Notes from the Diamond #1: Always Something New to Learn

Yazstremski waits for the bounce.

Don’t be afraid to take advice. There’s always something new to learn. — Babe Ruth

Trivia Question 1 of 108 — What baseball Hall of Fame catcher earned valedictorian honors while also posting a 75-3 record as a pitcher in high school? Answer furnished in main text. Ditto for an answer to the question, “Why 108?”

Boston Red Sox pitcher Brandon Workman at bat in the 9th inning of Game 3 of the 2013 World Series

The Wind Up.  Big differences in their physical demands aside, playing pro baseball and managing money for a living have much in common — a happy fact for those of us who find both endeavors engrossing and a godsend for money managers whose quarterly letters would be intolerably brief or dull absent baseball-related arcana.  Truth be told, the literature exploring parallels between baseball and investing is already so vast that Epsilon Theory (ET) faithful might reasonably pose the same question to ET management that Red Sox Faithful shouted at their TVs as the worst managerial miscue in living memory was unfolding before their eyes several years ago: “Why?!”  No, I’m not referring to Bosox manager Grady Little’s catastrophic act of omission in Game 7 of the 2003 American League Championship Series — acceding to star pitcher Pedro Martinez’s pleas that he continue pitching — but rather to the even dopier decision of Bosox manager John Farrell a decade later: letting pitcher Brandon Workman take his first-ever major league at-bat with the Sox and Cardinals tied 4-4 in the ninth inning of Game 3 of the 2013 World Series.  The Sox lost both games, of course, ending their season in 2003 and adding unnecessary angst to a stress-filled but ultimately triumphant season in 2013.  In due course, this series will explore both of the miscues just referenced plus other noteworthy hits, runs and errors in both money management and baseball, all with the aim of elevating readers’ investment games if not also their appreciation of America’s national pastime.[1]

Unwelcome Change.  I know, I know: in many folks’ eyes, football supplanted baseball as the national pastime long ago — a mutation as regrettable and seemingly irreversible as the shift toward extremism in American politics that Ben Hunt discusses so penetratingly in his multi-part note entitled Things Fall Apart.  Unable as I am to trump Ben (pun intended) in political punditry, I’ll generally avoid politics in this series, leaving it to Ben and other ET contributors to draw parallels if and as they see fit between the shifting fortunes of professional sports on the one hand and political factions on the other.  That said, I can’t resist quoting here the late political journalist Mary McGrory’s lament respecting mutually reinforcing trends she espied in the nation’s political and recreational proclivities long before POTUS 45 declined an invitation to throw out the ceremonial first pitch on Opening Day during his first year in office: “Baseball is what we were,” McGrory observed.  “Football is what we’ve become.”

The Pitch.  Shifting from wind up to pitch … ET faithful deserve an answer to this important question among others: why should they allocate a portion of their scarcest resource — time — to this note or indeed any of the 108 planned and presumably weekly missives comprising the series hereby commencing?  At least three reasons for doing so come to mind.  First, Babe Ruth had it right: there’s always something new to learn about any field of human endeavor, including the fun fact that, as the accompanying diagram confirms, baseballs have precisely 108 stitches.  Second, Ben Hunt has it right: sometimes the best way to replace bad habits with good ones in a chosen field is to look outside it for wisdom or inspiration — as Ben has done so effectively and entertainingly for us money management types with his Notes from the Field. Third, ET contributor par excellence Rusty Guinn has it right also: sometimes the best means of elevating one’s game is to take it on the road so to speak — to contemplate the origins and soundness of habits and beliefs outside one’s chosen profession or political persuasion with an eye toward assessing critically what Rusty refers to as an investor’s “priors”.  We all have ‘em, like it or not.

Anatomy of a baseball

No Guarantees.  I’ve put priors in quotes because I myself have never used that term in decades of writing about investing, nor do I expect to use jargon like it often if ever in this series.  But Rusty fancies the term; I like and respect Rusty (and Ben); and I’ve already learned much from Rusty’s series entitled Notes from the Road.  I won’t guarantee that readers will find these Notes from the Diamond comparably insightfulBut I will pledge that they’ll spawn chuckles on occasion, while also avoiding quotes from an overexposed baseball legend who’s understandably but unjustly remembered more for his malapropisms than for his central role in notching ten World Series titles for the Evil Empire (a/k/a New York Yankees).  After all, why subject readers to deja vus from Yogi Berra when the supply of edifying utterances from other baseballers is large and growing?

Superficial Stasis.  As skilled as Berra was behind the plate, the high school valedictorian referenced in the trivia question at page 1 was even more so, as well as a gifted philosopher in his own right.  Responding to a dinner companion’s jibe that the game he played for a living was intolerably slow, Hall of Fame catcher Johnny Bench intoned, “Baseball is a slow game — for slow minds.”  Rightly understood, investing as distinct from trading also entails prolonged periods of superficial stasis — superficial because effective investors must and do ponder more or less continuously whether newly arriving information necessitates portfolio changes, mindful that it seldom does.  Interestingly, the principle just flagged — favor inaction over action unless the latter is truly vital — is arguably the single most impactful insight spawned by the so-called Sabermetrics Revolution that’s transformed pro baseball in recent decades, i.e., the reshaping of what players, managers and — yes — umpires do or don’t do on the field based on advanced statistics not readily available before certain information technologies were developed.  Among many other insights these Notes will explore, Sabermetrics — a term derived from the acronym for Society for American Baseball Research or SABR — has confirmed decisively what baseball cognoscenti have long conjectured: that a base on balls or walk can be as good as a hit.   Indeed, for reasons to be explored in future notes, the “big data” revolution that’s transformed pro baseball no less than it’s transformed financial markets in recent decades has proven that walks can be better than hits for teams notching them under certain circumstances.

For the Love of It.  What other insights from baseball of potential utility to investors will these Notes explore?  At the risk of having Ben Hunt consign me to his necessarily large nursery of raccoons — i.e., finance types who pilfer Other People’s Money by, among other means, overpromising as habitually as Ted Williams reached base safely[2]  — I’ll answer the question just posed while also wrapping up this inaugural note by providing a sneak peek at insights I plan to explore in the 107+ notes to follow.  I’ve added “+” to 107 because, more than five decades after I first laid eyes on Fenway Park’s gorgeously green grass, and more than three decades after I sank into money management, I’m as intrigued as ever by both baseball and investing.  Whether such intrigue gives me an edge in the latter pursuit is unclear, but I like to think it does, just as I like to think that major leaguers who truly enjoy their work have an edge over those who don’t.  As in finance, which comprises a regrettably large sub-population of raccoons, professional baseball comprises numerous actors motivated primarily by money.  As in finance, it’s long been thus in baseball, as perhaps the edgiest player of all time confirmed when rebuking his fellow pros as his long and distinguished playing career (1905 – 1928) was nearing its end.  “The great trouble with baseball today,” Ty Cobb scolded, “is that most of the players are in the game for the money and that’s all. Not for the love of it, the excitement of it, the thrill of it.”

Coming Attractions.  Thrilling or not, the useful insights derivable by applying ongoing advances in baseball strategies and statistics to money management are legion.  I’m excited by the prospect of pinpointing many of them in future notes, including these:

  • Why it’s not merely useful but essential for professionals to “change their stripes” — a stubbornly enduring no-no in money management whose conscious violators include not a few investment pros as successful in their evolving endeavors as Johnny Bench was in his. Why did Bench switch from pitching to catching at a crucial point in his development as a player?  Because he and those advising him deduced correctly that his foremost physical skill — a strong throwing arm — would be optimally applied as a catcher, thus permitting Bench to use his smarts as well as his physical gifts as frequently as baseball rules permit.  We’ll explore Bench’s metamorphosis and its significance for investment pros in greater detail as this series unfolds.
  • How the metrics used to assess on-field performance condition the behavior of not only players but umpires — a phenomenon with great relevance to client-manager relations in institutional funds management. As we’ll see, the fleet-footed fellow whose most celebrated achievement as a baseballer was his breaking of Ty Cobb’s all-time stolen base record understood intuitively what many capital allocators understand dimly if at all . “Show me a guy who’s afraid to look bad,” said six-time All Star and Hall of Famer Lou Brock, “and I’ll show you a guy who can be beaten.”

Not afraid to look bad: Lou Brock (#20) in action in 1964

  • What practitioners pursuing excellence must do to maintain an edge as the information revolution advances. Quite apart from rules changes already implemented that preclude future career stats as stellar as those achieved by past outliers in each domain — e.g., Wes Crawford or Bob Gibson in baseball; Michael Steinhardt or Peter Lynch in money management — the relentless and mutually reinforcing advances of technology and transparency portend continued shrinkage in the pool of dominantly successful practitioners in professional baseball no less than in professional investing.[3]  By transparency, I mean the timely collection, compilation and dissemination of essentially all available objective data germane to the aforementioned professions.  As many readers are aware, and as future notes will discuss, enhanced transparency as just defined has reduced and will continue undermining the incomes of ballplayers as well as investment pros whose “edges” entail primarily their patrons’ imperfect understanding of their true as distinct from perceived skills.  In a baseball context, “patrons” as just used is defined broadly to include team owners and managers as well as fans — all of whom can easily and inexpensively access meaningfully large chunks of the roughly seven terabytes of data per game (including but by no means not limited to video bits and bytes) that major league baseball’s Statcast system collects via cameras and radar installed in every MLB stadium. That’s a quantum of data equivalent to the contents of 700,000 copies of Webster’s Collegiate Dictionary — and literally millions times the number of data points some of us learned how to record manually on paper scorecards back in the day.

Manual recording of Red Sox labors vs. Yankees 8/18/2006

Continuous Improvement.  Imagine if fiduciaries could evaluate investment pros as quickly, cheaply and thoroughly as baseball managements can evaluate players’ every movement  (or non-movement) using Statcast.  I’m unsure such enhanced scrutiny would produce uniformly better returns, but I’m sure that it would alter managers’ as well as clients’ behaviors, just as such scrutiny has altered how pro baseball gets played, who gets to play it, and for how much.  I’m sure too that even if investment pros’ labors remain as crudely understood as pro baseballers’ were before Statcast came along, future technological advances will compel investment pros seeking sustained excellence to change their stripes on a regular if not continuous basis.  How do I square the assertion just made with Ben’s championing of repeatable processes in Things Fall Apart? I’m not sure I can, or want to, his and Rusty’s invitation to contribute to ET being rooted in their laudable desire to foster diverse viewpoints under ET’s banner.  By my lights, choiceworthy processes in money management display the same cardinal virtue that my all-time favorite player displayed when fielding caroms off Fenway’s fabled Green Monster: such processes are less “repeatable” or static than they are adaptive and ever-changing.  The player in question, of course, was Carl Yazstremski, a Long Island native whose exceptional work ethic arguably made Puritan New England (a/k/a Red Sox Nation) a fitter venue for his sporting labors than his original home turf.  “I loved the game,” Yaz said after his 23-year career came to an end in 1983.  “But I never had any fun.  All hard work, all the time.”

Carl Yazstremski awaiting a carom off Fenway’s Green Monster in the 1967 World Series

Ernie Had It Right.  Like the best opening frame this Bosox fan has ever witnessed — a 50-minute masterpiece in which the Bosox scored 14 runs on 13 hits against the visiting Florida Marlins at Fenway in June 2003 — this initial installment of Notes from the Diamond has developed proportions more expansive than might reasonably have been expected.  As noted at page 1, readers can expect future installments to be shorter — but no less replete with pearls of wisdom from wizards of the diamond, including a gentleman who changed his stripes not once qua young Johnny Bench but multiple times en route to his own induction at Cooperstown.  Nicknamed “Mr. Sunshine” for his upbeat disposition, Ernie Banks (1931 – 2015) is forever known for his catchphrase, “It’s a beautiful day for a ballgame … Let’s play two”.  With so many useful parallels between baseball and investing to be drawn — and with so many members of ET Nation including yours truly wondering what comes next for the business of investing and their own roles within it — I’m keener than ever to craft the next note in this series … and the next.  Let’s play 108, why don’t we?

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Endnotes

[1] Workman’s first and to date only major league at bat went poorly, with a whiff plus two called strikes producing a blindingly quick out.  If the Red Sox, for whom Workman has played on-and-off since 2013, make the World Series in 2018, the odds are good that team manager Alex Cora will call on Workman to do some relief pitching.  That said, I’d bet my family’s most prized baseball-related possession — a ball inscribed for my children by Elden Auker — that Cora doesn’t let Workman bat, ever.  The last living pitcher to have faced Babe Ruth, Auker (1910 – 2006) showed his mettle early in his 10-year major league career: Ruth was the first batter Auker faced in the pitcher’s big league debut in 1933, striking out on just four pitches.

[2] Most readers know that Joe DiMaggio holds the record for consecutive games with a hit: 56 in 1941.  Some may be unaware of another seemingly unbreakable record, held by the best hitter in baseball in the 1940’s or indeed any other epoch: in 1949 Ted Williams reached base safely in an astounding 84 consecutive games.

[3] The all-time career leader in triples with 309, Crawford played before “live era” or post-1910 baseballs made home runs far more frequent than triples.  Gibson notched the all-time best single season earned run average (ERA) of 1.12 in 1968, a year before pitching mounds were lowered by a third to their current height of 10 inches.  Steinhardt made big bucks for himself and his clients during the first half of his career via block trading methods that were either illegal at the time or have since been outlawed.  And Lynch turbocharged his returns via the lawful exploitation of corporate disclosure protocols benefiting big institutions like Fidelity that post-2000 securities law reforms have rendered nugatory, including especially Regulation FD.


On Deck:

What baseball’s steroid era and private equity’s salad days have in common

 


Good Job!

Every dog needs a job. It’s how they make sense of their place in the pack. It’s the key to a Good Dog.

You don’t have to tell dogs what their job is. They tell you. Maggie the German Shepherd? Her job is to protect. Sam the Sheltie? His job is to herd. Not sheep, of course, because that would be too useful. Nope, just squirrels. Turns out it’s not easy to herd squirrels, but that doesn’t stop our “special” dog from giving it his all, every day, rain or shine. Eco the Golden Retriever, pictured above? His job was to love, which he did with grace and abandon for 12 years. Rest in peace, old friend. You were a Good Dog, and I miss you.

A dog knows perfectly well when she’s done a Good Job. You can see it in her gait, in her tail, in her ears … everything about the way she carries herself says, “yep, I done good. did you see how good I done? ‘cause I done good.” Conversely, a dog also knows when she hasn’t performed up to snuff. The hangdog look is a real thing. A dog knows honor and a dog knows shame, and there is no more important example that any animal can set for us poor benighted humans.

Why? Well, this is the money quote from Sheep Logic:

Because with no sense of shame there is no sense of honor. There is no mercy. There is no charity. There is no forgiveness. There is no loyalty. There is no courage. There is no service. There are no ties that bind us as citizens, as fellow pack members seeking to achieve something bigger and more important than our ability to graze on as much grass as we can. Something bigger like, you know, liberty and justice for all.

Unlike dogs, humans have a hard time knowing whether or not they’ve done a Good Job. We consistently overestimate our competence at tasks, and when we fail, we evince befuddlement — as if we’re looking for the Restore Saved Game function — rather than remorse or apology. We humans are more Yogi Bear than Lassie.

It’s a widespread behavioral phenomenon at every age and demographic category. But it’s endemic in the young.

I think our notions of what it means to do a Good Job are so stunted for three reasons.

We’ve trivialized honor.

We’ve personalized shame.

We’ve redefined pride.

We trivialize honor through our constant celebration of mere engagement as some sort of actual achievement. We give ourselves and our children these faux “Certificates of Achievement” in one form or another all the time, and once you start looking for them you will see them everywhere.

This is how the Nudging State and the Nudging Oligarchy bring us into the fold. This is how they neg us.

This is how our children become Industrially Necessary Eggs.

We personalize shame by attaching it to identity rather than to behavior. Shame over behavior is ephemeral and corrective. Shame over identity is existential and utterly self-destructive.

The personalization of shame is a merciless goal of the Nudging Oligarchy because we will pay any price to “fix” ourselves. And our children are their primary targets.

Wait, your body isn’t “perfect” like a Victoria’s Secret model? What a shame. But don’t worry, we can help you with that.

We redefine pride when we confuse it for participation and belonging, when we treat it as the opposite of shame rather than what it really is — the foremost of the Seven Deadly Sins.

Like honor and shame, pride has been reattached from behavior to identity by the Nudging State and the Nudging Oligarchy. Like honor and shame, our children are their primary targets.

As Hieronymus Bosch knew well, the demon holding up the mirror of Pride isn’t a fable. The demon is us.

We’ve turned honor into a cheap candy, shame into an existential identity crisis, and pride into a virtue.

  • No wonder hospital admissions for suicidal teenagers have doubled over the past ten years.
  • No wonder our girls cut themselves and our boys shoot themselves.
  • No wonder my Twitter timeline is, day in and day out, a dumpster fire.
  • No wonder our 2016 election was a Sophie’s Choice.

By the way, the right answer to a Sophie’s Choice is NO. The right answer to an impossible dilemma is simply this: Homey don’t play that game.

Whee! I bet you’re a real hoot at cocktail parties, Ben. But can we come back to Planet Earth now?

Yeah, sorry about that. Actually, sorry not sorry. But in any event we’ve got to answer this question:

So what DOES it mean to do a Good Job?

Here’s what it means to any self-respecting dog. Which is to say, here’s what it means to all dogs:

You know what your job is.

The job is in service to the pack.

You do the job better than the average dog.

That’s it. That’s the Good Dog’s definition of a Good Job. Like all old wisdom, it’s deceptively simple. Like all old wisdom, it’s applicable across time and endeavor. This is an algorithm, by the way.

I’ll discuss two applications of the Good Dog’s definition of a Good Job in this essay: professional sports and professional investing. In both fields, there’s a LOT of money at stake with answering our question du jour — what does it mean to do a good job? — and in both fields there’s a clear notion of what “the pack” represents — the team in professional sports and the portfolio in professional investing. Given these similarities, it surprises me that there’s not a commonly held language to address the issue.

I think that professional sports is actually more advanced in their language on this than professional investing, or at least more cohesive, so I’ll start there. This is particularly true in the major professional sport most similar to professional investing in terms of its research methodology and sheer number of observable score/price events — baseball.

The modern methodology of baseball analysis goes by the name sabermetrics, coined by the Godfather of modern baseball statistics, Bill James, and named after the Society for American Baseball Research. I’m not sure if my dad started getting the Bill James Abstract in 1980 or 1981, but it was definitely before James hit the (well-deserved) big time in the mid-80s. In his own way, I’d say that Bill James has been the most influential data scientist in the world over the past 40 years. Certainly he’s had a huge impact on my career. Many others who work with data for a living, like Nate Silver, say the same thing.

The central question that Bill James set out to answer in the late 1970s is the Good Job question: You say that Ted Williams was a great baseball player. How do you know? Compared to who? What does that statement even mean? What’s the relationship between the greatness of Ted Williams and the performance of the Boston Red Sox?

These are exactly the questions that investors should be asking about active asset management, too.

There’s an enormous body of work developed in the sabermetric community to answer the Good Job question, but here I want to focus on one specific thread — the idea of Wins Above Replacement (WAR). It’s an approach largely credited to Keith Woolner (he calls it Value Over Replacement Player, or VORP), although as with all great concepts there are plenty of parents and plenty of variations on this theme.

Here’s what WAR seeks to measure: if you were replaced with an average player for your specific position, how many fewer games would your team win?

This is a perfect application of the Good Dog’s definition of a Good Job, all in convenient algorithm form!

  1. You know what your job is. We compare shortstops to shortstops, left fielders to left fielders, relief pitchers to relief pitchers. We take into account all aspects of the job, including defense.
  2. The job is in service to the pack. We measure players in terms of how they contribute to winning games for the team. We care about individual statistics only as they relate to team outcomes, not as ends in themselves.
  3. You do the job better than the average dog. You and your major league peers are, by definition, above average. We have the performance data for easily available replacement players (minor league call-ups, mostly), and we’re going to use that as your performance benchmark.

WAR is the Good Job algorithm for baseball. Today, WAR and its variants are the foundation for almost every economic decision that general managers make, from drafts to trades to contracts, in how they structure their team. Not just in baseball, but in every professional team sport.

So what’s the equivalent of WAR for investing?

Well, there’s no snappy acronym in investing, so I’m going to make one up.

Let’s call it PAR — Performance Above Replacement.

In WAR we want to compare the offensive and defensive stats of a professional position player, like a left fielder, to a readily available replacement position player, like a AAA call-up.

In PAR we want to compare the offensive and defensive stats of a professional active manager, like a long/short equity hedge fund manager, to a readily available replacement manager, like an ETF.

What do I mean by offensive and defensive stats? I mean making a distinction between the investment manager’s performance when the market is up and when the market is down. Makes sense, right? There are bull market managers and there are bear market managers and there’s a lot of muddy area in-between. Let’s measure how active managers perform across this crucial dimension for your portfolio so that we don’t miss some skill that might otherwise get lost in the shuffle. This is particularly important for long/short equity and global macro investors because they’re constantly changing their gross and net exposures, and it is the driving force behind the most commonly uttered phrase of active managers trying to explain how they do a Good Job: “We capture x% of the upside in our market but only y% of the downside!” where, of course, x is greater than y. If you haven’t heard (or used) that line 5 bazillion times in your investing career, then … lucky you. In more technical terms (and I’m sorry to do this, but I promise you there will be a payoff), these active managers are saying: “I am doing a Good Job because my performance demonstrates convexity.”

The concept of convexity is at the heart of Performance Above Replacement.

Convexity? Woof … that’s a ten-dollar word if there ever was one.

Let’s say you’ve got an area of your portfolio — call it your “tactical overlay” portion of the portfolio — where you’d like to give active management a shot. You’ve identified an active manager who runs a long/short global macro fund, you’ve decided that this is potentially a “real” diversifying strategy, and now you want to look at the manager’s PAR. Since this manager plays in the Everything sandbox, you’re going to use a global 60/40 investable index (or better yet a global risk parity strategy … yes, I went there) as the “replacement player”, and you’re going to separate out how the manager performs in up markets versus down markets, using the S&P 500 for that distinction because that’s your benchmark.

Here are some stylized absolute return profiles on the left, and the corresponding relative return profile on the right. I’m simplifying things here by drawing straight lines instead of what would be a smattering of point observations (monthly performance numbers, for example), but you can use a linear regression to create the lines. Actually you’re running two linear regressions, one for the manager’s offensive stats (performance when the S&P 500 is up, in green) and one for the manager’s defensive stats (performance when the S&P 500 is down, in red). The blue line is the performance of the replacement strategy (a global 60/40 or risk parity fund). Both funds cross the y-axis slightly below zero (more so for the active manager) to reflect the management fees and expenses associated with the funds.

When you “normalize” the active manager’s performance versus the replacement strategy and the S&P 500, which is what the right-hand graph is doing, you see that this manager nicely outperforms the replacement strategy in difficult markets without underperforming nearly so much when markets are rocking, creating a shallow V-shape or upward bend to the performance line. THIS is convexity.

This manager clearly has positive PAR, meaning that she improves the performance of your portfolio versus what you would have done with a passive replacement strategy, once you take into account both offensive and defensive stats. This manager is like a talented defensive catcher (i.e., a position where it’s important to play good defense) who is a so-so offensive player. That’s a classic player type, and there are plenty of teams who would find a spot on their roster for that.

There are dozens of different tools and well-known performance analytic statistics (Sortino ratio, Jensen’s alpha, upside/downside capture) that will do some variant of this PAR calculation for you, and they’re all designed to capture different aspects of convexity. This sort of exercise is the mother’s milk of consulting gigs, and every consultant in the world would look at this data and tell you that this manager is doing a Good Job.

Pretty exciting, right? Here’s a methodology that clearly works in professional sports and can be directly brought over to professional investing. It’s empirically driven and mathematically sound.

But it doesn’t work.

Or at least it doesn’t work anymore. Like so many other aspects of our investing lives, these mathematically sound and empirically driven efforts to answer the Good Job question for active management have collapsed under the chaotic gravitational pull of The Three-Body Problem.

In exactly the same way that Quality has been absolutely useless as an investment factor for the past eight and a half years, so have our traditional measurements of active manager skill.

The orange line in the chart below is the S&P 500 Index from 1998 to today. The white line and blue-shaded area is the HFRX Global Hedge Fund Index divided by the S&P 500 Index. It represents the relative underperformance or outperformance of hedge funds versus the S&P 500, and today we are at all-time underperformance lows. There is no convexity here! At least not in the aggregate. It skipped town in March 2009, just as the Central Bank Brigade rode in to save the day.

Managers who used to “capture” more upside than downside don’t. Managers who used to demonstrate convexity in their results don’t. They still have lots of stories to tell you about how they manage gross and net exposure, lots of stories to tell you about volatility and risk management, and lots of stories to tell you about thematic opportunities. Most still express a great deal of pride in their investment process.

I’m not saying that these “proprietary processes” will never work again. I’m not saying that they’re not working now. I’m saying that if they’re working, they’re working very very faintly. So faintly that you have to believe in the story to stay the course, because it’s sure not in the aggregate results. I’m saying that the processes and the skills and the performance convexity of professional active investors are swamped by the gravitational pull of $20 TRILLION of central bank balance sheets, as are the traditional tools we’ve used to measure all that. Because that’s the point of the Three-Body Problem – any algorithmic understanding of the system will fail to predict what’s next.

So what’s to be done? Do we just give up trying to answer the Good Job question? If our evaluative tools for active managers are non-predictive, do we just throw ourselves onto the waves of the S&P 500 and hope for the best? Because that’s what a lot of investors are doing, including giant pension funds who should know better, even though doing so is an active management decision of the first order!

Here’s the thing. Yes, It’s more difficult than ever to answer the Good Job question regarding active investment management. It’s also never been more important.

Because while I have no way to predict what’s next in the Three-Body System, I can tell you with absolute certainty that there IS a next, and it will NOT look like now.

Because you ARE the active manager when you select this passively managed fund over that passively managed fund, and you are not as good of an active manager as you think you are.

As wonderful as it would be for investors to style themselves as baseball general managers, poring over advanced performance statistics to pick this or that great fund manager in some sabermetric nirvana, that’s just not in the cards. We have to find a better way, a way to answer the Good Job question in a Three-Body system. Because we’re not getting away from active management even if we wanted to.

Our answer, I think, is to go back to first principles, to go back to the code of the Good Dog. The answer, I think, is in convexity, but not in the mathematical over-scientificized cartoon of the word.

The answer, I think, is in convexity as a philosophy.

Convexity as a philosophy is about identifying what you are particularly good at, and then executing on THAT. It’s the key to unlocking a much more stable notion of identity — a Good Dog’s notion of identity. Good Dogs know what they’re good at, and I don’t need to calculate a Sortino ratio to know if they’re doing a Good Job.

We can do the same with our evaluation of active managers. We can tell when an active manager is doing a Good Job. We can see it in her demeanor, we can see it in her temperament, we can see it in her bravery, both personally and professionally. Every Good Dog is a Brave Dog. It’s the same with investment managers. We can see it in her humility — the virtuous opposite of sinful pride. We can see it in her sense of shame when a behavior is not up to snuff. Not identity, behavior. There’s no shame in identity. Ever.

There’s a sine qua non for adopting convexity as a philosophy in evaluating active managers, and it’s as simple as it is difficult: courage, both personally and professionally. We’ve got to be Brave Dogs, too.

To be clear, the behavioral attributes associated with a Good Dog’s notion of a Good Job are a necessary condition for approving an active manager, not a sufficient condition. Sam the Sheltie does a Good Job, too, but I wouldn’t exactly recommend an accomplished squirrel herder as a must-have addition to your farm. Even Maggie the German Shepherd, who does a Good Job of protecting the farm and is a player everyone would want on their team, has “regimes” where her above-replacement performance vanishes. I’ll put it this way … she apparently dislikes chickens almost as much as I do, such that if you’re a fox and you want to chow down on a free range hen or two, picnic-style in the middle of a grassy field while Maggie sits there and watches you eat … well, come on over. And that gets me to the second sine qua non of adopting convexity as a philosophy in our manager selection — we must have the process and the fortitude to scale our active risk allocations up and down based on what is working, including the ability to take risk completely away from our managers. Maggie is a VERY Good Dog. But when the chickens are loose her risk allocation here at the farm goes to zero. We find protection somewhere else.

Convexity as a philosophy is also at the heart of how we improve ourselves and our children as citizens.

Always be yourself. Unless you can be Batman. Then always be Batman.

It’s maybe the funniest movie line I know. Why is this funny? Because we have made a political and social fetish out of identity, out of the New Commandment to ALWAYS BE YOURSELF. Unless you can be Batman.

At the same time, we’ve attached pride and shame to identity, rather than to behavior where they belong, training ourselves and our children to be absurdly self-assured and prideful, and yet existentially ashamed all at the same time. ALWAYS BE YOURSELF is the most powerful story we tell ourselves. And the most dangerous if attached to pride and shame wrongly understood.

We can tell ourselves a new story. A story, dear Brutus, where the fault is not in our stars, but in ourselves. As is the achievement. As is the honor.

Find your pack. Here and here and here are some ideas on how to do that. And then do a Good Job with your service to the pack, no matter how big, no matter how small. You’ll figure it out.

Every dog needs a job to make sense of its place in the world. So does every human.

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