Whom Fortune Favors: Things that Matter #1, Pt. 1

President Camacho

Still, brave Turnus did not lose hope of seizing the shore first,
and driving the approaching enemy away from land.
And he raised his men’s spirits as well, and chided them:
‘What you asked for in prayer is here, to break through
with the sword. Mars himself empowers your hands, men!
Now let each remember his wife and home, now recall
the great actions, the glories of our fathers. And let’s
meet them in the waves, while they’re unsure and
their first steps falter as they land. Fortune favors the brave.’
So he spoke, and asked himself whom to lead in attack
and whom he could trust the siege of the walls.

— Virgil, The Aeneid, 10. 270-28

I had to take a verbal physical. A bunch of yes or no questions. But they were strangely worded, like, “Have you ever tried sugar… or PCP?”

— Mitch Hedberg

Imani: Am I not all you dreamed I would be?
Akeem: You’re fine. Beautiful! But if we’re going to be married, we should talk and get to know each other.
Imani: Ever since I was born, I have been trained to serve you.
Akeem: I know, but I’d like to know about you. What do you like to do?
Imani: Whatever you like.
Akeem: What kind of music do you like?
Imani: Whatever kind of music you like.
Akeem: I know what I like, and you know what I like, ’cause you were trained to know, but I would like to know what you like. Do you have a favorite food? Good! What is your favorite food?
Imani: Whatever food you like.
Akeem: This is impossible. I command you not to obey me.
— Coming to America (1988)

Natural selection, the process by which the strongest, the smartest, the fastest reproduced in greater number than the rest, a process which had once favored the noblest traits of man now began to favor different traits. While most science fiction of the day predicted a future that was more civilized and more intelligent, all signs indicated that the human race was heading in the opposite direction: a dumbing down. How did this happen? Evolution does not make moral judgments. Evolution does not necessarily reward that which is good or beautiful. It simply rewards those who reproduce the most.

— Opening Narration, Idiocracy (2006)

Lepidus: What manner o’ thing is your crocodile?
Antony: It is shap’d, sir, like itself, and it is as broad as it hath breadth; it is just as high as it is, and moves with its own organs. It lives by that which nourisheth it, and the elements once out of it, it transmigrates.
Lepidus: What colour is it of?
Antony: Of its own colour too.
Lepidus: ‘Tis a strange serpent.
Antony: ‘Tis so. And the tears of it are wet.
— William Shakespeare, Antony and Cleopatra, Act 2, Scene 7
He ended frowning, and his look denounc’d
Desperate revenge, and Battel dangerous
To less then Gods. On th’ other side up rose
Belial, in act more graceful and humane;
A fairer person lost not Heav’n; he seemd
For dignity compos’d and high exploit:
But all was false and hollow; though his Tongue
Dropt Manna, and could make the worse appear
The better reason, to perplex and dash
Maturest Counsels: for his thoughts were low;
To vice industrious, but to Nobler deeds
Timorous and slothful: yet he pleas’d the ear,
And with perswasive accent thus began.
— John Milton, Paradise Lost (1667)

For the whole earth is the tomb of famous men; not only are they commemorated by columns and inscriptions in their own country, but in foreign lands there dwells also an unwritten memorial of them, graven not on stone but in the hearts of men. Make them your examples, esteeming courage to be freedom and freedom to be happiness.

— Thucydides, Funeral Oration for Pericles

They don’t think it be like it is, but it do.

— Career journeyman Oscar Gamble, when asked about the New York Yankees clubhouse

The reality show president and the High King of Ireland

If you’ve seen the film, you know why it has become so fashionable to talk about Idiocracy’s prescience. If you haven’t, a brief synopsis: the film tells the story of humanity many years in the future. In this future, humans are very stupid. The biggest celebrity is the resilient star of a hit reality show about a man subjected to repeated groin injuries. Farmers water their fields with an electrolyte-laden sports drink since, after all, as the Brawndo company clearly states, “it’s got what plants crave.” Plus, with that kind of television programming available, it’s not like you’re going to have time to read debates among historians about whether Scipio Africanus truly ordered the salting of Carthaginian fields.

Well, all that and they elected a wrestling and adult film star as president.

Don’t worry. I’m not going where you think I’m going with this, although I will admit that even though I threatened to write in President Dwayne Elizondo Mountain Dew Herbert Camacho in two prior elections, when he actually appeared on the ballot I found it a bit more difficult to pull the lever.

So how did this happen (the movie plot, not Trump)? Well, the proximate cause proferred by the narrator is that all the smart, creative people saw overcrowding and a dangerous world and decided not to have kids. So it’s a gene pool argument. Underneath this purely genetic argument, however, lie truths about both evolution and social structures that form around and because of some of the trappings of genetics and lineage. From an evolutionary perspective, we are presented with the asymmetric potential of humanity that has solved most of its existential problems. If intelligence and creativity have little-to-no bearing on survival (more accurately, on a given human’s potential to procreate), what is the catalyst for the development of positive traits? Should procreation become associated with long-run maladaptive traits, however, the bigger issue becomes: how quickly do social power structures develop around and entrench those traits? How effectively do those structures prevent the emergence of adaptive traits when we need them again (e.g., knowing that you should probably just use water)?

You’re reading a note on a website long published with the header, “Politics trumps economics every time,” so I expect you won’t be surprised to learn that I think that over short periods of time, the pressure of the social structures is by far the stronger of these two dynamics. After all, the driving force behind the Idiocracy scenario is not entirely fictional. If you’ve participated in any sort of foray into genetic genealogy, you’ve seen the effect in action.

A few years back, a group of researchers from Trinity College Dublin identified that there was a strong relationship between certain genetic haplotypes and surnames that matched published lineages of a certain quasi-historical Irish king: the wonderfully named Niall of the Nine Hostages. Researchers found in subsequent testing of individuals with those surnames that many shared a mutation in their Y chromosome. At a location called 14902414 (don’t ask), where they expected to find guanine, which is what they’d find in researching any other human male they’d ever come across, they found adenine instead. We call this kind of mutation a “single nucleotide polymorphism.” These mutations are one of the most important ways we map the branching of lineages in male genetic history. Stable SNPs are passed down like a scar from generation to generation in a path-dependent chain.

Once this was discovered, we were off to the races in the usual ways. One of the largest DNA testing companies wasted no time in creating a special logo that was applied like “flair” to user accounts certifying them as a Descendant of Niall of the Nine Hostages! If you’re one of the few million men who would test positive for this mutation, you can still scrape a bit of your cheek into a vial, send it in and then download and print a certificate attesting to this, although they’ve softened the language somewhat. As always, lineage and genetics are far more complicated than they appear on the surface, and subsequent research made it clear that the mutation happened centuries before this man would have lived, probably in Cornwall and not Ireland, and included all sorts of other lineages as well.

Even if the specifics were a bit off, there was a kernel of truth in this mode of thinking: in general, rich people with swords who could afford food had more children that didn’t die early, and their children had more children who didn’t die early. In addition to really bad genealogical practices, this is why everyone you meet who has done any research into their family has found some super-famous king or viscount or third earl of something-somewhere from whom they’re descended. It’s also why when a particular common lineage seems to spring out of a place and time, we are drawn to the notion of the fecund king, whether it’s Niall or, say, Genghis Khan. A 13th century peasant farmer probably didn’t have healthy kids, and if he did he probably didn’t keep exquisite written records of them. But in the short run, evolution is a fickle, funny, random thing. Does the success of the line of someone like Niall mean that it had some significant, genetically heritable trait that made its members more likely to thrive? It’s possible, of course, and in many cases throughout history it is certainly true — evolution is a thing, after all — but over shorter horizons it is natural variation and randomness that dominate.

Yes, Niall himself may have successfully overcome his opponents because he was predisposed to carry more muscle mass and greater range of motion in his arms, and your 12th great-grandfather, the Marquis of Accepting Internet Strangers’ Shoddy Research, may have risen to his position from obscurity because of his stunning intellect. But power structures like nobility and primogeniture1 aren’t necessary to protect the remarkable. They are necessary to protect the weaker links in the chain that come as a result of even more remarkable genetic variation, and the resilience of the line over time is functionally the strength of the power structure that supports it — and must support it in order to endure such variation. In short, those power structures — the ideas of nobility, genetic superiority and divine right — are just narratives. Very, very strong ones.

1Or at least patrilineality. Unlike a lot of Germanic cultures, Irish (and later Scottish) traditions favored Tanistry, under which a sept could allow any male descendant of a chosen accepted ancestor to become the Tanist, the heir apparent. Often it was simply the King’s eldest son, but not always.

From the very beginning of Epsilon Theory — but reaching its zenith with When Does the Story Break — these pages and our thinking have focused on the almost-shocking resilience of the stories we tell ourselves and each other about markets and investing. In that piece, we placed the focus squarely on the inflection point: what does it look like when the narrative changes? When do gentlemen stop wearing the wigs they wore for 150 years? When and why do they stop wearing hats? When will we all stop knowing that we all know that markets are policy-controlled? When will Mike Judge’s future humanity accumulate enough negative results from maladaptive traits that marginally superior traits become relevant to reproduction again (so that we don’t die out as a result of malnourishment and repetitive concussive injuries to the groin)?

For such a narrative to break, our private knowledge — a collective state of understanding of something so agreed-upon as to be considered fact — must be influenced by new public knowledge. When it’s a pervasive idea, it resolves to a strong equilibrium, like the information surfaces we talked about in Through the Looking Glass. And it requires an awful lot of information for a narrative like this to break.

It’s true for High Kings of Ireland and it’s true for investing.

What manner o’thing is your manna

Let me tell you about an especially stupid investing idea that has managed to survive for a very long time.

Since we’ve covered dystopian fantasies, let’s imagine this stupid idea in context of something wonderful: let’s assume that we are 22 years old again, right out of college and talking to our first financial advisor about our 401(k) allocation. Now, it doesn’t matter if you’re a financial advisor yourself, an institutional allocator, an individual or a professional investor, you know what’s coming next. The book says 100% stocks. Maybe the home office dropped in some higher risk/return styles into their mean/variance model and so we probably get a dash of Chili P in the form of emerging markets and small caps too. All stocks, mostly U.S., with a bit more international, emerging markets and small cap than the average client. Sound about right?

Let’s unpack this advice. The financial advisor in this scenario is essentially telling his client the following:

I’m happy to inform you that the trillions of business decisions of billions of employees and managers of companies around the world, combined with the decisions of bankers who determined whether and how much to lend to those companies, the decisions of individuals who chose whether to buy or sell that company’s products, global weather phenomena, collective actions of terrorist groups, trillions of trading decisions made by computers and individuals alike on a microsecond-by-microsecond basis, the general pace of technological growth, the changing risk appetites of a dozen different classes of investors, the state of rule of law in various countries around the world, the changing policies of governments and central banks governing trade, commerce and financial markets, the current level of prices and valuations, and the way in which billions of individuals will perceive and estimate the outcomes of all of the above — that all these things together have conspired together to create an entity we call a stock, which, when taken in combination with a more or less arbitrarily determined number of other stocks and all of their differing characteristics, will create a stock market that just happens to have exactly the right amount of risk for you!

What a bunch of superstitious hogwash.

We treat asset classes like manna from heaven, preordained structures that were designed to meet our every need, in which the lowest-risk major asset class has just the right amount of risk for a retired person and the highest-risk major asset class is perfect for the most risk-seeking individual. The very idea pleases the ear because it asks little of us. You’ll eat your manna and like it! But be honest, can you think of anything else where the universe conspires so beautifully and elegantly to meet our needs?

Fortunately, at this point many investors at least pay lip service to the preeminence of asset allocation, but we often think of it in terms that commingle the types of risk we are taking and the amount of risk we take. We see this commingling — a thing we call asset classes, like broad definitions of stocks and bonds — as manna from heaven because we tend to inextricably link the concepts of asset classes with risk and return. We are trained by the investment industry to see our asset class decisions as a proxy for risk decisions. They aren’t, and the distinction matters.

It’s easy to get caught up in terminology and semantics here, so intead, think about the act of investing in its most fundamental sense. Strip away products, market conventions, regulation and structures like exchanges, even corporations. Investing is the act of using capital to buy an asset or pay expenses to support it. We invest so that we will either (1) produce income from the asset or (2) cause the asset to become more valuable in the eyes of other investors. In this sense we can think of our risk as the range of outcomes from (1) and (2) after considering the (3) nature of our claim on both. This is true for any investment.

What, then, is an asset class? Well, it’s a mostly sensible, if subjective, way to generalize how some investments are more like other investments. Asset classes define that similarity mostly in how their characteristics (1) and (2) above respond to the same stimuli. So ignoring that the right answer is, “because it’s just what we do”, why do we consider U.S. large cap stocks an asset class? Well, generally speaking, it should be because the things that cause risks to a company’s ability to generate earnings are pretty similar, and (rather self-prophesyingly) because the fact that it is considered an asset class influences how other investors are likely to respond similarly when they assess the value of all the other underlying constituents of the asset class.

In practice, however, the factors that influence the viability and the value of our claims on enterprises we invest in (i.e., companies, governments, properties, projects, etc.), and especially the magnitude of sensitivity to those factors, can be hugely variable within asset classes. TSLA and T theoretically have exposure to some of the same drivers of variability, but how much, really? Do people scale back their texting and phone plans during a recession? Eh, maybe. Do they stop buying $90,000 rolling batteries? Oh yeah. And yet, more often than not, investments like this move in sympathy. What is so fundamental about and shared within these asset classes that they can be aggregated like this? This is a critical thing to understand if you spend any time assessing risk or building portfolios:

The real reason that many investments behave like each other at all is that they are grouped into asset classes that most investors trade together.

It’s the sort of tautological, Schrodingeresque yarn that should be familiar to any Epsilon Theory reader: asset classes behave like asset classes because we treat them like asset classes. No matter how much we grouse about fundamentals not mattering, no matter how much we may wish this weren’t the case, it is. And it’s becoming truer as passive investing and indexing become more dominant. We may not think it be like it is, but it do.

If you find this dissatisfying, join the club. The cementing of this kind of mechanic is a big part of the hollow, petty, transactional, voodoo wasp-infested investing world we live in. I’m not asking you to pretend that it isn’t a thing. What I am asking you to do is consider whether it is right to anchor the way we think about portfolios and appropriate levels of risk for ourselves and our clients on the independent and recursively derived characteristics of “asset classes.”

In behavioral finance and cognitive psychology, this is a classic example of both the availability and anchoring heuristics. In the absence of a clear framework to assess how much risk we ought to take in our portfolios, we instead look at the continuum of risk/reward opportunities as expressed through these asset classes, whose risk characteristics are readily apparent — and available. We anchor on the “most risky” and “least risky” of those asset classes, and treat every individual as a relative or marginal analysis against those anchors. Thus, we arrive at all the variants of 60/40, 70/30 and 50/50 portfolios consisting of varying percentages of stocks and bonds. It’s a Coming to America conversation with every advisor: “How much risk is appropriate for a high-risk investor? Why, however much risk a broad market stock market index has.” “How much for a moderate risk investor? I don’t know, let’s add some bonds to whatever we just sold the last guy.”

The conflation of the types and amount of risk has other effects as well. A portfolio that is 80% bonds isn’t just less risky than a portfolio that is 80% stocks — it is also exposed to really different drivers of returns for what it holds. Thus, even in an asset class-conscious framework, the narrative holds. And it is a strong one.

Its missionaries take many forms: practitioners, econometricians, academics, and even regulators, who conduct all sorts of other analyses to support these conclusions. They anchor us to conventional definitions and groupings like asset classes, style boxes and the like, they take for granted assumptions (e.g., no leverage) that create massive bias in their conclusions, and they focus unerringly on improving utility theory to better understand what investors will do instead of identifying what they should do. In so doing they unwittingly conspire to force us into a set of investment options that reflect a sad mix of human behavioral tendencies, conclusions biased by massive abstractions and absurd faith in coincidences.

Have you ever tried sugar…or PCP?

I think it’s pretty unlikely this narrative goes anywhere any time soon. Its assumptions are too convenient, too perswasive, its conventions too embedded in product structure and regulation. Think Target Date funds, balanced funds and ’40 Act limitations. It’s also true that it can be pretty useful. As these pages have made clear, we have a pretty dim view of spending a lot of time sitting around talking stocks and we’re not in the business of wasting time on window dressing or fiddling. When we build portfolios, we use a lot of index-linked instruments — ETFs, futures, swaps — because they do a pretty good job of delivering many of the core sources of risk and return we want.

But believing in and using low-cost vehicles doesn’t require you to calibrate your whole framework of thinking around the characteristics of the indexes they track. So what is our framework? What will be robust to changing levels of risk and changing sentiment? What has a true north even when the drivers of asset classes are shifting? What allows us to answer something other than “Yes” or “No” when someone asks us whether we’ve ever tried sugar or PCP?

How much risk you take is probably the most important decision you will make as an investor. It is certainly the first decision you should make.

This is a deceptively simple point, but it matters. I am saying that before you spend a minute thinking about or designing an asset allocation, your complete focus should be on the quantity of risk you’re willing to take.

In some cases — decisions among similar asset classes — the risk decision is very obviously more important. This is most easily understood by example. Below we examine the risk and return of five different portfolios since January 2001 and rebalanced monthly:

  1. A portfolio invested 100% in the MSCI All Country World Index (“ACWI”)
  2. A portfolio invested 90% in ACWI and 10% in the S&P 500
  3. A portfolio invested 90% in ACWI and 10% in the MSCI Japan Index
  4. A portfolio invested 90% in ACWI and 10% in the MSCI Europe Index
  5. A portfolio invested 90% in ACWI and 10% in nothing (under a mattress)

Think of Portfolio 1 as our control. Portfolios 2, 3 and 4 represent — for the most part — an isolation of the “asset” dimension and an abstraction from risk. Portfolio 5 represents an isolation of the risk dimension. If we chose to overweight the U.S., Europe or Japan by 10% against a global market cap weighted index, the average difference in annualized return between the 10% overweight bets and the ACWI over this period was about 8 basis points. By contrast, taking off 10% of our risk took away about 30bp of return. Intuitively this is a function of the relative Sharpe ratios of various asset classes and how they differ, and so over different periods — such as ones in which the broad market was down — this analysis might have different signs. But over most of history and across most markets the magnitude, the importance of this decision, would be like what we show here.

Source: Salient Partners, L.P., as of 12/31/16. For illustrative purposes only. Past performance is no guarantee of future results. Certain performance information shown is compared to broad-based securities market indices. Broad-based securities indices are unmanaged and are not subject to fees and expenses typically associated with managed accounts or investment funds. Investments cannot be made directly in an index.

You could think about this in risk space as well. The volatility of the ACWI over this period was just under 16%, coincidentally not that far from what you would observe over many other long-term windows. In contrast, the volatility of the excess return between each individual market and the broad market — their tracking error — was always lower. On average using the U.S., Europe and Japan, the average tracking error is about 7.6%, less than half of the volatility of the market itself.

This analysis becomes a bit more convoluted if you’re comparing decisions across assets that tend to have very different amounts and types of risk — say, U.S. large caps and Treasurys. If we were able to achieve a similar level of risk from government debt, we’d see that the impact of the different types of risk becomes as significant as the risk decision itself. But even in this case, to get to a place where we are thinking in those terms, quantity of risk is our starting place. How much you own usually matters more than what you own.

For many investors, this is counterintuitive. It presents a strong contrast to the way in which many investors have taken advice from people like Peter Lynch and Warren Buffett, whose letters and books highlight the extent to which focusing on simple businesses they can understand or can “sketch with a crayon” has led to their own success. Much to Mr. Lynch’s dismay, for example, investors have often understood this to mean buying Procter & Gamble stock because they personally use a lot of Crest toothpaste and feel strongly that it’s a superior product to Colgate. I would extend this to include even the more sensible-sounding notion that a senior IT professional has some edge that should allow him to successfully manage a JNPR/CSCO pairs trade. Please.

Buffett and some others are probably an exception to our rule of thumb here, although only marginally so. Not because of his talent, but because of his extreme concentration. The idiosyncratic characteristics of the portfolio of companies in which he chooses to invest may sometimes be more different from those of other companies than the difference between holding the portfolio and holding cash. But that level of concentration is so extraordinarily rare among investors that I think it’s probably approximately correct to consider it irrelevant for our discussion.

So what am I saying to the “quality” and “buy what you know” investors? I am saying that unless you have a portfolio that is very concentrated in individual securities — by which I mean that more than 6 or 7% of your total net worth or investable assets are invested in an average stock or bond position — if you think that the unique characteristics of what you own are going to drive your success more than how much market risk you’re taking, you are wrong.

Measurement will be important as we walk down this road, but I don’t have a lot of interest in spilling more ink/electrons debating the best way to measure risk. We’ll get into it more in Part 2, but regardless of what measure for risk we choose, by and large, how much exposure we have to financial market risk will have more impact on our portfolio results than any other factor.

Primum non nocere

What does all this mean for the code-driven investor?

It means that anything lower in the priority must be considered in context of its impact on risk. This seems intuitive, but is extremely poorly understood. Take a look at this article from the world’s leading newspaper covering financial markets. Without tongue firmly planted in cheek, this author undertakes to compare hedge fund returns to private equity returns as part of explaining why private equity funds are raising so much more money. This is really stupid.

The first reason it is stupid is because the comparison is terrible. Most private equity — large buyout funds, anyway — is just levered stocks with high fees and a PM who calls himself a “deal guy” and wears Brioni instead of your long-only guy’s Brooks Brothers. It’s the exact same type of risk as mid-cap equities, and if it were in a constantly marked structure, it would demonstrate more risk than your average mid-cap equity benchmark. Not to be too on-the-nose about this, but hedge funds are usually hedged. Most try to avoid equity sources of risk, and almost universally avoid taking as much risk as traditional strategies. Evaluating and comparing absolute returns of these two assets because they’re both “alternatives” is like the guy with the butter-laden tomahawk ribeye gloating when I order the petit filet. Yes, we all saw the 26-ounce steak on the menu, guy.

The second and more disquieting reason it is stupid is because it’s kind of true. People and funds really are making this exact decision: to sell their hedge funds to fund private equity. At other times (usually after PE disappoints) they do the opposite. But I see decisions like this all the time. I see advisors trying to improve a client’s yield by swapping stocks for high yield. Selling their equity index fund to go into an unlevered low volatility equity fund. I see them going to cash because U.S. stocks feel expensive. I see them rotating from market-neutral hedge funds to high volatility CTAs and managed futures funds, or visa versa.  There are always good decisions why we don’t like Asset X and maybe some good reasons why we like Asset Y. But because our frameworks often don’t first think about the baseline expectations for risk and return for these assets, these decisions often fall victim to the pitfalls we highlighted in And They Did Live by Watchfires, where our temptation to tweak leads us to make small changes that have big unintended consequences. In a huge majority of cases, risk differences between assets will dominate the expected edge we have on views of the relative attractiveness of different types of return. More on this to come.

The other implication — and chief benefit — of starting the portfolio construction process with a risk target is that it frees us from the anchoring biases of a framework that begins from the arbitrarily determined characteristics of asset classes. That does place some onus on us to develop a view of the right amount of risk to take, of course. And while some of the techniques for developing such a view are standard fare, they also usually either revert to boundary constraints driven by asset classes and vehicles, or else focus on an exercise where the expected portfolio return just meets a return target or theoretically minimizes the probability of not reaching some horrifying outcome.

So, while I believe that your quantity of risk is the most important decision you can make, I can’t tell you how much risk you can tolerate. I can, however, generalize what I know many professional investors do in their personal portfolios:

  1. They take a lot more risk than you.
  2. They concentrate a lot more than you.
  3. The fact that they offer lower-risk products reflects their assessment of business risk, not investment merits.
  4. Tail risk becomes a much bigger consideration as we do more of #1 and #2.

I’ll be the first to say that the notion of “smart money” is mostly a myth, but there’s a reason why your fund managers behave like this. The notion that bonds are manna for conservative investors turns out to be just about right. Go figure. The idea that equities are manna for risk-seeking investors turns out to be pretty far off. For those of us in the risk-seeking camp, we need to start over on the question of the right amount of risk to take. For that, you’ll have to wait for Part 2.

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Break the Wheel: Things that Don’t Matter #3

Daenerys and Tyrion

King George III:

They say George Washington’s yielding his power and stepping away
Is that true?
I wasn’t aware that was something a person could do.
I’m perplexed.
Are they gonna keep on replacing whoever’s in charge?
If so, who’s next?
There’s nobody else in their country who looms quite as large…

― “Who’s Next”, Hamilton (2015)

Sean Maguire: Hey, Gerry, In the 1960s there was a young man that graduated from the University of Michigan. Did some brilliant work in mathematics. Specifically bounded harmonic functions. Then he went on to Berkeley. He was assistant professor. Showed amazing potential. Then he moved to Montana, and blew the competition away.
Gerry Lambeau: Yeah, so who was he?
Sean: Ted Kaczynski.
Gerry: Haven’t heard of him.
Sean: [yelling to the bartender] Hey, Timmy!
Timmy: Yo.
Sean: Who’s Ted Kaczynski?
Timmy: Unabomber.
 Good Will Hunting (1997)

Chef: Oh Lord have mercy. Children, children! No no, you’ve got it all wrong. Don’t you see, children? You have the heart, but you don’t have the soul. No, no. Wait. You have the soul, but you don’t have the heart. No, no. Scratch that. You have the heart and the soul, but you don’t have the talent.

South Park, Season 8, Episode 4

Horatio: O day and night, but this is wondrous strange!
Hamlet: And therefore as a stranger give it welcome.
There are more things in heaven and earth, Horatio,
Than are dreamt of in your philosophy.
 Hamlet, Act 1, Scene 5    

Daenerys Targaryen: Lannister, Targaryen, Baratheon, Stark, Tyrell — they’re all just spokes on a wheel. This one’s on top, then that one’s on top and on and on it spins crushing those on the ground.
Tyrion Lannister: It’s a beautiful dream, stopping the wheel. You’re not the first person who’s ever dreamt it.
Daenerys: I’m not going to stop the wheel, I’m going to break the wheel.
 Game of Thrones, Season 5, Episode 8 (2015)

The King is Dead

Some six centuries ago, European monarchies adopted the practice of declaring, “The King is dead! Long live the King!” upon the death of a monarch. In films and other adaptations, we usually get only the latter half of the expression, but there is clever intent buried in the repetition: there is to be no interregnum. When the old king dies, the new king immediately ascends with all his power and majesty, and probably most of his enemies as well. It is an instantaneous change not only in the power structure of a nation, but also in the mindset of any number of subjects, who have little time to lament the amount of time and effort they had spent fawning over and currying favor with the old king. They have to reset immediately: I’m sure this king will be better, much wiser, much less murderry. That sort of thing.

Our human nature helps us adapt. As Ben has pointed out numerous times, we want to believe.

We want to believe that this king will be different, and we’re usually instantly willing to reup on our social contract with him, giving up inalienable rights for the benefit of his wisdom and authority (or something). We want to believe that President Trump will be different, that he will finally turn over the tables in the Capitol and chase corrupt, conflicted, five-term congressmen into the reflecting pool with a whip. We want to believe that this time a friend/partner/spouse is done lying/cheating/hurting us. We do all this despite every bit of evidence telling us that what we believe is so unlikely as to be unworthy of mention.

And my goodness, we want to believe that the guy running this fund is going to be loads better than that idiot we just fired.

Sure, we’ve read Murder on the Orient Express, Charlie Ellis’s brilliant 2012 FAJ submission highlighting just how badly institutions pick funds and how badly they time it. We’ve seen the statistics. We’ve seen our own P&L and those of people we think highly of. More often than not, it doesn’t matter because we want to believe. In many cases because picking these funds is our job, we have to believe.

Epsilon Theory readers, my kids eat because I’m a fund manager. Mostly hot dogs and Kraft macaroni & cheese, but they eat. So it pains me to tell you that the amount of time, personnel and attention we all spend picking, talking to, debating and stressing over fund managers is ridiculous. This is why picking fund managers comes in at #3 on our list of Things that Don’t Matter.

So why doesn’t it matter?

Because just about all of us suck at it.

I’m being a bit hyperbolic. But only a little bit.

Earlier this month, Cliff Asness from AQR wrote a beautiful rant directed mostly at Rob Arnott from Research Affiliates and maybe a bit at the fine folks over at Bloomberg. No, it wasn’t a charming comparison of their luxuriant grey beards, but a debate about claims of data mining. Arnott and the story maybe not-so-indirectly imply that Cliff and AQR are insufficiently critical of data mining techniques among fund managers, to which Cliff offered his…uh…rather pointed rejoinder.

For the record, Cliff’s right on this one. I have either been a client or competitor of AQR/AMG in every year of my career, and there’s not a firm in the world that more rigorously — maybe even rigidly, at times — applies the scientific method to investing. (Hell, if I’m telling you to stop focusing on picking fund managers, I might as well pitch you on a competitor while I’m at it.)

So what’s Arnott’s beef? A legitimate one, even if AQR is about as far as you can get from being guilty of it. The idea is that a lot of fund managers out there, especially some of those of the quantitative or quantamental (ugh) persuasion, are engaging in shoddy, non-scientific research.

Properly implemented, the scientific method is a deductive process in which a researcher starts from a question he wishes to answer, forms a hypothesis around that question and then deductively produces predictions that he tests in order to validate (fine, “not reject”) the hypothesis and its related or subsequent predictions.

The very fair criticism of data mining is that it works in reverse, and in doing so, doesn’t work at all: it starts with the testing and ends with the hypothesis and predictions. This practice, whether consciously or unconsciously applied, is a big part of the replication crisis in academia and the poor performance of investment strategies that don’t bear out their backtests.

Data mining was one of the earliest forms of scientification — putting scientific terms, a systematic-seeming process and a presentation with a bunch of PhDs around a framework that is… well… bullshit. This trend is something we have talked about a lot on Epsilon Theory podcasts. From “Fact Checking”, to dumb ideas from brilliant men like Tyson’s “Rationalia”, to the fallacy-laden idea that opposition to specific policies directed at climate change as ineffectual constitutes disbelief in the fundamental science, scientification is on the rise. We are right to worry about this with our fund managers.

But here’s the real problem: as allocators, we are way, way worse. Just about every manager selection process I’ve ever seen, and some that I have even designed, are plagued by data mining and non-deductive reasoning.

The examples are many, and in almost every case they demonstrate explicit data mining. Now, usually they do so with some small modification to make it look less blatant — you know, since we’ve all read enough to at least want to not look like we’re just hiring the manager with the best performance. I’ve seen all sorts of these kinds of second-derivative screens, which are the allocator’s version of the payday lender setting rates by zip code and pretending they’re not preying on a particular demographic (zip codes are just numbers!). Instead of looking for top quartile managers, we’re looking for the ones with the best downside capture ratios. The best batting average. The best Sortino. The best Jensen’s alpha. The best residual alpha from our proprietary multi-factor model. Or my favorite, looking for good long-term performance and patting ourselves on the back about ignoring poor short-term alpha. Unfortunately, manager alpha — like many sources of returns — tends to mean-revert over longer periods (>3 years) and continues to trend over shorter ones (<1 year).

It isn’t that I’m taking special issue with any one of these metrics or the many tools allocators use to build portfolios. In fact, many of these are exactly the type of tools that I have used and continue to use in portfolio construction, since the general character and correlations of excess returns can be persistent over time. But I am taking issue with their use in selecting and predicting ex ante the existence of some quantity of alpha, for which they are all mostly useless. As an industry we embrace this pretense that “Manager A has alpha” is a valid hypothesis, and that by pursuing various types of analysis of returns we are somehow scientifically testing that hypothesis.

No, no, no! That’s not how this works. That’s not how any of this works.

Source: xkcd.com.

To start with a hypothesis that Manager A has alpha is begging the question in the extreme. This is equally true if we’re approaching it from the more strictly scientific “null hypothesis” construction. There is no economic or market-related intuition underlying the theory. If we start with the same premise for every manager (i.e., whether he has alpha) and analyze the returns, whether quantitatively or qualitatively, to reject or not reject the hypothesis, we are not doing scientific research. We are data mining and putting a scientific dress on it. And when our experience doesn’t match the research, we almost always come up with the same reason for firing them: they deviated from their process.

It’s a self-preservation thing, of course. We weren’t wrong. The manager just changed! He deviated from his process! Firm disruption! How could I have known?

In most cases, we probably couldn’t. We have a lot of fun on the Epsilon Theory podcast at the expense of the low replication rates of much of the research that happens across many fields right now, but those rates have nothing on the horror show that is financial markets research. (I say that, but the University of Wisconsin did accept a dissertation that was “an autoethnographic study of used-kimono-wearing as experienced by a folklorist… after inheriting a piece that had belonged to her grandmother.” Replicate that!)

Even well-defended factors and return drivers are often not robust to modest changes in methodology, shifts in in-sample vs. out-of-sample periods and the like. If those findings, which can be tested across millions of data points across companies, markets and decades, lack robustness, how much more challenged are we in trying to scientifically and mathematically uncover who is a good manager and who is a bad one?

It’s no wonder that this process finds so many of us — financial advisors, institutional allocators and individual investors alike — repeating that old refrain again. My process was good. This manager deviated from their process. This new one will be better. The king is dead. Long live the king.

Spokes on a wheel, friends. Kings that are on top until they’re not. We’ve all tried to stop the wheel. How do we break the wheel?

A Return to Real Deduction

The first step is recognizing that a deductive process must start from real economic intuition. What does real economic intuition look like?

A theoretical belief about why you should be paid for investing in something.

This is true and rather well-accepted with respect to market exposure. Most of us have a pretty good idea why we get paid for owning stocks. We’re exposing ourselves to economic uncertainty, political systems and credit markets, inflation and all sorts of other subsidiary risks. Concluding that accepting these risks ought to earn a return is something I think most investors understand fairly intuitively. Most of us — although clearly fewer than with stocks — have a good sense of why we ought to be paid for holding bonds. Commodities? Less clear. (Something-something-backwardation, something-something-storage-premium.)

Rather than starting from returns and working backward, our goal should be to develop this kind of intuition for why we ought to get paid for the active risk our fund managers are taking. In a perfect world, before we ran a single screen, before we looked at a single slide deck, before we looked at a single performance number, we would sit down — like we’re doing here with this Code — and map out the things we believe we will or might be paid for.

Where do we start? Let’s walk down a simplified road from economic intuition through deductive reasoning to a familiar hypothesis in the illustration below.

Deductive Process for Identifying a Potentially Valid Strategy

Source: Salient Partners, L.P., as of 04/21/17. For illustrative purposes only.

The economic intuition on the right should be familiar if you’re an Epsilon Theory reader. The deductions on each of the left and right side should look familiar if you’re a rabid Epsilon Theory reader, since they showed up as the two basic ways in which a stock-picker could outperform in “What a Good-Looking Question.” The hypothesis on the bottom right should be the most familiar of all: we’re basically conjecturing that buying cheap stuff works. Not our bit, but a good one!

Inserting economic intuition into those two deductions alone should get us a few dozen hypotheses. There truly are more things in heaven and earth that most of us are willing to dream in our returns analysis-oriented philosophy. Some of those should be well-worn and familiar, like value. Some may be more unique. Many will be flawed and — hopefully — dismissed before we do anything stupid with them.

Frankly and rather unfortunately, your only ability to test many of your hypotheses about fund managers is often going to be through qualitative mechanisms and through live experience. That doesn’t mean you can’t be scientific in your approach. In a perfect world you’d be able to approach a manager without knowing a lick about their performance, have an intellectual conversation about what it is that they do to make money, determine whether it lines up with one of the theoretical ways you think it may be possible to do so, and then evaluate their performance to see if it corroborates that. That’s in a perfect world.

But in an imperfect world, one of the main reasons obsessing over fund managers is one of the Things that Don’t Matter is that almost all practitioners shuffle through dozens of approaches to selecting funds. And almost all those approaches are variants of historical return analysis, or represent historical returns analysis in guise. There’s only one way out of this, and it may be an uncomfortable one:

We’ve got to stop using historical returns analysis for anything other than portfolio fit. Not use it less. Not use it smarter. Those are attempts to stop the wheel. We’ve got to break the wheel.

If we’re going to break the wheel, we must have a robust concept of the sources of return we’re willing to believe in, that we’re willing to develop a hypothesis around. We’ve also got to develop comfort with interview and evaluation techniques that go beyond asking about stocks. If our diligence process is not capable of identifying whether the manager can access that source of return that we believe in, then we have to change our process. We must change the questions we ask.

It’s easier to understand this for systematic managers because they fit neatly into a more behaviorally driven, scientific mindset. Figuring out that we believe in value and that a manager is accessing value credibly isn’t exactly rocket science. So let’s instead consider what is probably the most ubiquitous, hardest-to-crack example: the fundamental long/short equity manager. The stock picker. Assume you haven’t seen their returns (hah!). You’ve got an hour to figure out if they’re going to fit into a working archetype, if there’s a hypothesis to be drawn here. What do you do?

Here’s what you don’t do: you don’t let them walk through their deck. You don’t quiz them about their companies to see how intelligent or knowledgeable they are. They’re all going to be smart. The Unabomber was smart. In most cases, you probably don’t even let them talk about their overall investment philosophy, because they’re going to do it on their terms. Don’t look them in the eyes and pretend you’re going to be able to out them as someone who’s going to screw you over. It’s not possible. Instead, ask three questions:

  • How do you make money? Why should you outperform the market?
  • Ignore the first part of their response. Feel free to hum your favorite song from the Hamilton soundtrack in your head (Cabinet Battle #2, obviously), and when they finally get to the part where they say “mumble… mumble… rigorous bottom-up research…”, you’re back on! Interrupt them and say, “Yes, but why? Why are you and your team better at spotting things that the market misses?”
  • Let’s assume you’re right about all that. How do you get comfortable that it will work for the stock?

Then, and only then can we violate Things that Don’t Matter #2 and dive into a case study. Don’t let them tell you a stock story. Don’t let them give you the thesis. Not that there’s anything wrong with having a thesis (They should! They must!), but that’s the language of their process. Instead, take a position in the portfolio, and ask them how the position fits with their answers. How did you think you would make money on the stock? Was that a differentiated view? Why are you confident that your team is better at analyzing that characteristic of this company than the other 1,000,000 investors covering it? And how did you get comfortable that this thing you found would actually make the stock work, that it would influence the people who actually have to change the price of the stock by buying and selling?

And all this is not to prove a hypothesis, but to arrive at one in the first place. You see, none of this solves the problem that we all face as allocators to funds: there is almost never enough data to come to a firm statistical conclusion about whether a strategy is likely to outperform. For those of you — financial advisors and individuals, in particular — who must select funds without the benefit of meeting the people managing the funds, you are often even more hamstrung, since you are constrained to whatever information they are willing to provide you about their process and strategy. Sometimes it is possible to glean from the marketing materials whether there may be an alpha generative process buried in there, and sometimes it is not.

If we approach investing deductively, however, we at least have a chance of focusing on the few things that do matter, like whether the fund manager is doing any of the things that even have a chance of outperforming. Is this more deductive approach to fund selection enough? Is it worth it?

Sometimes. But in most cases, sadly, probably not.

I still need to buy 16 years’ worth of hot dogs and Kraft dinner, but I’ll level with you. In most cases, whether you pick this fund or that fund is not even going to register in comparison to the decisions you make about risk, asset allocation and diversification.

The stock example from “What a Good-Looking Question” is instructive here as well, and in an even more exaggerated way than for stocks themselves. While a 5% tracking error stock portfolio is not rare, a portfolio of multiple actively managed funds with that level of tracking error is exceedingly rare. If you are hiring three, four or more mutual funds, ETFs or other portfolios within an asset class like, say, U.S. stocks or emerging markets stocks, the odds in my experience are very strong that your tracking error is probably closer to 2-3%. The amount of risk coming from your managers’ active bets is probably less than 5%.

Source: Salient Partners, L.P., as of 04/21/17. For illustrative purposes only.

In all fairness, some of this is the point of active management. Part of the reason that these numbers are so low in this hypothetical example is that “alpha” in this example is, by definition, uncorrelated to the market exposure. But remember our other lesson from “I Am Spartacus” — the tracking error of our fund managers is rarely dominated by uncorrelated sources of alpha, but comes more typically from the static biases managers have toward structural sources of risk and return.

You could make the argument that the incremental return is worth the effort, especially in an environment where returns to capital markets are likely to be muted. And that’s a reasonable argument. But it’s all a question of degree. Is that source of return, challenging as it is to find, elusive as it has proven, worth the resources, time and focus it receives in our conversations with our constituents? Our investment committees? Our boards? Our clients?

So why bother at all? This is just an argument to go passive, right?

Oh, God, no!

First, as you all know by now, we are all active investors because we all make active decisions on the most important dimensions of portfolio construction: risk, asset class composition and secondary objectives like income. But more importantly, this is a universal issue. Those of us who use passive strategies for some of our portfolios — which is probably all of us at this point — have as much to gain from this advice as any other. Just two weeks ago, I made a minor point at a dinner about how S&P futures exposure was actually cheaper than ETFs and ended up getting bogged down in a serious 10-15 minute discussion on the topic. You’ve probably observed similar discussions over which low-cost ETF or passive mutual fund is the best way to access this market or that. This obsession really does transcend party lines on the ridiculous active vs. passive bike shed debate.

Neither should this be seen as a repudiation of active management at all. Again, investors should often be working with fund managers and advisors that do things that fall under the umbrella of active management. It does make sense to exploit behavioral sources of return. It does make sense to identify the very rare examples of information asymmetry. It does make sense to pursue active strategies in markets where the passive alternatives are poor or structurally biased themselves. It does make sense to consider market structure and the extent to which forced buyers and sellers create long-term pricing opportunities. It does make sense to pursue cost-effective active approaches that deliver characteristics (risk, yield, tax benefits) that would otherwise be part of the asset allocation process.

But in pursuing those, this code would advise you of the following:

  • Be judicious in the time and resources devoted to this exercise vs. the big questions, the Things that Matter.
  • Eschew the use of backward-looking return analysis. Really avoid it as much as humanly possible until you are testing a legitimate, deductive hypothesis about why you think a fund manager might be able to add value.
  • Apply a deductive process to everything you do.

After all, a code would not be a code at all unless we intended to pursue it with intellectual honesty. Most of the industry’s experience selecting fund managers has relied on rather less rigorous standards. And so it goes that Picking Funds is #3 on our list of Things that Don’t Matter.

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What a Good-Looking Question: Things that Don’t Matter #2

Peter Griffin buys a tank.

Peter Griffin: What can you tell me about this one?

Car Salesman: Oh, that’s just an old tank I use for those commercials where I declare war on high prices. Now about that sedan…

Peter Griffin: Hang on there, slick. Now I see your game. We come in here wanting a practical car, but then you dangle this tank in front of me and expect me to walk away. Now, I may be an idiot, but there is one thing I am not, sir, and that, sir, is an idiot. Now, I demand you tell me more about this tank!

Car Salesman: Well, if you’re looking for quality, then look no further.

Peter: That’s more like it! Tell me, what are the tank’s safety features?

Car Salesman: What a good-looking question. Three inches of reinforced steel protects your daughter from short-range missile attacks.

Peter: I see. And does the sedan protect against missiles?

Car Salesman: It does not.

Family Guy, Season 5, Episode 3, “Hell Comes to Quahog”

There was an unclouded fountain, with silver-bright water, which neither shepherds nor goats grazing the hills, nor other flocks, touched, that no animal or bird disturbed not even a branch falling from a tree. Grass was around it, fed by the moisture nearby, and a grove of trees that prevented the sun from warming the place. Here, the boy, tired by the heat and his enthusiasm for the chase, lies down, drawn to it by its look and by the fountain. While he desires to quench his thirst, a different thirst is created. While he drinks he is seized by the vision of his reflected form. He loves a bodiless dream. He thinks that a body, that is only a shadow. He is astonished by himself, and hangs there motionless, with a fixed expression, like a statue carved from Parian marble.

Flat on the ground, he contemplates two stars, his eyes, and his hair, fit for Bacchus, fit for Apollo, his youthful cheeks and ivory neck, the beauty of his face, the rose-flush mingled in the whiteness of snow, admiring everything for which he is himself admired. Unknowingly he desires himself, and the one who praises is himself praised, and, while he courts, is courted, so that, equally, he inflames and burns. How often he gave his lips in vain to the deceptive pool, how often, trying to embrace the neck he could see, he plunged his arms into the water, but could not catch himself within them! What he has seen he does not understand, but what he sees he is on fire for, and the same error both seduces and deceives his eyes.
― Ovid, Metamorphoses, Book III

Brian: Look, you’ve got it all wrong! You don’t need to follow me. You’ve got to think for yourselves! You’re all individuals!

Crowd: Yes! We’re all individuals!

Brian: You’re all different!

Crowd: Yes! We’re all different!

Man: I’m not.

Crowd: Shhh!

Life of Brian (1979)

There may be members of the committee who might fail to distinguish between asbestos and galvanized iron, but every man there knows about coffee — what it is, how it should be made, where it should be bought — and whether indeed it should be bought at all. This item on the agenda will occupy the members for an hour and a quarter, and they will end by asking the Secretary to procure further information, leaving the matter to be decided at the next meeting.

― C. Northcote Parkinson, Parkinson’s Law: Or the Pursuit of Progress

One of our portfolio managers at Salient started his career working the desk at a retail branch of a large financial services firm in Braintree, Massachusetts. He likes to tell the story of “Danny from Quincy” (pronounced Qwin’-zee). Danny is a rabid Boston sports fan who frequently called in to a local sports talk radio show. Your mind may have already conjured an image of our protagonist, but for the uninitiated, American sports talk radio is community theatre at its most bizarre (and entertaining), its callers a parade of exaggerated regional accents shouting really awful things at no one in particular. Local sports talk radio is even more of an oddity, since on the clear fundamental question, that is, which team everyone supports, practically all parties involved agree.

Lest Bostonians feel singled out, this phenomenon is infinitely transferable. In Buffalo, Pittsburgh, Chicago, Kansas City and Oakland, it is much the same. In each, the listener can expect the same level of anger, whether it is shouting about things everyone listening agrees on, like the ‘fact’ that the NFL has always preferred Peyton Manning to Tom Brady and that Deflategate just boiled down to jealousy, or relatively petty items of disagreement, like the ‘fact’ that Belichick reached on a player in the draft who would have been available in the 4th or 5th rounds when what they really needed was help at defensive back.

When Danny from Quincy wandered into our colleague’s Braintree branch, Danny’s voice was distinctive enough that he was immediately recognized. From their conversation, it was clear that this happened to Danny all the time. Here was a local celebrity minted by nothing other than the fact that he could shout agreed-upon concepts at the loudest possible volume and with proper non-rhotic diction.

It is hardly a novel observation that disputes among those who agree on the most critical questions and disagree on details are often among the most violent. After all, more died in the disputes between French Catholics and Huguenots alone than in all three of the Crusades. And it took twice as long for John Lennon and Paul McCartney to get in a recording studio together after the Yoko Ono Experience than it took for King George III to receive John Adams as ambassador after the Treaty of Paris. As investors, however, we have turned this seemingly normal human behavior into an art form.

There are all sorts of social and psychological reasons why we so enjoy wallowing in issues of lesser import with those with whom we otherwise largely agree. One of the main reasons is that big, important issues — the ones that divide us into broad groups — tend to be either issues outside of our control, or complex and more difficult to understand. By contrast, the smaller, less important issues are more likely to be understood by a wider range of people. Or at least they are more familiar.

In 1957, C. Northcote Parkinson’s eponymously titled book Parkinson’s Law: Or the Pursuit of Progress dubbed this phenomenon the Law of Triviality. In referencing the work of a finance committee, it concluded that “…the time spent on any item of the agenda will be in inverse proportion to the sum involved.” In other words, the more trivial something is, the more time we are likely to spend discussing it.

In his book, Parkinson dramatically reenacts the three agenda items before a finance committee: a $10 million nuclear reactor, a $2,350 bicycle shed and a $57 annual committee meeting refreshment budget. As you might expect, the details of a plan to build a nuclear reactor would fall well outside the abilities of even sophisticated committees, and even for those members with some sophistication, the task of bringing legitimate concerns or questions before an otherwise unknowledgeable group is daunting. In Parkinson’s example, the knowledgeable Mr. Brickworth considers commenting on the item but “…does not know where to begin. The other members could not read the blueprint if he referred to it. He would have to begin by explaining what a reactor is and no one there would admit that he did not already know.” He concludes that it is “better to say nothing.”

The item passes after two and a half minutes of discussion.

The next item before the committee is the discussion of a committee to build a bicycle shed for clerical staff. The discussion includes a range of topics, from cost to necessity to the choice of construction materials. As Parkinson puts it, “A sum of $2,350 is well within everybody’s comprehension. Everyone can visualize a bicycle shed. Discussion goes on, therefore, for 45 minutes, with the possible result of saving some $300. Members at length sit back with a feeling of achievement.” It is not difficult to guess where the meeting goes from there. It becomes a multi-hour marathon discussion of the $57 coffee budget, which leads to a demand for additional research and a subsequent meeting.

This dynamic should be familiar to almost anyone in the investment industry. Whether you are a financial advisor, institutional allocator, professional investor or just an individual trying to navigate the waters of an industry seemingly designed with the purpose of confusing investors, you’re at risk of more than a few Bike Shed discussions.

The code-driven investor doesn’t waste his time on the Things that Don’t Matter.

The Biggest Bike Shed of them All

Problematically, the biggest, most egregious Bike Shed probably dominates more discussions between asset owners (individuals, institutional investors) and asset managers than anything else: talking stocks.

Stop for a moment and take an inventory. If you’re an individual investor, think about your last meeting with your financial advisor. Financial advisors, pension fund execs, endowment managers, think about your last meeting with your fund managers. How much of the meeting did you spend talking about or listening to them talk about stocks and companies? A third of the meeting? Half? More? Maybe you were well-behaved and focused on things that matter, but let’s be honest with each other. We all talk about stocks way too much and we know it.

It makes me think a bit about doctors in the post-WebMD era. Once upon a time, an experienced and well-trained physician could practice medicine with deference — almost a sort of detached awe — from the patient. That is, until the internet convinced every one of us who ran in sheer terror from the syllabus for organic chemistry that we have every bit as much skill as a doctor in diagnosing ourselves with every kind of malady. For the professional investor — especially the professional investor in common stocks — this has been the case for centuries. There is no profession for which the lay person considers himself so prepared to succeed as in the management of stock portfolios.

Lest you feel any empathy for the professional in this case, our layperson isn’t entirely wrong. Not because he has some latent talent but because the average stock portfolio manager probably doesn’t. This shouldn’t be provocative. It also isn’t an opinion, as Nobel Prize winner Eugene Fama famously said, and as I rather less famously agreed in I Am Spartacus. It’s math. To pick winners and losers in the stock market is a zero-sum game, which means that for every winner who is overweight a good stock, there is a loser who is underweight. And both of them are paying fees.

As I wrote previously, it is true that this notion is driven by a narrow capitalization-weighted view of the world. It also doesn’t take into account that investors with different utility functions may differ in what they consider a win. Yet the point remains: so long as math is still a thing, on average, active managers won’t outperform because they can’t. This is a big reason why over long periods only 3% of mutual fund managers demonstrate the skill to do so after fees (Fama & French, 2010).

But the question of whether we ought to hire active stock managers isn’t even the Bike Shed discussion — after all, the phony active vs. passive debate took the top spot on this ignominious list. Instead, the mistake is the obscene amount of time we as investors spend thinking about, discussing and debating our views on individual stocks.

So why do we spend so much time doing this?

Well, for one, it’s a hell of a lot of fun. Whether we are investors on our own behalf or professionals in the industry, dealing with financial lives and investments can be drudgery. As individuals, it’s taxes and household budgets and 401(k) deferral percentages and paying people fees. As professionals, it’s due diligence and sales meetings and prospectuses and post-Christmas-party trips to HR training. Daydreaming about a stock where you really feel like you have a unique view that you haven’t heard from someone else is a blast by comparison.

Fun aside, familiarity plays an even more significant role. Each investor encounters companies with public stocks as a consumer and citizen on a daily basis. We are familiar with Apple because we buy their phones and tablet devices. We know Exxon because we have a friend or family member who works there. We work at another pharmaceuticals company and we think that gives us an edge in understanding Merck.

It is so important to recognize that these things give you an edge in talking about a stock, but absolutely zero advantage in investing in one. Lest we think that something is better than nothing, in this case, that is decidedly not so. When we know nothing, and know that we know nothing (h/t Socrates) about a company that will matter to its stock, we are far more likely to make sensible decisions concerning it, which typically means making no decision at all. When we know nothing and think we know something valuable, we are more likely to take actions for which we have no realistic expectation of a positive payoff. But it’s worse than taking a random uncompensated risk, because this kind of false-knowledge-driven investing also engenders all sorts of emotional and behavioral biases. These biases will drive you to hold positions longer than you should, ignore negative information and all other sorts of things that emotionally compromised humans do.

We also spend time doing this because talking about companies and stocks gives us a sort of feeling of parity that we usually don’t feel when we’re talking to our fund managers and financial advisors. These guys are often some of the smartest people we get to talk to. It can be intimidating. We look for any common ground we can find. We love being told we asked a very good or smart question. Strangely, my questions were much smarter when I worked at a $120 billion fund than since that time. I must have gotten stupider.

In case this is hitting a bit too close to home, let me assure you that you are not alone.

Before I was an asset manager — when I represented an asset owner — I was occasionally invited to speak at conferences. One such conference was in Monaco. Now, our fund had an investment with a hedge fund based there and given the travel expenses associated with conducting diligence meetings in Europe, combining the two made good fiscal sense. It also meant that our usual practice of conducting diligence in pairs wasn’t really feasible. So, I was running solo.

On Tuesday, I attended the conference, giving speeches to other asset owners about what effective diversification in a hedge fund portfolio looks like, and then speaking later on a panel to an audience of hedge funds on how to present effectively to pension fund prospects. I could barely leave the room without a mob of people looking for a minute of my time or a business card, and friends, I’m not a particularly interesting public speaker. I felt like a big shot.

On Wednesday, I met our fund manager for lunch. I don’t remember the name of the venue, but it was attached to some Belle Époque hotel with a patio overlooking the Mediterranean. From the front of the hotel, we were ushered through a sort of secret passageway by a tuxedoed man who, when we arrived at the patio, was joined by three similarly attired partners who proceeded to lift and move a 400-some-odd-pound concrete planter that isolated the table we would be sitting at from the rest of the patrons. When we had passed by and sat down — not without a Monsieur-so-and-so greeting and obsequious bow of the head to my host — they then lifted and returned the planter to its place and disappeared.

The gentleman welcomed me to his city graciously in Oxbridge English, but I knew from my notes that he spoke Italian, German and French as a native as well. I think he was conversant in Dutch and several other languages besides. He was an activist investor, and had such a penetrating understanding of the companies in which he invested (usually no more than 5 or 6 at any time) that I could tell immediately I was several leagues out of my depth. He was so intimately familiar with the tax loss carryforward implications of eight potential cross-border merger partners for a portfolio financial services holding that I deemed it impossible he didn’t sport an eidetic memory.

By the time I had finished a cup of bisque and he had finished (food untouched) passionately discussing solutions to flawed regulator-driven capital adequacy measures, I was so thoroughly terrified of this brilliant and just disgustingly knowledgeable man that I couldn’t help but grasp at the thing I knew I could hang with him on. I wasn’t going to be the sucker at this table!

“So, what about your position in this British consumer electronics retailer?”

And down we go into the rabbit hole, Alice. Ugh.

Look, we’ve all been there. Or maybe it’s just me and none of you have ever felt intimidated and stupid and reached out for something, anything. Either way, it’s so critical that you know that your fund manager, even your financial advisor, loves it when you want to talk stocks. Loves. It. He loves it because he knows his client will have some knowledge of them, which gives him a chance to establish common ground and develop rapport with you. It keeps the meeting going without forcing him to talk about the things he doesn’t want to talk about, namely his performance, his fees and how he actually makes money for his clients.

It’s a great use of time for him — he’s selling! — and an absolutely terrible use of time and attention for you, the investor. If they drive the conversation in that direction, stop them. If you commit an unforced error and try to get them to sell you the tank instead of the sedan, stop yourself.

Why It Doesn’t Matter

But is thinking about your individual stock investments and those made on your behalf really always such a terrible use of time? Even though I asked the question I just answered in a rhetorical way that might have indicated I was going to change my mind and go a different direction here, yeah, no, seriously, it’s a ridiculously bad use of time. Let me be specific:

If you are spending more than a miniscule fraction of your day (say, 5% of whatever time you spend working on or talking to people about investments) trying to pick or talk about individual stocks, and you are not (1) an equity portfolio manager or (2) managing a portfolio with multiple individual stock positions that are more than 5% of total capital each, this is absolutely one of the Five Things that Don’t Matter.

Why? The answer has more to do with the nature of stock picking than anything else, but in short:

  1. You probably don’t have an edge.
  2. Even if you do, being right about it won’t necessarily make the stock go up.
  3. And even if it sometimes did, it wouldn’t matter to your portfolio.

There are empirical ways to tell you how hard it is to have an edge. Academics and asset managers alike have published innumerable studies highlighting the poor performance of active equity managers against broad benchmarks and pointing out the statistical inevitability of outliers like Buffett or Miller. But you’ve probably already read those, and if you’re like me you want to know why. So here’s why it’s so damned hard.

There are only two possible ways to outperform as a stock-picker:

Method 1: Having a different view about a company’s fundamental characteristics than the market expects, being right, and the market recognizing that you are right.

Method 2: Having a view that market perception about a company will change or is changing, estimating how that will impact buying and selling behaviors, and being right.

That’s it. Any investment strategy that works must by definition do one of these things, whether consciously or subconsciously. Deep value investors, quality investors, Holt and CFROI and CROCE aficionados, DDM wonks, intrinsic value guys, “intuitive” guys, day traders, the San Diego Momentum Mafia, quants — whatever. It’s all packaging for different ways of systematically or intuitively cracking one of these two components in a repeatable way.

The problem for almost all of us — individuals, FAs, fund managers, asset owners — is that we want to think that doing truly excellent fundamental analysis guided by a rigorous process and well-constructed models is enough. Friends, this is the fundamental message of Epsilon Theory, so I hope this doesn’t offend, but fundamental analysis alone is never enough to generate alpha.

This is what leads us to focus our efforts vainly on trying to find the most blindingly intelligent people we can find to build the best models and find that one-off balance sheet detail in the 10-K notes that no one else has found. We’re then disappointed after three straight years of underperformance, and then we fire them and hire the next rising star. It is what leads us to spending time researching companies ourselves, evaluating their new products, comparing their profitability ratios to those of other companies, and the like.

This isn’t to say that fundamental analysis doesn’t have value to a valid equity investment strategy. It certainly can and may, but as a necessary but insufficient component of Method 1 described above. The missing and absolutely indispensable piece is an accurate picture of what the market actually knows and is expecting for the stock, and how participants will react to your fundamental thesis being correct.

This is where (probably) you, I and the overwhelming majority of fund managers and financial professionals sit. We may have the capacity to understand what makes a company tick, how it works. We may even be able to identify the key variables that will determine its success. But when it comes to really assessing what the next $500 million of marginal buyers and sellers — you know, the people who determine what the price of the thing actually is — really think about this stock and how they would respond to our thesis being right, I believe we are typically lost. We’ve built a Ferrari with no tires to grip the road. A beautiful, perfectly engineered, useless masterpiece of an engine.

This is one of the reasons I think that platforms that canvass the views of the people that mostly closely influence the decision-making framework of buy-side investors (i.e., sell-side research) are one of the rare forms of true and defensible edge in our industry. It’s also why I think highly of quantitative investors who systematically exploit behavioral biases that continuously creep into both Methods above over time. It’s why statistical arbitrage and high-speed trading methods work by focusing on nothing other than how the marginal buyer or seller will implement a change in their views. It’s why I think you can make an argument for activist investing on the basis that it takes direct control of both a key fundamental factor and how it is being messaged to market participants. It’s also why we’re so excited about the Narrative Machine.

But it’s also why — despite my biases toward all things technological — I also retain respect for the rare instances of accumulated knowledge and intuition about the drivers of investor behavior. I can add no thoughts or added value concerning the most recent allegations against him, but Lee Cooperman is the best case study I can think of for an investor who gets Method 1. This is a man who defines old school in terms of fundamental analysis. He sits at a marble desk, shelves behind him bedecked with binders of his team’s research and Value Line books flanking a recording studio-style window looking out on his trading floor. His process leverages a large team of hungry young analysts in a classic you-propose-I-dispose model. So yes, the fundamental analysis is the centerpiece. But in my opinion what set him and his returns apart was his ability from 50 years in this city, training or working with half of his competitors, to understand how his peers — the marginal buyer and seller — would be thinking about and would respond to what he discovered in his team’s fundamental analysis.

Ladies and gents, if you think the savvy kid from the Bronx who gets people in an intuitive sense doesn’t occupy a prominent seat at this table, you simply don’t know what you’re talking about.

But even so, let’s daydream. Let’s imagine that you are, in fact, Leon-effing-Cooperman in the flesh, with all his skills and experience. But instead of holding his relatively concentrated book, you’re holding what you and I probably own or advise for our clients or constituents (or at least should): some form of a balanced and diversified portfolio. Even if you knew that you were good at this one part of the game, would it even matter?

Sadly, not really.

You see, in a typical diversified investor’s portfolio, the idiosyncratic characteristics of individual securities — the ones driven by the factors truly unique to that company — are unlikely to represent even a fraction of a fraction of the risk an investor takes.

Consider for example a generalized case where an investor built a portfolio from an index portfolio — say US stocks — and a separate “tracking error” portfolio. This is kind of what we’re doing when we select an active manager. Even with relatively robust expectations for tracking error and the unrealistic assumption that all of the tracking error came from idiosyncratic (those unique to that security) sources with no correlation to our equity portfolio, the bets made on individual stocks account for less than 10% of total risk.

Percent of Portfolio Risk from Active Risk

Source: Salient Partners, L.P., as of 03/31/2017

Now think about this in context of our larger portfolio! In practice, most stock discussions take place in context of multi-manager structures or portfolios, in which case the number of stocks will rise and the level of tracking error will fall even further than the above. To take that even further, the majority of the sources of that tracking error will often not be related so much to the individual securities selected by the underlying managers, but a small number of systematic factors that end up looking like equity risk, namely (1) a bias to small cap stocks and (2) a bias toward or away from market volatility.

In the context of any adequately diversified portfolio, stock picks are a Bike Shed. If it is your job in the context of a very large organization to evaluate the impact of active management, you may bristle a bit at this. I remember how I justified it to myself by saying, “Well, I’m only talking about stocks this much because I want to get a picture of how she thinks about investing, and what her process is.” That’s all well and good, if true. Even so, consider whether the discussion is really allowing you to fully determine whether the advisor or fund manager has an edge under the Methods described above.

For the rest of us, spending time thinking about, discussing and debating your stock picks or those of your advisors is almost certainly a bad use of time, no matter how enjoyable. That’s why it sits at #2 on our Code’s list of Things that Don’t Matter. And if you still think we’ve given fund managers too much of a pass here, you’ll find more to like at #3.

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I Am Spartacus: Things that Don’t Matter #1

I am Spartacus!

Herald: I bring a message from your master, Marcus Licinius Crassus, commander of Italy. By common of His Most Merciful Excellency, your lives are to be spared! Slaves you were, and slaves you remain. But the terrible penalty of crucifixion has been set aside on the single condition that you identify the body or the living person of the slave called Spartacus.

Antoninus (Tony Curtis): I am Spartacus!

Other Slaves: I’m Spartacus!

— Spartacus (1960)

We are all active managers, friends. The sooner the better that we realize this and start focusing on the when and why it makes sense for investors, instead of wishcasting “good environments for active management” that don’t exist. While we may not be obscuring each other’s identities, it’s probably time for more of us to stand up and say, “I am an active manager!” Although, I suppose it is worth mentioning that shortly after this scene, Spartacus is forced to kill his best friend before being crucified.

“Active management is a zero-sum game before cost, and the winners have to win at the expense of the losers.”

— Eugene Fama, Ph.D., Investment News, October 7, 2013

Walter Sobchak: Am I wrong?

The Dude: No, you’re not wrong.

Walter: Am I wrong?

The Dude: You’re not wrong, Walter. You’re just an asshole.

Walter: All right then.

— The Big Lebowski (1998)

“You heard about it? Yeah you had to.

Mm hmm I know you changed your mind,

You ain’t the only one with bad news.

I know that it made you feel strange, huh?

You was right in the middle complainin’

and forgot what you was cryin’ about.”

— Mystikal, “Bouncin’ Back” (2001)

Ahchoo: Look, Robin, you don’t have to do this. I mean, this ain’t exactly the Mississippi. I’m on one side. I’m on the other side. I’m on the east bank, I’m on the west bank. It’s not that critical.

Robin: It’s the principle of the thing.

— Robin Hood: Men in Tights (1993)

It seems like every few years the debate on active vs. passive management comes back in full force — not that any of this is new, of course. DFA, Vanguard, and brilliant investors and writers like Charlie Ellis have been shouting from the mountaintop about what a waste of time active management is for decades now. So why the breathless excitement from the financial press on the topic this time? Mostly because they haven’t the faintest idea what they’re talking about.

Don’t mistake me: Charlie Ellis isn’t wrong. Jack Bogle isn’t wrong. Gene Fama isn’t wrong. But the basis for the broader active vs. passive debate is misleading at best, and outright fraud at worst. Let’s get a few objective, unequivocal facts out of the way about active management:

  1. There is no such thing as a “good” or “bad” environment for active management.
  2. Everyone — including you, dear reader — is an active investor.
  3. Costs matter. The rest of this debate is a waste of time.

This is why the debate over active vs. passive is #1 on my list of Things that Don’t Matter.

The myth of the good or bad environment for active management

Most investors have at least a passing familiarity with the notion of the zero-sum game. It is an academic and logically sound construct which says that if one investor is overweight or long a particular security relative to its market capitalization weighted share of that market, it stands to reason that another investor must necessarily be underweight or short.

This is true to the point of tautology, and there’s no disputing it. It’s true, and it’s used as the fundamental, deterministic argument for why active management can never  work. If every winner is offset with a loser and everyone is paying fees, over time the house is going to win. It’s also why Dr. Fama has famously and accurately said that if the data shows that active management is working, then the data is wrong.

But if this is the case, how it is possible that there are “good” or “bad” environments for active managers or stock pickers? Wouldn’t every environment just be equally bad to the tune of the drag from fees and expenses? If so, why are we talking about this historically bad period for fund managers?

The reason we are talking about it is that practically every study, allocator, advisor, researcher and article covering this topic considers passive management in context of a particular benchmark or index. However, not every pool of assets benchmarked against an index is necessarily seeking to outperform that index on an absolute basis. Even more to the point, these pools certainly don’t confine their investments to constituents of that index.

If you weighted each of the benchmarks used by investors, funds and institutions by the value of each of those pools of capital, you would end up with something that looked very different from the market capitalization of the world’s financial assets. By way of the most obvious example, I suspect that the total value of pools of capital that benchmark themselves formally against the S&P 500 Index (“S&P 500”) vastly exceeds the market capitalization of the S&P 500 itself. The value that does so informally is probably many multiples of that.

The way that this plays out in practice is surprisingly consistent. Consider a U.S. large-cap strategy. There are four biases that are ubiquitous — uniform might be nearer the mark — among both actively managed mutual funds and institutional separate accounts:

  • investments in small- and mid-cap stocks
  • investments in higher volatility / higher beta stocks
  • investments in international stocks
  • cash holdings

In other words, there is no good or bad environment for active management. There are good or bad environments for the relatively static biases that are almost universal among the pools of capital that benchmark themselves to various indices.

If you are an allocator, financial advisor or individual investor, you may have heard from your large-cap fund managers during the first half of 2016 how bad an environment it was for active management. Maybe they said that the market is ignoring fundamentals or that everything is moving together or that the market is adopting a short-term view.

That’s about 50% story-telling and 50% confirmation bias. It’s also 0% useful.

In an overwhelming majority of cases, that environment is simply one in which either small-caps underperformed or high beta / high-risk stocks did.

From the same investor vantage point, the second half of 2016 probably looked different. We often say that we don’t have a crystal ball, but I have a very reliable prediction about your annual reviews with your U.S. large-cap managers. They may inform you that “fundamentals started mattering again” in the second half of the year. The market started paying attention to earnings quality and management decisions and [insert generalization that will fill up the allotted time for the meeting here].

No they didn’t.

Small-cap and high-beta or high volatility stocks bounced back really hard. When you do your review with your active small-cap managers, you may be surprised when they, on the other hand, are doing so poorly relative to their benchmarks. Why? Because small-cap managers manage portfolios that are typically above the market cap of the Russell 2000 Index (“Russell 2000”) and nearly uniformly underperform when small-cap is trouncing large-cap.

Let’s take a look at how and why this is. The chart below splits up every month from January 2001 through January 2017 by the spread between the return of the Russell 2000 and the S&P 500. The chart plots the average excess return of each of the funds in the Morningstar Large Blend category against the S&P 500 by how pronounced the difference between small- and large-caps was for the period. In other words, what we’re looking at is whether large-cap funds have done better or worse vs. the S&P when large-caps are outperforming small-caps in general.

The results are stark. In the bottom decile of months for the large vs. small spread (i.e., the 10% of months where small-caps do the BEST), large-cap blend managers outperform the S&P by an annualized rate of just over 4%. By contrast, in the top decile for large-cap vs. small-cap, they underperform by an annualized rate of nearly 5%!

Those bad environments for stock picking your fund managers are so fond of telling you about? They’re only bad because almost all of your active managers are picking riskier stocks and putting small- and mid-caps in your large-cap fund.

Sources: Bloomberg, Ken French U.S. Research Returns, Morningstar as of 01/31/17. For illustrative purposes only. Past performance is no guarantee of future results.

Unfortunately for those of you who breathed a sigh of relief in August and September of 2016 because your active managers were ‘working’ again, this doesn’t necessarily mean your fund manager had a flash of brilliance from the patio of his Southampton rental. Low beta just spat up all the excess returns it generated in the first half of the year.

These kinds of biases are not confined to large-cap U.S. equity managers, of course. As mentioned, your small-cap managers are usually going to get smoked when small-caps are roaring. Your international equity managers are all buying emerging markets stocks around the edges of their portfolios (that’s why they were geniuses until the last three years or so, and now we think they’re stupid). Your fixed income guys are often just about all doing “core plus” even if they don’t say so on the wrapper. Your long/short equity and event funds have persistent sectoral biases.

Every category of active management has its own peculiar but fairly persistent bias against its benchmark.

OK, so active managers have consistent biases. So what? It still rolls up to the same zero-sum game, right? Yes, but it’s useful to think about and understand what’s going on underneath the hood. Namely, since we know that actively managed large-cap mutual funds and institutional separate accounts are usually underweight mega-caps, large-caps and lower risk stocks relative to the passive universe, we must fill in the gap: who is overweight these stocks to offset?

The answer is, well, strategies other than large-cap strategies, or ones that are not benchmarked to the S&P 500 or Russell 1000 Index (“Russell 1000”). That can include a wide variety of vehicles, but at the margin it includes (1) hedge funds, (2) individual or corporate holders of ‘un-benchmarked’ securities portfolios and (3) portfolios that are targeting a sub-set or variant of the large-cap universe. Clearly it also includes all sorts of strategies benchmarked to other markets entirely, one of the most common examples being multi-asset portfolios. As illustrated in the exhibit below, the S&P 500 is very obviously not completely owned by pools of capital that are benchmarked to the S&P 500.

For illustrative purposes only.

Hedge funds provide us with the most exaggerated example of one of the ways this happens. Let’s presume that large-cap mutual funds are underweight low volatility mega-cap stocks to the tune of $50 billion.

Now let’s examine two cases — in the first case, $25 billion in hedge fund capital is deployed to buy all $50 billion of that on a levered long basis. In the second case, $100 billion of hedge fund capital is used, meaning that the funds chose to hold 50% cash and spent the remaining 50% on the mega-cap stocks.

If the S&P 500 is up and a particular publication wants to talk about hedge fund returns, they’re going to talk about the first scenario as a heroic period of returns for hedge funds. In the second scenario, hedge funds are a scam run to prop up the richest 1%. Neither is true, of course — well, not on this basis alone, at least — because the benchmark isn’t capturing the risk posture that an investor is using as part of its asset allocation scheme to select that investment — in this case a long/short hedge fund.

Consider as well that many of the strategies that are ‘filling in’ for active large-cap managers’ underweights to Johnson & Johnson and ExxonMobil do so in tactical or multi-asset portfolios, many of which are going to be compared against different benchmarks entirely. Still, others may be executed under minimum volatility or income equity mandates. When you consider that the utility functions of investors in these strategies may be different, and that one investor may reasonably emphasize risk-adjusted returns rather than total returns, or that two investors might have meaningfully different needs for income in context of their overall financial situation, the argument starts to get very cloudy indeed.

There is no such thing as a passive investor

So when faced with an income objective like the example above, the response of many in the passive management camp is typically some form of, “Well, just buy more of a passive income equity fund, or move more money to bonds.”

It is this kind of argument that exemplifies why this active vs. passive debate feels so phony, so contrived. As it is too often applied, the mantra of passive management emphasizes avoiding funds that make decisions that many those allocators/advisors/investors will then make themselves and charge/pay for under the guise of asset allocation.

If a fund manager rotates between diversified portfolios of stocks, bonds, credit and other assets based on changing risks or income characteristics, he gets a Scarlet A for the vile, dastardly active manager he is. If an investor or allocator does the same thing by allocating between passively managed funds in each of those categories, he posts about it on Reddit and gets 200 up-votes.

If a fund manager invests in a portfolio of futures (lower cost passive exposure than ETFs, by the way) to reach a target level of risk and diversification without trying to pick individual securities at all, just go ahead and tattoo the “A” on their deserving forehead in permanent ink. If an investor or allocator does the same thing to build a portfolio that is equally or more distinct from a global cap-weighted benchmark using more expensive ETFs, we can only celebrate them and hope they pen a scathing white paper on the systemic risks embedded in risk-targeted investment strategies.

Everyone is often doing the same things — and usually paying for it — in different ways. To paraphrase Ahchoo (bless you), some of you are on the east bank and some of you are on the west bank. But this ain’t exactly the Mississippi. It’s not. That. Critical.

What IS critical is understanding why this debate occupies such an august (notorious?) spot on this list of Things that Don’t Matter. And here it is: I am fully confident that not a single passive investor owns a portfolio of global financial assets in the respective weights of their total value or market capitalization. Instead, they allocate away from the cap-weighted global financial assets standard based on (1) their risk appetite, (2) in order to better diversify and (3) to satisfy certain personal goals around income and taxes.

Let’s put some figures on this. Using a basic methodology from public sources (while acknowledging without having access to his letters that Paul Singer has adopted a similar approach) as of the end of 2015 or 2016 — we’re talking big numbers here, so the timeliness isn’t that important — global investable assets look something like the pie chart below.

Sources: BIS, Savillis, World Bank. For illustrative purposes only.

Yes, there’s overlap here. Yes, if you added in capital raised to invest in private companies it would add another 1.2% to equities, and including insider holdings in private companies would expand this more (although debatably). It also doesn’t include a range of commodities or commodities reserves because of the (generally) transitive nature of the former and indeterminate nature of the latter. But it’s good enough for our purposes. So does your portfolio look like this? If not, let me be the first to initiate you into the club of active managers.

Every investor is an active investor when it comes down to the major dimensions of asset allocation: risk, diversification, income and liquidity. Eliminating strategies as “Active” because they seek to manage risk, improve diversification, increase income or take advantage of greater (or lesser) liquidity is wrong-headed at best and hypocritical at worst. Most of all, it harms investors.

The S&P 500 example is not universally applicable, of course. Public large capitalization stocks are well-covered by indices, and so index funds that track the S&P 500 or Russell 1000 are generally sound examples of vehicles seeking to avoid the pitfalls of the zero-sum game. That is not always the case, however.

One example of this I like to use is the Alerian MLP Index. It is a perfectly acceptable representation of the energy MLP market, and deserves credit for being the first to track this growing asset class. It tracks 50 key constituents with around $300 billion in total market cap. The overall universe of listed midstream energy companies, however, is closer to 140-150 and sports a market cap of nearly $750 billion. There are several index funds and ETFs that track the index, and dozens of so-called actively managed funds that include a higher number of securities that look rather more like the cap-weighted market for energy infrastructure!

A more mainstream example of this might be the Dow Jones Industrial Index, famous for being used by CNBC every day and by a professional investor for the last time in the mid-1950s. This index of 30 stocks covers only a fraction of the breadth of listed stocks in the U.S. with meaningfully different characteristics on a dozen dimensions, and is tracked by a “passive” ETF with roughly $12 billion in assets. Meanwhile, lower cost large-cap mutual funds and accounts with 120 holdings built to deliver higher than typical income at a lower volatility than the market are “actively managed.” To make matters more complicated, many asset classes that are a meaningful — and diversifying — part of the cap-weighted global market simply do not have passive alternatives.

There is a wonderful local convenience store chain called Wawa where I went to college. I had a…uh…friend whose laziness was so well-developed that his diet was entirely driven by what was available at Wawa. If they didn’t have it, he didn’t eat it. Now, there are all sorts of delightful things to be had there, so don’t get me wrong. But if you’ve got something other than hot dogs, ham sandwiches or Tastykake Krimpets on your mind, you’re out of luck.

I’m sorry to say that the Index Fund Wawa is fresh out of vehicles owning securities issued by private companies, listed securities in certain niches of the markets (e.g., preferred securities in real estate) with meaningful diversification and income benefits, less liquid instruments and others unable to be held in daily or continuous liquidity vehicles. Many of these strategies have significant diversification potential and roles within portfolios. Many are often highly effective tools for adding income, efficient risk mitigation or other characteristics to portfolios. Many may even have higher expected returns or risk-adjusted returns. But you’ll have to leave the Wawa to get them.

None of this even begins to venture into hedge funds and other alternative strategies, and how they ought to be considered in context of the overall debate. To be sure, the answer is probably to observe that the same criticisms and defenses that can be brought to bear against (or on behalf of) active management apply to strategies like this as well.

But to a great extent for hedge funds (and to a lesser one for traditional strategies), there are potential sources of return that may be consistently exploited that have nearly the same empirical and fundamental underpinnings of market exposure as a source of potential return. At their core — and consistent with how we discuss them in Epsilon Theory — they are almost universally an expression of human behavior. Whether expressed through premia to value, momentum or carry premia, or else biases investors have toward quality, lottery payoffs, liquidity and the like, the great irony is that the most successful actively managed strategies are those that exploit the fact that many investors are often drawn to the appeal of active management under the guise of ‘beating the market.’

For this reason, it is somewhat baffling to see the disdain with which passionate passive investors treat many alternative strategies. If we believe that active management can persistently lead investors to predictable bad outcomes driven by understandable behavioral biases and responses to information, why would we be averse to approaches that seek to exploit this? Most investors can, however, see the forest for the trees on this issue. That is the reason why, despite the contraction in actively managed strategies more broadly, most projections for the market for liquid alternatives posit a doubling of assets in the space between 2015 and 20201.

1Both PWC and McKinsey’s work on this topic comes highly recommended.

Costs matter (and the rest of this debate is a waste of time)

Now admittedly, I have waited quite a long time to talk about one of the principal concerns around many actively managed strategies: cost.

In coming around to this critical consideration, it is worth circling back to the indisputable fact that Bogle, Fama and Ellis are right. Trying to beat the market in most markets by being overweight the right stocks and underweight the right stocks is a loser’s game. Doing that and paying fees for it makes it an expensive loser’s game. The reality is that investors need to put the pitchforks away and ask themselves a set of simple questions when considering actively managed funds:

  • Portfolio Outcomes: For a fund that is making active decisions that I would be responsible for in my asset allocation, like risk targeting, biasing toward income and yield or improving portfolio diversification, do the benefits justify the cost?
  • Incomplete or Non-Existent Indexes: When an active fund provides better diversification or coverage of an opportunity set, or covers an investment universe that is not investable through passive solutions, do the benefits justify the cost?
  • Exploiting Bad Behaviors: When investing to exploit the behaviors of other investors who are trying to beat the market to increase returns or improve risk-adjusted returns of my portfolio, do the benefits justify the cost?

It shouldn’t be any surprise that this will often lead you to the same conclusion as a passive management zealot, because adding value that justifies the cost on the above dimensions is still really hard. Active management should be evaluated with the same critical eye and cost/benefit analysis every one of us use when we make active decisions in our portfolio design and asset allocation. But because it won’t always be the case, the process matters, and the code you follow to draw your investment conclusions matters.

The active vs. passive debate, on the other hand, does not. Enough.

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A Man Must Have a Code

The Wire

Mallow: It lacks glamour?

Jael: It lacks mob emotion-appeal.

Mallow: Same thing.

― Isaac Asimov, Foundation

It is the artist’s function not to copy but to synthesize: to eliminate from that gross confusion of actuality which is his raw material whatever is accidental, idle, irrelevant, and select for perpetuation that only which is appropriate and immortal.

― William Ernest Henley, Views and Reviews: Essays in Appreciation

Principal: Mr. Madison, what you’ve just said is one of the most insanely idiotic things I have ever heard. At no point in your rambling, incoherent response were you even close to anything that could be considered a rational thought. Everyone in this room is now dumber for having listened to it. I award you no points, and may God have mercy on your soul.

Billy Madison: Okay, a simple “wrong” would have done just fine.

― Billy Madison (1995)

Homer Simpson as Max Power: Kids, there’s three ways to do things: the right way, the wrong way, and the Max Power way!

Bart Simpson: Isn’t that the wrong way?

Homer Simpson as Max Power: Yeah, but faster!

― The Simpsons, Season 10, Episode 13 “Homer to the Max”

Bunk Moreland: So, you’re my eyeball witness, huh?  So, why’d you step up on this?

Omar: Bird triflin’, basically. Kill an everyday workin’ man and all. I mean, I do some dirt, too, but I ain’t never put my gun on nobody that wasn’t in the game.

Bunk: A man must have a code.

Omar: Oh, no doubt.

― The Wire, Season 1, Episode 7

What is your code?

A few years back I worked at the Teacher Retirement System of Texas. I was responsible for hiring ostensibly sophisticated money managers—hedge funds and others generally regarded as some of the most intelligent people our society has to offer. But the most impressive people I worked with were not London-based portfolio managers but two of my fellow laborers. At a public pension plan in Austin. Go figure.

The first, Dale West, is still probably the most intelligent person I’ve ever worked with, and with my current partners Jeremy Radcliffe and Ben Hunt, would round out my fantasy Bar Trivia team, a list that unsurprisingly overlaps with my do-not-play-poker-with list. (No, in all seriousness, never play poker with Ben Hunt or Jeremy Radcliffe.) A former rising star in the Foreign Service posted in Bucharest, I’m pretty sure Dale was largely responsible for fomenting the overthrow of Ceaușescu, but he maintains that the most exciting thing he did was wire a report back to Washington about the grand opening of the first McDonald’s in Romania. He might also say he was still an undergraduate in Austin at the time. Likely story.

I also had the pleasure of working directly for Chief Investment Officer Britt Harris, one of the wisest men and investors I have known. Britt is a native of the Rio Grande Valley of South Texas, and, like Ben and me he takes peculiar pleasure in the “I’m just a country boy” hustle familiar to all accomplished southern gentlemen. As an investor-cum-philosopher-cum-preacher, Britt was and is famous for imparting that wisdom in particularly pithy turns of phrase—Britticisms, if you will. One such Britticism was the idea that any person who wants to be consistently successful as a human being, and especially as an investor, must have a World View.

In this sense, having a World View means having a center—a core set of philosophies about how the world works, what is objectively true and false, and what actually matters. More importantly, it means internalizing these philosophies so that they are second nature—and so that they become a natural lens through which we judge the world, and which we can describe succinctly to those who ask. It means having a confident view concerning how we come to any measure of knowledge about investing and markets.

To those who have studied philosophy, yes, I’m basically describing an epistemology for markets. But out of respect for the hustle, let’s call it a Code.

Unlike in abstract philosophy, however, developing a complete, fundamental view of the basis of our knowledge about markets is actually not a particularly good use of time and effort. Rationalists might argue for building thorough foundational theories on the underpinnings of human behavior, the resultant evolution of economic and financial systems and how those interact to create trillions of discrete price discovery events. Empiricists might argue instead for an ex-post analysis of price response to various identified factors or stimuli in order to develop a forward-looking framework for similar responses to similar stimuli.

The problem with both approaches is two-fold: first, the forces and individuals that comprise financial markets are far too complex to think we can ever have complete knowledge about what drives them.  Second, even when we can develop acceptable models, humans create massive error terms that we lump into the epsilon of our model, to be ignored and abstracted from. This, of course, is the genesis of Epsilon Theory as a framework for investors.

In the face of overwhelming complexity and the constant exogenous shock of human stupidity, what does it mean, then, to have a World View? What does it mean to have a Code? From my perspective, it means three things:

  1. You have a clear set of investing heuristics that are, by and large, provably true (i.e., what risks will be taken, and why do you believe they will be compensated?)
  2. You have a process for implementing those heuristics and for handling their exceptions (i.e., how do I take those compensated risks?)
  3. You can absorb new facts into your framework without breaking it.

The right way, the wrong way and the Wall Street way

The investment industry has embraced this notion of Codes to varying levels of success.

The best examples are natural, organic expressions of why an investment company was formed in the first place. Dimensional Fund Advisors (DFA), a Texas-based firm (sorry, California) we admire very much, came into existence as a commercial expression of the pioneering work on the value premium by Professors Gene Fama and Ken French. DFA doesn’t claim to have every answer to every question, but they claim to have one or two very big, important answers that matter an awful lot. And they built a firm and a Code around it.

Some Codes are willed into being by visionaries. The most famous such example is probably Bridgewater Associates, which is famous for discussing the “timeless and universal” principles that they believe underpin both the economy and financial markets. Above even these market-oriented principles, Bridgewater leans upon the principles established by Ray Dalio over many years, now compiled into a 100+ page tome. Not everyone may agree with all of the principles, but it is hard not to admire their Code and especially their commitment to it.

One family office in Ohio we think highly of has so embraced the importance of the processes that put their Code into action that firm policy dictates a regular verbatim reading of these policies and procedures as a group—aloud!

Most of the industry is less inspiring. I’ve met with hundreds of hedge funds, private equity funds, equity, fixed income and credit managers over the last decade as an allocator. Unfortunately, this experience provides very little to dispel the popular conception of Wall Street as being populated by charlatans or, worse, salesmen. Unfortunately, an entire mythology has formed around the ability of due diligence or manager selection teams to pluck out the good fund managers from the bad through huge checklists, data requests and face-to-face meetings where you can “look them in the eye” to find out whether they’re good or bad people and good or bad investors.

It’s all nonsense.

The sad reality – or the happy reality, for road-weary due diligence professionals – is that 90% of evaluating a fund manager can be boiled down to a single question: “How and why do you make money?”

When you ask this question, a fund manager with a Code’s eyes will light up. The one without will pause and give you a quizzical look. “What do you mean?” He was prepared to tell you about his investment philosophy. He was prepared to tell you about his investment process – he had the funnel graphic and everything! He was prepared to tell you which five names added the most to his P&L that quarter. He was prepared to tell you about the sector he moved from 2% to 4% overweight.

What he wasn’t prepared to do is tell you why any of that matters.

Rather than adopting a Code, individual investors, financial advisors and investment firms alike tend to try to define themselves by either a formal stated philosophy or some informal self-applied label of the type of investor they are. Invariably these descriptions are banal and infinitely transferable to the point of irrelevance.

I die a little bit inside when a fund manager tells me that his investment philosophy is something to the effect of, “We believe that our rigorous bottom-up, fundamental analysis process coupled with prudent risk management will allow us to produce above average risk-adjusted returns.” This kind of statement is the surest sign that a fund manager has absolutely no idea what he is doing that will actually make money, in addition to being a sign that he is probably spending half his day in committee meetings. That is, coincidentally, the only decision-making structure that could come up with such a ridiculously incoherent investment philosophy.

Slightly more frequently, the fund manager expresses his philosophy by communicating how he sees the world differently from everyone else by seeing it just like everyone else. “Wall Street is just focused on the next quarter—our philosophy is that we will win by having a longer-term perspective.” I might consider this a lovely Code if every other equity fund manager in New York hadn’t said the same thing to me earlier that week.

Often the response isn’t an attempt at philosophy but a reference to the size of a research team (i.e., look at our cube farm of disaffected millennials pretending to work on a dividend discount model while they look for tech jobs!), as if there were some self-evident transfer coefficient between headcount and returns.

In perhaps the most common case, the investor eschews the more formal philosophy statements in favor of the simply applied label, such as, “I’m a value investor.” This, of course, is another way to say that you like to buy things you think are cheap because you expect them to be more expensive later. In other words, you are an investor. Congratulations, your certificate is in the mail, and meetings are every other Thursday at the VFW hall. The number of fund managers who think this is an adequate description of how they generate returns, perhaps self-lauding their own simplicity in light of the perceived difference in the way everyone else sees the world, is absolutely staggering.

What does a code look like?

And yet the problem with these isn’t that they are bad philosophies. Okay, that’s part of the problem. But the real problem is that even if they were good, they wouldn’t be useful. And they aren’t useful because they aren’t measurable and because they don’t provide any mechanism for decision-making. In our view, to be successful a Code should be explicit in highlighting four key beliefs:

  1. The things that matter.
  2. The things that don’t matter.
  3. The things that don’t always matter, but which matter now.
  4. The process and tools you’ll use to focus on what matters and dispense with what does not.

It really is that simple. In future pieces, I will walk through my Code – our Code – in hopes that it will help to apply the principles of Epsilon Theory. And I promise—no funnel charts.

Okay, maybe a few funnel charts.

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