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.

PDF Download (Paid Subscription Required): http://www.epsilontheory.com/download/16093/

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.

PDF Download (Paid Subscription Required): http://www.epsilontheory.com/download/16113/

My Passion is Puppetry

Campaign
Company
Launch Date
epsilon-theory-my-passion-is-puppetry-april-6-2016-progressive-insurance “Flo” Progressive Insurance 2008
epsilon-theory-my-passion-is-puppetry-april-6-2016-geico “Rhetorical Question”
“Happier Than A … ”
“Did You Know?”
“It’s What You Do”
GEICO 2009
2012
2013
2014
epsilon-theory-my-passion-is-puppetry-april-6-2016-allstate “Mayhem” Allstate 2010
epsilon-theory-my-passion-is-puppetry-april-6-2016-farmers “University of Farmers” Farmers Insurance 2010
epsilon-theory-my-passion-is-puppetry-april-6-2016-state-farm-jingle “Magic Jingle” State Farm 2011
2011
epsilon-theory-my-passion-is-puppetry-april-6-2016-esurance “That’s Not How It Works” Esurance 2014
epsilon-theory-my-passion-is-puppetry-april-6-2016-nationwide “Chicken Parm You Taste So Good” Nationwide 2014

We are supposedly living in the Golden Age of television. Maybe yes, maybe no (my view: every decade is a Golden Age of television!), but there’s no doubt that today we’re living in the Golden Age of insurance commercials. Sure, you had the GEICO gecko back in 1999 and the caveman in 2004, and the Aflac duck has been around almost as long, but it’s really the Flo campaign for Progressive Insurance in 2008 that marks a sea change in how financial risk products are marketed by property and casualty insurers. Today every major P&C carrier spends big bucks (about $7 billion per year in the aggregate) on these little theatrical gems.

This will strike some as a silly argument, but I don’t think it’s a coincidence that the modern focus on entertainment marketing for financial risk products began in the Great Recession and its aftermath. When the financial ground isn’t steady underneath your feet, fundamentals don’t matter nearly as much as a fresh narrative. Why? Because the fundamentals are scary. Because you don’t buy when you’re scared. So you need a new perspective from the puppet masters to get you to buy, a new “conversation”, to use Don Draper’s words of advertising wisdom from Mad Men. Maybe that’s describing the price quote process as a “name your price tool” if you’re Flo, and maybe that’s describing Lucky Strikes tobacco as “toasted!” if you’re Don Draper. Maybe that’s a chuckle at the Mayhem guy or the Hump Day Camel if you’re Allstate or GEICO. Maybe, since equity markets are no less a financial risk product than auto insurance, it’s the installation of a cargo cult around Ben Bernanke, Janet Yellen, and Mario Draghi, such that their occasional manifestations on a TV screen, no less common than the GEICO gecko, become objects of adoration and propitiation.

epsilon-theory-my-passion-is-puppetry-april-6-2016-bernanke epsilon-theory-my-passion-is-puppetry-april-6-2016-yellen epsilon-theory-my-passion-is-puppetry-april-6-2016-draghi

For P&C insurers, the payoff from their marketing effort is clear: dollars spent on advertising drive faster and more profitable premium growth than dollars spent on agents. For central bankers, the payoff from their marketing effort is equally clear. As the Great One himself, Ben Bernanke, said in his August 31, 2012 Jackson Hole speech: “It is probably not a coincidence that the sustained recovery in U.S. equity prices began in March 2009, shortly after the FOMC’s decision to greatly expand securities purchases.” Probably not a coincidence, indeed.

Here’s what this marketing success looks like, and here’s why you should care.

This is a chart of the S&P 500 index (green line) and the Deutsche Bank Quality index (white line) from February 2000 to the market lows of March 2009.

epsilon-theory-my-passion-is-puppetry-april-6-2016-bloomberg

Source: Bloomberg Finance L.P., as of 3/6/2009. For illustrative purposes only.

Now I chose this particular factor index (which I understand to be principally a measure of return on invested capital, such that it’s long stocks with a high ROIC, i.e. high quality, and short stocks with a low ROIC, all in a sector neutral/equal-weighted construction across a wide range of global stocks in order to isolate this factor) because Quality is the embedded bias of almost every stock-picker in the world. As stock-pickers, we are trained to look for quality management teams, quality earnings, quality cash flows, quality balance sheets, etc. The precise definition of quality will differ from person to person and process to process (Deutsche Bank is using return on invested capital as a rough proxy for all of these disparate conceptions of quality, which makes good sense to me), but virtually all stock-pickers believe, largely as an article of faith, that the stock price of a high quality company will outperform the stock price of a low quality company over time. And for the nine years shown on this chart, that faith was well-rewarded, with the Quality index up 78% and the S&P 500 down 51%, a stark difference, to be sure.

But now let’s look at what’s happened with these two indices over the last seven years.

epsilon-theory-my-passion-is-puppetry-april-6-2016-bloomberg-2

Source: Bloomberg Finance L.P., as of 3/28/2016. For illustrative purposes only.

The S&P 500 index has tripled (!) from the March 2009 bottom. The Deutsche Bank Quality index? It’s up a grand total of 10%. Over seven years. Why? Because the Fed couldn’t care less about promoting high quality companies and dissing low quality companies with its concerted marketing campaign — what Bernanke and Yellen call “communication policy”, the functional equivalent of advertising. The Fed couldn’t care less about promoting value or promoting growth or promoting any traditional factor that requires an investor judgment between this company and that company. No, the Fed wants to promote ALL financial assets, and their communication policies are intentionally designed to push and cajole us to pay up for financial risk in our investments, in EXACTLY the same way that a P&C insurance company’s communication policies are intentionally designed to push and cajole us to pay up for financial risk in our cars and homes. The Fed uses Janet Yellen and forward guidance; Nationwide uses Peyton Manning and a catchy jingle. From a game theory perspective it’s the same thing.

Where do the Fed’s policies most prominently insure against financial risk? In low quality stocks, of course. It’s precisely the companies with weak balance sheets and bumbling management teams and sketchy non-GAAP earnings that are more likely to be bailed out by the tsunami of liquidity and the most accommodating monetary policy of this or any other lifetime, because companies with fortress balance sheets and competent management teams and sterling earnings don’t need bailing out under any circumstances. It’s not just that a quality bias fails to be rewarded in a policy-driven market, it’s that a bias against quality does particularly well! The result is that any long-term expected return from quality stocks is muted at best and close to zero in the current policy regime. There is no “margin of safety” in quality-driven stock-picking today, so that it only takes one idiosyncratic stock-picking mistake to wipe out a year’s worth of otherwise solid research and returns.

So how has that stock-picking mutual fund worked out for you? Probably not so well. Here’s the 2015 S&P scorecard for actively managed US equity funds, showing the percentage of funds that failed to beat their benchmarks over the last 1, 5, and 10 year periods. I mean … these are just jaw-droppingly bad numbers. And they’d be even worse if you included survivorship bias.

% of US Equity Funds that FAILED to Beat Benchmark

1 Year 5 Years 10 Years
Large-Cap 66.1% 84.2% 82.1%
Mid-Cap 56.8% 76.7% 87.6%
Small-Cap 72.2% 90.1% 88.4%

Source: S&P Dow Jones Indices, “SPIVA US Scorecard Year-End 2015” as of 12/31/15. For illustrative purposes only.

Small wonder, then, that assets have fled actively managed stock funds over the past 10 years in favor of passively managed ETFs and indices. It’s a Hobson’s Choice for investors and advisors, where a choice between interesting but under-performing active funds and boring but safe passive funds is no choice at all from a business perspective. The mantra in IT for decades was that no one ever got fired for buying IBM; today, no financial advisor ever gets fired for buying an S&P 500 index fund.

But surely, Ben, this, too, shall pass. Surely at some point central banks will back away from their massive marketing campaign based on forward guidance and celebrity spokespeople. Surely as interest rates “normalize”, we will return to those halcyon days of yore, when stock-picking on quality actually mattered.

Sorry, but I don’t see it. The mistake that most market observers make is to think that if the Fed is talking about normalizing rates, then we must be moving towards normalized markets, i.e. non-policy-driven markets. That’s not it. To steal a line from the Esurance commercials, that’s not how any of this works. So long as we’re paying attention to the Missionary’s act of communication, whether that’s a Mario Draghi press conference or a Mayhem Guy TV commercial, then behaviorally-focused advertising — aka the Common Knowledge Game — works. Common Knowledge is created simply by paying attention to a Missionary. It really doesn’t matter what specific message the Missionary is actually communicating, so long as it holds our attention. It really doesn’t matter whether the Fed hikes rates four times this year or twice this year or not at all this year. I mean, of course it matters in terms of mortgage rates and bank profits and a whole host of factors in the real economy. But for the only question that matters for investors — what do I do with my money?nothing changes. Stock-picking still won’t work. Quality still won’t work. So long as we hang on every word, uttered or unuttered, by our monetary policy Missionaries, so long as we compel ourselves to pay attention to Monetary Policy Theatre, then we will still be at sea in a policy-driven market where our traditional landmarks are barely visible and highly suspect.

Here’s my metaphor for investors and central bankers today — the brilliant Cars.com commercial where a woman is stuck on a date with an incredibly creepy guy who declares that “my passion is puppetry” and proceeds to make out with a replica of the woman.

epsilon-theory-my-passion-is-puppetry-april-6-2016-cars-ad

What we have to do as investors is exactly what this woman has to do: get out of this date and distance ourselves from this guy as quickly as humanly possible. For some of us that means leaving the restaurant entirely, reducing or eliminating our exposure to public markets by going to cash or moving to private markets. For others of us that means changing tables and eating our meal as far away as we possibly can from Creepy Puppet Guy. So long as we stay in the restaurant of public markets there’s no way to eliminate our interaction with Creepy Puppet Guy entirely. No doubt he will try to follow us around from table to table. But we don’t have to engage with him directly. We don’t have participate in his insane conversation. No one is forcing you keep a TV in your office so that you can watch CNBC all day long!

Look … I understand the appeal of a good marketing campaign. I live for this stuff. And I understand that we all operate under business and personal imperatives to beat our public market benchmarks, whatever that means in whatever corner of the investing world we live in. But I also believe that much of our business and personal discomfort with public markets today is a self-inflicted wound, driven by our biological craving for Narrative and our social craving for comfortable conversations with others and ourselves, no matter how wrong-headed those conversations might be.

Case in point: if your conversation around actively managed stock-picking strategies — and this might be a conversation with managers, it might be a conversation with clients, it might be a conversation with an Investment Board, it might be a conversation with yourself — focuses on the strategy’s ability to deliver “alpha” in this puppeted market, then you’re having a losing conversation. You are, in effect, having a conversation with Creepy Puppet Guy.

There is a role for actively managed stock-picking strategies in a puppeted market, but it’s not to “beat” the market. It’s to survive this puppeted market by getting as close to a real fractional ownership of real assets and real cash flows as possible. It’s recognizing that owning indices and ETFs is owning a casino chip, a totally different thing from a fractional ownership share of a real world thing. Sure, I want my portfolio to have some casino chips, but I ALSO want to own quality real assets and quality real cash flows, regardless of the game that’s going on all around me in the casino.

Do ALL actively managed strategies or stock-picking strategies see markets through this lens, as an effort to forego the casino chip and purchase a fractional ownership in something real? Of course not. Nor am I using the term “stock-picking” literally, as in only equity strategies are part of this conversation. What I’m saying is that a conversation focused on quality real asset and quality real cash flow ownership is the right criterion for choosing between intentional security selection strategies, and that this is the right role for these strategies in a portfolio.

Render unto Caesar the things that are Caesar’s. If you want market returns, buy the market through passive indices and ETFs. If you want better than market returns … well, good luck with that. My advice is to look to private markets, where fundamental research and private information still matter. But there’s more to public markets than playing the returns game. There’s also the opportunity to exchange capital for an ownership share in a real world asset or cash flow. It’s the meaning that public markets originally had. It’s a beautiful thing. But you’ll never see it if you’re devoting all your attention to CNBC or Creepy Puppet Guy.

PDF Download (Paid Subscription Required): http://www.epsilontheory.com/download/16289/