Rounders

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Mike McDermott: In “Confessions of a Winning Poker Player,” Jack King said, “Few players recall big pots they have won, strange as it seems, but every player can remember with remarkable accuracy the outstanding tough beats of his career.” It seems true to me, cause walking in here, I can hardly remember how I built my bankroll, but I can’t stop thinking of how I lost it.
– “Rounders” (1998)

I know it’s crooked, but it’s the only game in town.
– Canada Bill Jones (c. 1840 – 1880), described as “the greatest three-card monte sharp to ever work the boats”, on being told by his partner George Devol that a Faro game in Cairo, Illinois was rigged.

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David Howard: We’re up!
Linda Howard: We’re still down.
David Howard: How down?
Linda Howard: Down.
David Howard: How down is she?
Desert Inn Casino Manager: Down.
Desert Inn Casino Manager: You’re a nice guy. You make me laugh. But our policy is: we can’t give your money back.

– “Lost in America” (1985) 

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Boredom is the conviction that you can’t change … the shriek of unused capacities.
– Saul Bellow, “The Adventures of Augie March” (1953)


Anything becomes interesting if you look at it long enough.

– Gustave Flaubert (1821 – 1880)


She wanted to die, but she also wanted to live in Paris. 

– Gustave Flaubert (1821 – 1880)

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To me, at least in retrospect, the really interesting question is why dullness proves to be such a powerful impediment to attention. Why we recoil from the dull…surely something must lie behind not just Muzak in dull or tedious places but now also actual TV in waiting rooms, supermarkets’ checkouts, airport gates, SUVs’ backseats. Walkman, iPods, BlackBerries, cell phones that attach to your head. This terror of silence with nothing diverting to do. I can’t think anyone really believes that today’s so-called ‘information society’ is just about information. Everyone knows it’s about something else, way down.

– David Foster Wallace, “The Pale King” (2011)

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Carl:  This is crazy. I finally meet my childhood hero and he’s trying to kill us. What a joke.
Dug: Hey, I know a joke! A squirrel walks up to a tree and says, “I forgot to store acorns for the winter and now I am dead.” Ha! It is funny because the squirrel gets dead.

– “Up” (2009)

I’m a good poker player. I know that everyone says that about themselves, so you’ll just have to take my word for it. I’m also a good stock picker, which again is something that everyone says about themselves. At least on this point I’ve got a track record from a prior life to make the case. But I don’t consider myself to be a great poker player or a great stock picker. Why not? Because I get bored with the interminable and rigorous discipline that being a great poker player or a great stock picker requires. And I bet you do, too.

To be clear, it’s not the actual work of poker playing or stock picking that I find boring. I could happily spend every waking moment turning over a new set of cards or researching a new company. And it’s certainly not boring to make a bet, either on a hand or a stock. What’s boring is NOT making a bet on a hand or a stock. What’s boring is folding hand after hand or passing on stock after stock because you know it’s the right thing to do. The investment process that makes a great poker player or a great stock picker isn’t the research or the analysis, even though that’s what gets a lot of the attention. Nor is it the willingness to make a big bet when you believe the table or the market or the world has given you a rare combination of edge and odds, even though that’s what gets even more of the attention. No, what makes for greatness as a stock picker is the discipline to act appropriately on whatever the market is giving you, particularly when you’re being dealt one low conviction hand after another. The hardest thing in the world for talented people is to ignore our mental “shriek of unused capacities”, to use Saul Bellow’s phrase, and to avoid turning a low edge and odds opportunity into an unreasonably high conviction bet simply because we want it so badly and have analyzed the situation so smartly. In both poker and investing, we brutally overestimate the edge and odds associated with merely ordinary opportunities once we’ve been forced by circumstances to sit on our hands for a while.

As David Foster Wallace puts it so well, “the really interesting question is why dullness proves to be such a powerful impediment to attention.” Why do we increasingly suffer from a “terror of silence” where we use electronic information devices to fill the void? Why are most of you reading this note with at least one TV screen showing CNBC or Bloomberg within easy viewing distance? How many of us are bored to tears with the Fed’s Hamlet act on raising rates, and yet have been staring at this debate for so long that we have convinced ourselves that we have a meaningful view on what will transpire, even though it’s a decision where we have zero investing edge and unknowable risk/reward odds. I’m raising my hand as I re-read this sentence.

The biggest challenge of our investing lives is not finding ways to process more information, or even finding ways to process information more effectively. Our biggest challenge is finding the courage to focus on what matters, to admit that more or quicker information will not help our investment decisions, to recognize that our investment discipline suffers mightily at the hands of the impediment of dullness. Because let’s be honest… the Golden Age of the Central Banker is a really, really dull time for a stock-picking investor. I’m not saying that the markets themselves are dull or that market price action is boring. On the contrary, this joint is jumping. I’m saying that stock pickers are being dealt one dull, low conviction hand after another by global Central Banks, even though they’re forced to sit inside a glitzy casino with lots of lights and sounds and exciting gambling action happening all around them. We have little edge in a Reg-FD public market. We have at best unknowable odds and at worst a negatively skewed risk/reward asymmetry in a market where policy shocks abound. And yet we find ways to convince ourselves that we have both edge and odds, making the same concentrated equity bets we made back in happier times when idiosyncratic company fundamentals and catalysts were actually attached to a company’s stock price. Builders build. Drillers drill. Stock pickers pick stocks. We can’t help ourselves, even if the deck is stacked against us here in the only game in town.

Investment discipline suffers under the weight of dullness and low conviction in at least four distinct ways here in the Golden Age of the Central Banker.

First, just as there’s a winner on every poker hand that you sit out, there’s a winner every day in the markets regardless of whether or not you are participating. The business risk of sitting out too many hands weighs heavily on most of us in the asset management or financial advisory worlds. We can talk about maintaining our investment discipline all we like, but the truth is that all of us, in the immortal words of Bob Dylan, gotta serve somebody. If we’re not telling our investors or our board or our CIO that we have high conviction investment ideas … well, they’re going to find someone else who WILL tell them what they want to hear. And for those lucky few of you reading this note blessed with access to more or less permanent capital, I’ll just say that the conversations we have with ourselves tend to be even more pressuring than the conversations we have with others. No one forces me to “make a play” when I have a middle pair and a so-so kicker, but I’ve somehow convinced myself that I can take down a pot just because I’ve been playing tight for the past hour. No one forced Stanley Druckenmiller – one of the truly great investors of our era – to top-tick the NASDAQ bubble when he bought $6 billion worth of Internet stocks in March 2000. Why did he do it?

So, I’ll never forget it. January of 2000 I go into Soros’s office and I say I’m selling all the tech stocks, selling everything. This is crazy at 104 times earnings. This is nuts. Just kind of as I explained earlier, we’re going to step aside, wait for the next fat pitch. I didn’t fire the two gun slingers. They didn’t have enough money to really hurt the fund, but they started making 3 percent a day and I’m out. It is driving me nuts. I mean their little account is like up 50 percent on the year. I think Quantum was up seven. It’s just sitting there.

So like around March I could feel it coming. I just … I had to play. I couldn’t help myself. And three times during the same week I pick up a phone but don’t do it. Don’t do it. Anyway, I pick up the phone finally. I think I missed the top by an hour. I bought $6 billion worth of tech stocks, and in six weeks I had left Soros and I had lost $3 billion in that one play. You asked me what I learned. I didn’t learn anything. I already knew I wasn’t supposed to do that. I was just an emotional basket case and couldn’t help myself. So maybe I learned not to do it again, but I already knew that.

If living in the NASDAQ bubble can make Stan Druckenmiller convince himself that stocks trading at >100x earnings were a high conviction play only a few months after selling out of them entirely, what chance do we mere mortals have in not succumbing to 6-plus years of the most accommodative monetary policy in the history of man?

Second, every facet of the financial services industry is trying to convince you to play more hands, and we are biologically hard-wired to respond. I don’t have a good answer to Wallace’s question about why we all fear the silence and all feel compelled to fill the void with electronically delivered “information”, but I am certain that the business models of the Big Boy information providers all depend on Flow.So you can count on the “information” that we constantly and willingly beam into our brains being geared to convince us to join the casino fun. My favorite character in the wonderful movie “Up” is Dug the dog, who despite his advanced technological tools is a prisoner of his own biology whenever he hears the signal “Squirrel!”. We are all Dug the dog.

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Third, Central Bankers have intentionally sown confusion in our ranks. Like the barkers on CNBC and the sell-side, the Fed and the ECB and the BOJ and the PBOC are determined to force us into riskier investment decisions than we would otherwise choose to make. This is the entire point of extraordinary monetary policy over the past 6 years! All of it. All of the LSAPs, all of the TLTROs, all of the exercises in “Communication Policy” … all of it has been designed with one single purpose in mind: to punish investors who choose to sit on their hands and reward investors who make a bet, all for the laudable goal of preventing a deflationary equilibrium. And as a result we have the most mistrusted bull market in history, a bull market where traditional investment discipline was punished rather than rewarded, and where any investor who hasn’t been totally hornswoggled by Fed communication policy is now rightly worried about having the policy rug pulled out from underneath his feet.

Or to make this point from a slightly different perspective, while there is confusion between the concepts of investing and allocation in the best of times, there is an intentional conflation of the two notions here in the Golden Age of the Central Banker. The Fed wants to turn investors into allocators, and they’ve largely succeeded. That is, the Fed doesn’t care about your picking one stock over another stock or one sector over another sector or one company over another company. They just want to push you out on the risk curve, which for the vast majority of investors just means buying stocks. Any stock. All stocks. This is why the quality bias that most investors have – preferring solid management, strong balance sheets, and good cash flow generation to their opposites – has been largely immaterial as an investment factor (if not an outright drag on investment returns) over the past 6 years. If the King is flooding the town with easy credit, the deadbeat tailor will do relatively better than the thrifty mason every time. But try telling a true-believer that quality is just an investment factor, no more (and no less) privileged than any other investment factor. Honestly, I’ll get 50 unsubscribe emails just for writing this down.

Fourth, our small-number brains are good local data relativists, not effective cross-temporal or global data evaluators. Okay, that’s a mouthful. Translation: the human brain has evolved over millions of years and human society has been trained for tens of thousands of years to make sense of highly localized data patterns. Humans are excellent at prioritizing the risks and opportunities that they are paying attention to at any moment in time, and excellent at allocating their behavioral budget accordingly. It’s why we’re really good at driving cars or, in primate days of yore, surviving on the Serengeti plains. But if asked to compare the risks and rewards of a current decision opportunity with the risks and rewards of a decision opportunity last year (much less 10 years ago), or if asked to compare the opportunity we’ve been evaluating for months with something less familiar, we are utterly flummoxed. It’s not that we can’t remember or think on our feet, but there is an overwhelming attention and recency bias in human decision-making. That’s fine so long as we share the market with other humans, much less fine when we share the market with machine intelligences that excel at the information processing tasks we consistently flub. Whether it’s trading or investing, humans are no longer the apex predator in capital markets, but we act as if we are. 

So what’s an investor to do?

I can sum it up in one deceptively simple sentence: You take what the market gives you.

It’s deceptively simple because it implies a totally different perspective on markets than most investors (or allocators, frankly) bring to bear. It means approaching markets from a position of humility, i.e. risk tolerance, rather than from a position of hubris, i.e. return expectations. It’s all well and good to tell your financial advisor or your board or yourself that you’re “targeting an 8% return.” That’s great. I understand that’s your desire. But the market couldn’t care less what your desire might be. I think it’s so important to stop focusing on our “expectations” of the market, as if it were some unruly teenager that needs to get its act together and start doing what it’s told. It’s madness to anthropomorphize the market and believe that we can control it or predict its behavior. Instead, we need to focus on what we CAN control and what we CAN predict, which is our own reaction to what a stochastically-dominated social system like the market is going to throw at us over time. Tell me what your risk tolerance is. Tell me what path you’re comfortable walking. Then we can talk about the uncorrelated stepping stone strategies that will make up that path to get you where you want to go. Then we can talk about sticking to the path, which far more often means keeping risk in the portfolio than taking it out. Then we can talk about adaptively allocating between the stepping stone strategies as the risk they generate today differs from the risk they generated in the past. Maybe you’ll get lucky and one of the strategies will crush it, like US equities did in 2013. Excellent! But aren’t we wise enough to distinguish allocation luck from investment skill? I keep asking myself that rhetorical question, but I’m never quite happy with the answer.

You know, there’s this mythology around poker tournaments that the path to success is a succession of all-in bets where you “read” your opponent and make some seemingly brilliant bluff or call. I’m sure this mythology is driven by the way in which poker tournaments are televised, where viewers see a succession of exactly this sort of dramatic moment, complete with commentary attributing deep strategic thoughts to every action. What nonsense. The goal of great poker players is NEVER to go all-in. Going all-in is a failure of risk management, not a success. I’m exaggerating when it comes to poker, because the nice thing about poker tournaments is that there’s always another one. But I’m not exaggerating when it comes to investing. There’s only one Nest Egg (“Lost In America” is by far my favorite Albert Brooks movie), and thinking about investing and allocation through the lens of risk tolerance rather than return expectations is the best way I know to grow and keep that Nest Egg.

Taking What The Market Gives You has specific implications for each of the four ways in which the Golden Age of the Central Banker weakens investor discipline.

1) For the business risk associated with maintaining a stock-picking discipline and sitting out an equity market that you just don’t trust … it means taking complementary non-correlated strategies into your portfolio, as well as strategies that have positive expected returns but can make money when equities go down (like trend-following strategies or government bonds). It rarely means going to cash. (For more, see “It’s Not About the Nail”)

2) For the constant exhortations from the financial media and the sell-side to try a new game at the market casino … it means taking what you know. It means taking what you know the market is giving you because you have direct experience with it, not taking what other people are telling you that the market is giving you. Here’s my test: if I hear a pitch for a stock or a strategy and I find myself looking around the room (either literally or metaphorically) to see how other people are reacting to the pitch, then I know that I’m being sucked into the Common Knowledge Game. I know that I’m at risk of playing a hand I shouldn’t. (For more, see “Wherefore Art Thou, Marcus Welby?”)

3) For the communication policy of the Fed and the soul-crushing power of a risk-free rate that pays absolutely nothing … it means taking stocks that get as close as possible to real-world economic growth and real-world cash flows in order to minimize the confounding influence of Central Bankers and the game-playing that surrounds them. There’s nowhere to hide completely, as the volatility virus that started with the end of global monetary policy coordination in the summer of 2014 will eventually spread everywhere, but there’s no better place to ride out the storm than getting close to actual cash flows of companies that are determined to return those cash flows to investors. (For more, see “Suddenly Last Summer”)

4) For the transformation of the market jungle into a machine-dominated ecosystem … it means either adopting the same market perspective as a machine intelligence through systematic asset allocation strategies, or it means focusing on niche areas of the market where useful fundamental information is not yet aggregated for the machines. In either case, it means leaving behind the quaint notion that you can do fundamental analysis on large cap public companies and somehow gain an edge or identify attractive odds. (For more, see “One MILLION Dollars”)

One final point, and it’s one that seems particularly apropos after watching some bloodbaths in certain stocks and sectors over the past week or two. Investor discipline isn’t only the virtue of great investors when it comes to buying stocks. It’s also the virtue of great investors when it comes to selling stocks. I started Epsilon Theory a little more than two years ago in the midst of a grand bull market that I saw as driven by Narrative and policy rather than a self-sustaining recovery in the real economy. For about a year, I got widespread pushback on that notion. Today, it seems that everyone is a believer in the Narrative of Central Bank Omnipotence. What I find most interesting, though, is that not only is belief in this specific Narrative widespread, but so is belief in the Epsilon Theory meta-Narrative … the Narrative that it is, in fact, Narratives that drive market outcomes of all sorts. My hope, and at this point it’s only a hope, is that this understanding of the power of Narratives will inoculate a critical mass of investors and allocators from this scourge. Because the same stories and Narratives and low conviction hands that shook us out of our investment discipline on the way up will attack us even more ferociously on the way down.

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One MILLION Dollars

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Dr. Evil: Gentlemen, it has come to my attention that a breakaway Russian Republic called Kreplachistan will be transferring a nuclear warhead to the United Nations in a few days. Here’s the plan. We get the warhead and we hold the world ransom for…one MILLION dollars!
Number Two: Don’t you think we should ask for more than a million dollars? A million dollars isn’t exactly a lot of money these days. Virtucon alone makes over 9 billion dollars a year!
Dr. Evil: Really? That’s a lot of money.

“Austin Powers: International Man of Mystery” (1997)

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Dr. Manhattan: I have walked across the surface of the Sun. I have witnessed events so tiny and so fast they can hardly be said to have occurred at all. But you, Adrian, you’re just a man. The world’s smartest man poses no more threat to me than does its smartest termite.
“Watchmen” (2009)

Eddie Morra: I don’t have delusions of grandeur. I have an actual recipe for grandeur.
“Limitless” (2011)

Carl Van Loon: Have you been talking with anyone?
Eddie Morra: No, I haven’t been talking with anyone, Carl. I’m not stupid.
Carl Van Loon: I know you’re not stupid, Eddie, but don’t make the classic smart person’s mistake of thinking no one’s smarter than you.

“Limitless” (2011)

DIY’s newest frontier is algorithmic trading. Spurred on by their own curiosity and coached by hobbyist groups and online courses, thousands of day-trading tinkerers are writing up their own trading software and turning it loose on the markets. 

Interactive Brokers Group actively solicits at-home algorithmic traders with services to support their transactions. YouTube videos from traders and companies explaining the basics have tens of thousands of views. More than 170,000 people enrolled in a popular online course, “Computational Investing,” taught by Georgia Institute of Technology professor Tucker Balch. Only about 5% completed it.
Wall Street Journal, “Algorithmic Trading: The Play at Home Version” August 9, 2015

London day trader Navinder Sarao has been formally indicted by a U.S. federal grand jury on charges of market manipulation that prosecutors say helped contribute to the 2010 “flash crash,” according to a Sept. 2 court filing made public on Thursday. 

The Justice Department first announced criminal charges against Sarao in April and is seeking to have him extradited to the United States to stand trial. 

Sarao is accused of using an automated trading program to “spoof” markets by generating large sell orders that pushed down prices. He then canceled those trades and bought contracts at lower prices, prosecutors say.
CNBC, “US Federal Grand Jury Indicts ‘Flash Crash’ Trader” September 3, 2015

Anxiety in the industry surged last week after Li Yifei, the prominent China chief of the world’s largest publicly traded hedge fund, disappeared and Bloomberg News reported that she had been taken into custody to assist a police inquiry into market volatility. Her employer, the London-based Man Group, did little to dispel fears, declining to comment on her whereabouts. 

Ms. Li resurfaced on Sunday and denied that she had been detained, saying that she had been in “an industry meeting” and “meditating” at a Taoist retreat. But many in the finance sector are unconvinced.
New York Times, “China’s Response to Stock Plunge Rattles Traders” September 9, 2015

I’ve written several Epsilon Theory notes about modern market structure (“Season of the Glitch”, “Fear and Loathing on the Marketing Trail, 2014”, “The Adaptive Genius of Rigged Markets”, “Hollow Men, Hollow Markets, Hollow World”), all of which have been very well received. I’ve also written several Epsilon Theory notes about Big Data and non-human intelligences (“Troy Will Burn – the Big Deal about Big Data”, “First Known When Lost”, “Rise of the Machines”), all of which have generated a yawn. This divergence in reader reaction has puzzled me, because it seems so obvious to me that the issues are two sides of the same coin. So why can’t I communicate that?

It’s only over the last few days, after listening to old-school luminaries like Leon Cooperman and Dick Grasso rail against systematic investment strategies, index derivative hedging, and algorithmic market making as if they were the same thing (!) … it’s only after reading press stories that praise the US indictment of Navinder Sarao, the London trader who supposedly triggered the “Flash Crash” from his home computer, but condemn the Chinese detention of Man Group’s Li Yifei as if they were different things (!) … it’s only after seeing 500 commercials for “DIY trading platforms” on TV today as if this were a thing at all (!) … that I think I’ve finally figured this out.

We’re all Dr. Evil today, thinking that one million dollars is a lot of money, or that one second is a short period of time, or that we are individually smart or capable in a systemically interesting way. We use our small-number brains to make sense of an increasingly large-number investment world, and as a result both our market fears and our market dreams are increasingly out of touch with reality.

There are a million examples of this phenomenon I could use (including the phrase “a million examples” which, if true, would take me a lifetime to write and you a lifetime to read, even though neither you nor I considered the phrase in that literal context), but here’s a good one. A few months ago I wrote an Epsilon Theory note on the blurry distinction between luck and skill, titled “The Talented Mr. Ripley”, where I pointed out that it was now quite feasible with a few million dollars and a few months to build a perfect putting machine, one that would put every professional human golfer to shame. Judging from the reader emails I received on this, you might have thought I had just said that the world was flat and the sun was a big candle in the sky. “Preposterous!” was the gist of these emails – sometimes said nicely and sometimes (actually, most of the time) not so nicely – as apparently I know nothing about golf nor about the various failed efforts in the past to build a mechanical putting device.

Actually, I know a lot about these mechanical putting devices, and to compare them to the non-human putting intelligences that are constructible today is like comparing Lascaux cave art to HD television. It’s relatively child’s play to build a machine today that can identify and measure the impedance of every single blade of grass between a golf ball and the cup, one that measures elevation shifts of less than the width of an eyelash, one that applies force within an erg tolerance that human skin would interpret as the faintest breeze. That’s what I’m talking about. Do you know how the most advanced surreptitious listening devices, i.e. bugs, operate today? By measuring the vibrations in the glass window of the room where the conversation is taking place and translating those vibrations back into the sound waves that produced them. That’s what I’m talking about. Now replace “blades of grass” with “individual stock trades”. Now replace “conversation” with “investment strategy”. Arthur C. Clarke famously said that any sufficiently advanced technology is indistinguishable from magic. Do you really think we bring to bear less powerful magic in markets with trillions of dollars at stake than we do in spycraft and sports?

And let’s be clear, the machines are here to stay. They’re better at this than we are. The magic is in place because the magic works for the people and institutions that wield the magic, and no amount of rending of garments and gnashing of teeth by the old guard is going to change that. Sure, I can understand why Dick Grasso would suggest that we should go back to a pre-Reg NMS system of human specialists and cozy market making guilds, where trading spreads were measured in eighths and it made sense to pay the CEO of a non-profit exchange $140 million in “retirement benefits.” And I almost sympathize with the nostalgic remembrances of a long list of Hero Investors recently appearing on CNBC, pining for a pre-Reg FD system of entrenched management whispering in the ear of entrenched money managers, where upstart quants knew their place and the high priests of stock picking held undisputed sway. But it ain’t happening.

And let’s also be clear, the gulf between humans and machines is getting wider, not narrower. Even today, one of the popular myths associated with computer science is that non-human intelligences are brute force machines and inferior to humans at tasks like pattern recognition. In truth, a massively parallel processor cluster with in-line memory – something you can access today for less money than a junior analyst’s salary – is far better at pattern recognition than any human. And I mean “far better” in the same way that the sun is far better at electromagnetic radiation than a light bulb. Much has been made about how robot technologies are replacing low-end industrial and service jobs. Okay. Sure … I guess I’d be worried about that if I were working in a Foxconn factory or a Bay Area toll booth. But far more important for anyone reading this note is how non-human intelligences are replacing high-end pattern recognition jobs. Like trading. Or investing. Or asset allocation. Or advising.

The question is not how we “fix” markets by stuffing the technology genie back into the bottle and we somehow return to the halcyon days of yore where, in Lake Wobegon fashion, all of us were above average stock pickers and financial advisors. No, the question we need to ask ourselves is both a lot less heroic and far more realistic. How do we ADAPT to a market jungle where human intelligences are no longer the apex predator?

I’ve got two sets of suggestions, depending on whether you see yourself as a trader or an investor. It’s a lot to digest, so let’s look at traders in the balance of this week’s note and at investors next week.

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Every trader who ever lived believes that, like the Bradley Cooper character in “Limitless”, he or she has a recipe for grandeur. It doesn’t matter whether they find that recipe in prices or volumes or volatility or spreads or any other aspect of a security, all traders have an internalized pattern recognition system that they believe gives them a persistent edge. Most of them are wrong.

In modern large-number markets, any trading strategy based on naïve inference is certain to have zero edge, zero alpha. By naïve inference I mean selecting a strategy based solely on the econometric fit of a time series data matrix to some market outcome like price change. It’s a trading strategy that works because … it works. There’s no “why?” answered here, and as a result the strategy is certain to be derivative, non-robust, and quickly arbitraged. Or to put it in slightly different terms, whatever purely inductive trading strategy you think gives you an edge is already being used by thousands of non-human intelligences, and they’re using the strategy far more effectively than you are. To the degree a naïve inference strategy works at all, you’re just tagging along behind the non-human intelligences, picking up their crumbs.

What trading strategies have even a theoretical possibility of edge or alpha? Here are two.

Possibility 1: Find a market niche where your counterparties are non-economic or differently-economic market participants – like an oil futures market where a giant, lumbering integrated oilco seeks to hedge production, or where a sovereign wealth fund looks for inflation protection (Remember those happy days when giant allocators addressed inflation concerns in commodity markets? Me, neither.) – and scalp a few dimes by taking advantage of their very different preference functions. Traders who pursue this type of strategy have a name in biological systems. They’re called parasites. I call them beautiful parasites (see the Epsilon Theory note “Parasite Rex”), because they capture more pure alpha than any strategy I know.

Possibility 2: Find a market niche where you understand the impact of exogenous signals like news reports or policy statements on the behavioral tendencies of other human market participants, in exactly the same way that a good poker player “plays the player” as much as he plays the cards. These market niches tend to be sectors or assets that are driven less by fundamentals than they are by stories – think technology stocks rather than industrials – although here in the Golden Age of the Central Banker it’s hard to find any corner of the capital markets that’s not driven by policy and narrative. The game that these traders have internalized isn’t poker, of course, but is almost always some variant of what modern game theorists call “The Common Knowledge Game”, and what old-school game theorists like John Maynard Keynes called “The Newspaper Beauty Contest”.

What do these two examples of potentially alpha-generating trading strategies have in common? They operate in a world that a non-human intelligence – which is effectively a super-human inference machine – can’t figure out. Today’s effective alpha-generating trading strategies are based on a game (in the technical sense of the word, meaning a strategic interaction between humans where my decisions depend on your decisions, and vice versa) where you can have very different outcomes from one trade to another even if the external/measurable characteristics of the trades are identical. This is the hallmark of games with more than one equilibrium solution, which simply means that there are multiple stable outcomes of the game that can arise from a single matrix of descriptive data. It means that you can’t predict the outcome of a multi-equilibrium game just by knowing the externally visible attributes of the players. It means that the pattern of outcomes can’t be recognized with naïve (or sophisticated) inference techniques. It means that traders who successfully internalize the pattern recognition of strategic behaviors rather than the pattern recognition of time series data have a chance of not just surviving, but thriving in a market jungle niche.

Sigh. Look … I know that this note is going to fall on a lot of deaf ears. It’s an utterly un-heroic vision of what makes for a successful trader in a market dominated by non-human intelligences, as I’m basically saying that you should find some small tidal pool to crawl into rather than roam free like some majestic jungle cat. As such it flies in the face of every bit of heroic advertising that the industry spews forth ad nauseam every day, my personal fave being the “Type-E” commercials with Kevin Spacey shilling for E*Trade. Generalist traders are some of my favorite people in the world. They’re really smart. But they’re not smart enough. None of us are. After all, we’re only human.

epsilon-theory-one-million-dollars-september-15-2015-spacey

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Season of the Glitch

When I look over my shoulder
What do you think I see?
Some other cat lookin’ over
His shoulder at me.

Donovan, “Season of the Witch” (1966)

epsilon-theory-season-of-the-glitch-september-3-2015-blair-witch

Josh Leonard: I see why you like this video camera so much.
Heather Donahue: You do?
Josh Leonard: It’s not quite reality. It’s like a totally filtered reality. It’s like you can pretend everything’s not quite the way it is.

“The Blair Witch Project” (1999)

Over the past two months, more than 90 Wall Street Journal articles have used the word “glitch”. A few choice selections below:

Bank of New York Mellon Corp.’s chief executive warned clients that his firm wouldn’t be able to solve all pricing problems caused by a computer glitch before markets open Monday.

“BNY Mellon Races to Fix Pricing Glitches Before Markets Open Monday”, August 30, 2015

A computer glitch is preventing hundreds of mutual and exchange-traded funds from providing investors with the values of their holdings, complicating trading in some of the most widely held investments.

“A New Computer Glitch is Rocking the Mutual Fund Industry”, August 26, 2015

Bank says data loss was due to software glitch.

“Deutsche Bank Didn’t Archive Chats Used by Some Employees Tied to Libor Probe”, July 30, 2015

NYSE explanation confirms software glitch as cause, following initial fears of a cyberattack.

“NYSE Says Wednesday Outage Caused by Software Update”, July 10, 2015

Some TD Ameritrade Holding Corp. customers experienced delays in placing orders Friday morning due to a software glitch, the brokerage said..

“TD Ameritrade Experienced Order Routing, Messaging Problems”, July 10, 2015

Thousands of investors with stop-loss orders on their ETFs saw those positions crushed in the first 30 minutes of trading last Monday, August 24th. Seeing a price blow right through your stop is perhaps the worst experience in all of investing because it seems like such a betrayal. “Hey, isn’t this what a smart investor is supposed to do? What do you mean there was no liquidity at my stop? What do you mean I got filled $5 below my stop? Wait… now the price is back above my stop! Is this for real?”  Welcome to the Big Leagues of Investing Pain.

What happened last Monday morning, when Apple was down 11% and the VIX couldn’t be priced and the CNBC anchors looked like they were going to vomit, was not a glitch. Yes, a flawed SunGard pricing platform was part of the proximate cause, but the structural problem here – and the reason this sort of dislocation WILL happen again, soon and more severely – is that a vast crowd of market participants – let’s call them Investors – are making a classic mistake. It’s what a statistics professor would call a “category error”, and it’s a heartbreaker.

Moreover, there’s a slightly less vast crowd of market participants – let’s call them Market Makers and The Sell Side – who are only too happy to perpetuate and encourage this category error. Not for nothing, but Virtu and Volant and other HFT “liquidity providers” had their most profitable day last Monday since … well, since the Flash Crash of 2010. So if you’re a Market Maker or you’re on The Sell Side or you’re one of their media apologists, you call last week’s price dislocations a “glitch” and misdirect everyone’s attention to total red herrings like supposed forced liquidations of risk parity strategies. Wash, rinse, repeat.

The category error made by most Investors today, from your retired father-in-law to the largest sovereign wealth fund, is to confuse an allocation for an investment. If you treat an allocation like an investment… if you think about buying and selling an ETF in the same way that you think about buying and selling stock in a real-life company with real-life cash flows… you’re making the same mistake that currency traders made earlier this year with the Swiss Franc (read “Ghost in the Machine” for more). You’re making a category error, and one day – maybe last Monday or maybe next Monday – that mistake will come back to haunt you.

The simple fact is that there’s precious little investing in markets today – understood as buying a fractional ownership position in the real-life cash flows of a real-life company – a casualty of policy-driven markets where real-life fundamentals mean next to nothing for market returns. Instead, it’s all portfolio positioning, all allocation, all the time. But most Investors still maintain the pleasant illusion that what they’re doing is some form of stock-picking, some form of their traditional understanding of what it means to be an Investor. It’s the story they tell themselves and each other to get through the day, and the people who hold the media cameras and microphones are only too happy to perpetuate this particular form of filtered reality.

Now there’s absolutely nothing wrong with allocating rather than investing. In fact, as my partners Lee Partridge and Rusty Guinn never tire of saying, smart allocation is going to be responsible for the vast majority of public market portfolio returns over time for almost all investors. But that’s not the mythology that exists around markets. You don’t read Barron’s profiles about Great Allocators. No, you read about Great Investors, heroically making their stock-picking way in a sea of troubles. It’s 99% stochastics and probability distributions – really, it is – but since when did that make a myth less influential? So we gladly pay outrageous fees to the Great Investors who walk among us, even if most of us will never enjoy the outsized returns that won their reputations. So we search and search for the next Great Investor, even if the number of Great Investors in the world is exactly what enough random rolls of the dice would produce with Ordinary Investors. So we all aspire to be Great Investors, even if almost all of what we do – like buying an ETF – is allocating rather than investing.

The key letter in an ETF is the F. It’s a Fund, with exactly the same meaning of the word as applied to a mutual fund. It’s an allocation to a basket of securities with some sort of common attribute or factor that you want represented in your overall portfolio, not a fractional piece of an asset that you want to directly own. Yes, unlike a mutual fund you CAN buy and sell an ETF just like a single name stock, but that doesn’t mean you SHOULD. Like so many things in our modern world, the exchange traded nature of the ETF is a benefit for the few (Market Makers and The Sell Side) that has been sold falsely as a benefit for the many (Investors). It’s not a benefit for Investors. On the contrary, it’s a detriment. Investors who would never in a million years consider trading in and out of a mutual fund do it all the time with an exchange traded fund, and as a result their thoughtful ETF allocation becomes just another chip in the stock market casino. This isn’t a feature. It’s a bug.

What we saw last Monday morning was a specific manifestation of the behavioral fallacy of a category error, one that cost a lot of Investors a lot of money. Investors routinely put stop-loss orders on their ETFs. Why? Because… you know, this is what Great Investors do. They let their winners run and they limit their losses. Everyone knows this. It’s part of our accepted mythology, the Common Knowledge of investing. But here’s the truth. If you’re an Investor with a capital I (as opposed to a Trader with a capital T), there’s no good reason to put a stop-loss on an ETF or any other allocation instrument. I know. Crazy. And I’m sure I’ll get 100 irate unsubscribe notices from true-believing Investors for this heresy. So be it.

Think of it this way… what is the meaning of an allocation? Answer: it’s a return stream with a certain set of qualities that for whatever reason – maybe diversification, maybe sheer greed, maybe something else – you believe that your portfolio should possess. Now ask yourself this: what does price have to do with this meaning of an allocation? Answer: very little, at least in and of itself. Are those return stream qualities that you prize in your portfolio significantly altered just because the per-share price of a representation of this return stream is now just below some arbitrary price line that you set? Of course not. More generally, those return stream qualities can only be understood… should only be understood… in the context of what else is in your portfolio. I’m not saying that the price of this desired return stream means nothing. I’m saying that it means nothing in and of itself. An allocation has contingent meaning, not absolute meaning, and it should be evaluated on its relative merits, including price. There’s nothing contingent about a stop-loss order. It’s entirely specific to that security… I want it at this price and I don’t want it at that price, and that’s not the right way to think about an allocation.

One of my very first Epsilon Theory notes, “The Tao of Portfolio Management,” was on this distinction between investing (what I called stock-picking in that note) and allocation (what I called top-down portfolio construction), and the ecological fallacy that drives category errors and a whole host of other market mistakes. It wasn’t a particularly popular note then, and this note probably won’t be, either. But I think it’s one of the most important things I’ve got to say.

Why do I think it’s important? Because this category error goes way beyond whether or not you put stop-loss orders on ETFs. It enshrines myopic price considerations as the end-all and be-all for portfolio allocation decisions, and it accelerates the casino-fication of modern capital markets, both of which I think are absolute tragedies. For Investors, anyway. It’s a wash for Traders… just gives them a bigger playground. And it’s the gift that keeps on giving for Market Makers and The Sell Side.

Why do I think it’s important? Because there are so many Investors making this category error and they are going to continue to be, at best, scared out of their minds and, at worst, totally run over by the Traders who are dominating these casino games. This isn’t the time or the place to dive into gamma trading or volatility skew hedges or liquidity replenishment points. But let me say this. If you don’t already understand what, say, a gamma hedge is, then you have ZERO chance of successfully trading your portfolio in reaction to the daily “news”. You’re going to be whipsawed mercilessly by these Hollow Markets, especially now that the Fed and the PBOC are playing a giant game of Chicken and are no longer working in unison to pump up global asset prices.

One of the best pieces of advice I ever got as an Investor was to take what the market gives you. Right now the market isn’t giving us much, at least not the sort of stock-picking opportunities that most Investors want. Or think they want. That’s okay. This, too, shall pass. Eventually. Maybe. But what’s not okay is to confuse what the market IS giving us, which is the opportunity to make long-term portfolio allocation decisions, for the sort of active trading opportunity that fits our market mythology. It’s easy to confuse the two, particularly when there are powerful interests that profit from the confusion and the mythology. Market Makers and The Sell Side want to speed us up, both in the pace of our decision making and in the securities we use to implement those decisions, and if anything goes awry … well, it must have been a glitch. In truth, it’s time to slow down, both in our process and in the nature of the securities we buy and sell. And you might want to turn off the TV while you’re at it.

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