees for expressing wrongthink, I’ve started firing anyone who doesn’t see my copy of The Road to Serfdom and slam it down on the conference room table, shouting, “THIS is what we believe!” à la Maggie Thatcher.
The problem with most interpretations of information, however, is that fundamental data alone isn’t information in any real sense that matters. Facts about a company only become information when they are passed through the perceptions and preferences of the people who are participating in determining the security’s price. There is no objectively ‘right price’ for a security based on the available information about its business, its assets, its prospects or its profitability, because there is no objective sense in which changes in any of those things ought to result in changes in prices. There is only a price which reflects how that information is viewed through the collective lens of individuals or groups of individuals who participate in that market.
Now while two people functionally determine the current price of any security, the movement of prices in that security from that level are also influenced by a much larger group who are willing to buy for a little bit less than the guy setting the bid price, and those who are willing to sell for a little bit more than the guy setting the ask price. Those who’ve made those views explicit are part of the so-called order book, an actual group of people willing to buy and sell at certain prices. Greater is the group of individuals who haven’t explicitly put a line in the sand at all, but who do have a view that they have an interest in expressing. They are paying attention to the stock. Far, far larger still is the universe of investors and assets who are paying no attention to the security at all and play little to no role in its pricing, even if they own the thing. You can imagine it looking something like the below — a little bit of money is willing to trade close to the current bid-ask spread, and increasing amounts if you’re willing to sacrifice.
Source: Salient 2017. For illustrative purposes only
Again, excluding terminal events for a security — like its default, retirement, maturity or being called away — there are only two ways for a security to change in price:
Someone who had an explicit or implicit view in the “order book” — a blue or red bar from the above chart — changes their mind about the price at which they would buy or sell.
Someone who didn’t have a view before decides to express a view.
Many of the things we do to trade, like a market order or most common trading algorithms, cross the spread in order to find a trading partner. In other words, as the day wears on, a lot of the people who thought they’d only sell for $75.10 — but need to sell — end up saying that they’d take less. Those folks are making the price move by changing their mind about the price at which they’d buy or sell. In other situations, maybe we get a call from a client who needs money for a down payment for house. It’s a big, liquid stock, so we put in a market order. We take $74.90 for our shares despite having not expressed a view on price before that, and everyone else in the market tries to figure out why.
So why do these people change their mind? Are they, in fact, responding to the stimuli that financial TV suggest? Did a barrel of oil really just trade up by 15 cents because investors changed what they were willing to pay as a result of North Korean sabre rattling? Other than major sources of observable volatility — earnings, corporate actions and the like, and often even then — if anyone tells you they know, they are probably lying to you. All we know, because it is a tautology, is that it is absolutely a reflection of human behavior (which includes, mind you, the behaviors incorporated on the front-end of a systematic trading strategy or implicit in a trade execution algorithm). That doesn’t mean that people can’t make money off price movements over this horizon — plenty of stat arb and high-frequency trading firms do exactly that, albeit in different ways. But over the very short run, the drivers of market movement are noisy and overdetermined, meaning that there are more factors driving that noise than there is noise. They are also nearly impossible to generalize, other than to say that they are reflections of the behaviors of the individuals who caused them.
The great investor Benjamin Graham famously characterized his views on the matter in this way. “In the short run,” Graham said, “the market is a voting machine, but in the long run, it is a weighing machine.” This is a popular view. But with respect due to Mr. Graham, it is also wrong. Since I’ve bastardized and restated the words of one financial genius already, let’s make it two:
In the very short run, the market is a voting machine.
In the short run, the market is a voting machine.
In the long run, the market is a voting machine.
The Long-Run Voting Machine
There’s a contingent of people reading this who are probably saying to themselves, “Wait a minute. What about a bond? Every time I receive my coupon I book some return. Every day I get closer to maturity, and I can predict pretty accurately how a bond trading at a premium or discount is going to converge to par.” The implication of that argument is that while fundamental characteristics of an investment may only technically manifest themselves in some terminal event, they are effectively still very predictive because we can have a high degree of confidence around them for some types of investments. In other words, maybe sentiment is a bigger predictor for risky securities than it is for securities where the return is coming from predictable cash flows.
This is true.
If you intend to hold something to maturity, or if you hold an investment that is reliably paying enough cash flow to repay you over a reasonable length of time, all else being equal, the variability in the price attached to your investment and its returns, and the behaviorally driven component of those returns, ought to be lower. This is one of the reasons why we tend to buy and hold bonds in our client accounts to maturity. Yet, even here, your compound returns are going to be influenced by investor behaviors outside of that bond — you have to reinvest those coupons at rates determined by individual actors influencing prevailing interest rates, after all.
The other, more common argument — this is the Graham argument — is that these behaviorally driven features of markets are, even for investments in riskier parts of the capital structure like credit or equity, temporary noise on the path toward convergence of the investment’s price with its value. Investors have historically found comfort in the idea that the voting machine will someday converge to the weighing machine — that one day, everyone else will come to the conclusion that I have about this company and value it like I do.
This forms part of the story for a vast range of investment styles. For the investor who speaks the language of growth, it is indispensable. He is saying, explicitly or implicitly, “I believe this company will grow faster than other investors expect. When I’m right, the price will converge to the value implied by the higher earnings.” For the intrinsic value or quality investor (I’m talking to you, too, Holt, EVA, CFROI wonks), it is an even stronger impulse. He believes that a company’s ability to deploy its current assets and reinvest at higher rates than the market expects (or for a longer time than the market expects) forms a value that is essentially the stock-in-itself. That’s kind of what intrinsic means, isn’t it? Frankly, it is the multiples-driven value investor who approaches the question with the keenest awareness of behavioral influences on prices. He’s comfortable implying that investors tend to do a bad job of knowing which companies ought to be worth a lower multiple of their earnings/assets/cash flow, and that enough time will cause the outperformance of the cheap company to be recognized and rerated. Or maybe just the increase in earnings will cause investors to apply the same multiple to create a higher value. There is, at least, the self-awareness of behavior’s fickle influence.
In each of these cases, the investors recognize that the market is a noisy, behaviorally complicated voting machine in the short run. This is why when you meet with a fund manager, they will always always always tell you that the rest of the market is looking at the next quarter’s earnings, while they stand alone at the top of the mountain, summoning the courage to weather short-term storms in favor of long-term outcomes. They’re very brave. Lots of people have been talking about it. But in each of these cases, the reality is that other than significant sources of real cash flow distributions (i.e., not stock buy-backs or debt pay-downs, for fans of the “Shareholder Yield” concept), the convergence of the voting machine to the weighing machine can take a very, very, very long time. And it may never happen, for the forces that will cause it to take place are themselves behavioral in nature! Somebody’s gotta say they’re willing to buy your stock at that price, and that somebody is either a person or a computer programmed by a person.
If the market wants to convince itself that Amazon can and will someday raise its prices to generate actual profits, and that they will then use those profits to bestow untold trillions of dollars (or maybe bitcoins, by the time this actually happens) in dividends on its loyal investor base, it can do it for a very, very, very long time. If you do not think Amazon can manage to preach this narrative to its investor base for another 10, 25 or even 50 years, you are dead wrong.
Do you think I’m arguing against value investing? Against fundamental research? Because I’m not. Not even a little bit. OK, maybe a little bit in the case of most fundamental research. What I am arguing is that when these approaches work, they still work because of the lens of preferences and experience that those who participate in the pricing of the investment bring to the table with them. ANY criticism of “behavioral” methods of investing must also be a criticism of fundamental ones, because they both include assumptions about how humans will respond to something.
This has a lot of implications:
For asset owners and allocators: How much time and effort do you spend thinking about who else owns the investment? Who else might want to own it if some bigger thing happens in the world? To that investor’s situation? To the investment or company itself? Compare that to the amount of time you spend sifting through macro data, research reports and constructing models. If you’re like most of us, you’re spending <5% of your time and resources on the former and 95% on the latter. That’s a mistake.
For fund selectors: Spend more time developing theses about managers who — through intuitive or quantitative techniques — seek to understand what drives the behaviors of other investors (or non-investor influencers of securities prices), rather than simple security-based or macroeconomic analysis.
For all investors: Always keep in mind how prices are determined when you think about how certain trends and events may impact markets and your portfolio. Think about how regulation-driven moves toward passive instruments may change price-to-value convergence. Think about how an increase in private equity dollars may influence or change price-to-value convergence in public markets. Think about what behaviors a low global growth environment could induce on the part of financial advisors, institutions and individuals as they participate in the price-setting process.
OK, so how do we do all this? If the Market In-Itself is a myth, how do we adjust our thinking?
There is no mathematical proof that solves this conundrum for us, because we can’t know people’s full motivations, preferences and exogenous influences. We do not know what investors or traders are paying attention to, except by observing the results after-the-fact and coming up with stories to attach to those analyses. Even if we could, many of these behaviors are emergent properties of the market in the aggregate, meaning that the way people behave isn’t nearly as independent of the path or state of the overall market as we’d like it to be. The market is a complex system.
What we can do is recognize what we recognize about every other aspect of society: that these motivations, preferences and exogenous influences on our behavior are reflected in the tribes we select and the language we speak. We may not be able to observe specific behaviors in action, but we can understand a lot about investors by observing, for example, the sell side. Not because they have anything useful to say (sorry), and not even because we think that they somehow reflect the consensus about a fundamental fact about a company. Because the sell side is telling us who their customers are. The feedback mechanisms of industry conventions, of style boxes, of terminology and language that our fellow investors adopt — these, too, all tell us a great deal about investor behaviors. They can also give us insight — incomplete insight, but insight nonetheless — into things like sustained low volatility, limited liquidity, the rationale for the existence of behavioral premia like momentum, value and low volatility, and how they go through sustained periods of weak or strong performance.
And that’s exactly where we’re going in Part II: the languages and tribes of investing and how they can help us understand the behavioral drivers of the Long-Run Voting Machine.
Drummers are really nothing more than time-keepers. They’re the time of the band. I don’t consider I should have as much recognition as say a brilliant guitar player. I think the best thing a drummer can have is restraint when he’s playing — and so few have today. They think playing loud is playing best. Of course, I don’t think I’ve reached my best yet. The day I don’t move on I stop playing. I don’t practice ever. I can only play with other people, I need to feel them around me.
— Ginger Baker (founder of Cream), from a 1970 interview with Disc Magazine
La cuisine, c’est quand les choses ont le goût de ce qu’elles sont. (Good cooking is when things taste of what they are.)
— Maurice Edmond Sailland (Curnonsky) — 1872-1956
There are those who think that life Has nothing left to chance A host of holy horrors To direct our aimless dance
A planet of playthings We dance on the strings Of powers we cannot perceive The stars aren’t aligned Or the gods are malign Blame is better to give than receive
You can choose a ready guide In some celestial voice If you choose not to decide You still have made a choice
— Rush, “Freewill”, Permanent Waves (1980)
For the kingdom of heaven is like a man traveling to a far country, who called his own servants and delivered his goods to them. And to one he gave five talents, to another two, and to another one, to each according to his own ability; and immediately he went on a journey. Then he who had received the five talents went and traded with them, and made another five talents. And likewise, he who had received two gained two more also. But he who had received one went and dug in the ground, and hid his lord’s money. After a long time the lord of those servants came and settled accounts with them.
So he who had received five talents came and brought five other talents, saying, ‘Lord, you delivered to me five talents; look, I have gained five more talents besides them.’ His lord said to him, ‘Well done, good and faithful servant; you were faithful over a few things, I will make you ruler over many things. Enter into the joy of your lord.’ He also who had received two talents came and said, ‘Lord, you delivered to me two talents; look, I have gained two more talents besides them.’ His lord said to him, ‘Well done, good and faithful servant; you have been faithful over a few things, I will make you ruler over many things. Enter into the joy of your lord.’
Then he who had received the one talent came and said, ‘Lord, I knew you to be a hard man, reaping where you have not sown, and gathering where you have not scattered seed. And I was afraid, and went and hid your talent in the ground. Look, there you have what is yours.’
But his lord answered and said to him, ‘You wicked and lazy servant, you knew that I reap where I have not sown, and gather where I have not scattered seed. So you ought to have deposited my money with the bankers, and at my coming I would have received back my own with interest. Therefore, take the talent from him, and give it to him who has ten talents.
For to everyone who has, more will be given, and he will have abundance; but from him who does not have, even what he has will be taken away. And cast the unprofitable servant into the outer darkness. There will be weeping and gnashing of teeth.
— The Bible, The Gospel of Matthew 25:14-30
This note was featured in Meb Faber’s book The Best Investment Writing – Volume 2, alongside another Epsilon Theory note from Ben Hunt. Click here to get a copy.
I will never understand why more people don’t revere Rush.
With the possible exception of Led Zeppelin, I’m not sure there has been another band with such extraordinary instrumentalists across the board, such synergy between those members and their musical style and such a consistent approach to both lyrical and melodic construction. And yet they were only inducted into the Rock & Roll Hall of Fame in 2013. A short list of bands and singers the selection committee thought were more deserving: ABBA, Madonna, Jackson Browne, the Moonglows, Run DMC. At least they got in when Randy Newman did. I remember the first time I heard YYZ, the Rush tune named after the IATA airport code for Toronto’s Pearson International Airport, pronounced “Why Why Zed” in the charming manner of the Commonwealth. It was then that I decided I would be a drummer. I did play for a while, and reached what I would describe as just above a baseline threshold of competence.
That’s not a throwaway line.
There’s a clear, explicit line that every drummer (hopefully) crosses at one point. A step-change in his understanding of the role of the instrument. The true novice drummer always picks up the sticks and plays the same thing. Common time. Somewhere between 90-100 beats per minute. Eighth note closed hi-hat throughout. Bass drum on the down and upbeat of the first beat. Snare on second down beat. And then it’s all jazzy up-beat doodling on the snare for the rest of that bar until the down beat of four. Same thing for three measures, and on the fourth measure it’s time for that awesome fill he’s been practicing. I don’t know how many subscribers are drummers, but I assure you, literally couples of you are nodding your heads.
The fills and off-beat snare hits are all superfluous and not necessary to the principal role of a drummer in rock and roll: to keep the damned beat. But there are a number of reasons why every neophyte does these same things. Mimicry of more advanced players who can do the creative and interesting things without losing the beat, for one. We see Tony Williams, John Bonham, or Bill Bruford and do what it is we think they are doing to make the music sound good. The amateur often also thinks that these are the necessary things to be perceived as a more advanced player, for another. He doesn’t just imagine that his mimicry will make him sound more like the excellent players, but imagines himself looking like them to others. More than anything, the amateur does these things because he hasn’t quite figured out that keeping a good beat is so much more important than anything else he will do that he’s willing to sacrifice it for what he thinks is impressive.
This thought process dominates so many other fields as well. Consider the number of amateur cooks who hit every sauce or piece of meat with a handful of garlic powder, onion powder, oregano, salt, pepper and cayenne, when the simplicity of salt as seasoning dominates most of the world’s great cuisine. There is an instinct to think that complexity and depth must come from a huge range of ingredients or from complexity in preparation, but most extraordinary cooking begins from an understanding of a small number of methods for heating, seasoning and establishing bases for sauces. Inventiveness, creativity and passion can take cuisine in millions of directions from there, but many home cooks see the celebrity chef’s flamboyant recipe and internalize that the creative flourishes are what matters to the dish, and not the fact that he cooked a high-quality piece of meat at the right heat for the right amount of time.
If you’re not much of a cook, consider instead the 30-handicap golfer who wouldn’t be caught dead without a full complement of four lob wedges in his bag. You know, so that he can address every possible situation on the course. The trilling singer of the national anthem who can’t hold a pitch but sees every word of the song as an opportunity to sing an entire scale’s worth of notes. The karate novice who addresses his opponent with a convoluted stance. The writer who doesn’t know when to stop giving examples to an audience who understood what he was getting at half-way through the one about cooking.
I’m guessing at least one of these things pisses you off, or at the very least makes you do an internal eye roll. And yet, as investors we are guilty of doing this kind of thing all the time, any time the topic of diversification comes up.
It comes from a good place. We know from what we’ve been taught (and from watching the experts) that we should diversify, but we don’t have a particularly good way of knowing what that means. And so we fill our portfolios with multiple flavors of funds, accounts and individual securities. Three international equity funds with different strategies. Multiple different styles in emerging markets. Some value. Some growth. Some minimum volatility. Some call writing strategies. Some sector funds. Maybe some long/short hedge funds. Some passively managed index funds, some actively managed funds. Definitely some sexy stock picks. And in the end, the portfolio that we end up with looks very much like the global equity market, maybe with a tilt here or there to express uniqueness — that flashy extra little hit on the snare drum to look impressive.
This piece isn’t about the time we waste on these things. I already wrote a piece about that a few weeks ago. This is about the harm we do to our portfolios when we play at diversifying instead of actually doing it.
The Parable of the Two FA’s
So what does actually diversifying look like?
There are lot of not-very-useful definitions out there. The eggs-in-one-basket definition we’re all familiar with benefits from simplicity, which is not nothing. In addition, it does work if people have a good concept of what the basket is in the analogy. Most people don’t. Say you have $100, and you decide that a basket is an advisor or a fund. So you split the money between the two, and they invest in the same thing. You have not diversified. The other definitions for diversification tend to be more complicated, more quantitative in nature. That doesn’t make them bad, and we’ll be leaning on some of them. But we need a rule of thumb, some heuristic for describing what diversification ought to look like so that we know it when we see it. For the overwhelming majority of investors, that rule of thumb should go something like this:
Diversification is reducing how much you expect to lose when risky assets do poorly or very poorly without necessarily reducing how much total return you expect to generate.
Now, this is not exactly true, and it’s very obviously not the whole definition. But by and large it is the part of the definition that matters most. The more nuanced way to think about diversification, of course, is to describe it as all the benefits you get from the fact that things in your portfolio don’t always move together, even if they’re both generally going up in value. But most investors are so concentrated in general exposure to risky assets — securities whose value rises and falls with the fortunes and profitability of companies, and how other investors perceive those fortunes — that this distinction is mostly an academic one. Investors live and die by home country equity risk. Period. Most investors understand this to one degree or another, but the way they respond in their portfolios doesn’t reflect it.
I want to describe this to you in a parable.
There was once a rich lord who held $10 million in a S&P 500 ETF. He knew that he would be occupied with his growing business over the next year. Before he left, he met with his two financial advisors and gave them $1 million of his wealth and told them to “diversify his holdings.”
He returned after a year and came before the first financial advisor. “My lord, I put the $1 million you gave me in a Russell 1000 Value ETF. Here is your $1.1 million.” The rich man replied, “Dude, that’s almost exactly what my other ETF did over the same period. What if the market had crashed? I wasn’t diversified at all!” And the financial advisor was ashamed.
Furious and frustrated, the rich man then summoned his second financial advisor. “Sir, I put your $1 million in a Short-Duration Fixed Income mutual fund of impeccable reputation. Here’s your $1 million back.”
“Oh my God,” the lord replied, “Are you being serious right now? If I wanted to reduce my risk by stuffing my money in a mattress I could have done that without paying you a 65bp wrap fee. How do you sleep at night? I’m going to open a robo-advisor account.”
Most of us know we shouldn’t just hold a local equity index. We usually buy something else to diversify, because that’s what you do. But what we usually do falls short either because (1) the thing we buy to diversify isn’t actually all that different from what we already owned, or (2) the thing we buy to diversify reduces our risk and our return, which defeats the purpose. There’s nothing novel in what I’m saying here. Modern portfolio theory’s fundamental formula helps us to isolate how much of the variation in our portfolio’s returns comes from the riskiness of the stuff we invested in vs. the fact that this stuff doesn’t always move together.
Source: Salient 2017 For illustrative purposes only.
The Free Lunch Effect
So assuming we didn’t have any special knowledge about what assets would generate the highest risk-adjusted returns over the year our rich client was away on business, what answer would have made us the good guy in the parable? Maximizing how much benefit we get from that second expression above — the fact that this stuff doesn’t always move together.
Before we jump into the math on this, it’s important to reinforce the caveat above: we’re assuming we don’t have any knowledge about risk-adjusted returns, which isn’t always true. Stay with me, because we will get back to that. For the time being, however, let’s take as a given that we don’t know what the future holds. Let’s also assume that, like the Parable of the Two FA’s, our client holds $10 million in S&P 500 ETFs. Also like the parable, we have been asked to reallocate $1 million of those assets to what will be most diversifying. In other words, it’s a marginal analysis.
The measure we’re looking to maximize is the Free Lunch Effect, which we define as the difference between the portfolio’s volatility after our change at the margin and the raw weighted average volatility of the underlying components. If the two assets both had volatility of 10%, for example, and the resulting portfolio volatility was 9%, the Free Lunch Effect would be 1%.
If maximizing the Free Lunch Effect is the goal, here’s the relative attractiveness of various things the two FA’s could have allocated to (based on characteristics of these markets between January 2000 and July 2017).
Volatility Reduction from Diversification — Adding 10% to a Portfolio of S&P 500
Source: Salient 2017. For illustrative purposes only. Past performance is not indicative of how the index will perform in the future. The index reflects the reinvestment of dividends and income and does not reflect deductions for fees, expenses or taxes. The index is unmanaged and is not available for direct investment.
The two FA’s failed for two different reasons. The first failed because he selected an asset which was too similar. The second failed because he selected an asset which was not risky enough for its differentness to matter. The first concept is intuitive to most of us, but the second is a bit more esoteric. I think it’s best thought of by considering how much the risk of a portfolio is reduced by adding an asset with varying levels of correlation and volatility. To stop playing at diversification, this is where you start.
Volatility Reduction by Correlation and Volatility of Diversifying Asset
Source: Salient 2017. For illustrative purposes only. Past performance is not indicative of how the index will perform in the future. The index reflects the reinvestment of dividends and income and does not reflect deductions for fees, expenses or taxes. The index is unmanaged and is not available for direct investment.
If You Choose not to Decide
If there are some complaints that can be leveled against this approach, two of them, I think, are valid and worthy of exploration.
The first is that diversification cannot be fully captured in measures of correlation. If you read Whom Fortune Favors, you’ll know that our code recognizes that we live in a behaviorally-influenced, non-ergodic world. While I think we’d all recognize that U.S. value stocks are almost always going to be a poor diversifier against global equities (and vice versa), clearly there are events outside of the historical record or what we know today that could completely change that. And so the proper reading of this should always be in context of an adaptive portfolio management process.
The second complaint, as I alluded to earlier, is the fact that we are not always indifferent in our risk-adjusted return expectations for different assets. I’m sure many of you looked at the above chart and said to yourself, “Yeah, I’m not piling into commodities.” I don’t blame you (I’m still not satisfied with explanations for why I ought to be paid for being long contracts on many commodities), but that is the point. Not owning commodities or MLPs because you don’t get them isn’t the same as not expressing an opinion. If you choose not to decide, you still have made a choice.
When investors choose to forgo diversification, on any basis, they are implicitly betting that decisions that they make will outperform what diversification would have yielded them. It may not be optimal to own the most diversified portfolio you can possibly own, because anti-diversifying decisions might, in fact, be worth it. But it is exactly that thought process that must become part of our code as investors. It’s OK to turn down a free lunch, but you’d damn well better know that what you’re going to spend your money on is better.
So how do you quantify that implicit bet? Again, the Free Lunch Effect gives us our easiest answer. Consider the following case: let’s assume we had two investment options, both with similar risk of around 15%. For simplicity’s sake we’ll start from our naïve assumption that our assets produce, say, 0.5 units of return for every unit of risk we take. If the two assets are perfectly uncorrelated, how much more return would we need to demand from Asset 1 vs. Asset 2 to own more of it than the other? To own 100% Asset 1?
Well, the chart below shows it. In the case above, if you invest 100% of your portfolio in Asset 1, an investor who thinks about his portfolio in risk-adjusted terms is implicitly betting that Asset 1 will generate more than 3% more return per year, or an incremental 0.21 in return/risk units. If the assets are less similar, this implicit view grows exponentially.
Implied Incremental Return Expectation from Overweighted Asset
Source: Salient 2017. For illustrative purposes only. Past performance is not indicative of how the index will perform in the future. The index reflects the reinvestment of dividends and income and does not reflect deductions for fees, expenses or taxes. The index is unmanaged and is not available for direct investment.
A Chain of Linked Engagements
If we do not learn to regard a war, and the separate campaigns of which it is composed, as a chain of linked engagements each leading to the next, but instead succumb to the idea that the capture of certain geographical points or the seizure of undefended provinces are of value in themselves, we are liable to regard them as windfall profits.
— On War, Carl von Clausewitz
The point of this note isn’t to try to convince you to focus your portfolio construction efforts on higher volatility diversifiers like those highlighted earlier (although many of you should). It’s also not to argue that maximizing diversification should be your first objective (although most of us are so far from the optimum that moving in this direction wouldn’t hurt). It is to emphasize that portfolio construction and the decisions we make are a chain of linked engagements. It is to give you pause when you or your client asks for a ‘best new investment idea’. If your experiences are like mine, the question is nearly always expressed in isolation — recommend me a stock, a mutual fund, a hedge fund. These questions can never be answered in isolation. If you really must tinker with your allocation, sure, I can give you my view, but only if I know what else you own, and only if I know what you intend to sell in order to buy the thing.
Anyone who will make a recommendation to you without knowing those things is an idiot, a charlatan, or both.
Most of us, whether we are entrenched in financial markets or not, think about our decisions not in a vacuum but in terms of opportunity cost. If we buy A, we’re giving up B. If we invest in A, we’re giving up on B. If we do A, we won’t have time for B. Opportunity cost is fundamental to thinking about nearly every aspect of human endeavor but for some reason is completely absent from the way many investors typically think about building portfolios.
Look, if you didn’t completely follow where I was going with Whom Fortune Favors, I get it. Telling you to think about risk and diversification separately is more than a little bit arcane. But here’s where it comes together: an investor can only make wise decisions about asset allocation, about selecting fund managers, about tactical bets and about individual investments when he has an objective opportunity cost to assess those decisions against that allows him to make his portfolio decisions intentionally, not implicitly. That opportunity cost is the free lunch provided by diversification.
If we take this way of thinking to its natural extreme, we must recognize that we can, at any point, identify the portfolio that would have provided the maximum diversification, at least using the tools we’ve outlined here. For most periods, if you run through that analysis, you are very likely to find that a portfolio of those assets in which every investment contributes a comparable amount of risk to the whole — a risk parity portfolio, in other words — typically provides something near to that maximum level of diversification. I am not suggesting that your portfolio be the maximum diversification portfolio or risk parity. But I am suggesting that a risk parity portfolio of your investable universe is an excellent place to use as an anchor for this necessary analysis.
If you don’t favor it for various reasons (e.g. using volatility as a proxy for risk is the devil, it’s just levered bonds, etc.), then find your home portfolio that accomplishes similar goals in a way that is rules-based and sensible. Maybe it’s the true market portfolio we highlight in I am Spartacus. If you’re conservative, maybe it’s the tangency portfolio from the efficient frontier. And if you’re more aggressive, maybe it is something closer to the Kelly Optimal portfolio we discussed in Whom Fortune Favors. From there, your portfolio construction exercise becomes relatively simple: does the benefit I expect from this action exceed its diversification opportunity cost?
How do you measure it? If you have capital markets assumptions or projections, feel free to use them. Perhaps simpler, assume a particular Sharpe Ratio, say 0.25 or 0.30, and multiply it times the drop in diversification impact from the action you’re taking. Are you confident that the change you’re making to the portfolio is going to have more of an impact than that? That’s…really it. Now the shrewd among you might be saying, “Rusty, isn’t that kind of like what a mean-variance optimization model would do?” It isn’t kind of like that, it’s literally that. And so what? We’re not reinventing portfolio science here, we’re trying to unpack it so that we can use it more effectively as investors.
Recognize that this isn’t just a relevant approach to scenarios where you’re changing things around because you think it will improve returns dramatically. This is also a useful construct for understanding whether all the shenanigans in search of diversification, all that Chili P you’re adding, are really worth the headache. Is that fifth emerging markets manager really adding something? Is sub-dividing your regions to add country managers really worth the time?
In the end, it’s all about being intentional. With as many decisions as we have to manage, the worst thing we can do is let our portfolios make our decisions for us. Given the benefits of diversification, investors ought to put the burden of proof on anything that makes a portfolio less diversified. In doing so, they will recognize why this code recognizes the intentional pursuit of real diversification as the #2 Thing that Matters.
 I don’t want to hear it from the “but they stole people’s music and weren’t super nice about it” crowd. Zep played better rock and roll music than anyone before or after, and it’s not even close.
 And it can. Pueblan and Oaxacan cuisine feature moles with extraordinary complexity that does come from the melding of a range of seasonings and ingredients. Traditional American chilis, South Asian curries and soups from around the world often do as well. Dishes en croute (e.g. pate en croute, coulibiac, etc.) are notoriously tricky, too.
 Cue the fund-of-funds due diligence analyst pointing out that we would have, in fact, diversified our fraud risk. Die on that hill if you want to, friend.
Deep Thought: Yes. Though I don’t think you’re going to like it.
Fook: Doesn’t matter! We must know it!
Deep Thought: You’re really not going to like it!
Fook: Tell us!
Deep Thought: Alright. The answer to the ultimate question…of Life, the Universe, and Everything…is… “42”. I checked it thoroughly. It would have been simpler, of course, to have known what the actual question was.
— Douglas Adams, Hitchhiker’s Guide to the Galaxy
As investors, our process is usually to start from the answer and work our way back to the question. Unfortunately, the answers we are provided are usually pre-baked products, vehicle types or persistent industry conventions, which means that the answers we get when we actually focus on the questions that matter may be counterintuitive and jarring. The entire point of developing a personal code for investing is knowing which questions matter and ought to be asked first, before a single product, vehicle or style box gets thrown into the mix.
The purpose you undertake is dangerous.’ Why, that’s certain. ‘Tis dangerous to take a cold, to sleep, to drink; but I tell you, my lord fool, out of this nettle, danger, we pluck this flower, safety.
― William Shakespeare, Henry IV, Part 1, Act 2, Scene 3, Hotspur
Thomasina: When you stir your rice pudding, Septimus, the spoonful of jam spreads itself round making red trails like the picture of a meteor in my astronomical atlas. But if you stir backwards, the jam will not come together again. Indeed, the pudding does not notice and continues to turn pink just as before. Do you think this is odd?
Thomasina: Well, I do. You cannot stir things apart.
Septimus: No more you can, time must needs run backward, and since it will not, we must stir our way onward mixing as we go, disorder out of disorder into disorder until pink is complete, unchanging and unchangeable, and we are done with it forever. This is known as free will or self-determination.
Thomasina: Septimus, do you think God is a Newtonian?
Septimus: An Etonian? Almost certainly, I’m afraid. We must ask your brother to make it his first enquiry.
Thomasina: No, Septimus, a Newtonian. Septimus! Am I the first person to have thought of this?
Thomasina: I have not said yet.
Septimus: “If everything from the furthest planet to the smallest atom of our brain acts according to Newton’s law of motion, what becomes of free will?”
Septimus: God’s will.
Thomasina (derisively): No!
Septimus: Very well.
Thomasina: If you could stop every atom in its position and direction, and if your mind could comprehend all the actions thus suspended, then if you were really, really good at algebra you could write the formula for all the future; and although nobody can be so clever as to do it, the formula must exist just as if one could.
Septimus (after a pause): Yes. Yes, as far as I know, you are the first person to have thought of this.
— Tom Stoppard, Arcadia, (1993)
On this most important question of risk, we and our advisors often default to approaches which rely on the expectation that the past and present give us profound and utterly reliable insights into what we ought to expect going forward. As a result, we end up with portfolios and, more importantly, portfolio construction frameworks which don’t respect the way in which capital actually grows over time and can’t adapt to changing environments. That’s not good enough.
Most of these notes tend to stand on their own, but this one (being a Part 2) borrows a lot from the thinking in Part 1. If you’re going to get the most out of this note, I recommend you start there. But if you’re pressed for time or just lazy, I wanted you to take away two basic ideas:
That the risk decision dominates all other decisions you make.
That the risk decision is not exactly the same as the asset class decision.
Children of a Lazier God
Before I dive into the weeds on those ideas, however, I want to tell you about a dream I have. It’s a recurring dream. In this dream, I have discovered the secret to making the most possible money with the least possible effort.
Hey, I never said it was a unique dream.
It is, however, a unique investing case. Imagine for a moment that we had perfect omniscience into returns, but also that we were profoundly lazy – a sort of Jeffersonian version of God. We live in a world of stocks, bonds and commodities, and we want to set a fixed proportion of our wealth to invest in each of those assets. We want to hold that portfolio for 50+ years, sit on a beach watching dolphins or whatever it is people do on beach vacations, and maximize our returns. What do we hold? The portfolio only needs to satisfy one explicit and one implicit objective. The explicit objective is to maximize how much money we have at the end of the period. The implicit objective is the small matter of not going bankrupt in the process.
This rather curious portfolio is noteworthy for another reason, too: it is a static and rather cheeky case of an optimal portfolio under the Kelly Criterion. Named after John Kelly, Jr., a Bell Labs researcher in the 1950s, the eponymous criterion was formally proposed in 1956 before being expanded and given its name by Edward O. Thorp in the 1960s. As applied by Thorp and many others, the Kelly Criterion is a mechanism for translating assessments about risk and edge into both trading and betting decisions.
Thorp himself has written several must-reads for any investor. Beat the Dealer, Beat the Market and A Man for All Markets are all on my team’s mandatory reading list. His story and that of the Kelly Criterion were updated and expanded in William Poundstone’s similarly excellent 2005 book, Fortune’s Formula: The Untold Story of the Scientific Betting System that Beat the Casinos and Wall Street. The criterion itself has long been part of the parlance of the professional and would-be professional gambler, and has also been the subject of various finance papers for the better part of 60 years. For the less prone to the twin vices of gambling and authoring finance papers, Kelly translates those assessments about risk and edge into position sizes. In other words, it’s a guide to sizing bets. The objective is to maximize the geometric growth rate of your bankroll — or the expected value of your final bankroll — but with zero probability of going broke along the way. It is popular because it is simple and because, when applied to games with known payoffs, it works.
When we moonlight as non-deities and seek to determine how much we ought to bet/invest, Kelly requires knowing only three facts: the size of your bankroll, your odds of winning and the payout of a winning and losing bet. For the simplest kind of friendly bet, where a wager of $1 wins $1, the calculation is simple: Kelly says that you should bet the difference between your odds of winning and your odds of losing. If you have a 55-to-45 edge against your friend, you should bet 10% of your bankroll. Your expected compounded return of doing so is provably optimal once you have bet against him enough to prove out the stated edge — although should you manage to reach this point, you are a provably suboptimal friend.
Most of the finance papers that apply this thinking to markets have focused on individual trades that look more or less like bets we’d make at a casino. These are usually things with at least a kinda-sorta knowable payoff and a discrete event where that payoff is determined: a single hand of blackjack, an exercise of an option, or a predicted corporate action taking place (or not taking place). It’s a lot harder to get your head around what “bet” we’re making and what “edge” we have when we, say, buy an S&P 500 ETF instead of holding cash. Unless you really are omniscient or carry around a copy of Grays Sports Almanac, you’re going to find estimating the range of potential outcomes for an investment or portfolio of investments pretty tricky. Not that it stops anyone from trying.
Since I don’t want to assume that any of us is quite so good at algebra as to write the formula for all the future, at a minimum what I’m trying to do is get us to think about risk unanchored to the arbitrarily determined characteristics and traits of asset classes. In other words, I want to establish an outside bound on the amount of risk a person could theoretically take in a portfolio if his only goal was maximizing return. Doing that requires us to think in geometric space, which is just a fancy way of saying that we want to know how the realization of returns over time ends up differing from a more abstract return assumption. It’s easy enough to get a feel for this yourself by opening Excel and calculating what the return would be if your portfolio went up 5% in one year and down 5% in the next (works for any such pair of numbers). Your simple average will always be zero, but your geometric mean will always be less than zero, by an increasing amount as the volatility increases.
So, if we knew exactly what stocks, bond and commodities would do between 1961 and 2016, what portfolio would we have bought? The blend of assets if we went Full Kelly would have looked like this:
Source: Salient 2017. For illustrative purposes only.
Only there’s a catch. Yes, we would have bought this portfolio, but we would have bought it more than six times. With perfect information about odds and payoffs, the optimal bet would have been to buy a portfolio with 634% (!) exposure, consisting of $2.00 in stocks, $3.21 in bonds and $1.13 in commodities for every dollar in capital we had. After all was said and done, if we looked back on the annualized volatility of this portfolio over those 50 years, what would we have found? What was the answer to life, the universe and everything?
44. Sorry, Deep Thought, you were off by two.
Perhaps the only characteristic of this portfolio more prominent than its rather remarkable level of exposure and leverage, is its hale and hearty annualized volatility of 44.1%. This result means if all you cared about was having the most money over a 50+ year period that ended last year, you would have bought a portfolio of stocks, bonds and commodities that had annualized volatility of 44.1%, roughly three times the long-term average for most equity markets, and probably five times that of the typical HNW investor’s portfolio.
And before you go running off to tell my lovely, charming, well-dressed and distressingly unsusceptible-to-flattery compliance officer that I told you to buy a 44% volatility super-portfolio, allow me to acknowledge that this requires some… uh… qualification. Most of these qualifications are pretty self-explanatory, since the whole exercise isn’t intended to tell you what you should buy going forward, or even the right amount of risk for you. This portfolio, this leverage and that level of risk worked over the last 50 years. Would they be optimal over the next 50?
Of course not. In real life, we’re not omniscient. Whereas a skilled card counter can estimate his mathematical edge fairly readily, it’s a lot harder for those of us in markets who are deciding what our asset allocation ought to look like. Largely for this reason, even Thorp himself advised betting “half-Kelly” or less, whether at the blackjack table or in the market. When asked why, Thorp told Jack Schwager in Hedge Fund Market Wizards, “We are not able to calculate exact probabilities… there are things that are going on that are not part of one’s knowledge at the time that affect the probabilities. So you need to scale back to a certain extent.”
Said another way, going Full Kelly on a presumption of precise certainty about outcomes in markets is a surefire way to over-bet, potentially leading to a complete loss of capital. Now, scaling back is easy if we are starting from an explicit calculation of our edge as in a game of blackjack. It’s not as easy to think about scaling down to, say, a Half Kelly portfolio. There is, however, another fascinating (but intuitive) feature of the Kelly Optimal Portfolio that allows us to scale back this portfolio in a way that may be more familiar: the Kelly Optimal Portfolio can be generalized as the highest return case of a set of portfolios generating geometric returns that are most efficient relative to the risk they take.
This may sound familiar. In a way, it’s very much like a presentation of Markowitz’s efficient frontier. Markowitz plots the portfolios that generate the most return for a given unit of risk, but his is a single-period calculation. It isn’t a geometric approach like Kelly, but rather reflects a return expectation that doesn’t incorporate how volatility and non-linearities impact the path and the resulting compound return. There have been a variety of academic pieces over the years covering the application of geometric returns to this framework, but most have focused on either identifying a single optimal geometric portfolio or on utility. Bernstein and Wilkinson went a bit further, developing a geometric efficient frontier.
All of these analyses are instructive and useful to the investor who wants to take path into account, but because the efficient frontier is heavily constrained by the assumed constraint on leverage, it’s not as useful for us. What we want is to take the most efficient portfolio in geometric terms, and take up or down the risk of that portfolio to reflect our tolerance for capital loss. In other words, we want a geometric capital market line. The intuitive outcome of doing this is that we can plot the highest point on this line as the Full Kelly portfolio. The second, and perhaps more satisfying outcome, is that we can retrospectively identify that scaling back from Full Kelly just looks like delevering on this geometric capital market line.
The below figure plots each of these items, including a Half Kelly portfolio that defines ruin as any scenario in the path in which losses exceed 50%, rather than full bankruptcy. The Half Kelly portfolio delivers the highest total return over this period without ever experiencing a drawdown of 50%.
Source: Salient, as of December 31, 2016. For illustrative purposes only.
When we de-lever from the Full Kelly to Half Kelly portfolio, we drop from a terrifying 44% annualized volatility number (which experiences an 80% drawdown at one point) to 18.5%, closer to but still materially higher in risk than most aggressive portfolios available from financial advisors or institutional investors.
This can be thought of in drawdown space as well for investors or advisors who have difficulty thinking in more arcane volatility terms. The below exhibit maps annualized volatility to maximum loss of capital over the analysis period. As mentioned, the 50% maximum drawdown portfolio historically looks like about 18.5% in volatility units.
Source: Salient, as of December 31, 2016. For illustrative purposes only.
For many investors, their true risk tolerance and investment horizon makes this whole discussion irrelevant. Traditional methods of thinking about risk and return are probably serving more conservative investors quite well. And there are some realities that anyone thinking about taking more risk needs to come to terms with, a lot of which I’m going to talk about in a moment — there’s a reason we wanted to talk about this in geometric terms, and it’s all about risk. But for those with a 30, 40 or 50-year horizon, for the permanent institutions with limited cash flow needs, it’s reasonable to ask the question: is the amount of risk in the S&P 500 Index or in a blend of that with the Bloomberg Barclays Aggregate Bond Index the right amount of risk to take? Or can we be taking more? Should we be taking more?
Did you think that was rhetorical? Nope.
Many investors can – and if they are acting as fiduciaries probably ought to — take more risk.
If every hedge fund manager jumped off a bridge…
This may not be a message you hear every day, but I’m not telling you anything novel. Don’t just listen to what your advisors, fund managers and institutional peers are telling you. They’re as motivated and influenced by career risk concerns as the rest of us. Instead, look at what they’re doing.
The next time you have a conversation with a sophisticated money manager you work with, ask them where they typically put their money. Yes, many of them will invest alongside you because that is right and appropriate (and also expected of them). But many more, when they are being honest, will tell you that they have a personal account or an internal-only strategy operated for staff, that operates at a significantly higher level of risk than almost anything they offer to clients. Vehicles with 20%, 25% or even 30% volatility are not uncommon. Yes, some of this is hubris, but some of it is also the realization on the part of professional investors that maximizing portfolio returns — if that is indeed your objective — can only be done if we strip back the conventions that tell us that the natural amount of risk in an unlevered investment in broad asset classes is always the right amount of risk.
Same thing with the widely admired investors, entrepreneurs and business operators. The individual stocks that represent their wealth are risky in a way that dwarfs most of what we would be willing to tolerate in individual portfolios. We explain it away with the notion that they are very skilled, or that they have control over the outcomes of the company — which may be true in doses — but in reality, they are typically equally subject to many of the uncontrollable whims that drive broader macroeconomic and financial market outcomes.
Then observe your institutional peers who are increasing their allocations to private equity and private real estate. They’re not just increasing because hedge funds have had lower absolute returns in a strong equity environment, although that is one very stupid reason why this is happening. It’s also happening because institutions are increasingly aware that they have limited alternatives to meet their target returns. While few will admit it explicitly, they use private equity because it’s the easiest way to lever their portfolios in a way that won’t look like leverage. In a true sense of uncertainty or portfolio level risk, when the risk of private portfolios is appropriately accounted for, I believe many pools of institutional capital are taking risk well beyond that of traditional equity benchmarks.
Many of the investors we all respect the most are already taking more risk than they let on, but explain it away because it’s not considered “right thinking.”
To Whom Much is Given
When we make the decision to take more risk, however, our tools and frameworks for managing uncertainty must occupy more of the stage. This isn’t only about our inability to build accurate forecasts, or even our inability to build mostly accurate stochastic frameworks based on return and volatility, like the Monte Carlo simulations many of us build for clients to simulate their growth in wealth over time. It’s also because the kinds of portfolios that a Full Kelly framework will lead you to are usually pretty risky. Their risk constraint is avoiding complete bankruptcy, and that’s not a very high bar. The things we have to do to capture such a high level of risk and return also usually disproportionately increase our exposure to big, unpredictable events. If you increase the risk of a portfolio by 20%, most of the ways you would do so will increase the exposure to these kinds of events by a lot morethan 20%.
Taken together, all these things create that famous gap between our realized experience and what we expected going in. This is a because most financial and economic models assume that the world is ergodic. And it ain’t. I know that’s a ten-dollar word, but it’s important. My favorite explanation of ergodicity comes from Nassim Nicholas Taleb, who claims to have stolen it from mathematician Yakov Sinai, who in turns claims to have stolen it from Israel Gelfand:
Suppose you want to buy a pair of shoes and you live in a house that has a shoe store. There are two different strategies: one is that you go to the store in your house every day to check out the shoes and eventually you find the best pair; another is to take your car and to spend a whole day searching for footwear all over town to find a place where they have the best shoes and you buy them immediately. The system is ergodic if the result of these two strategies is the same.
There are infinite examples of investors making this mistake. My mind wanders to the fund manager who offers up the fashionable but not-very-practical “permanent loss of capital” definition of risk, a stupid definition that is the last refuge of the fund manager with lousy long-term performance. “Sure, it’s down 65%, but that’s a non-permanent impairment!” Invariably, the PM will grumble and call this a 7-standard deviation event because he assumed a world of ergodicity. Because of the impact of a loss like this on the path of our wealth, we’ll now have to vastly exceed the average expected return we put in our scenario models in Excel just to break even on it.
“It’s not a permanent impairment of capital!”
It matters what path our portfolios follow through time. It matters that our big gains and losses may come all at once. It matters to how we should bet and it matters to how we invest. You cannot stir things apart!
So if you’ve decided to take risk as an investor, how we do avoid this pitfall? Consider again the case of the entrepreneur.
The entrepreneur’s portfolio is concentrated, which means that much of his risk has not been diversified away. A lot of that is going to be reflected in the risk and return measures we would use if we were to plot him on the efficient frontier. That doesn’t necessarily mean his risk of ruin will appear high, and his analysis might, in fact, inform the entrepreneur that he ought to borrow and hold this business as his sole investment. He’s done the work, performed business plan SWOT analyses, competitor analyses, etc., and concluded that he has a pretty good grasp of what his range of outcomes and risks look like.
In an ergodic world, this makes us feel all warm and fuzzy, and we give ourselves due diligence gold stars for asking all the right questions. In a non-ergodic world, the guy dies using his own product. A competitor comes out of nowhere with a product that immediately invalidates his business model. A bigger player in a related industry decides they want to dominate his industry, too. And these are just your usual tail events, not even caused the complexity of a system we can’t understand but by sheer happenstance. For the entrepreneur, all sorts of non-tail events over time may materially and permanently change any probabilistic assessment going forward. How do we address this?
The first line of defense as we take more risk must be diversification. After all, there is a reason why the Kelly Portfolios distribute the risk fairly evenly across the constituent asset classes.
Even that isn’t enough. Consider also the case of the leveraged investor in multiple investments with some measure of diversification, for example a risk parity investor, Berkshire Hathaway, or the guy who went Full Kelly per our earlier example, but without the whole perfect information thing. This investor has taken the opposite approach, which is to diversify heavily across different asset classes and/or company investments. His return expectation is driven not so much by his ability to create an outcome but by the exploitation of diversification. As he increases his leverage, his sensitivity to the correctness of his point-in-time probabilistic estimates of risk, return and correlations between his holdings will increase as well. In an ergodic world, this is fine and dandy. In a non-ergodic world, while he has largely mitigated the risk of idiosyncratic tails, he is relying on relationships which are based on a complex system and human behaviors that can change rapidly.
Thus, the second line of defense as we take more risk must be adaptive investing. Sometimes the only answer to a complex system is not to play the game, or at least to play less of it. Frameworks which adapt to changing relationships between markets and changing levels of risk are critical. But even they can only do so much.
Liquidity, leverage and concentration limits are your rearguard. These three things are also the only three ways you’ll be able to take more risk than asset classes give you. They are also the three horsemen of the apocalypse. They must be monitored and tightly managed if you want to have an investment program that takes more risk.
It’s not my intent to end on a fearful note, because that isn’t the point at all. More than asset class selection, more than diversification, more than fees, more than any source of alpha you believe in, nothing will matter to your portfolio and the returns it generates more than risk. And the more you take, the more it must occupy your attention. That doesn’t mean that we as investors ought to cower in fear.
On the contrary, my friends, fortune favors the bold.
 Back in 1989, Grauer and Hakansson undertook a somewhat similar analysis on a finite, pre-determined set of weightings among different assets with directionally similar results. Over most windows the optimal backward-looking levered portfolio tends to come out with a mid-30s level of annualized volatility.
 For this and the other exhibits and simulations presented here, I’m very grateful to my brilliant colleague and our head of quantitative strategies at Salient, Dr. Roberto Croce.
 And that reason isn’t just “we’re at the end of a 30-year bond rally,” if you’re thinking about being that guy.
 One suspects Mr. Buffett would be less than thrilled by the company we’re assigning him, but to misquote Milton Friedman, we are all levered derivatives users now.
Walter: Did you learn nothing from my chemistry class? Jesse: No. You flunked me, remember, you prick? Now let me tell you something else. This ain’t chemistry — this is art. Cooking is art. And the shit I cook is the bomb, so don’t be telling me… Walter: The shit you cook is shit. I saw your setup. Ridiculous. You and I will not make garbage. We will produce a chemically pure and stable product that performs as advertised. No adulterants. No baby formula. No chili powder. Jesse: No, no, chili P is my signature! Walter: Not anymore. — Breaking Bad, Season 1, Episode 1
“There was only one decline in church attendance, and that was in the late 1960s, when the Vatican said it was not a sin to miss Mass. They said Catholics could act like Protestants, and so they did.“ — Rodney Stark, Ph.D.
She should have died hereafter; There would have been a time for such a word. To-morrow, and to-morrow, and to-morrow, Creeps in this petty pace from day to day To the last syllable of recorded time, And all our yesterdays have lighted fools The way to dusty death. Out, out, brief candle! Life’s but a walking shadow, a poor player That struts and frets his hour upon the stage And then is heard no more: it is a tale Told by an idiot, full of sound and fury, Signifying nothing. — William Shakespeare, Macbeth, Act 5, Scene 5
“I can’t do it if I think about it. I would fall down, especially if I’m wearing street shoes,” he said, laughing. “It wasn’t something I did because I wanted to. I didn’t even know I did that until someone showed me a video.” — Fernando Valenzuela about his unique windup to the LA Times (2011)
Baseball was in the midst of a crisis in 1981.
In the years prior, competition for talent in larger markets had driven player salaries higher and higher. This caused owners to seek increasing restrictions on free agency. The players’ union went on strike in June, right in the middle of the season. Fans were furious, and mostly with the owners, as is the usual way of things. We still hate millionaires, of course, but we positively loathe billionaires. While the strike ended by the All-Star break in early August, work stoppages and disputes of this sort have often been the signposts of baseball’s long, slow march to obscurity against the rising juggernaut of American football and the sneaky, if uneven, popularity of basketball. It was not a riskless gamble for either party, and as future strikes taught us, the aftermath could have gone very badly.
Fernando was an anomaly in another long, slow march — that of baseball’s transition from a pastime to something more clinical, more analytical, more athletic. We were at a midpoint in the shift from the everyman-made-myth that was Babe Ruth or the straight-from-the-storybook folk hero like Joe DiMaggio to the brilliant, polished finished products of baseball academies today. Only a few years after 1981, we would see the birth of the new generation of uberathletes in Bo Jackson, a man who many still consider among the most gifted natural athletes in history. Only a decade earlier, the top prospect in baseball was one Greg Luzinski. The two weighed about the same. Their body composition was just a little bit different.
Fernando was certainly a physical throwback of the Luzinski variety, but so much more. He was a little pudgy. His hair was, long, shaggy and unkempt. More to the point, everything he did was inefficient, out of line with trends in the league. His windup was long and tortured, with a high leg kick that reached shoulder level in his early years and chest level in his older, slightly chubbier years. It featured an unnecessary vertical jerk of his glove straight upward near the end, and most uniquely, a glance to the heavens that became a signature of Fernando-mania. To stretch the inefficiency to its natural limits, his most effective pitch was a filthy screwball, a pitch that had been popular for decades but had already significantly waned by the early 1980s. Fathers and coaches taught their sons that it would hurt their arms (which a properly thrown screwball does not do), and by the late 1990s the pitch that ran inside on same-handed batters was all but extinct, except in Japan, where a very similar pitch called the shuuto continued to find adherents.
There were many reasons he captured the national imagination. He was a gifted Mexican pitcher in Los Angeles, a city full of baseball-obsessed Mexican-Americans and migrant workers. He was also truly marvelous as a 20-year old rookie in 1981. His stretch of eight games between April 9th and May 14th still ranks as one of the most dominant in history. Eight wins. Eight complete games. Five shutouts. Sixty-eight strikeouts. And that was how he started his career!(1)
But more than anything, I think, it was the pageantry and the spectacle of it all. The chubby, mop-top everyman who came out of nowhere with a corny sense of humor, who threw from a windup out of a cartoon, who threw a pitch that nobody else threw anymore. It was inefficient and ornamental and just so unnecessary — and we loved it. I still do. It was even how I was taught to pitch growing up. My father told me and instructed me to throw with “reckless abandon”, and so in my windup I would rotate my hips and point my left toe at second base before kicking it in a 180-degree arc at a shoulder level, nearly falling to the ground from the violent shift in weight after every pitch.
Alas, the efficiency buffs who disdained such extravagances were and are mostly right. While Valenzuela had a long and decent career, the greatest pitchers of the modern era — Roger Clemens, Pedro Martinez and especially Greg Maddux — all thrived on efficient mechanics and a focus on a smaller number of high quality pitches.(2) While a screwball is nice, and in many ways unique, it also isn’t particularly effective as a strikeout pitch in comparison to pitches with more vertical movement like, say, curveballs, split-finger fastballs or change-ups, or pitches that can accommodate lateral movement AND velocity, like sliders and cut-fastballs.
There’s a lesson in this.
As humans, especially humans in an increasingly crowded world where we can be instantly connected to billions of other people, the urge to stand out, to carve out a different path, can be irresistible. This influences our behavior in a couple of ways. First, it drives us to cynicism. Think back on the #covfefe absurdity. If you’re active on social media, by the time you thought of a funny #covfefe joke, your feed was probably already filled with an equal number of posts that decided that the meme was over, using the opportunity to skewer the latecomers to the game. Those, too, were late to the real game, which had by that time transitioned to new ironic uses of the nonsense word. A clever idea that is shared by too many quickly becomes an idea worthy of derision. And so the equilibrium — or at least the dominant game theory strategy — is to be immediately critical of everything.
It also makes us inexorably prone to affectation. We must add our own signature, that thing that distinguishes us or our product; the figurative chili-powder-in-the-meth of whatever our form of productive output happens to be. Since we are all writers of one sort or another now, we feel this acutely in how we communicate. When part of what you want to be is authentic in your communication, our introspection becomes a very meta thing — we can talk ourselves into circles about whether we’re being authentic or trying inauthentically to appear authentic. But we’re always selling, and while our need for a unique message has exaggerated this tendency, at its core it clearly isn’t a novel impulse. People have been selling narratives forever. But if there’s a lesson in Epsilon Theory, surely it is that successful investors will be those who recognize, survive and maybe even capitalize on narrative-driven markets — not necessarily those whose success is only a function of their ability to push substance-less narratives of their own.
Perhaps most perniciously, our urge to stand out is also an urge to belong to a Tribe — to find that small niche of other humans that afford us some measure of human interaction while still permitting us to define ourselves as a Thing Set Apart. The screwball, the chili powder, the fancy windup, the obscure quotes about Catholicism from sociology Ph.D.s in your investing think-piece — instead of a barbaric yawp, it becomes a signal to your tribe. When pressed, our willingness to rip off the steering wheel and adopt a competitive strategy becomes dominant, a necessity. Lingering in the back of our heads as we go all-in on our tribe is the knowledge that our tribal leaders, no matter who they are, will sell us down the river every time.
In our investing lives, when we build portfolios, we know full well how many options our clients or constituents have, so these three competing impulses drive our behaviors: cynicism, affectation and tribalism. The cynical, nihilistic impulse shouts at us that nothing matters enough to justify risking being fired, and so we end up choosing the solution that looks most like what everyone else has done. That’s the ultimate equilibrium play we’re all headed toward anyway, right? The affectation impulse requires that we add a little something to distinguish us from our peers. A dash of chili powder. A screwball here or there, or an outlandish delivery to delight and astonish. Our tribal impulse compels us toward the right-sounding idea that makes us part of a group (I’m looking at you, Bogleheads). More frequently, we’re motivated by a combination of all three of these things in one convoluted, ennui-laden bit of arbitrary decision-making.
The real kick in the teeth of all this is that many of the things we are compelled to do by these impulses are actually good and important things, even Things that Matter. But because of the complex rationale by which we arrive at them (and other biases besides), we often implement the decisions at such a halfhearted scale that they become irrelevant. In other, worse cases, the decisions function like the tinkering we discussed in And They Did Live by Watchfires, potentially creating portfolio damage in service of a more compelling marketing message or to satisfy one of these impulses. In both cases, these flourishes and tilts are too often full of sound and fury, signifying nothing.
Too Little of a Good Thing
What, exactly, are we talking about? Well, how about value investing, for starters?
I think this one pops up most often as a form of the tribal impulse, although clearly many advisors and allocators use it as a way to add a dash of differentiation as well. Now, most of us are believers in at least a few investing tribes, each with its own taxonomy, rituals, acolytes and list of other tribes we’re supposed to hate in order to belong. But none can boast the membership rolls of the Value Tribe (except maybe the Momentum Tribe or the Passive Tribe). And for good reason! Unlike most investment strategies and approaches devised, buying things that are less expensive and buying things that have recently gone up in price can both be defended empirically and arrived at deductively based on observations of human behavior. The cases where science is really being applied to investing are very, very rare, and this is one of them. Rather than pour more ink into something I rather suppose everyone reading this believes to one extent or another, I’d instead direct you to read the splendid gospel from brothers Asness, Moskowitz and Pedersen on the subject. Or, you know, if you’re convinced non-linearities within a population’s conditioning to sustained depressing corporate results and lower levels of expected growth mean that such observations are only useful for analysis of the actions of an individual human and can’t possibly be generalized or synthesized into a hypothesis underpinning the existence of the value premium as an expression of market behavior, then don’t read it. Radical freedom!
What is shocking is how ubiquitous this belief is when I talk to investors, and how little investors demonstrate that belief in their portfolios. We adhere to the tribe’s religion, but now that it’s not a sin to skip out, we only attend its church on Christmas and Easter. And maybe after we did something bad for which we need to atone.
Value is the more socially acceptable tribe (let’s be honest, momentum has always had a bit of a culty, San Diego vibe), so let’s use that as our case study. Since I’m worried I’m leaving out those for whom cynicism is the chosen neurosis, let’s use robo-advisors to illustrate that case study. They’re instructive as a general case as well, since they, by definition, seek to be an industry-standard approach at a lower price point. Now, of the two most well-advertised robos, one — Wealthfront — mostly ignores value except in context of income generation. The other — Betterment — embraces it in a pretty significant way. I went to their very fine website and asked WOPR what a handsome young investment writer ought to invest in to retire around 2045. Here is what they recommended:
Source: Betterment 2017. For illustrative purposes only.
Pretty vanilla, but then, that’s kind of the idea of the robo-advisor. But I see a lot of registered investment advisors and this is also straight out of their playbook. It’s tough to find an anchor for the question “I know I want/need value, but how much?” As a result, one of the most common landing spots I see is exactly what our robot overlords have recommended: half of our large cap equities in core, and the other half in value. We signal/yawp a bit further: we can probably also afford to do it in the smaller chunks of the portfolios, too. Lets just do all of our small cap and mid cap equities in a value flavor. As for international and emerging equities, we don’t want to scare the client with any more line items or pie slices invested in foreign markets than we need, so let’s just do one big core allocation there.
I’m putting words in a lot of our mouths here, but if you’re an advisor or investor who works with clients and this line of thinking doesn’t feel familiar to you, I’d really like to hear about it. Because this is exactly the kind of rule of thumb I see driving portfolio decisions with so many allocators that I speak to. But how do we actually get to a portfolio like this? If you think there’s a realistic optimization or non-rule-of-thumb-driven investment process that’s going to get you here, let’s disabuse ourselves of that notion.
Could plugging historical volatility figures and capital markets expectations into a mean/variance optimizer get you to this split on value vs. core? In short? No. No, we know that this is an impossible optimizer solution because the diversification potential at the portfolio level — what we call the Free Lunch Effect in this piece — would continue to rise as we allocated more and more of our large cap allocation to a value style (and less and less to core). In other words, while the intuition might be that having both a core and value allocation is more diversifying (more pie slices!), that just isn’t true. In a purely quantitative sense, you’d be most diversified at the portfolio level with no core allocation at all!
Free Lunch Effect of Various Allocations to Large Cap Value vs. Large Cap Core in Example Portfolio
Source: Salient 2017. For illustrative purposes only.
If your instinct is to say that doesn’t look like much diversification, however, you’d be right as well. Swinging our large cap portfolio from no value to nothing but value reduces our portfolio risk by around 8bp without reducing return (i.e., the Free Lunch). That’s not nothing, but it’s damn near. The reason is that the difference between the Russell 1000 Value Index and the Russell 1000 Index or the S&P 500, or the difference between your average large cap value mutual fund and your average large cap blend mutual fund, is not a whole lot in context of how most things within a diversified portfolio interact. Said another way, the correlation is low, but the volatility is even lower, which means it has very little capacity to impact the portfolio. Take a look below at how much that value spread contributes to portfolio volatility. The below is presented in context of total portfolio volatility, so you should read this as “If I invested all 32% of the large cap portion of this portfolio in a value index and none in a core index, the value vs. core spread itself would account for about 0.1% of portfolio volatility.”
Percentage of Portfolio Volatility Contributed by LC Value-Core Spread
Source: Salient 2017. For illustrative purposes only.
Fellow tribesmen, does this reflect your conviction in value as a source of return? Some of you may quibble, “Well, this is just in some weird risk space. I think about my portfolios in terms of return.” Fine, I guess, but that just tells the same story. Consider how most value indices are constructed, which is to say a capitalization weighted splitting of “above average” vs. “below average” stocks on some measure (e.g., Russell) or multiple measures (e.g., MSCI) of value. We may have in our heads some of the excellent research on the value premium, but those are almost always expressed as regression alphas or as spread between high and low quintiles or deciles (Fama/French) or tertiles (Asness et al). In most cases they are also based on long/short or market neutral portfolios, or using methodologies that directly or indirectly size positions based on the strength of the value signal rather than the market capitalization of the stock. There are strategies based on these approaches that do capitalize on the long-term edge of behavioral factors like value. But that’s not really what you’re getting when you buy most of these indices or the many products based on them.(3)
So what are you getting? For long-only stock indices globally, probably around 80bp(4) and that assumes no erosion in the premium vs. long-term average. Most other research echoes this – the top 5 value-weighted deciles of Fama/French get you about 1.1% annualized over the average since 1972, and comparable amounts if you go back even further. Using the former figure, if you swung from 0% value to 32% value in your expression of your large cap allocation — frankly a pretty huge move for most investors and allocators — we’re talking about a 26bp difference in expected portfolio returns. Again, not nothing, but if our portfolio return expectations are, say, 8%, that’s a 3.2% contributor to our portfolio returns under fairly extreme assumptions.
Does this reflect your conviction in value as a source of return? No matter how we slice it, the ways we implement even fundamental, widely understood and generally well-supported sources of return like value seem to be a bit long on the sound and fury, but unable to really drive portfolio risk or return. Why is this so hard? Why do we end up with arbitrary solutions like splitting an asset class between core and value exposure like some sort of half-hearted genuflection in the general direction of value?
Because we have no anchor. We believe in value, but deep down we struggle to make it tangible. We don’t know how much of it we have, we don’t even know how much of it we want. We struggle even to define what “how much” means, and so we end up picking some amount that will allow us to sound sage and measured to the people who put their trust in us to sound sage and measured.
I’m going to spend a good bit of time talking about how I think about the powerful diversifying and return-amplifying role of behavioral sources of return like value as we transition our series to the Things that Matter, so I’ll beg both your patience and indulgence for leaving this as a bit of a resolutionless diatribe. I’ll also beg your pardon if it looks like I’ve been excessively critical of the fine folks who put together the portfolio that has been our case study. In truth, that portfolio goes much further along the path than most.
The point is that for various behavioral reasons, our style tilts like value, momentum or quality occupy a significant amount of our time, marketing and conversations with clients, and — by and large — signify practically nothing in terms of portfolio results. In case I wasn’t clear, yes, I am saying that value investing — at least the way most of us pursue it — doesn’t matter.
The Magically Disappearing Diversifier
The time we spend fussing around with miniscule style tilts, however, often pales in comparison to the labor we sink into our flourishes in alternatives, especially hedge funds. Some of this time is well-spent, and well-constructed hedge fund allocations can play an important role in a portfolio. When I’m asked to look at investors’ hedge fund portfolios, there are usually two warning signs to me that the portfolios are serving a signaling/tribal purpose and not some real portfolio objective:
Low volatility hedge funds inside of high volatility portfolios that aren’t using leverage
Hedge fund portfolios replacing Treasury or fixed income allocations
Because of the general sexiness (still, after all these years!) of hedge fund allocations to many clients or constituents, the first category tends to be the result of our affectation impulse. We want to add that low-vol, market-neutral hedge fund, or the fixed income RV fund that might have been taking some real risk back in 2006 when they could lever it up a bajillion times, not because of some worthwhile portfolio construction insight, but perhaps because it allows us to sell the notion that we are smart enough to understand the strategies and important enough to have access to them. Not everyone can get you that Chili P, after all. In some cases, sure — we are signaling to others that we are also part of that smart and sophisticated enough crowd that invests in things like this. In the institutional world, where it’s more perfunctory to do this, it’s probably closer to cynicism: “Look, I know I’m going to have a portfolio of low-vol hedge funds, so let’s just get this over with.”
For many clients and plans — specifically those where assets and liabilities are mostly in line and the portfolio can be positioned conservatively, say <10% long-term volatility — that’s completely fine. But for more aggressive allocations, there is going to be so much equity risk, so much volatility throughout the portfolio, that the notion that these portfolios will serve any diversification role whatsoever is absurd. They’re just taking down risk, and almost certainly portfolio expected returns along with it. Unless you feel supremely confident that you’ve got a manager, maybe a high frequency or quality stat arb fund, that can run at a 2 or 3 Sharpe, it is almost impossible to justify a place for a <4% volatility hedge fund in a >10% target risk portfolio. They just won’t move the needle, and there are better ways to improve portfolio diversification, returns or risk-adjusted returns.
The second category starts to veer out of “Things that Don’t Matter” territory into “Things that Do Matter, but in a Bad Way.” More and more over the last two years, as I’ve talked to investors their primary concern isn’t equity valuations, global demographics, policy-controlled markets, deflationary pressures, competitive currency crises, protectionism, or even fees! It’s their bond portfolio. The bleeding hedge fund industry has been looking for a hook since their lousy 2008 and their lousier 2009, and by God, they found it: sell hedge funds against bond portfolios! Absolute return is basically just like an income stream! There seems to be such a strong consensus for this that it may have become that cynical equilibrium.
No. Just no.
It’s impossible to overstate the importance of a bond/deflation allocation for almost any portfolio. This is an environment that prevails with meaningful frequency that has allowed the strong performance of one asset historically: bonds, especially government bonds (I see you with your hands raised in the back, CTAs, but I’m not taking questions until the end). The absolute last thing any allocator should be thinking about if they have any interest in maintaining a diversified portfolio, is reducing their strategic allocation to bonds. I’ll be the first to admit that when inflationary regimes do arrive, they can be long and persistent, during which the ability of duration to diversify has historically been squashed. The negative correlation we assume for bonds today is by no means static or certain, which is one of the reason I favor using more adaptive asset allocation schemes like risk parity that will dynamically reflect those changes in relationship. But even in that context, the dominance and ubiquity of equity-like sources of risk means that almost every investor I see is still probably vastly underweight duration.
Now many of us do have leverage limitations that start to create constraints, and so I won’t dismiss that there are scenarios where that constraint forces a rational investor not to maximize risk-adjusted returns, but absolute returns. I’m also willing to consider that on a more tactical basis, you may be smarter than I am, and have a better sense of the near-term direction of bond markets. In those cases, reducing bond exposure, potentially in favor of absolute return allocations, may be the right call. But if you have the ability to invest in higher volatility risk parity and managed futures, or if you have a mandate to run with some measure of true or derivatives-induced leverage, my strong suspicion is that you’ll find no cause to sell your bond portfolios in favor of absolute return.
Ultimately, it’s hard to be too prescriptive about all this, because our constraints and objective functions really may be quite different. To me, that means that the solution here isn’t to advise you to do this or not to do that, except to recommend this:
Make an honest assessment of your portfolio, of the tilts you’ve put on, and each of your allocations. Do they all matter? Are you including them because of a good faith and supportable belief that they will move the portfolio closer to its objective?
If we don’t feel confident that the answer is yes, it’s time to question whether we’re being influenced by the sorts of behavioral impulses that drive us elsewhere in our lives: cynicism, affectation and tribalism. In the end, the answer may be that we will continue to do those things because they feel right to us and our clients. And that may be just fine. A little bit of marketing isn’t a sin, and if your processes that have served you well over a career of investing are expressed in context of a particular posture, there’s a lot to be said for not fixing what ain’t broken. There’s nothing wrong with an impressive-looking windup, after all, until it adversely impacts the velocity and control of our pitches.
What is a sin, however, is when a half-hearted value tilt causes us to be comfortable not taking advantage of the full potential of the value premium in our portfolios. When the desire to get cute with low-vol hedge funds causes us to undershoot our portfolio risk and return targets. Perhaps most of all, when we spend our most precious resource — time — designing these affectations. We will be most successful when we reserve our resources and focus for the Things that Matter.
(1) Please – no letters about his relief starts in 1980. If MLB called him a rookie, imma call him a rookie.
(2) Probably the only exception in this conversation is Randy Johnson, who, while mostly vanilla in his mechanics, would probably get feedback from a coach today about his arm angle, his hip rotation and a whole bunch of other things that didn’t keep him from striking out almost 5,000 batters.
(3) As much as marketing professionals at some of the firms with products in this area would like to disagree and call their own product substantially different, they all just operate on a continuum expressed by the shifting of weightings toward cheaper stocks. Moving from left to right as we exaggerate the weighting scheme toward value, the continuum basically looks like this: Value Indices -> Fundamental Indexing -> Long-Only Quant Equity -> Factor Portfolios
(4) Simplistically, we’re just averaging the P2 and half of the P3 returns from the Individual Stock Portfolios Panel of Value and Momentum Everywhere, less the average of the full universe. An imperfect approach, but in broad strokes it replicates the general half growth/half value methodology for the construction of most indices in the space.
There are two kinds of stories we tell our children. The first kind: once upon a time, there was a fuzzy little rabbit named Frizzy-Top who went on a quantum, fun adventure only to face a big setback, which he overcame through perseverance and by being adorable. This kind of story teaches empathy. Put yourself in Frizzy-Top’s shoes, in other words.
The other kind: Oliver Anthony Bird, if you get too close to that ocean, you’ll be sucked into the sea and drowned! This kind of story teaches them fear. And for the rest of their lives, these two stories compete: empathy and fear.
— Oliver Bird, Legion, Chapter 4 (2017)
Skinner: What are you doing in here? Linguini: I’m just familiarizing myself with, you know, the vegetables and such. Skinner: Get out. One can get too familiar with vegetables, you know! — Ratatouille (2007)
It’s four in the morning, and he finds himself drawn to a hotel and casino that has been out of style for thirty years, still running until tomorrow or six months from now when they’ll implode it and knock it down and build a pleasure palace where it was, and forget it forever. Nobody knows him, nobody remembers him, but the lobby bar is tacky and quiet, and the air is blue with old cigarette smoke and someone’s about to drop several million dollars on a poker game in a private room upstairs. The man in the charcoal suit settles himself in the bar several floors below the game, and is ignored by a waitress. A Muzak version of “Why Can’t He Be You” is playing, almost subliminally. Five Elvis Presley impersonators, each man wearing a different colored jumpsuit, watch a late-night rerun of a football game on the bar TV.
A big man in a light gray suit sits at the man in the charcoal suit’s table, and, noticing him even if she does not notice the man in the charcoal suit, the waitress, who is too thin to be pretty, too obviously anorectic to work Luxor or the Tropicana, and who is counting the minutes until she gets off work, comes straight over and smiles. He grins widely at her, “You’re looking a treat tonight, m’dear, a fine sight for these poor old eyes,” he says, and, scenting a large tip, she smiles broadly at him. The man in the light gray suit orders a Jack Daniel’s for himself and a Laphroaig and water for the man in the charcoal suit sitting beside him.
“You know,” says, the man in the light gray suit, when his drink arrives, “the finest line of poetry ever uttered in the history of this whole damn country was said by Canada Bill Jones in 1853, in Baton Rouge, while he was being robbed blind in a crooked game of faro. George Devol, who was, like Canada Bill, not a man who was averse to fleecing the odd sucker, drew Bill aside and asked him if he couldn’t see that the game was crooked. And Canada Bill sighed, and shrugged his shoulders, and said. “I know. But it’s the only game in town.” And he went back to the game.
— Neil Gaiman, American Gods (2001)
I had a dream, which was not all a dream. The bright sun was extinguish’d, and the stars Did wander darkling in the eternal space, Rayless, and pathless, and the icy earth Swung blind and blackening in the moonless air; Morn came and went—and came, and brought no day, And men forgot their passions in the dread Of this their desolation; and all hearts Were chill’d into a selfish prayer for light: And they did live by watchfires… — George Gordon, Lord Byron, Darkness (1816)
A Year Without Summer
In 1816 — 200 years ago — much of the world was experiencing a “Year without Summer.” We now know this was a result of the 1815 eruption of Mount Tambora, a volcano on the sparsely populated Indonesian island of Sumbawa, an eruption which sent some 38 cubic miles of rock, ash, dust and other ejecta into the atmosphere. For reference, that’s roughly 200 times the volume of material ejected in the eruption of Mount St. Helens, but only a tenth or so the size of the Lake Toba explosion off Sumatra that some researchers believe caused one of the most perilous bottlenecks in human genetic history.
At the time in 1816, the world didn’t know the cause. Well, except for maybe the people living on Sumbawa. The effects, on the other hand, couldn’t be missed.
In New England, the clouds of ash that blocked the sun led to remarkable drops and extraordinary variations in temperature and precipitation. In the Berkshires, there was a deep freeze in May. It snowed in Boston as late as June 7. Cornfields in New Hampshire were ruined by frost on August 14. The Dartmouth College campus was blanketed by snow as late (early?) as September. It caused as near a true famine as the U.S. has ever experienced. Hardy crops — some strains of wheat, potatoes and the like — got most of the nation through the year, as did a culling of wild game that likely came as a bit of an unpleasant surprise to the squirrels, hogs and possums that were usually spared a place on the American table.
The situation was not much better in Western Europe, where average temperatures fell as much as 3-4°C. On the British Isles, failed wheat and potato crops meant famine for much of Ireland, Wales and Scotland. Germany had food riots. And in Switzerland, where Lord Byron was in residence with Shelley, the constant rain and cold led each to create a great deal of poetry, which, depending on your opinion of early romanticism, was either more or less catastrophic than the torrential rains that accompanied it. Under the circumstances, it is not surprising that Byron was inspired to write about the heat death of the universe some 35 years before Lord Kelvin proposed it rather more formally (and perhaps less melodramatically).
Byron’s poem, Darkness, envisions a world in which the sun has been extinguished, in which morning never comes. In this time of desperation, the world is literally tearing itself apart. Palaces are ripped to pieces for firewood, forests are set alight and people gather “round their blazing homes” just so they can see their own hands, and the faces of their family and friends. Everything the world has built is pulled apart piece by piece in search of a solution to the problem of darkness.
The stories we tell about such times of desperation tend to fall into the two archetypes Jemaine Clement’s character describes in Legion: stories of fear and stories of empathy. Byron gave us a story of fear. Empathy stories, on the other hand, follow the usual trope of necessity as the mother of invention. But even this is often just a fear story with a different outcome, not uncommonly summoning a sort of deus ex machina. Luke listening to Obi Wan’s disembodied voice instead of the computer as he aims his last shot at the Death Star. Gollum showing up to bite off Frodo’s ring finger and take a dive into Mt. Doom, saving the hobbit from the now too-strong temptation to wear the ring and return it to Sauron. And maybe there’s a story where Byron’s humanity finds a real solution to the coming darkness instead of tearing their homes and businesses apart looking for something else to burn.
The investment environment we face is not so dire as all this, but it does feel a bit grim, doesn’t it? Market returns have continued to defy the odds, but the data, our consultants, our advisors, our home offices and our instincts are telling us that the combination of demographic slowing, stagnant productivity, limited debt capacity, low rates and high valuations isn’t going to end well. Or at a minimum, we remain optimistic but confused. I’m sure we’ve all asked or heard clients and constituents asking us, “What the hell do we invest in when everything is expensive and nothing is growing?” In this call to action, are we successfully turning this into an empathy story? Or are we just ripping apart our homes for tinder so that it looks like we are doing something?
When it’s hard to see what’s two feet ahead of our own noses, when the game feels rigged, sometimes it feels like we have no choice but to stay at the table and play. After all, it’s the only game in town. And so instead of walking away and taking what the market gives us, we tweak, we tilt, we “take chips off the table,” we “go all in” and we hack, hack, hack at the beams and joists of our own homes for the great bonfire.
This bias to action is a road to ruin. That’s why the endless tweaking, trading and rebalancing of our portfolios takes spot #4 on our list of Things that Don’t Matter.
Of Priuses and Passive Investors
In 2011 a group of researchers at Berkeley examined an age-old question: are rich people driving expensive cars the asshats we all think they are? The findings? Yes, indeed they are! The study found that drivers of expensive cars were three times more likely than drivers of inexpensive cars to fail to yield to pedestrians at crosswalks requiring it, and four times more likely to go out of turn at a stop sign. The team performed similar tests in other non-traffic areas (e.g., cheating at games of chance, etc.) that arrived at the same conclusion, and furthermore identified that simply making people believe that they were part of the 2% Club made them behave more rudely.
My favorite discovery from the research was the odd outlier they discovered: the moderately priced Toyota Prius. Fully one third of Prius drivers blew by intrepid Berkeley grad students (taking a night off from throwing trash cans through the windows of some poor Wells Fargo branch, perhaps) who stepped into a busy crosswalk for science. This put it very near the top of the tables for rudeness. Most of you will recognize this as our old friend moral licensing: the subconscious tendency to feel empowered/entitled to do something bad, immoral or indulgent after having done something to elevate our estimation of our own value. The Prius owner has earned the right to drive like a jerk, since he’s saving the world by driving a hybrid car, after all. Alberto Villar of Amerindo Investment Advisors, who was the largest opera donor since Marie Antoinette, could easily justify stealing his clients’ money to make good on charitable pledges. Of course I can eat that Big Mac and large fries when I sneak over to the McDonald’s across the street from our San Francisco office — I ordered a Diet Coke, after all.
And so on behalf of insufferable hipsters, fraudulent philanthropists and Big Mac dieters everywhere, I would like to extend a gracious invitation to our club: ETF investors who pride themselves on being passive investors while they tactically trade in and out of positions over the course of the year.
Now there’s a lot of old research protesting too much that “ETFs don’t promote excessive trading!” A cursory review of news media and finance journals will uncover a lot of literature arguing exactly that, although the richest studies are several years old now. You’ll even find some informing you that leveraged ETFs aren’t being abused any more. Those of you who are closest to clients, are you buying what the missionaries are selling on this one?
I hope not.
Even when some of the original studies were published (most of which said that mutual funds were held around three years on average, while ETFs were held about two-and-a-half years), it was plainly evident to anyone who works with consumers of ETFs that basing claims on the “average” holding behavior was a poor representation of how these instruments were being held and traded. The people with skin in the game who weren’t selling ETFs were aware that holders fell by and large into three camps:
The long-term holders seeking out market exposure,
The speculators trading in and out of ETFs to generate additional returns, and
The increasingly sad and depressing long/short guys shorting SPY to hedge their longs, telling the young whippersnappers stories from a decade ago about “alpha shorts” before yelling for them to get off their lawn.
Source: Morningstar. For illustrative purposes only.
The mean holding period in the old research was still pretty long because Group 1 was a big group. I think that it was also because a lot of the ETF exposure that Group 2 was swinging around was in smaller, niche funds or leveraged ETFs. Both of these things are still true. They’re also becoming less true. A few weeks ago, Ben Johnson from Morningstar published this chart of the ten largest ETFs and their average holding period. There’s all sorts of caveats to showing a chart like this — some of the causes of ETF trading aren’t concerning — but if SPY turning over every two weeks doesn’t get your antennae twitching, I’m not sure what to tell you.
There are a lot of reasons to believe that we are lighting our houses on fire with the almost comically active use of “passive” instruments, and trading costs are one of them. Jason Zweig wrote an excellent piece recently highlighting research from Antti Petajisto on this topic. Petajisto’s work in the FAJ estimates that “investors” may be paying as much as $18 billion a year to trade ETFs. Zweig, perhaps feeling rather charitable, concedes that as a percentage of overall trading volume, this number isn’t really all that high. And he’s technically correct.
But who cares about trading volume, at least for this discussion, which isn’t really about the liquidity of the market? If — as so many investors and asset managers are fond of saying — the ETF revolution is but a trapping of the broader active vs. passive debate (insert audible yawn), we should really be thinking of this in terms of the asset size of the space. And in context of the $3 trillion, give or take, that is invested in ETFs, $18 billion is a LOT. It’s 60bp, which would be a lot even if it weren’t impacting investors who often make a fuss over whether they’re paying 15bp or 8bp in operating expenses.
And then there’s taxes. Now, actively managed strategies, especially those implemented through mutual funds, have plenty of tax issues and peculiarities of their own. But the short-term gains taxable investors are forcing themselves into by timing and day-trading ETFs are potentially huge. If we assume, say, a 6% average annual portfolio return, the investor who shifts 100% of his return from long-term gains into short-term gains is costing himself 60-120bp per year before we consider any time value or compounding effects of deferring tax liabilities. Given that the largest ten ETFs all have average holding periods of less than a year, this doesn’t seem to be all that inappropriate an assumption.
The growing Group 2 above, our day traders — oops, I mean, our “passive ETF investors” — may be giving away as much as 1.2%-1.8% in incremental return. Those fee savings sure didn’t go very far, and the direct costs of all this tinkering may not even be the biggest effect!
Every piece of data on this topic tells the same story: when we try to time our cash positions to have “ammo to take advantage of opportunities,” when we decide a market is overbought, when we rotate to this sector because of this “environment” that is about to kick off, when we move out of markets that “look like they’ve gotten riskier,” when we get back in because there’s “support” at a price, we are burning down our houses to live by watchfires.
There are two ways in which we as investors do this, one familiar and one less so.
Of Clients and Crooked Card Games
First, the familiar. We stay in the crooked game because it’s what’s expected of us. It’s tempting to think of the desire, this inclination toward constant “tactical” trading as an internal impulse. A response to boredom or, perhaps, an addiction to certain of the chemical responses associated with winning, with risking capital, even with losing. I think that’s probably true for some investors. I know that when I sat in an allocator’s seat, when I heard a portfolio manager tell me he had “fallen in love with the market” when he was six years old and started trading options with his dad when he was 10, I didn’t see that as a particularly good thing. One can get too familiar with vegetables, you know.
But just as often, the impulse to stay in the game is external, and that pressure usually comes from the client. I’m empathetic to it, and it’s not unique to our industry.
Have you ever sent a document to a lawyer and gotten no comments back? Have you ever visited a doctor and gotten a 100% clean bill of health with no recommendations? Have you ever taken your car to a mechanic and had them tell you about just the thing you brought it in for? Have you ever consulted with a therapist or psychiatrist who didn’t find something wrong with you, even if they had the bedside manner to avoid using those exact words? It isn’t just that those folks are being paid for the additional services they’re proposing. There is a natural feeling among professional providers of advice that they must justify their cost to their clients even if the best possible advice is to do nothing.
The result is that the crooked card game usually takes three different forms, which, in addition to all the fees and tax impact discussed above, may add risk and harm returns for portfolios in other ways as well:
The Cash Game: When investors feel concerned about the timing of their entry into markets, the direction of markets, upcoming events, or some other factor and temporarily sell investments and go to cash, they’re playing the Cash Game. I recently had a meeting with an intermediary who had recently launched a system to integrate all client holdings (including accounts held away). Their initial run identified average aggregate cash positions of more than 15%!
The Performance–Chasing Game: I’ve talked about this ad nauseam in prior notes. We investors find all sorts of vaguely dishonest ways to pretend that we aren’t just performance-chasing. It doesn’t work, and a goodly portion of the damage done by tinkering and “tactical” moves is just performance-chasing in guise, even if we are high-minded enough to pretend that we’re making the decision because “the fund manager changed his process” or euphemistically inclined enough to say the investment “just wasn’t working,” whatever that means.
The In-Over-Our-Heads Game: Still other games are essentially designed to “fleece the odd sucker,” causing investors to seek out hedges and interesting trades to take advantage of events and “low cost” insurance for portfolios. As a case study, please take a gander at the size and volume of instruments and funds tracking the VIX. Please look at the return experience of holders of those various instruments. It’s not the vehicles themselves that are flawed, but the way in which these markets prey on misplaced expectations of investors that they know when insurance is cheap or expensive. As a quick test: if you can’t define gamma without looking it up on Investopedia, you probably shouldn’t own any of these instruments, much less be flopping in and out of them. This concept is broadly transferable to a variety of things investors do to “hedge” — buying S&P puts, buying short ETFs, etc.
I know I’m not treading new ground here. Borrowing from the work done in a thorough survey on the literature that itself concludes a 1.0% impact from the ways in which investors trade in and out of funds, the figures are pretty consistent. The folks over at Dalbar concluded in 2016 that investors in equity mutual funds underperformed equity indices by 3.5% over the last 20 years, 1.5% of which they attribute to “panic selling, exuberant buying and attempts at market timing.” Frazzini and Lamont previously estimated 0.85%. In 2007, Friesen and Sapp said 1.56%. We’ve got something for hedge fund investors, too.
You’ve heard this story before. So why am I telling you this?
Because when I meet or speak with investors, I often worry that when they think about dominant narratives and observations about human behaviors, they are focused on identifying tradable trends and signals. In rare cases, that is a worthwhile endeavor. And we’ve made no secret that we’re spending a lot of time thinking about the Narrative Machine — after all, if we believe that investors systematically make mistakes that cost them returns and money, it should be possible to identify ways to capitalize on the actions taken by others.
But far more often, the message from the analysis of prevailing narratives is to back away from the table. Investors I’ve spoken to in the past few years have heard a voice of caution against rotating away chunks of portfolios that by all rights ought to be invested in bonds based on flimsy rationale like, “rates couldn’t possibly get lower!” I’ve likewise cautioned against haphazardly fleeing equity markets into cash on the basis of historically high valuations, perceived political turmoil and the like. There will come times where it may be right to make strong positive observations on opportunities for tactical allocations, but as in all decisions we make when investing, it is imperative that we be aware that the hurdle for staying at the table to play the only game in town is very high. Our skepticism about opportunities to play it should be extreme.
Of Bambi and Battle Tanks
Since I’m advising you to be skeptical, I’ll forgo the apocryphal (it’s real to me, dammit!) story I was going to tell at this point in my little piece. I was going to tell you a story my brother told me once about a high school classmate, an M1A1 Abrams tank and a whitetail deer. It is apparently not normal in polite company to discuss the disintegration of adorable animals, and so I won’t unless you buy me a drink (Lagavulin and water, please). What I will do is highlight that the often-overlooked pitfall of the tinkering mentality is the tendency to use very big tools to accomplish very small things, for which the intended aim is almost always overwhelmed by the unintended consequence. Pointing a 120mm smoothbore cannon at a tiny animal isn’t going to shrink the explosion it causes. Likewise, pointing a major change in risk posture or asset allocation at an event we’re a bit nervous about isn’t going to change the fact that we’ve made a change to some very fundamental characteristics of the portfolio.
This happens all the time.
In the last year, I’ve met with advisors, allocators and investors convinced of the inexorable, unstoppable, indomitable rise of interest rates who exited their government and investment-grade bond portfolios — in many cases, the only remnant of their portfolio standing against them and a downturn in risk assets — in favor of higher yielding equity portfolios that wouldn’t be as exposed to the environment they expect. I’ve seen investors leaving passive equity allocations in favor of concentrated private deals because they are concerned about the broader economy’s impact on stocks. I’ve seen investors switch asset classes because they didn’t like the manager they were invested with.
There may be reasons for some of those views, and in some cases even for acting on them. But I am always concerned when I see changes like that unaccompanied by consideration of the magnitude of the unintended consequences: are we still taking the right amount of risk? Are we achieving adequate diversification? As we close out the list of Things that Don’t Matter, I look forward to publishing our list of things that actually DO, because these questions play prominently. There is hope. There are things we can do, and most of them will run contrary to our instincts to take rapid, “nimble” action in our portolios.
Within that thread of hope, a plea first to readers who prefer poetry: that we feel disillusioned or confused about the outcomes for markets does not mean we ought to be more active, more nimble in modifying our asset allocation, however good and wise those things sound when we say them to ourselves and our clients. All the data tell us that we are likely to find ourselves warming our hands at a watchfire before long. To those who prefer poker: you don’t have to play the game. It is OK to step away from the table, walk back to the elevator bank and call it a night, to take what the market gives us.
Make no mistake: the alternative is worse. It’s an expensive alternative. It’s often a risk-additive alternative. It’s a tax-producing alternative. It’s an alternative that frankly most of us just aren’t in a position to successfully execute. There is a reason that most global macro and GTAA hedge funds hire traders who have success in individual markets, even individual types of trading strategies within individual markets. It’s because being able to effectively determine when to switch among managers, among asset classes and among drivers of risk and return is very, very hard. The data bear this out, and no matter how hard we feel like we have to do something, it won’t change the fact that lighting our house on fire isn’t going to make the sun come back.
Understanding the dominant impact of narratives in markets today doesn’t mean abandoning our well-designed processes and our work determining asset allocation, risk targets and portfolio construction in favor of a haphazard chasing of the narrative-driven theme for the day. It means that human behavior and unstructured forms of information should — must — increasingly play a role in the structure of each of those processes in the first place.
After all, all investing is behavioral investing. Anyone who tells you different is either incompetent, selling something or both. One of the most pointless such behaviors — our unquenchable desire to act — nearly completes our list of the Things that Don’t Matter.