Et in Arcadia ego

“And I said: Don’t you know that he said I will foller ye always even unto the end of the road…Neighbor, you caint get shed of him”

– Blood Meridian, by Cormac McCarthy

And rear a tomb, and write thereon this verse:

‘I, Daphnis in the woods, from hence in fame

Am to the stars exalted, guardian once

Of a fair flock, myself more fair than they.’

– Eclogues, No. V, by Virgil

There is a field at the end of a lane in Tennessee that sits long abandoned. A rusting livestock gate is held fast to the fence by heavy gauge wire, twisted by hand to keep it from swinging open. It may be that a caretaker once allowed sheep to graze here to keep the brambly bushes at bay. They have been absent for some time.

The name of the lane is Caldwell Cemetery Road. At its end is a graveyard of graveyards, a field of broken monuments and faded inscriptions set into soft Tennessee limestone. There are perhaps a dozen raised tombs besides. One hopes they are architectural and not sepulchral, because most are now little more than broken lean-tos, exposed on at least one side to the world and the elements. Far to the back of the burial ground, through tall weeds and bushes, a broken headstone lies on the grass. Rev. W. G. Guinn, it reads, born August 15, 1795. He was my fourth great-grandfather.

His son, one of the last of his short dozen children, died at 41. A few years later in 1892, that son’s wife dragged their seven children between the ages of 7 and 21 to Texas, where they became tenant farmers. It was a steep fall. You see, the Rev. William Guinn was an Important Man.

You would not go very wrong to say that the Methodist minister in the deep antebellum south was the most important man in town. While the Calvinists have since given way to the Baptists there, the swelling masses of pioneers and settlers who braved the Great Wagon Road through the Great Appalachian Valley of Virginia were, as a rule, Scots-Irish. Which meant that they were Presbyterian. Which meant that they were one camp meeting and a preacher on a horse away from being Methodists.

The preacher in a small town officiated marriages. He was the trusted arbiter of disputes. He was a voice of civil authority in letters to far-off politicians and governments. He blessed new homesites and new businesses. His church on Sunday would house the most concentrated version of a dispersed community. His home often served as the orphanage, homeless shelter and welfare office. All of this was true for the Rev. Guinn, beyond which he served as postmaster, justice of the peace and in many other roles over the course of his life. He may not have been the richest man in town. He may have been the most important.

And now his grave is forgotten and his monument broken, the fatal cracks no doubt caused by the fall of some ancient tree themselves already smoothed by rains and time. How long did it take for people to forget that they had even forgotten him? One generation? Two? Thirty years? Fifty?

There is a phrase I hear from time to time among investors and allocators: ‘our time horizon is infinite’. It is a phrase used to justify performance over other-than-infinite horizons, often very fairly. It is a belief used to justify illiquidity in investments, often very fairly. It is an expression sprinkled casually over all manner of short-termism and knee-jerk responses from boards, committees, bosses and constituencies. But within that truth, there is another that we should remember:

Your time horizon is not infinite. Your institution’s time horizon is not infinite.

To those who would roll their eyes and respond, “It might as well be. For all intents and purposes, it is effectively infinite,” please accept this amendment:

Your time horizon is not effectively infinite. Your institution’s time horizon is not effectively infinite.

‘Et in Arcadia ego’ is a stylization of a theme from Virgil’s Eclogues: even in Arcadia, there am I. The I, my friends, is death. Even in paradise, death is coming, and death is there. Even for our great institutions, for our university endowments and our great charitable foundations, death will come. This isn’t fatalistic. It isn’t morbid. It isn’t bearish. It can be bullish! It can be optimistic! Like a fire through the floor of a stagnant forest, the death that comes for these institutions may be their reformation into something newer and better. It may be great or small changes in the way society is ordered. It may be a change in their mission brought about by its achievement! One day we will conquer the diseases foundations have been established to research, and even that will be a death of a kind.

There are other deaths we cannot avoid. Smaller ones. Changes in governance. Changes in law. Changes in tax schemes. Changes in securities law and regulation. Changes in student loan markets. Changes in philanthropy and in centers of wealth. These are all a death for us as investors, because they may change what we ought to be doing, and because they may invalidate the strategies we employed before. Amid those deaths, we have one governing rule: 

Your time horizon is the shortest period over which you may be forced by circumstance, behavior, prudence, constituencies, governments or outside forces to sell what you own.

This may still be a very long time! And so it may be the case that this reality should have no influence on our portfolios. But it must have an influence on our frameworks, our process and our risk management. It should color our strategic asset allocation reviews, and it should be part of the language of our engagement with oversight boards and other constituencies.

If I may be permitted a post-script, it is my personal belief that it should have one more effect: Our great universities and grand foundations should be spending more of those endowments to better execute their missions today. A lot more. Et in Arcadia, ego.

Punting and the Tyranny of Risk Memes

Last Sunday, with just under six minutes remaining on the clock in overtime, the Dallas Cowboys faced a 4th down and 1 from their opponent’s 42-yard line. Jason Garrett, the Dallas coach, sent out his punting unit. In a matter of minutes, they would go on to lose to their in-state rival Houston Texans.

It was a monumentally and objectively bad coaching decision. It would have been a bad decision for any team in the league. It was an even worse decision for the Cowboys, a team with a quarterback/running back combination with a historical success rate of 94.7% converting 4th and 1 situations. As ESPN pointed out later that evening, that is a marginally higher success rate than the rate at which kickers have converted extra points since they were moved to the 15-yard line. If you are not a fan of American football, the extra point is typically regarded as a mere formality – an early chance to visit the restroom.

Because of their location on the field, the punt’s value was also lower. A punt into the end zone would cause a touchback and yield only 22 yards of field position. Because of this risk, punters in this situation are often accordingly more conservative, targeting higher punts that terminate around the 10-15 yard line to avoid the touchback. For the Cowboys on this day, a well-executed kick still netted only 32 yards of field position. In exchange for those 32 yards of field position, the coach of the Dallas Cowboys rejected a play which – for this team – had the success rate of an extra point, and which would have provided multiple additional opportunities to advance into scoring range. You could spend hours mining historical scenarios, splits and advanced statistics for some kind of support for the decision. You won’t find it.

The press conference that follows is inevitable and all too easy to predict. The coach will explain away the decision with the sort of milquetoast response we simultaneously demand and bemoan from entertainers. You know you will hear a variant of ‘We believed in our defense’. It’s a nonsense statement, of course, since the defense could just as easily make a stop at the 42-yard line if they failed to convert. You will hear an appeal to experience and being ‘on-the-ground.’ You will hear a plea that ‘every situation is different’ and a vague allusion to what was ‘unique about that situation’. But that isn’t the point. The point, like with so many memes and narratives, is to make us sit down and shut up. The meme used to produce this response was field position!

The coach who summons this meme wants to be seen as wise – a sage, prudent leader. And it works. Every time. No one ever got fired for punting for field position! Oh sure, the media and fans will criticize him for 3-4 days. It will get mentioned the following Sunday, and then never again.

Risk-related memes are everywhere in the investment industry, too. Like the memes in football, most are built on sage-sounding ideas.

The risk management! meme is probably the most popular. It shuts down discussion by subtly implying that others in the conversation are not sufficiently focused on prudently managing risk. If you want to get someone to stop arguing with you in an investment discussion, just imply that they aren’t being prudent. One senior investor at a prior stop in my career loved responding to well-considered investment recommendations from younger investors with some variant of, ‘It’s not about the doing all the good deals, but avoiding all the bad ones.’  It’s not that there isn’t some shred of truth in this. It’s that everyone in the room who hears this knows that the discussion is over, ended by someone who wasn’t prepared to discuss the actual merits of the investment.

Most others are built around the client’s best interest! meme. Want to get a sharp, ethical professional on your team to sit down and shut up? Imply he or she isn’t considering what is best for the client. It doesn’t have to be true. Once this meme enters the room, other discussions stop. Other considerations end. Don’t you care about the client? 

These memes are so powerful because our true obligations to prudently manage risks and act in clients’ best interests are so sacred. Like any other meme or narrative, they force us to take a side. To signal.

But make no mistake. When we take score – and we do – the institutions that allow executives and PMs to use risk memes to get staff to sit down and shut up will be the losers.

Every time. 

Mailbag: Deadly. Holy. Rough. Immediate.

A challenging question from reader David S. He quotes from and responds to an excerpt from Deadly. Holy. Rough. Immediate.

“Over very long periods, you will generally be paid based on the risks an average investor (including all of his liquidity sensitivities, his investment horizons, etc.) would be taking if he made that investment.” (from Deadly. Holy. Rough. Immediate.)

Isn’t this idea built on risk spreads, building up from the risk-free rate?  But in a world where central banks set risk-free rates for other reasons, is the concept of a risk-free rate even coherent?  In other words, does anyone really think Italian government debt is safer than U.S. government debt right now?

Again, it’s a useless theoretical question.  I think risk spreads work; will continue to work; and, even if I felt otherwise, I wouldn’t be foolish enough to try to predict the timing.  But how solid is the theoretical foundation on this one?

Over a sufficiently long horizon, I’d say it’s about a 6 out of 10 (which is about as good as it gets in this game).

There are probably more finance papers on the topic of the relationship between risk and return, or premia for the fancy among us, than any other. Many of them are purely empirical (e.g. what are the long-term Sharpe ratios of different asset classes over various horizons?). Many are purely theoretical (e.g. how should markets with mostly rational actors function to price risk?). Some are a bit of both (e.g. how much of variability in stock prices is driven by changes in expectations vs. changes in discount rates?). Even as a Hayekian who thinks that prices separate us from Communists and the animals, I’m kind of with you. To practitioners, the explanations and frameworks offered by these papers are often unsatisfying.

Over many very long horizons, the data will show you that the Sharpe ratios of major asset classes are similar. In other words, the relationship between the variability in price and long-term returns above a risk-free rate appears to be pretty consistent across assets. You’ll hear this factoid a lot in defense of the idea that long-term risk-adjusted returns of assets should be comparable if investors are at all rational. But this is one of those cases where I think we’ve got to be a little bit skeptical of a surprisingly geometric cow. One exaggerated example?

Commodities.

Their long-run Sharpe ratio is not far off from those of financial assets (this obviously depends on horizon – you’ve, uh, gotta go back for this one). But any sort of attempt to build a theory about why our return expectations for commodities should have anything to do with how volatile their prices are ends up looking like a dog chasing its tail. The practitioner sees this, because he sees how much of a commodity’s price changes are directly driven by non-economic actors, substitutability, seasonality, weather, extraction costs, storage costs, hedgers, etc. Plus, y’know, supply and demand.

This is part of the reason why many practitioners do NOT treat commodities – and this includes things like Bitcoin and other cryptocurrencies, by the way – as investable asset classes. We may have some expectation of their rise, but it is hard to determine in any meaningful theoretical way why we should expect to be paid with returns in any proportion to the risks we are taking on by owning them. Incidentally, I don’t think you need to believe there is a commodity risk premium to justify holding commodities in a portfolio. I would say the same thing about cryptocurrencies if I believed there was a state of the world in which they wouldn’t be treated as a highly correlated speculative asset in any kind of sell-off event for risky assets.

This isn’t just a commodity phenomenon. To David’s point, I think it is obvious that there is a portion of the risk we take in owning financial assets – stocks, bonds and other claims on cash flows – that we probably ought not to expect to be paid for either, or at least for which the smooth, ‘rational actor’ transmission mechanism between risk and the price demanded for it is perhaps not-so-smooth. Low-vol phenomenon, anyone? A half dozen other premia? But prices for financial assets are also hilariously overdetermined. That means that if we line up all the things that influence those prices, we will explain them many times over. It’s a topic that occupies the entire lives and careers of people smarter and more dedicated to the subject than I am, so I hesitate to give it the short shrift I am here. But in the interest of responding somewhat substantively, let me tell you in short what I think:

  • I think that the risk differences caused by placement in capital structure and leverage should have a pretty strong long-term relationship with return, because they describe an actual cash flow waterfall connected to economic reality. This is why I feel confident that I’m going to be paid some spread – even if it isn’t completely proportionate – for risks I take by owning risky financial assets.
  • I think that the risk differences caused by country and currency have a weaker relationship with return. You’ll be able to find examples where this isn’t true, but in general, capital markets still exhibit very local characteristics. Assuming that the differences in realized risk between markets in two countries will give us reliable information about how participants in those markets are pricing their relative risk may be pretty unrealistic.

In practice, I think that the first bullet alone is powerful enough to make it a foundational principle of portfolio construction. Perhaps the most important. I also think it is strong enough that it matters even if you think that a significant portion of price variability and movement is driven by abstraction, game-playing and narrative.

P.S. Folks, if you’re thinking about writing me that volatility isn’t risk, please don’t.

Year In Review

We’ve had a heckuva busy year at Epsilon Theory, so to ring out 2017 I thought it might be helpful to distribute a master list of our publications over the past 12 months. We’re long essay writers trying to make our way in a TLDR world, so even the most avid follower may well need a map!

It’s also a good opportunity to give thanks where thanks are due.

First, a heartfelt thank you to my partners at Salient for contributing a ton of resources to make Epsilon Theory happen, never once asking me to sell product, and allowing me the leeway to speak my mind with a strong voice that would make a less courageous firm blanch. Epsilon Theory isn’t charity, and it’s the smart move for a firm playing the long game, but no less rare for all that.

Second, an equally heartfelt thank you to the hundreds of thousands of readers who have contributed their most precious resource – their time and attention – to the Epsilon Theory effort. We live in a world that is simultaneously shattered and connected, where we are relentlessly encouraged to mistrust our fellow citizens IRL but to engage with complete strangers on social media. It’s an atomized and polarized existence, which works really well for the Nudging State and the Nudging Oligarchy, less well for everyone else. The lasting impact of Epsilon Theory won’t be in what we publish, but in how we’re able to bring together truth-seekers of all stripes and persuasions, because it’s your engagement with the ideas presented here that will change the world. I know that sounds corny, but it’s happening.

Now on to the 2017 publishing map.

Our big initiative for this year was to publish two coherent sets of long-form notes, one by yours truly and one by my partner Rusty Guinn.

My series of essays is called Notes From the Field. As many long-time readers know, I’m originally from Alabama but now live out in the wilds of Fairfield County, Connecticut, on a “farm” of 44 acres. I put that word in quotations because although we have horses and sheep and goats and chickens and bees, my grandfather – who owned a pre-electrification, pre-refrigeration, pre-pasteurization dairy farm in the 1930s – would surely enjoy a good belly laugh at my calling this a farm. Still, I’ve learned a few things over the years from the farm and its animals, and they’ve helped me to become a better investor.

  1. Notes From the Field: The eponymous note has two essays: “Fingernail Clean”, introducing the concept of the Industrially Necessary Egg – something we take for granted as proper and “natural” when it’s anything but, and “Structure is a Cruel Master”, introducing the genius of both humans and bees – our ability to build complex societies with simple algorithms.
  2. The Goldfinch in Winter: What can a bird teach us about value investing? To everything there is a season.
  3. Horsepower: The horse and horse collar revolutionized European agriculture in the 10th and 11th centuries, a revolution that lives on in words like “horsepower” and changed the course of human civilization. Today we are struggling with a productivity devolution, not revolution, and there is nothing more important for our investments and our politics and our future than understanding its causes and remedies.
  4. The Arborist: We are overrun with Oriental Bittersweet, privet, and kudzu — or as I like to call them, monetary policy, the regulatory state, and fiat news — invasive species that crowd out the small-l liberal virtues of free markets and free elections. What to do about it? Well, that’s citizenship, and I’ve got some ideas.
  5. Always Go To the Funeral: Going to the funeral is part of the personal obligation that we have to others, obligation that doesn’t fit neatly or at all into our bizarro world of crystalized self-interest, where scale and mass distribution are ends in themselves, where the supercilious State knows what’s best for you and your family, where communication policy and fiat news shout down authenticity, where rapacious, know-nothing narcissism is celebrated as leadership even as civility, expertise, and service are mocked as cuckery. Going to the funeral is at the heart of playing the meta-game – the game behind the game – of social systems like markets and elections, and it’s something we all need to understand so that we’re not played for fools.
  6. Sheep Logic: We think we are wolves, living by the logic of the pack. In truth we are sheep, living by the logic of the flock. In both markets and politics, our human intelligences are being trained to be sheep intelligences. Why? Because that’s how you transform capital markets into a political utility, which is just about the greatest gift status quo political institutions can imagine.
  7. Clever Hans: You don’t break a wild horse by crushing its spirit. You nudge it into willingly surrendering its autonomy. Because once you’re trained to welcome the saddle, you’re going to take the bit. We are Clever Hans, dutifully hanging on every word or signal from the Nudging Fed and the Nudging Street as we stomp out our investment behavior.
  8. Pecking Order: The pecking order is a social system designed to preserve economic inequality: inequality of food for chickens, inequality of wealth for humans. We are trained and told by Team Elite that the pecking order is not a real and brutal thing in the human species, but this is a lie. It is an intentional lie, formed by two powerful Narratives: trickle-down monetary policy and massive consumer debt financing.

The Three-Body Problem: What if I told you that the dominant strategies for human investing are, without exception, algorithms and derivatives? I don’t mean computer-driven investing, I mean good old-fashioned human investing … stock-picking and the like. And what if I told you that these algorithms and derivatives might all be broken today?

Rusty’s series of essays, Things that Matter (and Things that Don’t), connects to mine with his just published The Three-Body Portfolio. It’s a wonderful piece on its own (I can’t believe I didn’t think of the Soylent Green reference – Epsilon is people!) and is a great segue to his 2017 serial opus. In chronological order:

  1. With A Man Must Have a Code, Rusty begins the conversation about why we think that all investors ought to have a consistent way of approaching their major investment decisions.
  2. In I am Spartacus, Rusty writes that the passive-active debate doesn’t matter, and that the premise itself is fraudulent.
  3. In What a Good-Looking Question, Rusty writes that trying to pick stocks doesn’t matter, and is largely a waste of time for the majority of investors.
  4. In Break the Wheel, Rusty argues that fund picking doesn’t matter either, and he takes on the cyclical, mean-reverting patterns by which we evaluate fund managers.
  5. In And they Did Live by Watchfires, Rusty highlights how whatever skill we think we have in timing and trading (which is probably none) doesn’t matter anyway.
  6. In Chili P is My Signature, Rusty writes that the typical half-hearted tilts, even to legitimate factors like value and momentum, don’t matter either.
  7. In Whom Fortune Favors (Part 2 here), Rusty writes that quantity of risk matters more than anything else (and that most investors probably aren’t taking enough).
  8. In You Still Have Made a Choice, Rusty writes that maximizing the benefits of diversification matters more than the vast majority of views we may have on one market over another.
  9. In The Myth of Market In-Itself (Part 2 here), Rusty writes that investor behavior matters, and he spends a lot of electrons on the idea that returns are always a reflection of human behavior and emotion.
  10. In Wall Street’s Merry Pranks, Rusty acknowledges that costs matter, but he emphasizes that trading costs, taxes and indirect costs from bad buy/sell behaviors nearly always matter more than the far more frequently maligned advisory and fund management expenses.

But wait, there’s more!

You’ve got two more essays from Rusty:

  1. Before and After the Storm
  2. Gandalf, GZA and Granovetter

You’ve got 10 more essays from me:

  1. Harvey Weinstein and the Common Knowledge Game
  2. Mailbag! Fall 2017 Edition
  3. Mailbag! Midsummer 2017 Edition
  4. Gradually and Then Suddenly
  5. Tell My Horse
  6. Westworld
  7. The Horse in Motion
  8. Mailbag! Life in Trumpland
  9. The Evolution of Competition
  10. Fiat Money, Fiat News

Oh yeah, and you’ve got eleven 2017 podcasts here.

So there’s your 2017 Epsilon Theory map. 2018 will be even better.

You Still Have Made a Choice: Things that Matter #2

Drummers are really nothing more than time-keepers. They’re the time of the band. I don’t consider I should have as much recognition as say a brilliant guitar player. I think the best thing a drummer can have is restraint when he’s playing — and so few have today. They think playing loud is playing best. Of course, I don’t think I’ve reached my best yet. The day I don’t move on I stop playing. I don’t practice ever. I can only play with other people, I need to feel them around me.

— Ginger Baker (founder of Cream), from a 1970 interview with Disc Magazine

La cuisine, c’est quand les choses ont le goût de ce qu’elles sont.
(Good cooking is when things taste of what they are.)

— Maurice Edmond Sailland (Curnonsky) — 1872-1956

There are those who think that life
Has nothing left to chance
A host of holy horrors
To direct our aimless dance

A planet of playthings
We dance on the strings
Of powers we cannot perceive
The stars aren’t aligned
Or the gods are malign
Blame is better to give than receive

You can choose a ready guide
In some celestial voice
If you choose not to decide
You still have made a choice

 — Rush, “Freewill”, Permanent Waves (1980)

For the kingdom of heaven is like a man traveling to a far country, who called his own servants and delivered his goods to them. And to one he gave five talents, to another two, and to another one, to each according to his own ability; and immediately he went on a journey. Then he who had received the five talents went and traded with them, and made another five talents. And likewise, he who had received two gained two more also. But he who had received one went and dug in the ground, and hid his lord’s money. After a long time the lord of those servants came and settled accounts with them.

So he who had received five talents came and brought five other talents, saying, ‘Lord, you delivered to me five talents; look, I have gained five more talents besides them.’ His lord said to him, ‘Well done, good and faithful servant; you were faithful over a few things, I will make you ruler over many things. Enter into the joy of your lord.’ He also who had received two talents came and said, ‘Lord, you delivered to me two talents; look, I have gained two more talents besides them.’ His lord said to him, ‘Well done, good and faithful servant; you have been faithful over a few things, I will make you ruler over many things. Enter into the joy of your lord.’

Then he who had received the one talent came and said, ‘Lord, I knew you to be a hard man, reaping where you have not sown, and gathering where you have not scattered seed. And I was afraid, and went and hid your talent in the ground. Look, there you have what is yours.’

But his lord answered and said to him, ‘You wicked and lazy servant, you knew that I reap where I have not sown, and gather where I have not scattered seed. So you ought to have deposited my money with the bankers, and at my coming I would have received back my own with interest. Therefore, take the talent from him, and give it to him who has ten talents.

For to everyone who has, more will be given, and he will have abundance; but from him who does not have, even what he has will be taken away. And cast the unprofitable servant into the outer darkness. There will be weeping and gnashing of teeth.

The Bible, The Gospel of Matthew 25:14-30

This note was featured in Meb Faber’s book The Best Investment Writing – Volume 2, alongside another Epsilon Theory note from Ben Hunt. Click here to get a copy.

I will never understand why more people don’t revere Rush.

With the possible exception of Led Zeppelin[1], I’m not sure there has been another band with such extraordinary instrumentalists across the board, such synergy between those members and their musical style and such a consistent approach to both lyrical and melodic construction. And yet they were only inducted into the Rock & Roll Hall of Fame in 2013. A short list of bands and singers the selection committee thought were more deserving: ABBA, Madonna, Jackson Browne, the Moonglows, Run DMC. At least they got in when Randy Newman did. I remember the first time I heard YYZ, the Rush tune named after the IATA airport code for Toronto’s Pearson International Airport, pronounced “Why Why Zed” in the charming manner of the Commonwealth. It was then that I decided I would be a drummer. I did play for a while, and reached what I would describe as just above a baseline threshold of competence.

That’s not a throwaway line.

There’s a clear, explicit line that every drummer (hopefully) crosses at one point. A step-change in his understanding of the role of the instrument. The true novice drummer always picks up the sticks and plays the same thing. Common time. Somewhere between 90-100 beats per minute. Eighth note closed hi-hat throughout. Bass drum on the down and upbeat of the first beat. Snare on second down beat. And then it’s all jazzy up-beat doodling on the snare for the rest of that bar until the down beat of four. Same thing for three measures, and on the fourth measure it’s time for that awesome fill he’s been practicing. I don’t know how many subscribers are drummers, but I assure you, literally couples of you are nodding your heads.

The fills and off-beat snare hits are all superfluous and not necessary to the principal role of a drummer in rock and roll: to keep the damned beat. But there are a number of reasons why every neophyte does these same things. Mimicry of more advanced players who can do the creative and interesting things without losing the beat, for one. We see Tony Williams, John Bonham, or Bill Bruford and do what it is we think they are doing to make the music sound good. The amateur often also thinks that these are the necessary things to be perceived as a more advanced player, for another. He doesn’t just imagine that his mimicry will make him sound more like the excellent players, but imagines himself looking like them to others. More than anything, the amateur does these things because he hasn’t quite figured out that keeping a good beat is so much more important than anything else he will do that he’s willing to sacrifice it for what he thinks is impressive.

This thought process dominates so many other fields as well. Consider the number of amateur cooks who hit every sauce or piece of meat with a handful of garlic powder, onion powder, oregano, salt, pepper and cayenne, when the simplicity of salt as seasoning dominates most of the world’s great cuisine. There is an instinct to think that complexity and depth must come from a huge range of ingredients[2] or from complexity in preparation, but most extraordinary cooking begins from an understanding of a small number of methods for heating, seasoning and establishing bases for sauces. Inventiveness, creativity and passion can take cuisine in millions of directions from there, but many home cooks see the celebrity chef’s flamboyant recipe and internalize that the creative flourishes are what matters to the dish, and not the fact that he cooked a high-quality piece of meat at the right heat for the right amount of time.

If you’re not much of a cook, consider instead the 30-handicap golfer who wouldn’t be caught dead without a full complement of four lob wedges in his bag. You know, so that he can address every possible situation on the course. The trilling singer of the national anthem who can’t hold a pitch but sees every word of the song as an opportunity to sing an entire scale’s worth of notes. The karate novice who addresses his opponent with a convoluted stance. The writer who doesn’t know when to stop giving examples to an audience who understood what he was getting at half-way through the one about cooking.

I’m guessing at least one of these things pisses you off, or at the very least makes you do an internal eye roll. And yet, as investors we are guilty of doing this kind of thing all the time, any time the topic of diversification comes up.

It comes from a good place. We know from what we’ve been taught (and from watching the experts) that we should diversify, but we don’t have a particularly good way of knowing what that means. And so we fill our portfolios with multiple flavors of funds, accounts and individual securities. Three international equity funds with different strategies. Multiple different styles in emerging markets. Some value. Some growth. Some minimum volatility. Some call writing strategies. Some sector funds. Maybe some long/short hedge funds. Some passively managed index funds, some actively managed funds. Definitely some sexy stock picks. And in the end, the portfolio that we end up with looks very much like the global equity market, maybe with a tilt here or there to express uniqueness — that flashy extra little hit on the snare drum to look impressive.

This piece isn’t about the time we waste on these things. I already wrote a piece about that a few weeks ago. This is about the harm we do to our portfolios when we play at diversifying instead of actually doing it.

The Parable of the Two FA’s

So what does actually diversifying look like?

There are lot of not-very-useful definitions out there. The eggs-in-one-basket definition we’re all familiar with benefits from simplicity, which is not nothing. In addition, it does work if people have a good concept of what the basket is in the analogy. Most people don’t. Say you have $100, and you decide that a basket is an advisor or a fund. So you split the money between the two, and they invest in the same thing. You have not diversified[3]. The other definitions for diversification tend to be more complicated, more quantitative in nature. That doesn’t make them bad, and we’ll be leaning on some of them. But we need a rule of thumb, some heuristic for describing what diversification ought to look like so that we know it when we see it. For the overwhelming majority of investors, that rule of thumb should go something like this:

Diversification is reducing how much you expect to lose when risky assets do poorly or very poorly without necessarily reducing how much total return you expect to generate.

Now, this is not exactly true, and it’s very obviously not the whole definition. But by and large it is the part of the definition that matters most. The more nuanced way to think about diversification, of course, is to describe it as all the benefits you get from the fact that things in your portfolio don’t always move together, even if they’re both generally going up in value. But most investors are so concentrated in general exposure to risky assets — securities whose value rises and falls with the fortunes and profitability of companies, and how other investors perceive those fortunes — that this distinction is mostly an academic one. Investors live and die by home country equity risk. Period. Most investors understand this to one degree or another, but the way they respond in their portfolios doesn’t reflect it.

I want to describe this to you in a parable.

There was once a rich lord who held $10 million in a S&P 500 ETF. He knew that he would be occupied with his growing business over the next year. Before he left, he met with his two financial advisors and gave them $1 million of his wealth and told them to “diversify his holdings.”

He returned after a year and came before the first financial advisor. “My lord, I put the $1 million you gave me in a Russell 1000 Value ETF. Here is your $1.1 million.” The rich man replied, “Dude, that’s almost exactly what my other ETF did over the same period. What if the market had crashed? I wasn’t diversified at all!” And the financial advisor was ashamed.

Furious and frustrated, the rich man then summoned his second financial advisor. “Sir, I put your $1 million in a Short-Duration Fixed Income mutual fund of impeccable reputation. Here’s your $1 million back.”

“Oh my God,” the lord replied, “Are you being serious right now? If I wanted to reduce my risk by stuffing my money in a mattress I could have done that without paying you a 65bp wrap fee. How do you sleep at night? I’m going to open a robo-advisor account.”

Most of us know we shouldn’t just hold a local equity index. We usually buy something else to diversify, because that’s what you do. But what we usually do falls short either because (1) the thing we buy to diversify isn’t actually all that different from what we already owned, or (2) the thing we buy to diversify reduces our risk and our return, which defeats the purpose. There’s nothing novel in what I’m saying here. Modern portfolio theory’s fundamental formula helps us to isolate how much of the variation in our portfolio’s returns comes from the riskiness of the stuff we invested in vs. the fact that this stuff doesn’t always move together.

Source: Salient 2017 For illustrative purposes only.

The Free Lunch Effect

So assuming we didn’t have any special knowledge about what assets would generate the highest risk-adjusted returns over the year our rich client was away on business, what answer would have made us the good guy in the parable? Maximizing how much benefit we get from that second expression above — the fact that this stuff doesn’t always move together.

Before we jump into the math on this, it’s important to reinforce the caveat above: we’re assuming we don’t have any knowledge about risk-adjusted returns, which isn’t always true. Stay with me, because we will get back to that. For the time being, however, let’s take as a given that we don’t know what the future holds. Let’s also assume that, like the Parable of the Two FA’s, our client holds $10 million in S&P 500 ETFs. Also like the parable, we have been asked to reallocate $1 million of those assets to what will be most diversifying. In other words, it’s a marginal analysis.

The measure we’re looking to maximize is the Free Lunch Effect, which we define as the difference between the portfolio’s volatility after our change at the margin and the raw weighted average volatility of the underlying components. If the two assets both had volatility of 10%, for example, and the resulting portfolio volatility was 9%, the Free Lunch Effect would be 1%.

If maximizing the Free Lunch Effect is the goal, here’s the relative attractiveness of various things the two FA’s could have allocated to (based on characteristics of these markets between January 2000 and July 2017).

Volatility Reduction from Diversification — Adding 10% to a Portfolio of S&P 500

Source: Salient 2017. For illustrative purposes only. Past performance is not indicative of how the index will perform in the future. The index reflects the reinvestment of dividends and income and does not reflect deductions for fees, expenses or taxes. The index is unmanaged and is not available for direct investment.

The two FA’s failed for two different reasons. The first failed because he selected an asset which was too similar. The second failed because he selected an asset which was not risky enough for its differentness to matter. The first concept is intuitive to most of us, but the second is a bit more esoteric. I think it’s best thought of by considering how much the risk of a portfolio is reduced by adding an asset with varying levels of correlation and volatility. To stop playing at diversification, this is where you start.

Volatility Reduction by Correlation and Volatility of Diversifying Asset

Source: Salient 2017. For illustrative purposes only. Past performance is not indicative of how the index will perform in the future. The index reflects the reinvestment of dividends and income and does not reflect deductions for fees, expenses or taxes. The index is unmanaged and is not available for direct investment.

If You Choose not to Decide

If there are some complaints that can be leveled against this approach, two of them, I think, are valid and worthy of exploration.

The first is that diversification cannot be fully captured in measures of correlation. If you read Whom Fortune Favors, you’ll know that our code recognizes that we live in a behaviorally-influenced, non-ergodic world. While I think we’d all recognize that U.S. value stocks are almost always going to be a poor diversifier against global equities (and vice versa), clearly there are events outside of the historical record or what we know today that could completely change that. And so the proper reading of this should always be in context of an adaptive portfolio management process.

The second complaint, as I alluded to earlier, is the fact that we are not always indifferent in our risk-adjusted return expectations for different assets. I’m sure many of you looked at the above chart and said to yourself, “Yeah, I’m not piling into commodities.” I don’t blame you (I’m still not satisfied with explanations for why I ought to be paid for being long contracts on many commodities), but that is the point. Not owning commodities or MLPs because you don’t get them isn’t the same as not expressing an opinion. If you choose not to decide, you still have made a choice.

When investors choose to forgo diversification, on any basis, they are implicitly betting that decisions that they make will outperform what diversification would have yielded them. It may not be optimal to own the most diversified portfolio you can possibly own, because anti-diversifying decisions might, in fact, be worth it. But it is exactly that thought process that must become part of our code as investors. It’s OK to turn down a free lunch, but you’d damn well better know that what you’re going to spend your money on is better.

So how do you quantify that implicit bet? Again, the Free Lunch Effect gives us our easiest answer. Consider the following case: let’s assume we had two investment options, both with similar risk of around 15%. For simplicity’s sake we’ll start from our naïve assumption that our assets produce, say, 0.5 units of return for every unit of risk we take. If the two assets are perfectly uncorrelated, how much more return would we need to demand from Asset 1 vs. Asset 2 to own more of it than the other? To own 100% Asset 1?

Well, the chart below shows it. In the case above, if you invest 100% of your portfolio in Asset 1, an investor who thinks about his portfolio in risk-adjusted terms is implicitly betting that Asset 1 will generate more than 3% more return per year, or an incremental 0.21 in return/risk units. If the assets are less similar, this implicit view grows exponentially.

Implied Incremental Return Expectation from Overweighted Asset

Source: Salient 2017. For illustrative purposes only. Past performance is not indicative of how the index will perform in the future. The index reflects the reinvestment of dividends and income and does not reflect deductions for fees, expenses or taxes. The index is unmanaged and is not available for direct investment.

A Chain of Linked Engagements

If we do not learn to regard a war, and the separate campaigns of which it is composed, as a chain of linked engagements each leading to the next, but instead succumb to the idea that the capture of certain geographical points or the seizure of undefended provinces are of value in themselves, we are liable to regard them as windfall profits.

— On War, Carl von Clausewitz

The point of this note isn’t to try to convince you to focus your portfolio construction efforts on higher volatility diversifiers like those highlighted earlier (although many of you should). It’s also not to argue that maximizing diversification should be your first objective (although most of us are so far from the optimum that moving in this direction wouldn’t hurt). It is to emphasize that portfolio construction and the decisions we make are a chain of linked engagements. It is to give you pause when you or your client asks for a ‘best new investment idea’. If your experiences are like mine, the question is nearly always expressed in isolation — recommend me a stock, a mutual fund, a hedge fund. These questions can never be answered in isolation. If you really must tinker with your allocation, sure, I can give you my view, but only if I know what else you own, and only if I know what you intend to sell in order to buy the thing.

Anyone who will make a recommendation to you without knowing those things is an idiot, a charlatan, or both.

Most of us, whether we are entrenched in financial markets or not, think about our decisions not in a vacuum but in terms of opportunity cost. If we buy A, we’re giving up B. If we invest in A, we’re giving up on B. If we do A, we won’t have time for B. Opportunity cost is fundamental to thinking about nearly every aspect of human endeavor but for some reason is completely absent from the way many investors typically think about building portfolios.

Look, if you didn’t completely follow where I was going with Whom Fortune Favors, I get it. Telling you to think about risk and diversification separately is more than a little bit arcane. But here’s where it comes together: an investor can only make wise decisions about asset allocation, about selecting fund managers, about tactical bets and about individual investments when he has an objective opportunity cost to assess those decisions against that allows him to make his portfolio decisions intentionally, not implicitly. That opportunity cost is the free lunch provided by diversification.

If we take this way of thinking to its natural extreme, we must recognize that we can, at any point, identify the portfolio that would have provided the maximum diversification, at least using the tools we’ve outlined here. For most periods, if you run through that analysis, you are very likely to find that a portfolio of those assets in which every investment contributes a comparable amount of risk to the whole — a risk parity portfolio, in other words — typically provides something near to that maximum level of diversification. I am not suggesting that your portfolio be the maximum diversification portfolio or risk parity. But I am suggesting that a risk parity portfolio of your investable universe is an excellent place to use as an anchor for this necessary analysis.

If you don’t favor it for various reasons (e.g. using volatility as a proxy for risk is the devil, it’s just levered bonds, etc.), then find your home portfolio that accomplishes similar goals in a way that is rules-based and sensible. Maybe it’s the true market portfolio we highlight in I am Spartacus. If you’re conservative, maybe it’s the tangency portfolio from the efficient frontier. And if you’re more aggressive, maybe it is something closer to the Kelly Optimal portfolio we discussed in Whom Fortune Favors. From there, your portfolio construction exercise becomes relatively simple: does the benefit I expect from this action exceed its diversification opportunity cost?

How do you measure it? If you have capital markets assumptions or projections, feel free to use them. Perhaps simpler, assume a particular Sharpe Ratio, say 0.25 or 0.30, and multiply it times the drop in diversification impact from the action you’re taking. Are you confident that the change you’re making to the portfolio is going to have more of an impact than that? That’s…really it. Now the shrewd among you might be saying, “Rusty, isn’t that kind of like what a mean-variance optimization model would do?” It isn’t kind of like that, it’s literally that. And so what? We’re not reinventing portfolio science here, we’re trying to unpack it so that we can use it more effectively as investors.

Recognize that this isn’t just a relevant approach to scenarios where you’re changing things around because you think it will improve returns dramatically. This is also a useful construct for understanding whether all the shenanigans in search of diversification, all that Chili P you’re adding, are really worth the headache. Is that fifth emerging markets manager really adding something? Is sub-dividing your regions to add country managers really worth the time?

In the end, it’s all about being intentional. With as many decisions as we have to manage, the worst thing we can do is let our portfolios make our decisions for us. Given the benefits of diversification, investors ought to put the burden of proof on anything that makes a portfolio less diversified. In doing so, they will recognize why this code recognizes the intentional pursuit of real diversification as the #2 Thing that Matters.


[1] I don’t want to hear it from the “but they stole people’s music and weren’t super nice about it” crowd. Zep played better rock and roll music than anyone before or after, and it’s not even close.

[2] And it can. Pueblan and Oaxacan cuisine feature moles with extraordinary complexity that does come from the melding of a range of seasonings and ingredients. Traditional American chilis, South Asian curries and soups from around the world often do as well. Dishes en croute (e.g. pate en croute, coulibiac, etc.) are notoriously tricky, too.

[3] Cue the fund-of-funds due diligence analyst pointing out that we would have, in fact, diversified our fraud risk. Die on that hill if you want to, friend.


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Whom Fortune Favors: Things that Matter #1, Pt. 2


Click here to read Part 1 of Whom Fortune Favors


Fook: There really is an answer?

Deep Thought: Yes. There really is one.

Fook: Oh!

Lunkwill: Can you tell us what it is?

Deep Thought: Yes. Though I don’t think you’re going to like it.

Fook: Doesn’t matter! We must know it!

Deep Thought: You’re really not going to like it!

Fook: Tell us!

Deep Thought: Alright. The answer to the ultimate question…of Life, the Universe, and Everything…is… “42”. I checked it thoroughly. It would have been simpler, of course, to have known what the actual question was.

— Douglas Adams, Hitchhiker’s Guide to the Galaxy

As investors, our process is usually to start from the answer and work our way back to the question. Unfortunately, the answers we are provided are usually pre-baked products, vehicle types or persistent industry conventions, which means that the answers we get when we actually focus on the questions that matter may be counterintuitive and jarring. The entire point of developing a personal code for investing is knowing which questions matter and ought to be asked first, before a single product, vehicle or style box gets thrown into the mix.

The purpose you undertake is dangerous.’ Why, that’s certain. ‘Tis dangerous to take a cold, to sleep, to drink; but I tell you, my lord fool, out of this nettle, danger, we pluck this flower, safety.

William Shakespeare, Henry IV, Part 1, Act 2, Scene 3, Hotspur

Thomasina: When you stir your rice pudding, Septimus, the spoonful of jam spreads itself round making red trails like the picture of a meteor in my astronomical atlas. But if you stir backwards, the jam will not come together again. Indeed, the pudding does not notice and continues to turn pink just as before. Do you think this is odd?

Septimus: No.

Thomasina: Well, I do. You cannot stir things apart.

Septimus: No more you can, time must needs run backward, and since it will not, we must stir our way onward mixing as we go, disorder out of disorder into disorder until pink is complete, unchanging and unchangeable, and we are done with it forever. This is known as free will or self-determination.

Thomasina: Septimus, do you think God is a Newtonian?

Septimus: An Etonian? Almost certainly, I’m afraid. We must ask your brother to make it his first enquiry.

Thomasina: No, Septimus, a Newtonian. Septimus! Am I the first person to have thought of this?

Septimus: No.

Thomasina: I have not said yet.

Septimus: “If everything from the furthest planet to the smallest atom of our brain acts according to Newton’s law of motion, what becomes of free will?”

Thomasina: No.

Septimus: God’s will.

Thomasina: No

Septimus: Sin.

Thomasina (derisively): No!

Septimus: Very well.

Thomasina: If you could stop every atom in its position and direction, and if your mind could comprehend all the actions thus suspended, then if you were really, really good at algebra you could write the formula for all the future; and although nobody can be so clever as to do it, the formula must exist just as if one could.

Septimus (after a pause): Yes. Yes, as far as I know, you are the first person to have thought of this.

— Tom Stoppard, Arcadia, (1993)

On this most important question of risk, we and our advisors often default to approaches which rely on the expectation that the past and present give us profound and utterly reliable insights into what we ought to expect going forward. As a result, we end up with portfolios and, more importantly, portfolio construction frameworks which don’t respect the way in which capital actually grows over time and can’t adapt to changing environments. That’s not good enough.

Most of these notes tend to stand on their own, but this one (being a Part 2) borrows a lot from the thinking in Part 1. If you’re going to get the most out of this note, I recommend you start there. But if you’re pressed for time or just lazy, I wanted you to take away two basic ideas:

  • That the risk decision dominates all other decisions you make.
  • That the risk decision is not exactly the same as the asset class decision.

Children of a Lazier God

Before I dive into the weeds on those ideas, however, I want to tell you about a dream I have. It’s a recurring dream. In this dream, I have discovered the secret to making the most possible money with the least possible effort.

Hey, I never said it was a unique dream.

It is, however, a unique investing case. Imagine for a moment that we had perfect omniscience into returns, but also that we were profoundly lazy – a sort of Jeffersonian version of God. We live in a world of stocks, bonds and commodities, and we want to set a fixed proportion of our wealth to invest in each of those assets. We want to hold that portfolio for 50+ years, sit on a beach watching dolphins or whatever it is people do on beach vacations, and maximize our returns. What do we hold? The portfolio only needs to satisfy one explicit and one implicit objective. The explicit objective is to maximize how much money we have at the end of the period. The implicit objective is the small matter of not going bankrupt in the process.

This rather curious portfolio is noteworthy for another reason, too: it is a static and rather cheeky case of an optimal portfolio under the Kelly Criterion. Named after John Kelly, Jr., a Bell Labs researcher in the 1950s, the eponymous criterion was formally proposed in 1956 before being expanded and given its name by Edward O. Thorp in the 1960s. As applied by Thorp and many others, the Kelly Criterion is a mechanism for translating assessments about risk and edge into both trading and betting decisions.

Thorp himself has written several must-reads for any investor. Beat the Dealer, Beat the Market and A Man for All Markets are all on my team’s mandatory reading list. His story and that of the Kelly Criterion were updated and expanded in William Poundstone’s similarly excellent 2005 book, Fortune’s Formula: The Untold Story of the Scientific Betting System that Beat the Casinos and Wall Street.  The criterion itself has long been part of the parlance of the professional and would-be professional gambler, and has also been the subject of various finance papers for the better part of 60 years. For the less prone to the twin vices of gambling and authoring finance papers, Kelly translates those assessments about risk and edge into position sizes. In other words, it’s a guide to sizing bets. The objective is to maximize the geometric growth rate of your bankroll — or the expected value of your final bankroll — but with zero probability of going broke along the way. It is popular because it is simple and because, when applied to games with known payoffs, it works.

When we moonlight as non-deities and seek to determine how much we ought to bet/invest, Kelly requires knowing only three facts: the size of your bankroll, your odds of winning and the payout of a winning and losing bet. For the simplest kind of friendly bet, where a wager of $1 wins $1, the calculation is simple: Kelly says that you should bet the difference between your odds of winning and your odds of losing. If you have a 55-to-45 edge against your friend, you should bet 10% of your bankroll. Your expected compounded return of doing so is provably optimal once you have bet against him enough to prove out the stated edge — although should you manage to reach this point, you are a provably suboptimal friend.

Most of the finance papers that apply this thinking to markets have focused on individual trades that look more or less like bets we’d make at a casino. These are usually things with at least a kinda-sorta knowable payoff and a discrete event where that payoff is determined: a single hand of blackjack, an exercise of an option, or a predicted corporate action taking place (or not taking place). It’s a lot harder to get your head around what “bet” we’re making and what “edge” we have when we, say, buy an S&P 500 ETF instead of holding cash. Unless you really are omniscient or carry around a copy of Grays Sports Almanac, you’re going to find estimating the range of potential outcomes for an investment or portfolio of investments pretty tricky. Not that it stops anyone from trying.

Since I don’t want to assume that any of us is quite so good at algebra as to write the formula for all the future, at a minimum what I’m trying to do is get us to think about risk unanchored to the arbitrarily determined characteristics and traits of asset classes. In other words, I want to establish an outside bound on the amount of risk a person could theoretically take in a portfolio if his only goal was maximizing return. Doing that requires us to think in geometric space, which is just a fancy way of saying that we want to know how the realization of returns over time ends up differing from a more abstract return assumption. It’s easy enough to get a feel for this yourself by opening Excel and calculating what the return would be if your portfolio went up 5% in one year and down 5% in the next (works for any such pair of numbers). Your simple average will always be zero, but your geometric mean will always be less than zero, by an increasing amount as the volatility increases.

So, if we knew exactly what stocks, bond and commodities would do between 1961 and 2016, what portfolio would we have bought? The blend of assets if we went Full Kelly would have looked like this:

Source: Salient 2017. For illustrative purposes only.

Only there’s a catch. Yes, we would have bought this portfolio, but we would have bought it more than six times. With perfect information about odds and payoffs, the optimal bet would have been to buy a portfolio with 634% (!) exposure, consisting of $2.00 in stocks, $3.21 in bonds and $1.13 in commodities for every dollar in capital we had. After all was said and done, if we looked back on the annualized volatility of this portfolio over those 50 years, what would we have found? What was the answer to life, the universe and everything?

44. Sorry, Deep Thought, you were off by two.

Perhaps the only characteristic of this portfolio more prominent than its rather remarkable level of exposure and leverage, is its hale and hearty annualized volatility of 44.1%. This result means if all you cared about was having the most money over a 50+ year period that ended last year, you would have bought a portfolio of stocks, bonds and commodities that had annualized volatility of 44.1%, roughly three times the long-term average for most equity markets[1], and probably five times that of the typical HNW investor’s portfolio.

And before you go running off to tell my lovely, charming, well-dressed and distressingly unsusceptible-to-flattery compliance officer that I told you to buy a 44% volatility super-portfolio, allow me to acknowledge that this requires some… uh… qualification. Most of these qualifications are pretty self-explanatory, since the whole exercise isn’t intended to tell you what you should buy going forward, or even the right amount of risk for you. This portfolio, this leverage and that level of risk worked over the last 50 years. Would they be optimal over the next 50?

Of course not. In real life, we’re not omniscient. Whereas a skilled card counter can estimate his mathematical edge fairly readily, it’s a lot harder for those of us in markets who are deciding what our asset allocation ought to look like. Largely for this reason, even Thorp himself advised betting “half-Kelly” or less, whether at the blackjack table or in the market. When asked why, Thorp told Jack Schwager in Hedge Fund Market Wizards, “We are not able to calculate exact probabilities… there are things that are going on that are not part of one’s knowledge at the time that affect the probabilities. So you need to scale back to a certain extent.”

Said another way, going Full Kelly on a presumption of precise certainty about outcomes in markets is a surefire way to over-bet, potentially leading to a complete loss of capital. Now, scaling back is easy if we are starting from an explicit calculation of our edge as in a game of blackjack. It’s not as easy to think about scaling down to, say, a Half Kelly portfolio. There is, however, another fascinating (but intuitive) feature of the Kelly Optimal Portfolio that allows us to scale back this portfolio in a way that may be more familiar: the Kelly Optimal Portfolio can be generalized as the highest return case of a set of portfolios generating geometric returns that are most efficient relative to the risk they take[2].

This may sound familiar. In a way, it’s very much like a presentation of Markowitz’s efficient frontier. Markowitz plots the portfolios that generate the most return for a given unit of risk, but his is a single-period calculation. It isn’t a geometric approach like Kelly, but rather reflects a return expectation that doesn’t incorporate how volatility and non-linearities impact the path and the resulting compound return. There have been a variety of academic pieces over the years covering the application of geometric returns to this framework, but most have focused on either identifying a single optimal geometric portfolio or on utility. Bernstein and Wilkinson went a bit further, developing a geometric efficient frontier.

All of these analyses are instructive and useful to the investor who wants to take path into account, but because the efficient frontier is heavily constrained by the assumed constraint on leverage, it’s not as useful for us. What we want is to take the most efficient portfolio in geometric terms, and take up or down the risk of that portfolio to reflect our tolerance for capital loss. In other words, we want a geometric capital market line. The intuitive outcome of doing this is that we can plot the highest point on this line as the Full Kelly portfolio. The second, and perhaps more satisfying outcome, is that we can retrospectively identify that scaling back from Full Kelly just looks like delevering on this geometric capital market line.

The below figure plots each of these items, including a Half Kelly portfolio that defines ruin as any scenario in the path in which losses exceed 50%, rather than full bankruptcy. The Half Kelly portfolio delivers the highest total return over this period without ever experiencing a drawdown of 50%.

Source: Salient, as of December 31, 2016. For illustrative purposes only.

When we de-lever from the Full Kelly to Half Kelly portfolio, we drop from a terrifying 44% annualized volatility number (which experiences an 80% drawdown at one point) to 18.5%, closer to but still materially higher in risk than most aggressive portfolios available from financial advisors or institutional investors.

This can be thought of in drawdown space as well for investors or advisors who have difficulty thinking in more arcane volatility terms. The below exhibit maps annualized volatility to maximum loss of capital over the analysis period. As mentioned, the 50% maximum drawdown portfolio historically looks like about 18.5% in volatility units.

Source: Salient, as of December 31, 2016. For illustrative purposes only.

For many investors, their true risk tolerance and investment horizon makes this whole discussion irrelevant. Traditional methods of thinking about risk and return are probably serving more conservative investors quite well. And there are some realities that anyone thinking about taking more risk needs to come to terms with, a lot of which I’m going to talk about in a moment — there’s a reason we wanted to talk about this in geometric terms, and it’s all about risk. But for those with a 30, 40 or 50-year horizon, for the permanent institutions with limited cash flow needs, it’s reasonable to ask the question: is the amount of risk in the S&P 500 Index or in a blend of that with the Bloomberg Barclays Aggregate Bond Index the right amount of risk to take? Or can we be taking more? Should we be taking more?

Did you think that was rhetorical? Nope.

Many investors can – and if they are acting as fiduciaries probably ought to — take more risk.

If every hedge fund manager jumped off a bridge…

This may not be a message you hear every day, but I’m not telling you anything novel. Don’t just listen to what your advisors, fund managers and institutional peers are telling you. They’re as motivated and influenced by career risk concerns as the rest of us. Instead, look at what they’re doing.

The next time you have a conversation with a sophisticated money manager you work with, ask them where they typically put their money. Yes, many of them will invest alongside you because that is right and appropriate (and also expected of them). But many more, when they are being honest, will tell you that they have a personal account or an internal-only strategy operated for staff, that operates at a significantly higher level of risk than almost anything they offer to clients. Vehicles with 20%, 25% or even 30% volatility are not uncommon. Yes, some of this is hubris, but some of it is also the realization on the part of professional investors that maximizing portfolio returns — if that is indeed your objective — can only be done if we strip back the conventions that tell us that the natural amount of risk in an unlevered investment in broad asset classes is always the right amount of risk.

Same thing with the widely admired investors, entrepreneurs and business operators. The individual stocks that represent their wealth are risky in a way that dwarfs most of what we would be willing to tolerate in individual portfolios. We explain it away with the notion that they are very skilled, or that they have control over the outcomes of the company — which may be true in doses — but in reality, they are typically equally subject to many of the uncontrollable whims that drive broader macroeconomic and financial market outcomes.

Then observe your institutional peers who are increasing their allocations to private equity and private real estate. They’re not just increasing because hedge funds have had lower absolute returns in a strong equity environment, although that is one very stupid reason why this is happening. It’s also happening because institutions are increasingly aware that they have limited alternatives to meet their target returns. While few will admit it explicitly, they use private equity because it’s the easiest way to lever their portfolios in a way that won’t look like leverage. In a true sense of uncertainty or portfolio level risk, when the risk of private portfolios is appropriately accounted for, I believe many pools of institutional capital are taking risk well beyond that of traditional equity benchmarks.

Many of the investors we all respect the most are already taking more risk than they let on, but explain it away because it’s not considered “right thinking.”

To Whom Much is Given

When we make the decision to take more risk, however, our tools and frameworks for managing uncertainty must occupy more of the stage. This isn’t only about our inability to build accurate forecasts, or even our inability to build mostly accurate stochastic frameworks based on return and volatility, like the Monte Carlo simulations many of us build for clients to simulate their growth in wealth over time. It’s also because the kinds of portfolios that a Full Kelly framework will lead you to are usually pretty risky. Their risk constraint is avoiding complete bankruptcy, and that’s not a very high bar. The things we have to do to capture such a high level of risk and return also usually disproportionately increase our exposure to big, unpredictable events. If you increase the risk of a portfolio by 20%, most of the ways you would do so will increase the exposure to these kinds of events by a lot more than 20%.

Taken together, all these things create that famous gap between our realized experience and what we expected going in. This is a because most financial and economic models assume that the world is ergodic. And it ain’t. I know that’s a ten-dollar word, but it’s important. My favorite explanation of ergodicity comes from Nassim Nicholas Taleb, who claims to have stolen it from mathematician Yakov Sinai, who in turns claims to have stolen it from Israel Gelfand:

Suppose you want to buy a pair of shoes and you live in a house that has a shoe store. There are two different strategies: one is that you go to the store in your house every day to check out the shoes and eventually you find the best pair; another is to take your car and to spend a whole day searching for footwear all over town to find a place where they have the best shoes and you buy them immediately. The system is ergodic if the result of these two strategies is the same.

There are infinite examples of investors making this mistake. My mind wanders to the fund manager who offers up the fashionable but not-very-practical “permanent loss of capital” definition of risk, a stupid definition that is the last refuge of the fund manager with lousy long-term performance. “Sure, it’s down 65%, but that’s a non-permanent impairment!” Invariably, the PM will grumble and call this a 7-standard deviation event because he assumed a world of ergodicity. Because of the impact of a loss like this on the path of our wealth, we’ll now have to vastly exceed the average expected return we put in our scenario models in Excel just to break even on it.

“It’s not a permanent impairment of capital!”

It matters what path our portfolios follow through time. It matters that our big gains and losses may come all at once. It matters to how we should bet and it matters to how we invest. You cannot stir things apart!

So if you’ve decided to take risk as an investor, how we do avoid this pitfall? Consider again the case of the entrepreneur.

The entrepreneur’s portfolio is concentrated, which means that much of his risk has not been diversified away. A lot of that is going to be reflected in the risk and return measures we would use if we were to plot him on the efficient frontier. That doesn’t necessarily mean his risk of ruin will appear high, and his analysis might, in fact, inform the entrepreneur that he ought to borrow and hold this business as his sole investment. He’s done the work, performed business plan SWOT analyses, competitor analyses, etc., and concluded that he has a pretty good grasp of what his range of outcomes and risks look like.

In an ergodic world, this makes us feel all warm and fuzzy, and we give ourselves due diligence gold stars for asking all the right questions. In a non-ergodic world, the guy dies using his own product. A competitor comes out of nowhere with a product that immediately invalidates his business model. A bigger player in a related industry decides they want to dominate his industry, too. And these are just your usual tail events, not even caused the complexity of a system we can’t understand but by sheer happenstance. For the entrepreneur, all sorts of non-tail events over time may materially and permanently change any probabilistic assessment going forward. How do we address this?

The first line of defense as we take more risk must be diversification. After all, there is a reason why the Kelly Portfolios distribute the risk fairly evenly across the constituent asset classes.[3]

Even that isn’t enough. Consider also the case of the leveraged investor in multiple investments with some measure of diversification, for example a risk parity investor, Berkshire Hathaway[4], or the guy who went Full Kelly per our earlier example, but without the whole perfect information thing. This investor has taken the opposite approach, which is to diversify heavily across different asset classes and/or company investments. His return expectation is driven not so much by his ability to create an outcome but by the exploitation of diversification. As he increases his leverage, his sensitivity to the correctness of his point-in-time probabilistic estimates of risk, return and correlations between his holdings will increase as well. In an ergodic world, this is fine and dandy. In a non-ergodic world, while he has largely mitigated the risk of idiosyncratic tails, he is relying on relationships which are based on a complex system and human behaviors that can change rapidly.

Thus, the second line of defense as we take more risk must be adaptive investing. Sometimes the only answer to a complex system is not to play the game, or at least to play less of it. Frameworks which adapt to changing relationships between markets and changing levels of risk are critical. But even they can only do so much.

Liquidity, leverage and concentration limits are your rearguard. These three things are also the only three ways you’ll be able to take more risk than asset classes give you. They are also the three horsemen of the apocalypse. They must be monitored and tightly managed if you want to have an investment program that takes more risk.

It’s not my intent to end on a fearful note, because that isn’t the point at all. More than asset class selection, more than diversification, more than fees, more than any source of alpha you believe in, nothing will matter to your portfolio and the returns it generates more than risk. And the more you take, the more it must occupy your attention. That doesn’t mean that we as investors ought to cower in fear.

On the contrary, my friends, fortune favors the bold.


[1] Back in 1989, Grauer and Hakansson undertook a somewhat similar analysis on a finite, pre-determined set of weightings among different assets with directionally similar results. Over most windows the optimal backward-looking levered portfolio tends to come out with a mid-30s level of annualized volatility.

[2] For this and the other exhibits and simulations presented here, I’m very grateful to my brilliant colleague and our head of quantitative strategies at Salient, Dr. Roberto Croce.

[3] And that reason isn’t just “we’re at the end of a 30-year bond rally,” if you’re thinking about being that guy.

[4] One suspects Mr. Buffett would be less than thrilled by the company we’re assigning him, but to misquote Milton Friedman, we are all levered derivatives users now.


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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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Chili P is My Signature: Things that Don’t Matter #5

Jesse After His Chili P Phase

Walter: Did you learn nothing from my chemistry class?
Jesse: No. You flunked me, remember, you prick? Now let me tell you something else. This ain’t chemistry — this is art. Cooking is art. And the shit I cook is the bomb, so don’t be telling me…
Walter: The shit you cook is shit. I saw your setup. Ridiculous. You and I will not make garbage. We will produce a chemically pure and stable product that performs as advertised. No adulterants. No baby formula. No chili powder.
Jesse: No, no, chili P is my signature!
Walter: Not anymore.
Breaking Bad, Season 1, Episode 1

“There was only one decline in church attendance, and that was in the late 1960s, when the Vatican said it was not a sin to miss Mass. They said Catholics could act like Protestants, and so they did.“
— Rodney Stark, Ph.D.

She should have died hereafter;
There would have been a time for such a word.
To-morrow, and to-morrow, and to-morrow,
Creeps in this petty pace from day to day
To the last syllable of recorded time,
And all our yesterdays have lighted fools
The way to dusty death. Out, out, brief candle!
Life’s but a walking shadow, a poor player
That struts and frets his hour upon the stage
And then is heard no more: it is a tale
Told by an idiot, full of sound and fury,
Signifying nothing.
— William Shakespeare, Macbeth, Act 5, Scene 5

“I can’t do it if I think about it. I would fall down, especially if I’m wearing street shoes,” he said, laughing. “It wasn’t something I did because I wanted to. I didn’t even know I did that until someone showed me a video.”
— Fernando Valenzuela about his unique windup to the LA Times (2011)

Fernando-mania

Baseball was in the midst of a crisis in 1981.

In the years prior, competition for talent in larger markets had driven player salaries higher and higher. This caused owners to seek increasing restrictions on free agency. The players’ union went on strike in June, right in the middle of the season. Fans were furious, and mostly with the owners, as is the usual way of things. We still hate millionaires, of course, but we positively loathe billionaires. While the strike ended by the All-Star break in early August, work stoppages and disputes of this sort have often been the signposts of baseball’s long, slow march to obscurity against the rising juggernaut of American football and the sneaky, if uneven, popularity of basketball. It was not a riskless gamble for either party, and as future strikes taught us, the aftermath could have gone very badly.

But not this time. You see, baseball had a secret weapon to quickly bring fans back after the 1981 strike: a “short fat dark guy with a bad haircut.” His name was Fernando Valenzuela.

Fernando was an anomaly in another long, slow march — that of baseball’s transition from a pastime to something more clinical, more analytical, more athletic. We were at a midpoint in the shift from the everyman-made-myth that was Babe Ruth or the straight-from-the-storybook folk hero like Joe DiMaggio to the brilliant, polished finished products of baseball academies today. Only a few years after 1981, we would see the birth of the new generation of uberathletes in Bo Jackson, a man who many still consider among the most gifted natural athletes in history. Only a decade earlier, the top prospect in baseball was one Greg Luzinski. The two weighed about the same. Their body composition was just a little bit different.

Fernando was certainly a physical throwback of the Luzinski variety, but so much more. He was a little pudgy. His hair was, long, shaggy and unkempt. More to the point, everything he did was inefficient, out of line with trends in the league. His windup was long and tortured, with a high leg kick that reached shoulder level in his early years and chest level in his older, slightly chubbier years. It featured an unnecessary vertical jerk of his glove straight upward near the end, and most uniquely, a glance to the heavens that became a signature of Fernando-mania. To stretch the inefficiency to its natural limits, his most effective pitch was a filthy screwball, a pitch that had been popular for decades but had already significantly waned by the early 1980s. Fathers and coaches taught their sons that it would hurt their arms (which a properly thrown screwball does not do), and by the late 1990s the pitch that ran inside on same-handed batters was all but extinct, except in Japan, where a very similar pitch called the shuuto continued to find adherents.

There were many reasons he captured the national imagination. He was a gifted Mexican pitcher in Los Angeles, a city full of baseball-obsessed Mexican-Americans and migrant workers. He was also truly marvelous as a 20-year old rookie in 1981. His stretch of eight games between April 9th and May 14th still ranks as one of the most dominant in history. Eight wins. Eight complete games. Five shutouts. Sixty-eight strikeouts. And that was how he started his career!(1)

But more than anything, I think, it was the pageantry and the spectacle of it all. The chubby, mop-top everyman who came out of nowhere with a corny sense of humor, who threw from a windup out of a cartoon, who threw a pitch that nobody else threw anymore. It was inefficient and ornamental and just so unnecessary — and we loved it. I still do. It was even how I was taught to pitch growing up. My father told me and instructed me to throw with “reckless abandon”, and so in my windup I would rotate my hips and point my left toe at second base before kicking it in a 180-degree arc at a shoulder level, nearly falling to the ground from the violent shift in weight after every pitch.

Alas, the efficiency buffs who disdained such extravagances were and are mostly right. While Valenzuela had a long and decent career, the greatest pitchers of the modern era — Roger Clemens, Pedro Martinez and especially Greg Maddux — all thrived on efficient mechanics and a focus on a smaller number of high quality pitches.(2) While a screwball is nice, and in many ways unique, it also isn’t particularly effective as a strikeout pitch in comparison to pitches with more vertical movement like, say, curveballs, split-finger fastballs or change-ups, or pitches that can accommodate lateral movement AND velocity, like sliders and cut-fastballs.

There’s a lesson in this.

As humans, especially humans in an increasingly crowded world where we can be instantly connected to billions of other people, the urge to stand out, to carve out a different path, can be irresistible. This influences our behavior in a couple of ways. First, it drives us to cynicism. Think back on the #covfefe absurdity. If you’re active on social media, by the time you thought of a funny #covfefe joke, your feed was probably already filled with an equal number of posts that decided that the meme was over, using the opportunity to skewer the latecomers to the game. Those, too, were late to the real game, which had by that time transitioned to new ironic uses of the nonsense word. A clever idea that is shared by too many quickly becomes an idea worthy of derision. And so the equilibrium — or at least the dominant game theory strategy — is to be immediately critical of everything.

It also makes us inexorably prone to affectation. We must add our own signature, that thing that distinguishes us or our product; the figurative chili-powder-in-the-meth of whatever our form of productive output happens to be.  Since we are all writers of one sort or another now, we feel this acutely in how we communicate. When part of what you want to be is authentic in your communication, our introspection becomes a very meta thing — we can talk ourselves into circles about whether we’re being authentic or trying inauthentically to appear authentic. But we’re always selling, and while our need for a unique message has exaggerated this tendency, at its core it clearly isn’t a novel impulse. People have been selling narratives forever. But if there’s a lesson in Epsilon Theory, surely it is that successful investors will be those who recognize, survive and maybe even capitalize on narrative-driven markets — not necessarily those whose success is only a function of their ability to push substance-less narratives of their own.

Perhaps most perniciously, our urge to stand out is also an urge to belong to a Tribe — to find that small niche of other humans that afford us some measure of human interaction while still permitting us to define ourselves as a Thing Set Apart. The screwball, the chili powder, the fancy windup, the obscure quotes about Catholicism from sociology Ph.D.s in your investing think-piece — instead of a barbaric yawp, it becomes a signal to your tribe. When pressed, our willingness to rip off the steering wheel and adopt a competitive strategy becomes dominant, a necessity. Lingering in the back of our heads as we go all-in on our tribe is the knowledge that our tribal leaders, no matter who they are, will sell us down the river every time.

In our investing lives, when we build portfolios, we know full well how many options our clients or constituents have, so these three competing impulses drive our behaviors: cynicism, affectation and tribalism. The cynical, nihilistic impulse shouts at us that nothing matters enough to justify risking being fired, and so we end up choosing the solution that looks most like what everyone else has done. That’s the ultimate equilibrium play we’re all headed toward anyway, right? The affectation impulse requires that we add a little something to distinguish us from our peers. A dash of chili powder. A screwball here or there, or an outlandish delivery to delight and astonish. Our tribal impulse compels us toward the right-sounding idea that makes us part of a group (I’m looking at you, Bogleheads). More frequently, we’re motivated by a combination of all three of these things in one convoluted, ennui-laden bit of arbitrary decision-making.

The real kick in the teeth of all this is that many of the things we are compelled to do by these impulses are actually good and important things, even Things that Matter. But because of the complex rationale by which we arrive at them (and other biases besides), we often implement the decisions at such a halfhearted scale that they become irrelevant. In other, worse cases, the decisions function like the tinkering we discussed in And They Did Live by Watchfires, potentially creating portfolio damage in service of a more compelling marketing message or to satisfy one of these impulses. In both cases, these flourishes and tilts are too often full of sound and fury, signifying nothing.

Too Little of a Good Thing

What, exactly, are we talking about? Well, how about value investing, for starters?

I think this one pops up most often as a form of the tribal impulse, although clearly many advisors and allocators use it as a way to add a dash of differentiation as well. Now, most of us are believers in at least a few investing tribes, each with its own taxonomy, rituals, acolytes and list of other tribes we’re supposed to hate in order to belong. But none can boast the membership rolls of the Value Tribe (except maybe the Momentum Tribe or the Passive Tribe). And for good reason! Unlike most investment strategies and approaches devised, buying things that are less expensive and buying things that have recently gone up in price can both be defended empirically and arrived at deductively based on observations of human behavior. The cases where science is really being applied to investing are very, very rare, and this is one of them. Rather than pour more ink into something I rather suppose everyone reading this believes to one extent or another, I’d instead direct you to read the splendid gospel from brothers Asness, Moskowitz and Pedersen on the subject. Or, you know, if you’re convinced non-linearities within a population’s conditioning to sustained depressing corporate results and lower levels of expected growth mean that such observations are only useful for analysis of the actions of an individual human and can’t possibly be generalized or synthesized into a hypothesis underpinning the existence of the value premium as an expression of market behavior, then don’t read it. Radical freedom!

What is shocking is how ubiquitous this belief is when I talk to investors, and how little investors demonstrate that belief in their portfolios. We adhere to the tribe’s religion, but now that it’s not a sin to skip out, we only attend its church on Christmas and Easter. And maybe after we did something bad for which we need to atone.

Value is the more socially acceptable tribe (let’s be honest, momentum has always had a bit of a culty, San Diego vibe), so let’s use that as our case study. Since I’m worried I’m leaving out those for whom cynicism is the chosen neurosis, let’s use robo-advisors to illustrate that case study. They’re instructive as a general case as well, since they, by definition, seek to be an industry-standard approach at a lower price point. Now, of the two most well-advertised robos, one — Wealthfront — mostly ignores value except in context of income generation. The other — Betterment — embraces it in a pretty significant way. I went to their very fine website and asked WOPR what a handsome young investment writer ought to invest in to retire around 2045. Here is what they recommended:

Source: Betterment 2017. For illustrative purposes only.

Pretty vanilla, but then, that’s kind of the idea of the robo-advisor. But I see a lot of registered investment advisors and this is also straight out of their playbook. It’s tough to find an anchor for the question “I know I want/need value, but how much?” As a result, one of the most common landing spots I see is exactly what our robot overlords have recommended: half of our large cap equities in core, and the other half in value. We signal/yawp a bit further: we can probably also afford to do it in the smaller chunks of the portfolios, too. Lets just do all of our small cap and mid cap equities in a value flavor. As for international and emerging equities, we don’t want to scare the client with any more line items or pie slices invested in foreign markets than we need, so let’s just do one big core allocation there.

I’m putting words in a lot of our mouths here, but if you’re an advisor or investor who works with clients and this line of thinking doesn’t feel familiar to you, I’d really like to hear about it. Because this is exactly the kind of rule of thumb I see driving portfolio decisions with so many allocators that I speak to. But how do we actually get to a portfolio like this? If you think there’s a realistic optimization or non-rule-of-thumb-driven investment process that’s going to get you here, let’s disabuse ourselves of that notion.

Could plugging historical volatility figures and capital markets expectations into a mean/variance optimizer get you to this split on value vs. core? In short? No. No, we know that this is an impossible optimizer solution because the diversification potential at the portfolio level — what we call the Free Lunch Effect in this piece — would continue to rise as we allocated more and more of our large cap allocation to a value style (and less and less to core). In other words, while the intuition might be that having both a core and value allocation is more diversifying (more pie slices!), that just isn’t true. In a purely quantitative sense, you’d be most diversified at the portfolio level with no core allocation at all!

Free Lunch Effect of Various Allocations to Large Cap Value vs. Large Cap Core in Example Portfolio

Source: Salient 2017. For illustrative purposes only.

If your instinct is to say that doesn’t look like much diversification, however, you’d be right as well. Swinging our large cap portfolio from no value to nothing but value reduces our portfolio risk by around 8bp without reducing return (i.e., the Free Lunch). That’s not nothing, but it’s damn near. The reason is that the difference between the Russell 1000 Value Index and the Russell 1000 Index or the S&P 500, or the difference between your average large cap value mutual fund and your average large cap blend mutual fund, is not a whole lot in context of how most things within a diversified portfolio interact. Said another way, the correlation is low, but the volatility is even lower, which means it has very little capacity to impact the portfolio. Take a look below at how much that value spread contributes to portfolio volatility. The below is presented in context of total portfolio volatility, so you should read this as “If I invested all 32% of the large cap portion of this portfolio in a value index and none in a core index, the value vs. core spread itself would account for about 0.1% of portfolio volatility.”

Percentage of Portfolio Volatility Contributed by LC Value-Core Spread

Source: Salient 2017. For illustrative purposes only.

Fellow tribesmen, does this reflect your conviction in value as a source of return? Some of you may quibble, “Well, this is just in some weird risk space. I think about my portfolios in terms of return.” Fine, I guess, but that just tells the same story. Consider how most value indices are constructed, which is to say a capitalization weighted splitting of “above average” vs. “below average” stocks on some measure (e.g., Russell) or multiple measures (e.g., MSCI) of value. We may have in our heads some of the excellent research on the value premium, but those are almost always expressed as regression alphas or as spread between high and low quintiles or deciles (Fama/French) or tertiles (Asness et al). In most cases they are also based on long/short or market neutral portfolios, or using methodologies that directly or indirectly size positions based on the strength of the value signal rather than the market capitalization of the stock. There are strategies based on these approaches that do capitalize on the long-term edge of behavioral factors like value. But that’s not really what you’re getting when you buy most of these indices or the many products based on them.(3)

So what are you getting? For long-only stock indices globally, probably around 80bp(4) and that assumes no erosion in the premium vs. long-term average. Most other research echoes this – the top 5 value-weighted deciles of Fama/French get you about 1.1% annualized over the average since 1972, and comparable amounts if you go back even further. Using the former figure, if you swung from 0% value to 32% value in your expression of your large cap allocation — frankly a pretty huge move for most investors and allocators — we’re talking about a 26bp difference in expected portfolio returns. Again, not nothing, but if our portfolio return expectations are, say, 8%, that’s a 3.2% contributor to our portfolio returns under fairly extreme assumptions.

Does this reflect your conviction in value as a source of return? No matter how we slice it, the ways we implement even fundamental, widely understood and generally well-supported sources of return like value seem to be a bit long on the sound and fury, but unable to really drive portfolio risk or return. Why is this so hard? Why do we end up with arbitrary solutions like splitting an asset class between core and value exposure like some sort of half-hearted genuflection in the general direction of value?

Because we have no anchor. We believe in value, but deep down we struggle to make it tangible. We don’t know how much of it we have, we don’t even know how much of it we want. We struggle even to define what “how much” means, and so we end up picking some amount that will allow us to sound sage and measured to the people who put their trust in us to sound sage and measured.

I’m going to spend a good bit of time talking about how I think about the powerful diversifying and return-amplifying role of behavioral sources of return like value as we transition our series to the Things that Matter, so I’ll beg both your patience and indulgence for leaving this as a bit of a resolutionless diatribe. I’ll also beg your pardon if it looks like I’ve been excessively critical of the fine folks who put together the portfolio that has been our case study. In truth, that portfolio goes much further along the path than most.

The point is that for various behavioral reasons, our style tilts like value, momentum or quality occupy a significant amount of our time, marketing and conversations with clients, and — by and large — signify practically nothing in terms of portfolio results. In case I wasn’t clear, yes, I am saying that value investing — at least the way most of us pursue it — doesn’t matter.

The Magically Disappearing Diversifier

The time we spend fussing around with miniscule style tilts, however, often pales in comparison to the labor we sink into our flourishes in alternatives, especially hedge funds. Some of this time is well-spent, and well-constructed hedge fund allocations can play an important role in a portfolio. When I’m asked to look at investors’ hedge fund portfolios, there are usually two warning signs to me that the portfolios are serving a signaling/tribal purpose and not some real portfolio objective:

  1. Low volatility hedge funds inside of high volatility portfolios that aren’t using leverage
  2. Hedge fund portfolios replacing Treasury or fixed income allocations

Because of the general sexiness (still, after all these years!) of hedge fund allocations to many clients or constituents, the first category tends to be the result of our affectation impulse. We want to add that low-vol, market-neutral hedge fund, or the fixed income RV fund that might have been taking some real risk back in 2006 when they could lever it up a bajillion times, not because of some worthwhile portfolio construction insight, but perhaps because it allows us to sell the notion that we are smart enough to understand the strategies and important enough to have access to them. Not everyone can get you that Chili P, after all. In some cases, sure — we are signaling to others that we are also part of that smart and sophisticated enough crowd that invests in things like this. In the institutional world, where it’s more perfunctory to do this, it’s probably closer to cynicism: “Look, I know I’m going to have a portfolio of low-vol hedge funds, so let’s just get this over with.”

For many clients and plans — specifically those where assets and liabilities are mostly in line and the portfolio can be positioned conservatively, say <10% long-term volatility — that’s completely fine. But for more aggressive allocations, there is going to be so much equity risk, so much volatility throughout the portfolio, that the notion that these portfolios will serve any diversification role whatsoever is absurd. They’re just taking down risk, and almost certainly portfolio expected returns along with it. Unless you feel supremely confident that you’ve got a manager, maybe a high frequency or quality stat arb fund, that can run at a 2 or 3 Sharpe, it is almost impossible to justify a place for a <4% volatility hedge fund in a >10% target risk portfolio. They just won’t move the needle, and there are better ways to improve portfolio diversification, returns or risk-adjusted returns.

The second category starts to veer out of “Things that Don’t Matter” territory into “Things that Do Matter, but in a Bad Way.” More and more over the last two years, as I’ve talked to investors their primary concern isn’t equity valuations, global demographics, policy-controlled markets, deflationary pressures, competitive currency crises, protectionism, or even fees! It’s their bond portfolio. The bleeding hedge fund industry has been looking for a hook since their lousy 2008 and their lousier 2009, and by God, they found it: sell hedge funds against bond portfolios! Absolute return is basically just like an income stream! There seems to be such a strong consensus for this that it may have become that cynical equilibrium.

No. Just no.

It’s impossible to overstate the importance of a bond/deflation allocation for almost any portfolio. This is an environment that prevails with meaningful frequency that has allowed the strong performance of one asset historically: bonds, especially government bonds (I see you with your hands raised in the back, CTAs, but I’m not taking questions until the end). The absolute last thing any allocator should be thinking about if they have any interest in maintaining a diversified portfolio, is reducing their strategic allocation to bonds. I’ll be the first to admit that when inflationary regimes do arrive, they can be long and persistent, during which the ability of duration to diversify has historically been squashed. The negative correlation we assume for bonds today is by no means static or certain, which is one of the reason I favor using more adaptive asset allocation schemes like risk parity that will dynamically reflect those changes in relationship. But even in that context, the dominance and ubiquity of equity-like sources of risk means that almost every investor I see is still probably vastly underweight duration.

Now many of us do have leverage limitations that start to create constraints, and so I won’t dismiss that there are scenarios where that constraint forces a rational investor not to maximize risk-adjusted returns, but absolute returns. I’m also willing to consider that on a more tactical basis, you may be smarter than I am, and have a better sense of the near-term direction of bond markets. In those cases, reducing bond exposure, potentially in favor of absolute return allocations, may be the right call. But if you have the ability to invest in higher volatility risk parity and managed futures, or if you have a mandate to run with some measure of true or derivatives-induced leverage, my strong suspicion is that you’ll find no cause to sell your bond portfolios in favor of absolute return.

Ultimately, it’s hard to be too prescriptive about all this, because our constraints and objective functions really may be quite different. To me, that means that the solution here isn’t to advise you to do this or not to do that, except to recommend this:

Make an honest assessment of your portfolio, of the tilts you’ve put on, and each of your allocations. Do they all matter? Are you including them because of a good faith and supportable belief that they will move the portfolio closer to its objective?

If we don’t feel confident that the answer is yes, it’s time to question whether we’re being influenced by the sorts of behavioral impulses that drive us elsewhere in our lives: cynicism, affectation and tribalism. In the end, the answer may be that we will continue to do those things because they feel right to us and our clients. And that may be just fine. A little bit of marketing isn’t a sin, and if your processes that have served you well over a career of investing are expressed in context of a particular posture, there’s a lot to be said for not fixing what ain’t broken. There’s nothing wrong with an impressive-looking windup, after all, until it adversely impacts the velocity and control of our pitches.

What is a sin, however, is when a half-hearted value tilt causes us to be comfortable not taking advantage of the full potential of the value premium in our portfolios. When the desire to get cute with low-vol hedge funds causes us to undershoot our portfolio risk and return targets. Perhaps most of all, when we spend our most precious resource — time — designing these affectations. We will be most successful when we reserve our resources and focus for the Things that Matter.


(1) Please – no letters about his relief starts in 1980. If MLB called him a rookie, imma call him a rookie.

(2) Probably the only exception in this conversation is Randy Johnson, who, while mostly vanilla in his mechanics, would probably get feedback from a coach today about his arm angle, his hip rotation and a whole bunch of other things that didn’t keep him from striking out almost 5,000 batters.

(3) As much as marketing professionals at some of the firms with products in this area would like to disagree and call their own product substantially different, they all just operate on a continuum expressed by the shifting of weightings toward cheaper stocks. Moving from left to right as we exaggerate the weighting scheme toward value, the continuum basically looks like this: Value Indices -> Fundamental Indexing -> Long-Only Quant Equity -> Factor Portfolios

(4) Simplistically, we’re just averaging the P2 and half of the P3 returns from the Individual Stock Portfolios Panel of Value and Momentum Everywhere, less the average of the full universe. An imperfect approach, but in broad strokes it replicates the general half growth/half value methodology for the construction of most indices in the space.


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