Notes From the Road: Roadkill

Get well soon balloon

Most species do their own evolving, making it up as they go along, which is the way Nature intended. And this is all very natural and organic and in tune with mysterious cycles of the cosmos, which believes that there’s nothing like millions of years of really frustrating trial and error to give a species moral fiber and, in some cases, backbone.

This is probably fine from the species’ point of view, but from the perspective of the actual individuals involved it can be a real pig, or at least a small pink root-eating reptile that might one day evolve into a real pig.

— Reaper Man by Terry Pratchett (1991)


This is Part 2 of the multi-part Notes from the Road series, introduced with Bayes and the Boreen. The Series explores how popular, otherwise adaptive methods we use to develop theories about political and financial markets based on priors and lived experience can subject us to unexpected new risks. The series tells the story of a range of journeys in history, sports, the arts and nature to illustrate the sources of those risks.


If, as Ben has written, memes are self-sustaining ideas that live in the human brain, I think there’s one that may predate all of the rest: Only the strong survive!

It’s a dumb meme about how we think evolution works that has spread, ironically, because of the way evolution actually works. Despite growth in scientific literacy, the popular conception of evolution continues to celebrate the idea that better/stronger/smarter things will prosper, and worse/weaker/dumber things will fail. The reality is much less sexy. Evolution is the process whereby nature necessarily favors traits which improve the ability of an organism to suvive until it reproduces. The idea that we are successful because of objectively superior traits – because only the strong survive! – is an idea perfectly adapted to the human ego. But on almost no dimension would we have judged our mammal ancestors superior to the dinosaurs they outlasted. But outlast they did, because – by sheer luck – their traits were better adapted to a post-Chicxulub state of the world.

That last observation is an important one. When we consider evolution as it truly is, we still usually focus on the organism, or in an Epsilon Theory context, the idea or the investment strategy in isolation. An individual organism mutates a new trait, which either makes it more or less well-adapted to the current environment. If more, then over time the trait is more likely to propagate. If less, then organisms carrying the trait will probably die along with it.  But for all the value that there is in constant improvement of our processes and philosophies in similar ways, the survival of a species or idea isn’t just a function of its own changing traits – it’s a function of the changing states of the world and the people in it.

For our investment principles and strategies, like any organism, observing that evolution is both a function of the traits of our ideas AND changes in the state of the world reveals two types of risks to our models and frameworks for understanding it:

  • Type 1 – The False Positive: We think and act like our principles are based on immutable laws of nature. They aren’t, and we get a rude shock when the world changes.
  • Type 2The False Negative: We believe that principles others believe are immutable laws are only representative of some temporary state of the world. We try to predict the change in the world, and it never happens. We waste returns, fees and client goodwill in the process.

Evolution is a painful journey for the individual. There’s not much solace in our failures becoming Harvard Business School case studies that help the species – or other investors. We must find some kind of middle ground between allowing ourselves to become speedbumps to a change in the state of the world on the one hand, or victims to the coyotes who would tell us “This Time It’s Different” about every bit of normal variability in the world on the other. We have to find that middle ground in our non-investing lives, too. Which of our heuristics and principles for evaluating life decisions are objectively true, or are at least true enough? Which are adaptations to our past environments and experiences, and will those be relevant to our new situation? When we make big life decisions, are the priors we rely on, well…reliable?  In the end, we muddle through, and more often than not, make it up as we go along.

Incidentally, that’s exactly what I’m doing. Next week, it’ll be 27 hours with a 2- and 3-year old in a blue pickup on the 1,712 miles of Dwight D. Eisenhower’s asphalt dream between old home and new. In honor of this journey, since we’re talking about growth, evolution and risk, and since I’m moving up to a part of the country where I won’t be able to talk about this sort of thing in polite company any more, I figure it’s as good a time as any to write about roadkill. And that’s saying something, because it’s always a good time to write about roadkill.

Full disclosure. If you’ve read this far, you’ve read the word ‘roadkill’ five times: once in Ben’s email, once at the top of this essay, twice in the prior paragraph and once in this sentence. You clicked on it, and I kind of feel like you’re already in for at least a penny here. But if you were squeamish about Ben’s disgusting tick infestation picture from a couple months ago, this one may not be for you.


Profiles in Roadkill: Dasypus Novemcinctus

Now that we’ve gotten all that out of the way, we can start talking vehicular critterslaughter. Allow me to introduce you to someone special.  This handsome fellow on the left is a nine-banded armadillo – one of the three state mammals of Texas, because unlike the boring-ass state you live in, Texas gets THREE state mammals. Take that, James Madison and your exquisitely reasoned Federalist Paper 62. Armadillos are remarkable little creatures who followed an unusual and narrow genetic path that has produced some of the strangest land mammals alive today. In addition to its signature armor plating, the armadillo reproduces from an egg which separates into four parts after fertilization. That means that nearly all litters consist of 4 identical creatures of the same sex. What’s more, the implantation of that fertilized egg is typically delayed by the mother by several months to better align with the spring season. Very handy, that.

The armadillo can inflate its intestines to float. It can hold its breath for six minutes to submerge. And that armor really is as tough as we think it is. Tough enough to defeat a .38 revolver. Like its closest cousins, the anteater and tree sloth, the armadillo is a marvel of specialized adaptations. One of evolution’s many weird, slimy miracles.

Also, when an armadillo sees headlights, it gets so terrified that it jumps straight up in the air and gets slammed by a car that would otherwise have passed right over it.


Profiles in Roadkill: Odocoileus virginianus

The armadillo, however, probably isn’t the animal most people (outside of Texas, anyway) think of when they think of victims of automobile-related critter flattenings. In honor of the trek we will take through the beautiful and too-unfairly-maligned state of Mississippi (which is also probably better than your state since it has two state land mammals), it is time we recognize the famousest of roadkill, the white-tailed deer. So common is the sad sight of one of these beautiful creatures along US highways that it causes the otherwise stonehearted, rage-filled American motorist to descend into our country’s unique style of gallows humor. Get well soon, gross deer. Get well soon.

Like the armadillo, evolution has gifted the white-tailed deer with extreme traits that are well-adapted to the challenges it faced during its emergence as a species. First, it is a remarkable jumper. While deer fences tend to be around eight feet tall, the average individual can actually jump somewhat higher than that, in some cases as much as 12 or even 15 feet. Somewhat less when it needs to jump forward and not just up.

Second, probably because of the adaptive benefits of a better field of vision for spotting predators, deer’s eyes are positioned closer to the sides of their head than the front. That means that deer, like many other prey animals, sacrifice binocular vision and depth perception to, you know, get eaten less by things behind them and to their sides. The downside is that it is more difficult for deer to judge distance and the depth of objects in front of them. Incidentally, in addition to being particularly stupid, this is one of the reasons why white-tails don’t always jump over fences they almost certainly could – poor depth perception means that they can’t be sure if they’re going to clear it.

Third, whether because of the need to manage temperatures and heat, to avoid predators, or other reasons they keep to themselves, thank you very much, white-tailed deer are crepuscular, which means they are most active in the twilight hours of dawn and dusk. That adaptation means that their vision is attuned to modest levels of light.

Like the armadillo, the combination of these natural talents has done wonders for making white-tailed deer one of the most successful and widely distributed mammal species in the world.

It also means that when a deer leaps into a road, it spots your distant car in its remarkable peripheral vision, turns its head, is blinded by your headlights because of the attunement of the rods in its eyes to take in more light, and because of its lousy visual acuity and depth perception, can’t make out the closing distance of your vehicle until it’s too late, at which time it leans upon its remarkable leaping abilities so that it can take out your windshield because screw you AND your Volvo.


Profiles in Roadkill: Sciurus carolinensis

Although the deer is the most iconic roadkill animal, it’s not the most common. The most common is the state mammal of one of the most beautiful states in our fair union, but one that admittedly only manages to have a single state mammal, so take my kind words about its trees, mountains and coastlines for the damning faint praise that they are. It’s your time to shine, Interstate 85 and North Carolina.

The 1993 data from an ongoing survey of roadkill (weirdly created for schools as a testing ground for teaching the scientific method) reported just over 750 squirrels in its sample. If anyone is curious, there were only 308 raccoons and 4 coyotes. The noble possum comes in second, at 348. Squirrels are the undisputed kings of roadkill, and yes, the extremely disappointing state mammal of the State of North Carolina. By the way, this really IS disappointing, because North Carolina could have selected one of its many legitimately interesting and endangered/threatened species, like the Carolina Northern Flying Squirrel. The state is also one of the last homes east of the Mississippi for the Townsend’s big-eared bat, which adapted a whispered form of echolocation that probably serves as a countermeasure to the active sonar jamming skills of its primary prey – moths.

Now, obviously some of the reason so many squirrels become double-thumps in the road is because – despite my efforts as a kid with a BB-gun – there are a lot of squirrels. But that’s kind of the point. There are a lot of squirrels because squirrels are a very successful species. Part of why they are a very successful species is because they are very successful at avoiding predation, mostly by hawks and other birds with a taste for tree-rat.  Part of the reason they are so successful at avoiding predation is that they adapted an instinctive tendency to run in seemingly random zig-zag motions that involve unpredictable changes in both speed and direction. Very good defense against a hawk flying at high speed toward a fixed point.

Not so much against a speeding teenager driving his mom’s Yukon.


All three of these animals are incredibly successful and still growing their geographic footprint. All three are incredibly well-adapted to the challenges that they faced over the course of their evolution. All three are well-prepared for the challenges they face in most of their daily lives. All three get dead real quick when their evolutionary strengths are transformed into circumstantial weaknesses.

Part of the reason I wrote this, the second note in this series, was to make you look at that hilarious and morbid roadside pizza party deer. That and to pursue some tortured analogy to compare you, dear reader, to roadkill. But there’s an important investment lesson here, too: Survival is the only way we measure the success of an adaptation, and the species that treats past adaptations as timeless and universal – as laws of physics – will go extinct.  

The trick is in knowing what, among all the things we do as investors, reflects timeless and universal principles, and what reflects our adaptation to states of the world which will change. It’s not always easy to tell the difference.

Timeless and Universal Principles

For my part, I think timeless and universal principles of investing must be either tautologies or generalized reflections of human behavior. Heuristics which are based on states of the world (e.g. I like this asset class because it is cheap, I favor this sector because of its growth characteristics, I’m concerned about this country because of higher-than-usual geopolitical risk) don’t really fit. Philosophies which are driven by views on the superiority of certain constructs (e.g. asset classes, instruments, etc.) are similarly ephemeral. I think there are really four timeless and universal principles, and we’ve written about each before:

  1. 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 [1]. – Whom Fortune Favors
  2. We must be supremely confident that we have information about the returns on various investments to justify decisions which reduce the diversity of our sources of return.You Still Have Made a Choice
  3. Humans have evolved to demonstrate preferences for certain types of investments and returns. Those preferences – and the fact that other humans will shrewdly seek to exploit those preferences – will influence returns.The Myth of Market In Itself
  4. Taxes, fees and transaction costs will reduce returns.Wall Street’s Merry Pranks

I think it’s a good framework. You may not, in which case you should replace it with what you think these rules are. Or y’know, by sending me an email telling me how stupid I am. Both are fine. But identifying these rules means acknowledging that all of our other philosophies are either successful adaptations OR new things we’re trying out because we are guessing they will be better suited for some future state of the world. After all, if we’re going to update our Bayesian estimates, we’ve got to have some kind of experiment.

It isn’t hard to identify beliefs and strategies that look well-adapted over the last decade, by which I mean investment strategies whose reputations have survived. Structurally owning more assets in U.S. financial markets looks well-adapted during this age of the world. So has owning more stocks in technology companies. Believing that there is no need for an investor to have a financial adviser seems like a very well-adapted trait. Aversion to any strategies which try to pick which securities will outperform. Keeping things simple with a 60/40 portfolio of stocks and bonds. Leveraged strategies. Aversion to, skepticism about and usually derisive attitudes towards hedge funds. Those of us who saw what worked in 2009 and 2010 and stuck with it as the new normal probably have a pretty confident assessment of some of our adaptations. More than a few of us and our clients have adopted some of the above as heuristics – our rules of thumb around which we generalize our investment beliefs into process.

What does treating well-adapted-looking traits like permanent states of the world look like? Below is one innocuous-looking example from social media marketing. I’ve removed any author’s name to protect the innocent.

There are good principles in here. But look at these more closely to see temporarily well-adapted traits creep in. A decade of dominance from US stock markets and low volatility has created a world of investors who now think that saying “keep things simple” and “avoid excessive diversification”, which are smart-sounding dog whistles for “just buy US large cap ETFs”, is timeless and universal advice. It’s not. And it’s going to get a lot of investors hurt.

Unfortunately, the memeability of common sense! advice like this is is exactly how an adapted trait evolves into a species-defining characteristic. Survival and reproduction. And then extinction.

Identifying the line between timeless principles and adaptations gets even harder over very long periods. 30 years. 50 years. Owning more bonds than our timeless principles might otherwise recommend. Relying on those same bonds to be diversifying against stocks. Knowing that commodities are not really investable, that real assets should just be a personal asset. Trusting that risky assets will always generate positive returns over a long enough horizon. As periods get longer, our confidence that our heuristics are not situational adaptations, but timeless and universal principles, grows.

All of this is Roadkill thinking. Oh, we may not get run over right away. It may never happen – during our investment lifetimes, anyway. We may go quietly in our sleep like so many armadillos, convinced that we adapted to survive cars just because we never got run over. But believing that the strategies we developed are timeless and universal strategies just because they’ve worked for us during our careers so far, or because they have worked for others for what feels like a very long period of time, is Roadkill thinking.

This first kind of Roadkill thinking is of the Type 1 error variety I mentioned earlier – false positives when identifying timeless and universal truths about markets.

Type 2 errors in Roadkill thinking are usually the more pernicious. It’s easy to think that the solution to our fears that an investment environment may be changing is to be creative, to throw a bunch of ideas at the wall, because that’s what we think adaptation looks like. And it is, in a way. But while adaptation through (mostly) random mutation works at the species level, at the individual level, it is literally murder. If our adaptive strategy is trying to time the turn in value or the market top, we will probably fail individually. If our adaptive strategy is to hold a quarter of our portfolio in cryptocurrencies to insulate us against what’s next, we will probably fail individually. If our adaptive strategy is to drain the swamp by…sorry, lost my train of thought, there. And sure, our failures will inform and improve the odds of success of other investors at large. A fat lot of good that does us. There’s a reason why coyotes with no skin in the game are so drawn to fields where they can promise disruption, new ideas, and high risk/high reward opportunities: because they share in all the upside of the aggregate while subjecting us to the risk of individual ruin along the way.

What does matter is that pursuit of these strategies often comes at the explicit or implicit expense of the ideas that really are permanent. We have finite dollars and finite attention, and our attempts to do something about environments that confuse us are usually distractions. In the same way that we’re probably all Coyotes from time to time, I think we’ve got a lot of Roadkill in us, too. I certainly do, anyway. There’s no extricating it from our nature, but as with so many things, simply acknowledging it goes a long way toward being mindful of its influence:

  1. Roadkill doesn’t know what its timeless and universal investment principles are.
  2. Roadkill doesn’t discern between temporarily effective adaptations and timeless principles.
  3. Roadkill randomly tries new adaptations even when they violate timeless and universal principles.

If we would not be Roadkill – or worse, food for coyotes – we would do well to subject our priors to constant challenge. What assumptions are we making about our investments, intentionally or unintentionally? What priors are built into our portfolio construction and investment selection methodologies? Are they always true, or maybe artifacts of an environment or industry convention?

For my part, were I sitting on an investment committee during a period of slowing in population growth, after a sustained long-term rally in multiple types of risk assets, following an extended period of falling interest rates, in the face of historically significant household and government debt, with increasing abstraction sitting between valuations and value, I would hold very loosely to all but my core principles. During every regular review, I would subject my conventions – sectors, style definitions, benchmarks, asset class definitions, risk measurement methodologies, and the like – to scrutiny.

More to the point, when we write about Narrative, we write in part because we believe that Common Knowledge about investment strategies and investable assets is part of what makes them work. This is our theory, and not a fact, but I think that Narrative analysis can inform earlier, less individually risky attempts at adaptation as environments change. Big if true. And I think it is.

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We had a little fun at North Carolina’s expense, but it’s a wonderful state and a wonderful place with a lot of people that are hurting – and will be hurting – for a long time. From my experience with Hurricane Harvey in Houston, there are few organizations that do as much good as the United Way. If you can, consider giving now to the United Way of Coastal Carolina. Or if you want to make amends for laughing at the balloon deer, the Outer Banks SPCA and the Dare County Animal Shelter will be in desperate need of help over the next few weeks.


[1] This is, incidentally, why I am not one of those who thinks that volatility is a terrible ex ante way of thinking about risk. If price sensitivity matters to individual investors – and it does – it matters to how the return investors will demand for taking that risk, even if that perception is completely irrational and they should be thinking about “permanent impairments to capital” or some other phrase that has survived because it sounds clever in marketing materials. My experience with investor behavior also tells me that unrealized returns often become realized when they’re big, negative numbers.


A Taxonomy of Humans, Evolution and Aliens (by Silly Rabbit)

Netflix recommendation system

High level, but still interesting, overview of how Netflix recommendation system works from Wired. Short answer: “The three legs of this stool would be Netflix members; taggers who understand everything about the content; and our machine learning algorithms that take all of the data and put things together.” The tagging piece is probably the most interesting (“dozens of in-house and freelance staff who watch every minute or every show on Netflix and tag it. The tags they use range massively from how cerebral the piece is, to whether it has an ensemble cast, is set in space, or stars a corrupt cop”) and point to the continued need for ‘human-in-the-loop’ content tagging for machine learning systems.

A taxonomy of humans according to Twitter

Sam Levine, an artist and programmer from Brooklyn, scraped Twitter’s ad creation page to produce a full list of all user segments, their names, descriptions and user count: a taxonomy of human beings according to Twitter and its data brokers. My favorite tag: “Buyers of deli bulk meat.”

Emergent physics behind evolution

Fascinating interview with Nigel Goldenfeld, Director of the NASA Astrobiology Institute for Universal Biology, on Seeing Emergent Physics Behind Evolution:

“People tend to think about evolution as being synonymous with population genetics. I think that’s fine, as far as it goes. But it doesn’t go far enough. Evolution was going on before genes even existed, and that can’t possibly be explained by the statistical models of population genetics alone. There are collective modes of evolution that one needs to take seriously, too. Processes like horizontal gene transfer, for example.”

The aliens on Earth

Continuing on the theme of evolution, this is a fascinating piece on ctenophores as aliens on earth:

“Leonid Moroz has spent two decades trying to wrap his head around a mind-boggling idea: even as scientists start to look for alien life in other planets, there might already be aliens, with surprisingly different biology and brains, right here on Earth. Those aliens have hidden in plain sight for millennia. They have plenty to teach us about the nature of evolution, and what to expect when we finally discover life on other worlds.”

Chinese science fiction

And finally, on the subject of aliens, I can not recommend strongly enough Liu Cixin’s The Three-Body Problem ( 三体 ) science fiction trilogy, which recently won a Hugo Award. Deeply intelligent and expansive science fiction on the scale of Asimov’s Foundation series. Without giving too much of a spoiler, my favorite quote is from the second book in the trilogy (The Dark Forest) which turns Johann Wolfgang von Goethe‘s “If I love you, what business is it of yours?” into “If I destroy you, what business is it of yours?”

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Algorithmic Complexes, Alpha Male Brains, and Winnie the Pooh (by Silly Rabbit)

Massively complex complexes of algorithms

Let me come straight out with it and state, for the record, that I believe the best current truth we have is that we humans, along with all other living beings, are simply massively complex complexes of algorithms. What do I mean by that? Well, let’s take a passage from the terrific Homo Deus by Yuval Noah Harari, which describes this concept at length and in detail:

In recent decades life scientists have demonstrated that emotions are not some mysterious spiritual phenomenon that is useful just for writing poetry and composing symphonies. Rather, emotions are biochemical algorithms that are vital for the survival and reproduction of all mammals. What does this mean? Well, let’s begin by explaining what an algorithm is, because the 21st Century will be dominated by algorithms. ‘Algorithm’ is arguably the single most important concept in our world. If we want to understand our life and our future, we should make every effort to understand what an algorithm is and how algorithms are connected with emotions. An algorithm is a methodical set of steps that can be used to make calculations, resolve problems and reach decisions. An algorithm isn’t a particular calculation but the method followed when making the calculation.

Consider, for example, the following survival problem: a baboon needs to take into account a lot of data. How far am I from the bananas? How far away is the lion? How fast can I run? How fast can the lion run? Is the lion awake or asleep? Does the lion seem to be hungry or satiated? How many bananas are there? Are they big or small? Green or ripe? In addition to these external data, the baboon must also consider information about conditions within his own body. If he is starving, it makes sense to risk everything for those bananas, no matter the odds. In contrast, if he has just eaten, and the bananas are mere greed, why take any risks at all? In order to weigh and balance all these variables and probabilities, the baboon requires far more complicated algorithms than the ones controlling automatic vending machines. The prize for making correct calculations is correspondingly greater. The prize is the very survival of the baboon. A timid baboon — one whose algorithms overestimate dangers — will starve to death, and the genes that shaped these cowardly algorithms will perish with him. A rash baboon —one whose algorithms underestimate dangers — will fall prey to the lion, and his reckless genes will also fail to make it to the next generation. These algorithms undergo constant quality control by natural selection. Only animals that calculate probabilities correctly leave offspring behind. Yet this is all very abstract. How exactly does a baboon calculate probabilities? He certainly doesn’t draw a pencil from behind his ear, a notebook from a back pocket, and start computing running speeds and energy levels with a calculator. Rather, the baboon’s entire body is the calculator. What we call sensations and emotions are in fact algorithms. The baboon feels hunger, he feels fear and trembling at the sight of the lion, and he feels his mouth watering at the sight of the bananas. Within a split second, he experiences a storm of sensations, emotions and desires, which is nothing but the process of calculation. The result will appear as a feeling: the baboon will suddenly feel his spirit rising, his hairs standing on end, his muscles tensing, his chest expanding, and he will inhale a big breath, and ‘Forward! I can do it! To the bananas!’ Alternatively, he may be overcome by fear, his shoulders will droop, his stomach will turn, his legs will give way, and ‘Mama! A lion! Help!’ Sometimes the probabilities match so evenly that it is hard to decide. This too will manifest itself as a feeling. The baboon will feel confused and indecisive. ‘Yes . . . No . . . Yes . . . No . . . Damn! I don’t know what to do!’

Why does this matter? I think understanding and accepting this point is absolutely critical to being able to construct certain classes of novel and interesting algorithms. “But what about consciousness?” you may ask, “Does this not distinguish humans and raise us above all other animals, or at least machines?”

There is likely no better explanation, or succinct quote, to deal with the question of consciousness than Douglas Hofstadter’s in I Am a Strange Loop:

“In the end, we are self-perceiving, self-inventing, locked-in mirages that are little miracles of self-reference.”

Let’s accept Hofstadter’s explanation (which is — to paraphrase and oversimplify terribly — that, at a certain point of algorithmic complexity, consciousness emerges due to self-referencing feedback loops) and now hand the mic back to Harari to finish his practical thought:

“This raises a novel question: which of the two is really important, intelligence or consciousness? As long as they went hand in hand, debating their relative value was just an amusing pastime for philosophers, but now humans are in danger of losing their economic value because intelligence is decoupling from consciousness.”

Or, to put it another way: if what I need is an intelligent algorithm to read, parse and tag language in certain reports based on whether humans with a certain background would perceive the report as more ‘growth-y’ vs ‘value-y’ in its tone and tenor, why do I need to discriminate whether the algorithm performing this action has consciousness or not, or which parts of the algorithms have consciousness (assuming that the action can be equally parallelized either way)?

AI vs. human performance

Electronic Frontier Foundation have done magnificent work pulling together problems and metrics/datasets from the AI research literature in order to see how things are progressing in specific subfields or AI/machine learning as a whole. Very interesting charts on AI versus human performance in image recognition, chess, book comprehension, and speech recognition (keep scrolling down; it’s a very long page with lots of charts).

Alpha male brain switch

Researchers led by Prof Hailan Hu, a neuroscientist at Zhejiang University in Hangzhou, China have demonstrated activating the dorsal medial prefrontal cortex (dmPFC) brain circuit in mice to flip the neural switch for becoming an alpha male. This turned the timid mice bold after their ‘alpha’ circuit was stimulated.  Results also show that the ‘winner effect’ lingers on and that the mechanism may be similar in humans. Profound and fascinating work.

Explaining vs. understanding

And finally, generally I find @nntaleb’s tweets pretty obnoxious and low value (unlike his books, which I find pretty obnoxious and tremendously high value), but this tweet really captured me: “Society is increasingly run by those who are better at explaining than understanding.” I pondered last week on how allocators and Funds of Funds are going to allocate to ‘AI’ (or ‘ALIS’). This quote succinctly sums up and generalizes that concern.

And finally, finally, this has nothing to do with Big Compute, AI, or investment strategies, but it is just irresistible: Winnie the Pooh blacklisted by China’s online censors: “Social media ban for fictional bear follows comparisons with Xi Jinping.” Original FT article here (possibly pay-walled) and lower resolution derivative article (not pay-walled) by inUth here. As Pooh says “Sometimes I sits and thinks, and sometimes I just sits…”

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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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