Investing Books For A Teenager

A friend asked for some recommendations.

My nephew is 16 and wants to “get rich in the stock market”. He knows nothing. Is decent at school/math. I want to send him five books. He probably won’t have the patience for stuff that is too dry or dense.

My response:

I think it’s helpful to get a glossary understanding of concepts in the first place. Khan Academy is great for that. Of course that it just to explain terms but my book recs would have more to do with think of the markets as competitive games with prices as point spreads.

To that end my recs for core reading:

  • The Most Important Thing by Howard Marks
  • Fooled By Randomness by Nassim Taleb
  • The Psychology of Money by Morgan Housel
  • 4 Pillars of Investing by William Bernstein
  • We both agreed Moneyball by Michael Lewis fits beautifully in this context so that would round out the list.

For a bit more advanced I’d recommend:

  • The Little Book That Beats The Market by Joel GreenblattThe reason this book is great besides being short is that it a hands-on demonstration of how to have a process and marries understanding core business math with an investing process (sorting, filtering, measuring and normalizing). There’s many implementations of the strategy floating around the web with modifications so if he wants to dig there’s plenty of fertile soil. While the vanilla strategy is mined into oblivion at this point, the real objective is to understand the process because that’s universal and applies to trading as well as investing. It’s a mental template.
  • The Accounting Game: Basic Accounting Fresh from the Lemonade Stand by Darrell Mullis and Judith OrloffI read this a few years ago and it’s a hand-on, easy way to learn the basics of accounting. It explains how balance sheets, income statements, and cash flow statements interconnect. It describes how you book items and the tradeoffs involved. It helped me appreciate how much judgement is actually included in accounting as well as how you can tell different stories with the way you choose to do accounting. Accounting feels like a subject I’d enjoy which is a sentence I never thought I’d say. I took my own notes here.

For my other collections see:

The Options Cage

Collecting options is freedom. Freedom is the most revered American ideal. In an orgasm of deductive logic, flowing straight from that idea is most Americans’ prized ambition — “financial freedom”. Sparkling with alliteration, the phrase has led countless dreamers to spend weekends at conferences learning the latest fashion for deriving “passive income”. I’m not judging this goal. To some extent, we all have it in some form. But be honest. When someone uses this phrase earnestly, you kind of want to die of boredom.

I’ll tell you why. Because it’s code for “I’m waiting to live”. As if your life needed rehearsals or prerequisites. This is the person who asks a genie for “a thousand more wishes”. Just delaying the bull and its horns.

Anne-Laure Le Cunff writes:

We are obsessed with optionality. Not sure what to do with your life? Most people will tell you to get a degree. Not quite sure what to do with this degree? Go to grad school. Still not quite sure? Get a consulting role at a big firm so you can decide what kind of job you enjoy. And so on and so forth. We fall prey to the optionality fallacy. As Erik Torenberg puts it, it can be “like spending your whole life filling up the gas tank without ever driving.”

She continues:

The problem is not with optionality itself. The problem is that we tend to assume optionality is built by keeping as many doors open for as long as possible; by staying on the main road for as far as can go instead of taking the risk of making a wrong turn.

This is familiar to anyone who knows a stingy rich person. When options become an end in themselves, it becomes harder to exercise or spend them.

When Options Are Self-Defeating

Having too few options is desperate. Too many options is crippling. Think of your wardrobe. You probably lie somewhere in between a 1-outfit-per-weekday minimalist and a  hoarder. Having a few suits or dresses to choose from based on the season is reasonable. But if having clothes you’ll never wear forces you to rent a larger apartment, it’s a high price to pay to hedge the “what if I get invited to the Oscars and need a ball gown” scenario. The hint to the option obsession is in the previous sentence — hedge. In fact, the logic of option-seeking is inherited from finance brain disease. But unlike financial options which carry an explicit “theta” or time decay, life options have opaque costs.  We can use finance logic to just as easily argue against option hoarding.

“Innumerate Cowards”

I’ll turn the heavy lifting to Byrne Hobart who describes option obsession as not only a “bad deal financially” but “utterly cowardly”. In one of his all-time lines, Byrne spits:

One might cynically describe the MBA’s dream as not so much “Have lots of optionality” as “Own a call option on the proceeds of the continued sale of put options.”

Byrne is actually underselling how cynical this is. What he calls cynical, many fund folk would describe as “great work if you can get it”. The dream is often literally the business of the MBA. Byrne describes mundane examples of option-collecting as well. Holding excessive cash, the “open calendar”, avoiding intimate relationships. These are all ways to preserve optionality. But if taken too far are cowardly:

Many otherwise smart and well-adjusted people have talked themselves into being the Ebenezer Scrooge of optionality, always hoarding the ability to do something later, never actually doing anything when “later” arrives, and giving up a lot in the process.

And when it comes to options, there’s always that nagging question of price:

Ultimately, there’s a finite net amount of optionality in the world, and it’s zero: every time you pay for the option to buy or sell something in the future, you need a counterparty. If there’s a bias towards being systematically long something with a total net supply of zero, the buyers will tend to overpay.

The Accidental Complacent

If the financial argument doesn’t suit you consider a behavioral one. Professor Mihir Desai eloquently describes how the safety of having many choices gradually neuters us. His tone is less aggressive than Byrne’s. Mihir is impartial as to the net effect of risk-averse paths on our happiness, but his words are a warning to those who find self-castration impermissible.

The emphasis are mine:

This individual has merely acquired stamps of approval and has acquired safety net upon safety net. These safety nets don’t end up enabling big risk-taking—individuals just become habitual acquirers of safety nets. The comfort of a high-paying job at a prestigious firm surrounded by smart people is simply too much to give up. When that happens, the dreams that those options were meant to enable slowly recede into the background. For a few, those destinations are in fact their dreams come true—but for every one of those, there are ten entrepreneurs, artists, and restaurateurs that get trapped in those institutions.

Of course, this is not a pitiable outcome. And in fact, maybe those serial options acquirers are simply masking a deep risk aversion that underlay their affinity for optionality. Even if not explicitly stated, optionality was always the end rather than a means to an end.

In fairness, these optionality-obsessed professionals often wind up happier than the other type I’ve become accustomed to seeing in my office: the lottery ticket buyers. These individuals are just one payday away from securing the resources they need to begin their work toward their true ambition, be it political, civic, or familial. They believe that one Silicon Valley startup or one stint at a hedge fund will allow them to begin their true journey.

While the serial option and lottery ticket buyers seem like different creatures, they are, in fact, close cousins. Both types postpone their dreams and undertake choices that they think will enable their dreams. But they fail to understand that all of these intervening choices will change them fundamentally—and they are, in fact, the sum total of those choices.


While this post is more concerned with our individual choices, it’s worth mentioning that there intellectual circles in which the collective obsession with options reflects a deeper malaise about our futures. Our society is curling itself in a shell of optionality as a reaction to a more uncertain world. You may recognize this as one of Peter Thiel’s primary laments — indefinite optimism. Thiel’s criticism of our incremental approach to progress is cast in relief to the US in the wake of its triumph in WWII.

Scott Alexander, in his review of Thiel’s Zero To One, explains:

But Thiel says the most successful visionaries of the past did the opposite of this. They knew what they wanted, planned a strategy, and achieved it. The Apollo Program wasn’t run by vague optimism and “keeping your options open”. It was run by some people who wanted to land on the moon, planned out how to make that happen, and followed the plan.

The discourse around stagnation or lack thereof falls under the topic of “progress studies” if you want to follow the breadcrumbs. I wanted to point out that speculating on the link between option lust and human advancement is a thing (of course it is).

Let’s return to the use of options in your individual life.

Exercising Options

Options are like an extra room in your house. The cost of the extra space is not marginally excessive and can pay off in unforeseen circumstances. Like if your friend needs a place to stay or if the stork forgot to take you off its mailing list.  But you don’t want to go full McMansion. Instead, let’s think about how to use the space we have better. Let’s explore strategies for exercising options, not collecting them.

Understanding The Stop-Loss Method

Financial options are contractual. They have “hard” optionality. We can replicate financial options by employing a stop-loss strategy. To do this, we need to pre-commit to cutting our losses once our self-defined threshold (the “strike price”) is breached. This is “soft” optionality because it relies on our discipline as opposed to a contract. In the context of investing, soft optionality is inferior because our discipline is uneven and we are exposed to gap risks. But when it comes to life, the stop-loss can be preferred. Byrne argues that while the payoff diagram is the same, the stop-loss method forces you to actually do stuff. The key to this is fortitude. Byrne argues that fortitude is a muscle you can train by re-framing your failures as learning experiences. If you are able to treat sunk costs as, well, sunk then you can just think of them as tuition. This is both philosophically and practically different from the cowardly option collector.

Here’s an example.

  • Cowardly option-collector strategy

    You’ve been saving for years, imagining that you will one day leave the rat race and start a business. Notice, that I didn’t say a bakery or a bar. No, you aren’t even that specific. You are saving for the most open-ended option. A “business”.

  • Stop-loss strategy

    You start a side-hustle in your spare time. You allow yourself a fixed amount of hours and expenses to reach a milestone. If you don’t make it, you pre-commit to cutting bait. No regrets.

The cowardly method saves you time and energy. Instead of doing work on the side you save more money and have no risk. But you also don’t learn how to build, sell, hire, manage in ways you are not used to. These new skills are options in themselves. They can enhance any resume. You will likely discover a pivot as you begin to dig. By exercising options in relatively low-stakes settings along the way, you improve your ability to exercise options more effectively when the stakes are higher.

Enabling Fortitude

I believe that collecting options and actively exercising them along the way is a more full way to live than passively collecting options that you may not even know how to exercise in the future. The stop-loss method resonates. But since it rests on fortitude is not easy. Marching headfirst into winds of fear and potential embarrassment is hard. I will share 2 mental hacks for lowering the stakes. The winds are not as strong as they seem.

2-Way Doors

Reversible decisions are 2-way doors.  Sure, it can hurt to go back to an old job. You might not get the same pay. Your ego will be bruised. It’s a risk for sure. But a survivable one. What is the point of your surviving anyway if you can’t take survivable risks? Don’t underestimate how many decisions are reversible.


Recently I have gravitated to the idea of multiple lives. I’ve seen the idea expressed in overlapping contexts which makes it even more compelling. I first noticed it in how Josh Waitzkin, the chess prodigy, who later turned his attention to martial arts, surfing, and coaching embodied a serial approach to life. Every 5 to 10 years, he would undertake a new life. George Mack’s thread described Waitzkin’s emphasis on focus as a tool to live accomplish this. I’ve seen Marc Andreesen espouse going deep as a higher-yielding use of time. For example, if you choose to do open source work recognize it’s better to make major contributions to one project (as opposed to minor contributions to multiple projects). When you combine Andreesen and Waitzkin’s wisdom you find a philosophy that is more akin to “going all-in” rather than collecting options.

What does this have to do with enabling fortitude? It offers a contrast to safety. It reminds you that mastery and depth are rewards in themselves. And that you can exercise options serially, especially if you are willing to cut out distractions. It’s permission to focus on the quality of experience, not quantity. There’s almost a samurai honor to it that increases the consolation prize if you fail conventionally. Internalizing an appreciation for depth and craft rewards the journey, not the terminal payoff that option-collectors can’t turn their gaze from.

You don’t only live once. You don’t need to keep insuring against FOMO. You can choose strength.

Anne-Laure makes it practical:

One day you will be dead, but it takes about seven years to master something. If you live to be 88, after age 11, you have 11 opportunities to be great at something. Most people never let themselves die and cling onto that one life. But you can spend a life building things, another life writing poems, and another life looking for facts. You have many lives. Each of them is an opportunity to try something new and increase your optionality. Live them.

Avoid Upside Decay

The logic of options love rests on the idea of non-linearity. The payoffs are dominated by extremely low-probability, high magnitude events. It would be a shame to discover that these options you’ve collected have a much smaller upside than you believed. Unlike the random gyrations of a stock, you can influence the value of your options. Since you plan to exercise and not just collect options you should make sure you maximize what is under your control.

The key to this is to never take your reputation for granted. If your character cannot be trusted you will not be able to exercise your options or you will find the upside to be much smaller than you imagined. In Upside Decay: Why Some People Never Get Lucky, Brian Lui lays out a framework based on strong and weak ties. You can think of strong ties as contractual while weak ties are informal.

Strong ties are conspicuous. Weak ties are inconspicuous but numerous, and help in unexpected ways. When weak ties are activated, they can be more helpful in aggregate than strong ties. But weak ties will not help an unvirtuous organization! Weak tie assistance is voluntary and altruistic. This means that they only help those they think are virtuous. Without weak ties, organizations resort to strong ties and hard assets. This leads them to adopt a mercantilist approach. Their zero-sum mindset alienates others and makes them even less virtuous, because their positive-sum actions are now viewed suspiciously by others. Left with no choice but to double down on their zero-sum approach, they’ll antagonize all their weak ties and enter upside decay. This also explains why their good luck disappears but they don’t suffer much additional bad luck. Weak ties mostly aren’t motivated enough to hinder an unvirtuous organization, but they’ll gladly refuse to help.

Avoiding upside decay is simple but difficult. The organization needs to build a virtuous culture that leads to a positive feedback loop. At the same time, it needs to punish bad actions that have short-term benefits. This is hard because investments in a virtuous culture have no visible effect at the start, so they will tend to be unrewarded. Punishing unvirtuous actions is also difficult because the bad actor can point to the tangible benefits, while the long-term upside decay is invisible. It must be vigilantly enforced from the very top of the organization.

Go back and re-read the excerpts and insert yourself in place of “organization”. You can destroy your upside with one act of reputational suicide or by an accumulation of minor slights. The perceived gain from each of those tiny overreaches is invisibly offset by a diminished mass of right tail possibility. And that will cost you far more in the long run (possible counterpoint: I wonder if the age of grift we are in is a bet on weak ties becoming less effective as fungible avatars and more distributed end markets disintermediate reputation from actions. That or the price you get to sell your reputation is especially high. Call me old-fashioned for wanting people to come to my funeral).

A nice example of someone thinking about ways to not just avoid upside decay, but actively costing themselves dollars today in an effort to increase it is Ungated’s Rob Hardy. In Transitioning To The Gift Economy, he explains why giving away his work for free will pay off later. This is an active bet on the value of weak ties as opposed to strong ties. This is not surprising. We live in a world where digital (content, information, software) and financial supply is plentiful. Curation and trust become the complement that goes up in value.


Options themselves are not problems. You need them. The problem can arise when you lose sight of why you want them. It’s understandable.  Life is messy. We can drift in the wind for long periods.  Sometimes collecting options is the most legible thing to do. Maybe anything else is too hard right now. If so, keep in mind:

  • Options decay

    If you are in “explore” (as opposed to “exploit”) mode, name that state. You are in an option-collecting holding pattern. Remember to keep this transitory. Don’t let your life pass without acting. Ask yourself, “what is going to change in the future that will compel me to exercise my option?”

  • Opportunity costs are real

    Remember, when you acquire one option (like pursuing a grad degree) you forgo others. In fact, the options with well-marked signs usually lead to well-marked places. If that happens to bother you, don’t pursue the wrong ones.

  • Practice exercising options

    Remember the stop-loss method. The cost of failure is tuition but you will always salvage self-education and self-knowledge.

Option Lenses

If “high” was expensive and “low” was cheap then trading would be easy. I’ve discussed this tension in:

I was recently asked the following question:

Hey Kris, got a beginner question for you if you have some time. Why do people recommend selling ATM spreads instead of slight OTM? If there’s a smile, it seems to make sense to sell the higher IV wing.

Re-stated more generally, the question is:

Why would I ever buy a higher IV or “skewed” option to sell a lower IV option?

You can get into a long discussion about greeks, liquidity, jump probabilities, distributions and their moments, and spot-vol correlations. They will all lead you back to the idea that “high IV” doesn’t mean expensive IV. It’s not an encouraging answer if you are looking for simplicity.

But let me offer a constructive perspective to help you along.

It’s not hard to understand why skew exists in option markets:

  • supply/demand of risk (ie hedging and overwriting flows)
  • correlations increasing when risk premiums expand (here’s my thread on dispersion)
  • fundamentally, a stock is more levered when its equity value falls

In addition to those, I’m sure there are technical (ie lots of math) reasons involving jump models and higher statistical moments. I’m not smart enough for that. Many option traders probably aren’t. But one of the ways to survive/thrive is to take a more intuitive approach.

The logic flows as follows:

  1. Markets are pretty smart. It’s naive to think “high” equals expensive.
  2. Implied vols are a useful ruler for comparing vols but I can’t read too much into them as valuation tools since the underlying distributions are unknowable.
  3. Market prices contain extra intelligence or assumptions about a stock’s distribution but Black-Scholes assumes a singular distribution leading to differential implied vols. (Those differences are a fudge because we are standardizing the underlying distribution, even though we know the market is capable of handicapping a multitude of conditional distributions.)
  4. Focus on relative pricing to make your process less model-dependent. This lets the model errors “cancel out”.

Here’s an example of this relative thinking that I explained to the learner:

Suppose I found 20 reasonably correlated names that all have skews more expensive that at-the-money IV. If you sorted the skewed options as a percent of ATM vol there would be a top half and bottom half of expensiveness. But if you looked at just the cheapest one naively in isolation you would want to sell the skewed option. But zoomed out in a cross sectional view you would have wanted to buy it.

If you are only trading one name you are in the domain of my post Structuring Directional Option Trades. In this case your fundamental analysis is upstream of your option trade expression. So be careful about mixing up vol trading which requires a zoomed out lens and directional options trading which requires a deep  understanding of a single name’s distribution (see Real Talk On Options Trading).

A possible compromise between the approaches is to look at a time series of the skew relative to ATM to see if it’s low end or high end of normal. This will still deceive you in cases when all the skews in the market converge. For example when all skews in the market are “high”, if you look at your name in isolation you still won’t know if it’s relatively “high”. A proper cross-sectional method will benchmark to a liquid name or basket that can be considered “fair”.

So that’s 3 lenses. Cross sectional, fundamental, and time series. It would be nice if your trade idea looked good on a all 3 filters, but option traders usually have limited visibility into fundamentals so it’s too high a bar for pulling a trigger.

How can option traders make up for that incomplete picture? The same way poker players use betting patterns to narrow a hand.

Here’s a clue:

Mindset Boosters

Here are a few things I’ve enjoyed recently that cultivate a mindset that counteracts the trader residue I narrowly described in How I Misapplied My Trader Mindset To Investing:

  • Liminal Warmth 

    I came across this blog via the Twitter account @liminal_warmth. I was deep into several posts that grabbed my attention. There are lots of essays so I reached out to ask for which posts LW recommends. And voila, this thread will get you started.

    LW lives their own divergent script so it’s not surprising that the writing is unique and provocative. In addition to living in a van in a desert and writing tons of fiction, LW is a solopreneur/freelancer with tons of hard and soft skills for hire.

    I’ll single out an excerpt I found resonant from The Weirdness of Becoming Attractive in Your 30s (Link):

    Weirdly enough developing more empathy and more compassion and listening more and being more respectful of other people started working its way into my feelings toward myself… and I started hating who I was a little less. And I realized for the first time that attraction is as much about how you make other people feel as how you look (and arguably much more important). This completed a puzzle piece in my communication style that had always been missing. And it was so weird because I suddenly had this massive wave of empathy for everyone around me and I wanted everyone to feel special and pretty and liked because I knew how much it hurt to not feel that way. So again, I spent more time being actively interested in other people and trying to make them feel good and got more feedback loop results where I got positive attention in response and I felt amazing that I was able to make other people feel good and happy too.

    There’s nothing more addicting than watching people believe in themselves. Just observe a kid that learned to ride a bike or swim. I have a saying that compliments are the cheapest source of capital. Not in a fake or hollow way. But when someone is just doing their thing and you notice it’s awesome, even if it’s not grandly remarkable, just tell them. It unlocks people in a way that everyone wins.

  • The Scarcity Struggle (essay)

    This post is an outstanding reference for battling a zero-sum mindset. It chronicles the author’s own journey but many of you will be able to relate. It’s much better than my own writing on the topic so I will just leave you to read it.

    It reminds me of a hack we use around our house: “You can’t be negative when you are in a state of gratitude”. You are the object of someone else’s envy for one reason or another. Everyone is dust eventually. No point in doing anyone else but you.

On #Voltwit Melees

The corner of finance Twitter or #fintwit that is concerned with options (#voltwit) is a melee lately. There’s passive aggression in the form of subtweets and outright battles on people’s timelines. I won’t re-hash the feuds but there are 2 categories of accounts catching heat:

  1. Clever sounding accounts with weak track records

    They are accused of being marketers without substance to back it up. It’s the “podcast-appearances-as-contra-indicator” effect. If those with edge stay quiet, the silver-tongued must be imposters. Of course, the asset management business is not this cut-and-dry (Twitter Spaces would actually be a fun venue to dissect why this is a grey area if anybody wants to tackle it). There are good reasons why genuinely strong managers talk. But also, a weak manager that may have been lucky might not talk. So the podcast-hopper can be the real deal, and the podcast non-hopper can be hiding, content to profit from their own private, captive audience.

  2. People whose followings dwarf their accomplishments

    Some of this stems from people being haters (or worse…there is some terrible behavior out there). Some it stems from people who have hard-earned reputations feeling like their craft is being diluted or sullied by imposters. It reminds me of “Batesian” mimicry in nature. The harmless Kingsnake mimics the colors of the venomous coral snake as a form of defense. It can fool many predators…except the real coral snake itself. Game recognizes game. And game also recognizes not game.

A few thoughts about this:

  • Some of the malice has been fired at young people who are outspoken and trying to build businesses but are also upfront about their lack of relative experience. The rules of engagement about what is out of bounds and what isn’t is self-regulating by bystanders. The crowd is the arbiter of decency. This is probably the strongest reminder I had of the trading pits and I didn’t even include it in my post Twitter Reminds Me Of The Trading Pits. On the trading floor, there were exchange rules just as Twitter has user policies, but there is lots of latitude within the rules that are governed by social norms and enforced by the community.
  • People that are using social media to grow their influence, risk living and dying by the sword. Furthermore, I think most pros would tell you that the conversion rate of influence to institutional money is close to zero. Retail is different, but still, the verdict is out on the ROI of social efforts and in what segments it might be more effective. I suspect it’s far more effective in say self-storage syndication (the irony of using Moontower as a subtweet in a discussion of subtweets IS why you’re here right?) than raising money for a factor ETF.
  • Benchmarking a track record in the options world is tricky. The vol community is not homogeneous. There are long vol funds, risk premia funds, over-writing strategies, tail funds, and absolute return or vol arbitrage funds. In addition, the bulk of the capital in the vol trading space is held by private market-making firms like Citadel Securities, SIG, and Jane Street.

With that context, here’s a few related links:

  • Chris Cole Explains How To Build A Portfolio That Outperforms For 100 Years (podcast)
    Bloomberg Odd Lots

    3 key ideas:

    1. “Prepare not predict”

    You don’t know what the future holds, so you should diversify for all weather

    2. The recency bias in almost all investing advice you see today

    The conventional wisdom in the US would look nothing like what the Japanese believe. Sure, we might be exceptional, and there are many differences between the US and other developed nations. But if that’s your bet, at least know that you are making it and not ignoring broader base rates.

    3. Sharpe ratio is useful at the portfolio level, not individual investment level.

    He uses a powerful and correct analogy. Your portfolio is a team of complementary players (investments). If they are all scorers your team cannot win in the long-run. Long vol and long tail strategies look terrible in isolation. If you fail to appreciate the impact of convexity and correlation in portfolio construction, you don’t understand diversification. You are a baby who can’t reach the pedals. A good starting place for learners is The Diversification Imperative.

    Overall the episode is an outstanding reference. It’s one of the first places I’d point a novice who was starting to learn about portfolio construction. That said, there is one section that I (and probably other vol folk) find distracting to the whole message, but it should not lessen your view of Chris’ understanding of proper diversification. [That’s the section about back-fitting vol surfaces to extend the history of options to a time before they were listed. The purpose is to backtest a vol allocation. But since options markets are forward-looking any constructed implied vol history is doing more hand-waving than a pageant winner. Backtesting a vol allocation even with the official history is a highly speculative exercise since options markets have evolved so much. I’d have little confidence in any assumptions about liquidity and slippage to say the least.]

  • Speaking of #voltwit feuds. Here’s a well-respected but anonymous account, @quantian1, going after Chris Cole. This tweet is a doorway to a deep understanding of portfolio construction. How did it go down?

    1. Quantian called out Chris’s poor returns.

    Chris’ published returns for his stand-alone fund fall way short of how smart Chris sounds (and is). This would seem to make him a target for a seasoned anonymous account (the reason anon accounts can be extremely credible is that many employers forbid social media presences, so many professionals will not use their own names. But the ecosystem is pretty efficient at recognizing who is legit despite the alt identity. I find that anon accounts serve the same truth-finding function as short-sellers since they can speak freely).

    2. Quantian’s critique is sophisticated because Quantian understands the value of tail strategies:

    I love tail risk funds, and I love the idea of diversifying with a high-vol, convex asset. But this isn’t that! This barely has more vol than a t-bill. It’s *less* volatile than a 30-year zero. You need to allocate a *huge* chunk of capital to this to have it work. If you had a fund which was routinely posting +30%, +40% months in a crisis, and was +100% in March, then that’s absolutely worth paying 2 and 20 for a 5-10% position in. But if you’re a vol fund up a measly 150 bps in Feb of 2018? That’s not worth the price of admission. If you are selling tail risk insurance, it needs to be as capital efficient as possible to allow your investors to maximize their beta exposure elsewhere. Imagine if insurance required you to post collateral equal to half the car’s value- nobody would buy it, it’s not insurance.

    3. Chris responds head-on to Quantian’s critiques but in private. Here’s what Quantian revealed:

    Let it be known that Chris has graciously responded to my questions about vehicle structure to a sufficient degree that I consider this beef “squashed”. The fund is a small component of assets relative to SMA overlays, which are adjusted to fit the client and perform quite well

    Quantian’s “apology” is pretty on-brand:

    I do consider the willingness to engage with anonymous trolls on Twitter, many of whom live in basement apartments and drink Leoville-Las Cases because they cannot afford Latour, to be a positive characteristic in an investment manager, so he gets bonus points for that too.

    Chris has been building a brand in public for over a decade, he’s a popular speaker at vol conferences and well-respected within the industry. On the one hand, you could say what Quantian basically said: for an investment manager to indulge an “anonymous troll” is gracious. But it’s not gracious, so much as tactical. It was actually a strong move because Chris defended himself from a formidable, well-respected adversary competently. This actually makes him stronger. Going back to my first bullet about these #fintwit feuds…how many investment managers are not willing to expose themselves to the scrutiny? Live by the sword or avoid public battles altogether.

    I should call attention to a wonky extension of this discussion. It’s the importance of the tail allocation living under the same umbrella as the risk-on investments to maximize the synergies of portfolio margining. This lessens the drag of the hedge and demonstrates why vol “solutions” often make more sense than stand-alone tail funds. It’s an adjacent discussion to why you want individual managers to run their strategies at as high a vol or leverage as possible subject to prudent margin management. This is more fee efficient. Too bad many professional investors don’t understand fee math. But this principle is also important because it means that vol is best managed at the portfolio level and not the individual manager level. If there is an investment that has an annual volatility of 40% and the equivalent fund running at 20% and they have the same fee structure you should pick the 40% vol version and allocate half as much. Notice how this incentive is the mirror opposite of an asset-gathering manager — they want to run maximum diversification to keep their vol low and the assets sticky.

    [And if you really want to examine incentives, think about the PMs at the fund. The non-equity owners want maximum vol since their downside is just losing their job, but their upside is a percent of their performance. Their equity-owning counterparts want the assets to stick. Notice how the non-equity-owning PM has the same incentive as the LP, not the GP.

    Comp structures, just like fee structures, are about shifting incentives to create alignment. But there’s a lot of haggling under the hood that looks an awful lot like options trading. When you negotiate comp, do you ever wonder who the patsy is? Or do you think you are in the ballpark of fair value AFTER considering all the levers/scenarios.]

Talking To The Diamond Hands

There was a Tweet circulating recently that said if you invested $25,000 in AMZN 20 years ago instead of college you’d have $25mm today. You can replace AMZN with BTC to be more dramatic. The “should have” game is prevalent these days. It’s also a tired one. After all, we can’t just assume anyone would sit tight during the 90% drawdowns these moonshots endured en route to their epic returns. They are survivors of giant asset tournaments whose other entrants had equal or even more compelling stories at the time. Still, people cannot help but dream. It’s the same type of fantasy Lotto sells with its “dollar and a dream” slogan. It conjures images of a beachfront mansion or flipping off your boss on the way out the door.

It’s a cheap thrill…but it doesn’t need to be.

Missing a chance is still a chance to learn. It’s a prompt to think deeply about your goals and the meaning of risk. I’ve said 10 million is the new million. That means many people feel they missed out. You feel like you missed out. Stop for a moment. Don’t just waste that feeling on a daydream. You are going to use it to learn about yourself.

Let me show you how.

How Finance Brains Think Of Risk

The “should have” game is a delusion. You were not going to drop $25k into AMZN in 1999 and not also plop $25k into other internet stocks. You were not going to watch it drop 90% and then not sell as soon as it recovered back to unchanged. 

So how about a slightly less delusional game? The “could have, should have” game. This is different because it suggests AMZN made it onto a narrowed menu you actually ordered from. It’s like kicking yourself for taking a job at YHOO instead of AMZN or FB in 2004. That is a true missed encounter.

I’ll share a personal story of a “should have, could have”. It’s not an accident I’m writing this post in the wake of Coinbase going public.

The First Clue I Was Narrow-Minded

Back in 2017, I met one of my wife’s friends who had just left a VP-level bank job the prior year to join Coinbase. Work was a drag at the time, easily the most forgettable of my career (most vol traders will agree), and crypto was having its coming-out party. If you were a normie going down the rabbit hole, that was the year. And this friend facilitated my growing interest. She introduced me to another Coinbase colleague. He had also left a lucrative bank job to join the crypto party. I was paying attention.

This second Coinbaser invited me to dinner. He and one of their product managers wanted to pick my brain on futures trading GUIs. I hit it off with these guys, we were having an exciting conversation, notwithstanding Boulevard’s blue hair vibe. At some point, the product manager who was about 22 went to the restroom. The senior guy, in a hushed tone, turned to me.

“So one of the reasons [the 22-year-old] wanted to talk to you is he has a high-class problem. He’s sitting on a giant pile of ETH he’s been mining since college. At current prices, he’s rich, but doesn’t know anything about investing. He needs advice and we thought you could help.”

As I was soaking that it in, our young tycoon was returning. There was no need to tippy-toe. The whiz kid cut right to it. He explained respectfully and with great maturity his “problem”.

What did I say to him?

“I don’t have much to say. If you listened to my opinion years ago you would never be in this beautiful predicament. I would never have held on this long, so there is nothing I can say that you should listen to. But now that you are here, I can offer one way to think about it — sell an amount that makes you feel like you never have to take a job just for money. You are 22 and achieved freedom.”

I don’t even know if this is good advice. It feels like such a dowdy perspective that it can only come from someone who would never have scored that big. Just hearing his story had a deep impact on me. After that dinner, I reflected quite a bit on what it would take to truly have, what we now label, diamond hands. How did he not sell earlier? Especially as a college student?! As far as I could tell he was very smart. So I just put him in the same box as a big-wave surfer. The insane box. We’ll come back to that.

I stayed engaged with the Coinbase crew. We all liked and respected each other. My wife’s good friend urged me to get a job there. She assured me her help would increase my chances. But ultimately I didn’t take it seriously. I had a coveted PM seat in traditional finance. The lazy shield of confirmation bias was deflecting the vibrant energy I was picking up from these people that I knew were smart. Fast forward to Coinbase’s IPO. One of these friends has become close to our family and her bold bet (and 100 hour work weeks for 5 years) have paid off beyond anything including she could have imagined. We are beaming happy for her. But I would not have made the same sacrifices. I have no right to benchmark this missed opportunity to our friend’s best effort. It’s one thing to say you want to be rich, and another to actually do what it takes. 

As for thinking the 22-year-old was insane…I was wrong. It took until now to appreciate how narrow-minded I was. Not about crypto (there’s plenty of “should haves” on that front but they are the false kind. I was never going to make a giant bet on it). I was narrow-minded about how to think about risk. This essay is about the evolution of my thinking on the topic of risk. 

Let’s begin with what we know about risk.

Textbook Risk

There is no reward without risk. This is irreducible. The question is how much risk should you take given a menu of positive and negative outcomes. There are 3 embedded sub-questions that go into a sizing decision.

  1. What are the odds of each scenario?
  2. What is the payoff in each scenario?
  3. What are your constraints?

All 3 questions vary widely in how complicated they are because they depend on the context. The simple end of the spectrum is the controlled game scenario. Your objective is usually a well-defined win condition (think Monopoly) while the odds and payoffs are transparent (think casino games). On the complex end of the spectrum are real-world business/investment decisions where odds are opaque. The endgame is not towards a well-defined outcome but an evolving series of trade-offs. 

The investing world’s view of risk starts by understanding the simple, controlled setting. It then takes the math up a notch to account for more complexity. It’s the difference between deriving a “basic strategy” cheat sheet for blackjack and constructing an endowment portfolio from an infinite array of investment choices. This necessarily requires assumptions as we move from a single equation to a full model of how returns work, correlate, and feedback to each other. The degrees of freedom simply explode as we move from the first problem to the second. 

An example can show you just how far you can travel across this spectrum. Imagine being called into an economics experiment to bet on coin flips. The goal is to have the most money at the end of your limited time in the lab. This is a controlled experiment with transparent goals and odds. This is as easy as it gets. Turns out even educated people get it wrong. Quant Victor Haghani performed this experiment. Even trained economists disproportionately construct strategies that are an order of magnitude worse than optimal (I think about this a lot. Investing is difficult enough, but can the people who manage your money solve even the most basic version of these problems, the types with known solutions? If you can’t add, how can I expect you to multiply?)

The framework for solving sizing decisions in this controlled experiment comes from the literature on Kelly betting. The gist of it is, given a bet’s expected value and a bankroll, there is an optimal bet size that maximizes your long-term wealth. The framework prioritizes maximization under the constraint that we don’t want to go broke and lose our ability to play this advantageous game in the future. It does this by presuming a diminishing utility of wealth (ie the absolute joy of making a buck is less than the absolute pain of losing one).

Much of conventional thinking about risk and portfolio construction is just an extension of a Kelly framework where sizing depends on edge. Quants layer in more math and yet even more assumptions to build complex models. These models accommodate correlations, probabilities, and distributions that are unknowable.

Yet only in the controlled games, are these variables are known. So conventional finance is actually an inversion of the Haghani problem. The burden has shifted from knowing what you should do given the inputs, to “if you only knew the right value of the inputs”. In other words, a garbage-in-garbage-out problem. This is hardly a revelation. Most serious investors don’t take predictions seriously as it is. In fact, the only thing finance has is a sound framework to understand how to bet if you just knew the inputs. 

Recall our 3 sizing subquestions:

  1. What are the odds of each scenario?
  2. What is the payoff in each scenario?
  3. What are your constraints?

The simplest game world has tame answers to all three questions with the wave of a math wand. 

Investing is not simple. It is a wicked learning environment. On a daily basis, analysts furnish guesses for #1 and #2. 

#3, our constraints, are addressed by ideas like:

Risk frameworks like Kelly and its intellectual cousins like risk-parity loom so large because they are one of the only things we understand well (it’s also why portfolio construction is the lowest-hanging fruit to improve performance). They address our constraints. But notice what you inhaled from these concepts whether or not you realize it:

The assumption that you care to maximize long-term wealth.

Like Kelly’s “maximize long-term wealth” betting prescriptions, sound financial advice is entirely built on “get rich slow and steady” math. I can sense the puzzled look on your face. You’re thinking “Duh, so what?”

The reason this is interesting is because of what you are taking for granted: 

This is just one approach to risk, but it happens to garner 100% of the attention!

It’s so odorless, you did not even notice. Let’s see what we can learn if we don’t take this for granted. 

A Wide Range In How People Think Of Risk

The textbook view of risk described above is reasonable and widely used for a reason. It’s true there is plenty of debate around “garbage-in” details like samples and distributions. Investors wrangle over where diversification ends and “deworsification” begins. Still, the caveats encompassing these matters are incremental when we zoom out to the level of constraints.

Why? Because the assumptions regarding what matters are upstream of any risk management machinery.

Consider RoaringKitty of GME fame or Bill Hwang of Archegos. These gunslingers pressed risks beyond what any typical investor would consider reasonable. It’s possible they are stupid. But I find it hard to believe they are incapable of learning about textbook risk. Considering what they pulled off, it’s harder to believe they weren’t exposed to at least some risk literature. If basic risk management was hard to understand, this would be an open-and-shut case of ignorance. But “don’t put all your eggs in one basket” is something you hear at least by the time you’re in high school. These guys knowingly didn’t wear helmets.

Is there any way to defend them given that they are neither stupid nor insane?

Well, not if you need to protect you’re way of seeing the world. Defending them is to create dissonance with what you know. This is exactly why we should do it. These guys had significant amounts of their own money on the line and probably aren’t stupid (but certainly overconfident 1). 

I want to understand the mentality.

How To Ask A Normal Person How They Think About Risk

Whenever you see stories of big bets, the focus is always on why the bettor believed the world had priced some proposition incorrectly. It’s focused on the reason for the prediction. It’s a fine question and should be asked. But the more underexplored question is “why did you choose to bet the size you did?”

Press people on this question. They are not used to answering it. Most people rely on “feel” for this and if they have lots of practice making bets this is totally reasonable. They might have a tacit intuition for the volatility of the bet and the hit ratio. But with large bets, including life decisions, intuition can be a worse guide at the very least because the outcome of any large bet (money, job, spouse) influences the rest of your life in complex ways. 

So you want to answer this question rigorously. I don’t mean in a technical, quanty way. I mean in a deeper way. Giant bets are about desires. If the desire is to “maximize long-term CAGR” then you can refer them to many acceptable frameworks for coming up with a bet size. It’s a common desire with a conventional set of answers. 

Imagine 2 scripts:

  1. “Why did you put 90% of your money in SPY?”

    Because I’m young and want to retire someday.

    Ok, fine. There’s a dull but necessary conversation invoking asset allocation stuff. Send them to a robo-advisor site for some light reading and move on.

  2. “Why did you put 90% of you money in [insert turd coin]?”

    Because I want to 10x this sh*t!

    Ok, this is where things might get interesting. You need a litmus test to find out if it actually will. Your next question:

    “What if you’re wrong?”

    [They start citing a bunch of reasons for their investment. Books, podcasts, Substacks, some rich person they know…]

    You respond:

    “I understand now why you made the investment. You have high conviction. But what if you’re wrong?”

    They will almost certainly respond with more reasons for why they did the investment or repeat the ones they already gave you. That’s ok. They aren’t investors and don’t know to separate the investment process which includes research and security selection with sizing which is a risk management issue. Give them a pass on this. This is where you explain, that risk management is like a separate branch that is not affected by biases of the analysis. Like checks and balances in the government. The risk management branch is focused on survival no matter how exciting the thesis is. If your YOLO’ing friend is skeptical, remind them that the reason the best investors have risk management is that even they are often wrong. It’s this independent throttling function that keeps them in business.


    “I’m asking a risk management question here. What if you’re wrong?”

    This can go a few ways. They might be too dense. They might need to think about this more because until now they haven’t deeply considered the possibility that they are wrong. Especially if they are already up lots of money on the trade. These will end the conversation. Some small part of the time they will retreat to think about it. More likely, they’re wondering what it’s going to be like when they are rich and you are poor. Ask them to buy drinks now while they feel flush. 

    But…if they have answers to “what if they’re wrong on this bet-of-a-lifetime”, then you are making progress. You are about to learn what makes this person tick. You are about to get on a “why” train like you are 6-years-old.

What I Learned From Asking

If you are coming from conventional finance, you are used to conventional portfolios. If you deal with individuals, you emphasize asset allocation, keeping costs low, diversification. All of this is in the context of people’s goals. Most just want to have enough money to retire at some point and something to leave their kids. They expect investing to bridge current assets with future liabilities. If you deal with institutions, it’s the same problem but the details vary. 

You are so used to seeing it, that divergence from the template is deeply unsettling.  You presume the strays are ignorant of “best practices”. Often times they are, and if they learned the basics might change their behavior.

But what if they know the conventional playbook, grok it, and actively ignore it.

Many of you might know someone with a white-knuckle concentration in crypto. Many finance types including myself see a sub 5 or 10% allocation as reasonable. (It appears to have a super-delta to our infi-liquidity regime. Losing 10% of your portfolio would suck but you’d live so it’s not the most reckless idea). Now there are people that might have started with 5% and didn’t rebalance. They could easily have a majority of their wealth in crypto. 

So here’s your homework. If you know one of them, and you are certain they understand the dangers of concentration, sit them down, and ask them about it. Be open-minded. Recite the script above. “What if you’re wrong? Why are you taking this much risk?”

If they understand conventional finance and ignore it, they see risk in a very different way than you do. It made me curious. 

The Conversation

I find having a giant chunk of your net worth in extrinsic premium insane, but everyone’s different. So I wanted to understand as best I could. I had one of the longest conversations I can remember recently with someone who has about half their net worth in various coins, including a few coins that are more under the radar. The allocation was small to start but appreciation caused its portfolio weight to skyrocket. 

Before I share what I learned, a bit of background:

  • This person was a multi-millionaire even before investing in crypto.
  • The person’s portfolio is highly diversified across asset classes and securities (albeit levered to economic growth, but that’s typical).
  • The person is in their 40s, owns a successful small business, and married to an MD.
  • The person has an extensive history of giving generously both in money and time.
  • This person keeps a countdown of how many weekends they have with their kids before they are off to college. (I actually told the person about that sobering Tim Urban essay after I heard that.)
  • This person might be the most type-A planner I have ever met. Sets goals, and tirelessly works backward to figure what they need to be doing all the time. If that’s Mario, I’m Wario. I can’t relate to the mindset but I respect it. 
  • If crypto went to zero, the person is fine. The person admits it would be upsetting, but not crippling. 

What did I learn?

I’ll just cut right to punchline. They are only interested in this for truly life-changing money. In other words, base 10 changes in wealth (See Nick Maggiulli’s Climbing the Wealth Ladder or Trung Phan’s thread about rich people).

This person’s specific logic went like this:

  • I’m confident I can secure a comfortable retirement via a thrifty lifestyle, safe employment, and a hefty financial buffer.
  • I must balance competing goals: a desire for more time with the kids while they are young and a desire to make as large a philanthropic impact as I can muster.  A 10x change in wealth would allow me to give much more money away and give me more time with my kids.
  • If my working life was shortened by a few years after the kids already went away to college, this is is much less appealing. I want to be done as fast as possible otherwise I don’t care that much.
  • I don’t see “volatility”. I see “velocity”. Velocity is good. It speeds things up! It would be riskier to my goals if there was no velocity since the possibility of 10x would be off the table. 

Reflections From The Conversation

First, let me spell out some observations from the chat.

  • The person’s preference curve regarding the retirement age is discontinuous. If they can’t retire soon, then they are indifferent between say  60 and 65. This is a hyperbolic discounting of current risk. It flattens at some rate while the kids grow, before leveling off when they leave the nest. 

  • In this person’s mind, the biggest risk is not taking a chance to achieve the ideal. This framework is not the natural framework of finance that targets the best median outcome. This is a quantized version of outcomes. Structure a tolerable worst-case scenario, lower the median outcome, fatten the upside.

Look, I still think this view is crazy. Not because of the goals actually, but because it feels static. In a dynamic situation, the right course of action is unclear and greatly changes the shape of the payoffs. Practically speaking:

  • If you average down in a sell-off, the downside risks increase.
  • A purely discretionary approach invites an unprotected tryst with Greed and Fear. Watch your wallet.
  • Nobody really knows how they will feel to lose half their net worth. Will they go on tilt? Will they become depressed?

I could go on. I’m sure you can too. But our objections are beside the point. What we discovered is how personal the logic was. 

Risk Abstracted

By actively listening and translating a thoughtful non-finance person’s views about risk, I’ve distilled a list of reference thoughts on risk.

Risk with a capital “R” is qualitative

In finance, risk is often proxied by volatility, but that is a context-based definition. Risk, in its most meaningful sense, is the possibility of not achieving your goals

Goals vary

Categorize Your Goals

You can think of goals as “need to have” and “like to have” These are deeply personal. If you have Lambos and yachts in your “need to have” you have necessarily downgraded basic shelter into “like to have”. 

The Role Of Thymos

Byrne Hobart, discussing Fukuyama’s idea of the “Last Man”:

Thymos, which can be literally translated as “spiritedness” and more figuratively and vividly means the desire for recognition and glory. Thymos describes the urge to excel, even—especially!—at great risk to oneself. Fukuyama’s ultimate source, Hegel, spends a lot of time meditating on the original thymos-inducing practice of forcing another human being to submit to one’s will; modern societies find healthier and less direct ways to harness this desire. Plato divides the soul into reason, desire, and thymos. Reason and desire are enough for a pleasurable existence—you have wants, and you figure out how to meet them. Thymos is necessary to motivate sacrifices for public service and glory.

The boldface is mine. Humans are not robots. The call to glory for its own sake is a human impulse. We climb Everest because it exists. Think of artists. Most starve. I’d never choose to hang my future security on the vagaries of such chance. But the fact that others do makes my life better. An equilibrium where everyone optimizes for the “best” median return is dull. The line between a need for an intervention and raising a glass to a visionary is not cut-and-dry in real-time. 

Regret Minimization

By now everyone has heard of Jeff Bezos’ regret minimization framework. The idea is hard to implement because it rests on you being able to predict what you will regret. I found Jim Carrey’s version similar but more compelling (speaking of a guy vibrating with thymos…next time you Netflix check Jim & Andy: The Great Beyond). His father was a great sax player who abandoned his dream and became an accountant. He was fired and crushed at age 51.  Jim internalized the fuel: “you can fail at what you don’t love”. To Jim, choosing between what you love and not love is not much of a choice.

Divergent goals demand divergent strategies

If you needed to come up with ransom money in 1 day, the riskiest thing you could do is NOT bet everything on roulette.

Things You Can Do

Talk to others about risk

Animal spirits are pulsing through Americans’ mouse-clicking fingers. More than ever, it’s important to talk to people about the risks they are taking. Use the script above. Ask “what if you’re wrong?” Coax them to separate the rationale for the trade from risk management. You may not be satisfied by what you hear, but that’s not your objective. You just want to make sure your loved ones’ actions serve their “need to haves” even if yours are different. 

Revisit your plan

I found this Julian Shapiro’s essay Life Planning to be a nice reminder that you write your own script.  

I especially like his advice: Beware the echo chamber

This is my final, high-level caution about ordering your values: beware people surrounding you who mislead you as to what you care about. Because, whether you realize it or not, you’re the average of the people you hang out with. 

He gives examples of different archetypes of people you might hang out with. Every parent already understands the lesson — you have to have intention about who you spend time with. You will absorb the values that surround you (I recount my slide into zero-sum thinking based on my environment in How I Misapplied My Trader Mindset To Investing).

Julian continues: 

Many others think “making the most out of life” means doing nothing more than finding a spouse, buying a home, securing a job, and raising kids.

I’m not passing judgment. The point is: Has exposure to certain people caused you to neglect what you value by adopting others’ values through osmosis?

To break free from this groupthink, take a moment to identify what you would truly regret not having done by the time you’re 80.

That’s the easiest way to snap yourself out of it:

Ask yourself, What would I be doing if I could start all over again?

When most people do this, they’re delighted by how many things they think they care about suddenly fall by the wayside.

Set financial goals

See my short essay in the Moontower Money Wiki: A Word About Goals 

Set your own risk management rules

Think dynamically. Every public investment including BTC that has gone up 100x, 1000x, or more has experienced massive drawdowns along the way. Looking at charts is misleading because they do not convey emotion. The doubt and pain that occur in those drawdowns don’t translate. So you need to steel yourself against them in advance. Expect to experience them and have a plan so your amygdala doesn’t take the wheel. 

Ways to do this:

  • Know Thyself

It’s never a perfect science to handicap your own risk tolerance. Some starting points to jog your brain:

    • A Way To Quantify Risk Tolerance and Determine Appropriate Equity Exposure (via Financial Samurai)

    • How Tails Constrain Investment Allocations (via Moontower)

      This posts bridges the gap between investment risk and human capital risk. It considers how much you can risk in relation to your earnings potential. It’s not a practical recipe but walking through the logic will bring more rigor to your thinking. 

  • Match Your Risk Management Strategy To Your Goals
    • Re-balancing

      Conventional finance thinking advocates for diversification and re-balancing. The primary reason for this is to avoid concentration. You are actively avoiding have a single investment dominate your portfolio. There is a major survivorship bias in pointing to anyone that has become extremely rich by concentration, whether it’s through their investment portfolio or by having the bulk of their worth in their own business. The illusion obscures 2 realities:

1. The mega-rich will get that way because of highly concentrated bets. Exceptions that come to mind are some of the top HF managers in the world. You are not them. (If you are one and you are this far into my blog post then…call me, maybe?)

2. You don’t see the rest of the tournament entrants. Remember, most stocks go to zero. Re-balancing is why stock indices do not. See Is There Actually An Equity Premium Puzzle?

Re-balancing is a convergent strategy since you sell winners and buy losers. It’s a bet on mean reversion. To understand its concave payoff profile see Ensembles and Rebalancing (via Newfound Research)

    • Trend

      If you prefer a convex payoff profile similar to a long option position, you can follow a trend strategy. A trend strategy is a set of rules that cuts your losers quickly and keeps you in your winners.  The cost of implementing the strategy is the “chop”. The options equivalent is the “theta” or time decay. 

      Trend is conceptually simple. Your stop-loss will be triggered more often than you catch a trend. So a trend strategy is a tradeoff between hit ratio and slugging percentage. If you lose on 2/3 of your bets, but your winners are 3x your losers, then you are ahead (although such a strategy trades much more than buy-and-hold incurring higher transaction and tax costs). There is infinite literature out there on trend-following but if you want to understand how trend looks like a long straddle position see Straddles and Trend Following (via Newfound Research)

    • Gorilla

      Gorilla investing is another strategy designed to look like a long option. It rebalances away from losers, into winners. It explicitly bets against mean reversion. It’s a divergent strategy that growth investors employ in winner-take-all businesses. 

      The gist of it is to invest an equal amount in a list of candidates that are competing for a giant market. As the winners start pulling away, you shed the losers and reallocate the proceeds back into the winners. This comes with its own suite of risks. Off the top of my head:
      • Umm, you overestimate the TAM
      • The eventual market winner comes from outside your original list.
      • As more entrants enter the market, you need to consider adding them to your portfolio, which will dilute your ultimate return. 

The suitability of this strategy requires extensive judgment, but I highlight it because it is another example of an investing algorithm (in addition to trend or rebalance), and the goal is to have you be methodical in your risk management rules regardless of whether you are trying to simply save for the future or construct a homerun-or-nothing portfolio. Your goals are your own, but your framework should give you a chance. 

If you want to learn more about this strategy see the notes for Gorilla Game or pick up the book. 

Wrapping Up

Investing is all about bridging our current assets to our future liabilities. For many of us, filling out the advisor’s template works. There are enough degrees of freedom in them to handle a possible switch from public to private school, or your spouse retiring early. But when you see what looks like insane risk by a smart person, it’s an opportunity to learn about other life scripts. In the story of the turtle and the hare, some people root for the hare. They are fine with Neil Young’s lyrics “better to burn out than fade away”.

The liability they are filling is their own definition of a life fulfilled. 

What can you learn from talking to Diamond hands? You can learn about people. 




How I Misapplied My Trader Mindset To Investing

I graduated in 2000. It was the height of dot-com mania. I took a job with Susquehanna, one of the largest derivatives trading market-makers in the world. My first year as a clerk was a rotation through different rings1 on the American Stock Exchange. I learned to trade ETFs, equity options, and index options.  After a year, I was off to spend 3 months at the mother ship studying theory and mock-trading in the physical pit they fashioned in a conference room. I still refer to my ragged notebook from those sessions to write my options theory blog posts.

Susquehanna is rightfully famous for its trader education program. It is an enormous source of edge to them. They ask you to sign a 3-year non-compete after the training ends to secure your job as a full-time trader with your own p/l. While I resented the non-compete at the time, I think it was a good trade in hindsight. I got an amazing experience at a young age. The firm’s way of thinking about risk and reward is recognizable to anybody that emerged from its deep-rooted culture.

But there’s a twist. A darker angle that I have been reflecting on.

The four-letter version of culture is cult. You see, Susquehanna had (I’d say “has” but I am a generation removed from the firm and this post is really about me not them) a tangible culture. Today, living near Silicon Valley, culture is discussed a lot. I’ve heard it described as “what you reward and what you punish”. Susq had a distinctly strong culture, but since I was young and impressionable, I had a cultish adherence to it. The downside of a strong culture, is a weaker mind will overinternalize it. That was me. Plenty of traders were able to take the best of the culture without overgeneralizing it to life. I missed the memo to not take it too seriously.

This post is about how I misapplied the lessons of my trading career to my investing life.

Mother’s Milk

Indoctrination started as early as the interview process. You witness Susquehanna’s preference for using games, especially poker to teach “decision-making under uncertainty.”2 Games are closed systems. Taleb warns of “ludic fallacies” in trying to transfer lessons from games to markets. Still, there are enough parallels that an elite trading firm that has trained countless recruits deems the poker table a timeless professor. 3 Using pot odds to compute risk/reward, bayesian thinking to narrow competitors hands, seating position to calibrate possible starting hands. Then there were meta lessons. Who’s the fish? The sharps’ job is not to play against one another but extract the dead money. This takes self-awareness. It requires balancing the confidence to act when you have the edge vs the risk of overconfidence when imagining yourself in the pecking order.

To a young mind, sorting the world to organize the immense amount of info that was coming at me professionally, I started to form heuristics. Taken too far, these heuristics would become oversimplifications when extended to investing. I’ll give 2 examples of how I reduced my environment.

1. Zero-Sum Edge

Strictly speaking, options trading is zero-sum. Sure, it’s possible that if you buy call options from me, and I hedge them, that we both win. But in that case, the counterparties I hedged my option deltas with lost. The p/l reflects the transfer of risk and the total risk is conserved. Markets generate prices. Prices facilitate the flow of risk from those who do not want to hold a risk to those that do in search of expected profit.

As derivatives market-makers, the most adaptive starting point to isolate the mathematical edge is to assume the underlying stocks were fairly priced. I traded MSFT options for a few years. I never had an opinion on MSFT stock price. I figured there are thousands of smart, informed investors duking it out to set its price. From my seat at the table, the point spread incorporated all substantive information. But in the small arena of vol intelligence, I could have an edge. That was our expertise.

Building on this zero-sum world, our edge was just a casino vig. Without tourists punting on earnings or hedging, there was no business. We were not interested in giving the card-counters or informed counterparties action. A large focus of the job was to discern toxic from benign flow (I’ve written about how this is the entire basis of payment for order flow). In fact, when we identified the sharps we tried to bet with them. Likewise, if we isolated benign customers we thought about how to maximize their LTV by trying to price more tightly and have them coming back to us. In this case, the casino host is a fitting if dim analogy.

The focus on who the customer is permeated every decision. If a customer quoted a risk reversal (a spread between a put and a call on different OTM strikes) we’d typically lean the market as if they were going to be a buyer of the put. Why? Think of a simple decision tree. If the customer is a buyer of the put they could be informed about an upcoming negative catalyst, but there’s also a large chance they are hedging by collaring their stock. A hedge is benign. We might not even hedge the Greeks it saddled us with (hedging is the cost of reducing risk, so if the risk was not outsize to our substantial capital AND we didn’t think the trade had any information in it, we wouldn’t hedge. The accumulated delta risks were best aggregated at the firm level for centralized hedging). However, if the customer, bought calls the probability that they were “smart” is much higher since they are probably not hedging but speculating. We might even overhedge while trying to do as little size as possible on our wrongly leaned bid/ask.

Over and over we obsessed over who we were trading with. You’d just start filing “paper” (lingo for customers) as “smart” or benign (a more colorful expression would be “donkey”). Of course, they were playing a different game and the execution edge they were giving up was the cost of doing business. But 20 years ago, you could drive a truck full of money through the wide bid/offer spreads. Any uninformed trader using the options market was facing a vig so large that their returns were doomed if they kept coming back. And many customers did go out of business as surely as our profits grew (if you are unconvinced see Understanding Edge).

I came to believe edge was only possible on short cycles. Large sample sizes and frequent trading would quickly reveal if you had one. How could you trust stock pickers with their small sample sizes and inability to validate statistical edge? I generalized a useful assumption, “the stock is fairly priced”, as gospel truth. This made me agnostic about what I was trading. Everything was just a number on a screen. A video game. Only the flows mattered. Only the patterns of buying and selling. Asset managers focused on fundamentals were tourists with elaborate stories and fancy suits.

2. Other People’s Money

Speaking of asset managers, my view of funds was especially dark. It still kinda is. I’ve written:

Asset management is the vitamin industry. It sells noise as signal. It sells placebos.  There will always be one edge that never goes out of style — marketing.

Working for a firm that had no outside capital and made profits consistently, the idea of earning single-digit returns or even losing looked idiotic. Why bother? Firms with provable edges don’t try to raise money. If it’s provable it does not need more eyeballs on it. In my view, the adverse selection of being able to invest in a fund mirrored the adversity of getting filled on a highly competitive price you made. It’s the Groucho Marx thing — “I refuse to join any club that would have me as a member.” It didn’t help that my girlfriend (now wife) would take me to her holiday parties with the Greenwich crowd where I’d always remember some overconfident hedgie craft some vision of the world. I remember one encounter with a partner who said I “looked like a trader”. WTF? (With the benefit of maturity, my insecure impulse to want to pound him was super cringe. Thanks for reading my self-therapy).

The biggest indignity came when I interviewed for an execution trader job at a famous long/short fund. I had an especially warm intro to this firm. It was the heydey of hedge funds and they had no clue how to price comp. The position would have doubled my pay. Unfortunately, I was rejected after a very strong interview with the head trader. Backchanneling, the feedback was “You would have been bored”. This single data point solidified my feeling that these overfed funds were dog-and-pony shows. (From what you can tell of my awareness skills at this point, you agree, it couldn’t have been me right? Umm, right?!)

What I Was Thinking

I’m a decade into my career.

I don’t believe anyone except the house could have an edge. I have still given no thought to personal investing. I followed the society script of saving for a condo. In the first decade of my career, I witnessed the dot-com crash, 9/11, and the Great Financial Crisis in the wake of subprime defaults. Markets were nothing but pump and dumps. Investing was astrology.

Trading was different.

Market-making was a picks and shovel business. The job was to find prices that cannot simultaneously be true. “I’m sellling this here because I can buy this here.” And those things need to have a real, almost arbitrage, relationship between each other. A short wire between them, for example, a simple call spread. Sure, real investors claim they do this on longer timelines, where the disparities are greater, but so is the length of the wire between the 2 ideas. You’d have to pull one thing so far to exhaust the slack in the wire. In the meantime, you were collecting that 2% management fee and long a performance call. This looked like a racket to me.

For my thinking to evolve, I needed a mutation.


In 2012, I moved to SF become a portfolio manager at a vol-focused hedge fund. My journey through market-making took me into several option markets including energy, softs, ags, and precious metals. I used to bounce around trading pits as a member of all three exchanges4 in the Nymex building. Now, it was time to take a bird’s eye seat and move up the edge/capacity continuum. If you were willing to accept a worse risk/reward, you could increase capacity. And this made sense. The economics would need to flip. Instead of me earning 70% of my profits (I had a backer in my independent years after leaving Susq in 2008), I would earn a smaller cut of a bigger pie so the investors would receive most of the edge.

Can you believe it? A fund could be a win-win solution to a customer’s needs. It only took me a decade of unwavering skepticism (a total affront to my wife by the way who has been on the buy-side for the better part of 20 years).

From this seat, I learned the more formal language of investing and finance. I learned how allocators thought about correlations and diversification. I learned how they thought about liabilities and what they considered to be risk. I then started to lurk on Twitter. I learned that Michael Mauboussin has written about everything I was taught about trading. He just did it from a skyscraper, instead of on a broker’s buy/sell pad. I learned that what I called edge was called alpha. I learned how beta was a form of risk premia levered to growth. So returns didn’t occur because stock prices “just go up”. Returns come from the economy growing and earnings going up. The transmission mechanism to stocks was still very noisy. But it’s less noisy in the long term (assuming the economy is growing).

In short, while trading is a zero-sum game, investing is not!

Zero-sum Thinking Is Naturally Short Term

The major mistake of my trading mindset is how short-term it oriented me.

  • I failed to appreciate compounding 

    Trading businesses are capacity constrained. The partners at Susq were plowing money into technology and growing the business. I remember feeling betrayed when they started hiring salespeople and analysts. We were a trader-first firm but now we were being asked to cooperate with the types of people I considered showmen and dumb flow. Instead, I was missing the broad view. Susq needed to deploy their rapidly increasing capital. That would mean building out a sell-side business, but it later would mean developing fundamental views. The idea that “stocks are fairly” priced would remain useful for option traders, but was Susq going to just dump any excess money into Vanguard funds? No, they were going to figure out stock-picking. The world of trading is not investing. The bets have endpoints. You win a tournament, you take the profits off the table. You hunt for a new bet.

    But investing is about re-investing. That’s how you compound. 

  • Taxes

    I’ve lived in the highest tax domiciles in the US and have been paid on a W2 my whole career. The ratio of my earnings and lifetime p/l to my wealth is embarrassing. Part of the trading mentality is short-termism. Today I’m thinking more about bets that pay off longer in the future. Bets that build under the surface, accumulating value. Value that is not marked and therefore untaxed. Human capital works that way. Ownership often works that way.

    Sure, a mercenary mindset can be worth it. But just as a ballplayer needs to earn a giant 1 year-deal to make it appetizing relative to a longer-term contract, you must be thoughtful about how you align your rewards with your efforts. Short-term certainty creates reinvestment risk. Weigh them carefully.

Combining Influences

I’m deeply grateful for the lessons trading and Susq taught me. I’m disappointed in how I misapplied them. That’s on me. There were others who sat in on the same classes and were not as slavish or myopic.

The experience on the buy-side, meeting people on Twitter, and being a better listener has been a revelation. When I combine these influences with my trading experience I have incorporated the following thoughts about investing:

  • At a high level, I focus on asset allocation.

    Risk and correlation are my primary concerns. Focus on the shape of returns and how the systemic risks you are underwriting are correlated to each other. Do this qualitatively. For example, I think of real estate as an idiosyncratic risk based on local supply/demand, but its systematic risks are interest rates and liquidity.

    Presume returns will be driven by market-implied parameters. This is the agnostic part I accept from trading. If you invest in large-cap US equities today, they offer say a 3-4% risk premia over the risk-free rate, in exchange for 20% volatility and fat tails. It’s not a great proposition, but the point is I don’t pretend I would get more out of my equity allocation. Size that proposition appropriately.

  • Taxes

    Put high turnover or income-producing investments in tax-advantaged accounts. Use ETFs over mutual funds in taxable accounts. 

  • Default to passive if not looking at a niche strategy

    Passive allocation allows you to draft on the increasing efficiency of markets and not pay too much in fees.

  • Private investments

    I appreciate that people can find an edge in their respective domains. I was spoiled by trading. Expiration cycles, large sample size, and a lack of beta meant edge, positive or negative, reveal you faster.

    Investing is a more wicked domain. My default belief is still that edge is rare and mostly unavailable to me. Storytellers can hide in the randomness and low signal-to-noise. And I’m not fully immune from them anyway. 

    Still, I believe if you filter well, the number of times you get burned will just be the cost of doing business. Any private investment has to satisfy my doubt as to why I should be invited. And once invited, I am mostly judging character and ability. This is admittedly an act of faith. I’m pattern-matching to successful traders I’ve seen. I’m comfortable betting on people. Not because I even know if I am good at this, but because I think there are more ways to fail forward. If I constrain my risks at the sizing level I can more easily enjoy the positivity that emerges from partnering, helping, and believing in one another. It’s more holistic than a spreadsheet. 

    In a recent interview with Meb Faber, Ted Seides articulated my wife and my feelings exactly:

Most of the [private] investments are actually people that I’ve known for a long time. I don’t have investments with the big brand-name people. And part of that, for me, there’s an angle on active management, and certainly, this style of active management that I think is completely lost in the active-passive debate, which is the relationship aspect of it. Because I can give money to a manager, and yes, I will get the returns that come from that, but who knows what else is going to happen, both potentially financially and also just in life, right?

There’s so much optionality that comes from having great relationships with people. It’s one of the reasons why it was easy for me to have a bias towards sticking with managers. I can’t stand ending those relationships with people I respect and think are smart. And I’ll happily, like, take a little bit of a financial hit in the short term if I think it’ll keep going for the long term. 

Wrapping Up

There are many ways you can apply the lessons of trading to life. There are adaptive ways to apply options reasoning to other domains. You can also live a totally unexciting life of collecting options5but not exercising any.

Knowing when to apply analogies is an art that requires choosing pertinent references classes and having awareness of what actually matters. 6We are at the mercy of initial conditions, frames, and contexts. You have blindspots coming from your training as surely as they come from the womb. The trading business smells so much like investing that I confused zero-sum with positive-sum because the wrapping looked the same.

Seinfeld said “Pain is knowledge rushing in to fill a gap. When you stub your toe on the foot of the bed, that was a gap in knowledge. And the pain is a lot of information really quick.” The pain of lagging a bull market made me examine my lack of emphasis on investing (As traders say, “nothing like price to change sentiment”). With more personal capital and years removed from 2 market crashes, I came to realize I should pay more attention to investing. As I examined how institutional allocators think about their goals and liabilities, I realized I should think longer-term. It’s why I came to Twitter. To plug into broader learning and more ways of thought.

Investing is a rich topic because the longer-term orientation forces you to learn more about yourself. You question your objectives and risk tolerance. You question what you know and how you came to know it. In that sense, investing is deeply about people and growth. It’s a conclusion I never could have imagined when I was bum-hunting on the trading floor.

I’m building a guide to investing. It’s a work-in-progress but currently has a full introduction, foundational beliefs, and the basics of risk. 

See the Moontower Money Wiki

Why Investing Feels Like Astrology

 Markets turn financial capital into physical capital.

Albert Wenger

That is my favorite definition of finance. I heard it years ago when Wenger was interviewed on Invest Like The Best.

The quote continues:

Finance bridges the fact that people need to borrow from the future to work on something today which will result in physical capital in the future which acts as the collateral for the loan or equity up front. 

I like this because it explains the economic purpose and mechanism of finance simply, yet abstractly. It is without prejudice to conventional objects of its abstraction like banks and funds on the supply side of capital or companies on the demand side. These objects can be substituted with other social constructs in ensuing centuries and the definition will hold.

If you listen to the interview, Wenger adds an opinion to his definition:

Markets have been the most efficient way to allocate financial capital.

I’m publishing this essay in 2021. Let me tell you that Wenger’s opinion feels pretty shaky. GME and DOGE are the tips of the absurdity spear. But since I agree with him (see Dinosaur Markets), I have felt pressure to examine my own model of how markets work. The role of finance is clear but the practice of it, investing, is far more art than science as textbooks might lure you to believe. It would be a grave omission for the next generation of textbooks to not discuss reflexivity, for example. It’s not that conventional definitions of finance are broken, it’s how two-dimensional the process is described. The returns are presented as if they mechanically spit out of a wood chipper. In reality, the wood chipper looks like it can stand up and beg more trees to jump inside it.

That sentient woodchipper is of course the market. The problem isn’t with markets. It’s with your formative beliefs about markets. Markets are an emergent system where the actors learn, act, and get feedback. Repeat loop. They all do this at the same time. That means that some of their lessons are artifacts of their own behavior. It’s like taking your pulse with your thumb, forgetting that it has a faint pulse of its own. Markets are layers of sedimentary behavior, compressing at an increasing rate, on top of a core finance function. That increasing rate scales with the modern speed of information creation and spread.

[A common criticism of crypto is that it’s just reinventing well-functioning features of conventional finance. So what? That observation is secondary to the speed at which it is doing so. It reminds me of when I moved from equities trading in 2005 to commodities. When I started on the NYMEX, the underlying was still not electronic! Once the market began to modernize, it had the advantage of leapfrogging many of the inefficiencies equity markets might have worked through as they moved to the screens.]

The layers of market sediment are sufficiently thick, and the core of the finance function is so sufficiently buried, that a focus on fundamentals will leave you feeling like markets are astrology. Prices feel governed by tides of celestial sentiment rather than waves from a named storm or measurable weather pattern. I don’t think this is new. My feeling is that it was always this way, but since there were fewer layers of learned-Vizzini sediment, the textbook illusion that prices are closely tied to fundamentals wasn’t as visibly challenged.

This post is superficially about the danger of believing the textbook-style investing delusion. But it offers a framework that extends the textbook views in ways that better align the objective (investing effectively) with what is required (focus on the correct inputs which are, sometimes, but rarely fundamental).

Regular readers know the tyranny of my trading experience means everything looks like an options nail. No judgment if you turn back, but I promise no math.

The Elements Of Value

Let’s re-purpose the concepts of intrinsic and extrinsic value. You were warned.

Intrinsic Value

The financial definition of “intrinsic value” depends on context. In options, it is the amount the contract is in-the-money. The difference between the stock price and the strike price. For an out-of-the-money option, the intrinsic value is zero.

A comparable idea in stock valuation might be book value. That’s the value of a business if you liquidated all its assets today and satisfied its liabilities. It is a simple accounting value of a company. It is unconcerned with the asset’s ability to earn money. If Elon Musk started a THC-infused lemonade stand its book value would be comprised of the street value of the THC syrup, a basket of lemons, and the Martian goblets he’d serve drinks in. Assume he’s the only employee and plans to sell 5 drinks a day on the way to the office out of the back of his cybertruck. Let’s be generous and assume the lemons are organic. The accounting value of this company is like eighty-six bucks. The equity will trade for $11 billion. So book value is $86. Equity value, $11B. If this was like options world, we’d say the intrinsic is $86. That’s what you’d get for the assets today.

This is not a helpful use of the term “intrinsic value” because it ignores the earnings power of the assets in the hands of the right operator. In reality, equity is the residual claim on a business once all liabilities have been met. The equity owner has unbounded upside in exchange for being the most subordinate in the cap structure. So equity itself looks like an option.

Luckily, there is a notion of intrinsic value that applies to stocks but is not so conservative that it would lead us to believe that anything Elon Musk tried to do would only be worth $86. We can borrow Warren Buffet’s version of intrinsic. The exact details don’t matter for our purposes (this feels irreverent to say since it’s some investors’ sacred cow, but if I’m not giving away too much, it only gets more irreverent from here. Sorry, not sorry). The gist of it is some measure of a stock’s expected future earnings discounted for risk and time value of money. More compactly, intrinsic value is a company’s earnings power times a multiple.

The key to this definition is that it smushes together a very traditional definition of intrinsic (book) value with a forward-looking estimate of earnings. But it’s a conservative estimate. Nothing that would turn your mood ring red or even get Elon out of bed in the morning.

Other assets have intrinsic values as well. Pseudonymous writer @Jesse_Livermore, on the Infinite Loops podcast:

I think the intrinsic value of an asset is what its worth in and of itself. From owning it for, for its own sake. I think a good way to test this is to just ask yourself, for any asset or anything whatever it is, what would be the most that you would pay for it if you were stuck with it forever. [Assume] you can bequeath it to other people when you die and so forth, but you’re stuck with it as is. You can’t ever translate it into cash in a market. What is the most you would pay for that thing? That is my test for what intrinsic value is.

He gives the example of a home. Even if you did not think it would go up in value, it still has consumption value since it saves you rent. You could also rent it out. In both cases, the intrinsic value will look something like Buffet’s definition. The sum of many years rent discounted for some costs.


Before moving on, what have we established?

  • Stocks themselves are options. You can pretend they are zero-strike calls or calls struck at book value. It doesn’t matter, they are options. 

  • Our definition of intrinsic value is a conservative sum of future cash flows

  • Intrinsic value is a property of any asset. It can be zero if nobody is willing to pay even a scrap value for it.  [Craigslist and Ebay raised the intrinsic value of many items indirectly by lowering the cost to exchange them. It raised intrinsic by lowering the strike price.]

Extrinsic Value

Borrowing from options-land, extrinsic value is the “it could happen” premium. It’s driven mechanically by 2 inputs: time and volatility. All else equal, a 1-year option is worth more than a 1-week option. Similarly, if the underlying stock has the potential to change the world in the next year, perhaps it will cure cancer, its volatility will be high since its market is every human. Or it might fail all drug trials and be a zero. The range of possibilities gives the options more value than the options on, say, a giant widget company whose business has predictable cash flows.

But, remember we are moving from the world of financial options to thinking of the companies themselves as options. To do this, we are going to decompose extrinsic value into 2 components: imagination and liquidity premiums.

Imagination Premium

Let’s continue with the drug company.

We already assigned an intrinsic value that incorporated an expectation of future cash flows. Unfortunately, estimating any future cash flows from this drug company conservatively is impossible. No, this is a company whose value is made up solely of possibility. The probability-weighted forking paths that underpin its traded value feels…well, not like our definition of intrinsic. The discrepancy traces itself back to the fact that this particular company is less a business and more just a black box holding a far out-of-the-money call option. Yes, all equity above book value is an option but this one feels entirely comprised of time and volatility value.

This company is what AMZN was in 1998, braced on the cusp of a connected, online world. The entire value of the company was extrinsic. The implied volatility of AMZN back then was regularly in the 100-200% range, a straightforward reflection of justified qualitative uncertainty. Was it different this time? [narrator: it was]

So we can say that certain companies have option value above and beyond our modestly padded definition of intrinsic value. Is TSLA a car company, battery company, software company, self-driving car company, solar company? The market is assigning a massive premium above what any multiple-on-grounded-earnings could furnish. Not unlike AMZN over 20 years ago. This type of premium is again extrinsic. We are going to call it Imagination Extrinsic to a) honor its visionary nature and b) to distinguish it from another component of extrinsic: liquidity.

Liquidity Premium

@Jesse_Livermore’s work refers to an idea he calls “transactional value”. It is the value that permits you to pay more than intrinsic value for an asset because you know you could sell it back into a liquid market.

Here’s Jesse parsing intrinsic value from transactional value:

The intrinsic value of equities would be the cash flow stream of the equities themselves, which you can collect and they belong to you and you can spend them and do whatever you want with them.

The transactional value would be the value that comes from the fact that there’s this “network of confidence” in the market, that people have been doing this for hundreds of years and we know that when you wake up tomorrow, the S&P is not going to be at 500. It’s going to be near where it was yesterday and people are kind of anchored to where its price is…You can basically take all your money, 100% of it, and put it into the stock market and know that you’ll be able to get a lot of that out anytime you need to. That’s the transactional value, which is the premium.

The idea that liquidity commands a premium is not new. If you have any money in a savings account today, you are paying a liquidity premium in the form of negative real interest rates. The treasury market discounts off-the-run securities because they are thinly traded even though they mature to the same value as their on-the-run counterparts. But I don’t want to dismiss Jesse’s notion of transactional value because it’s not novel. His expression of it is illuminating. For example, currency is made entirely of transactional value. The fact that we can rely on it to trade warrants a premium entirely out of proportion to the value of paper that represents it.

We will call this component of premium: Liquidity Extrinsic


Let’s take inventory. Asset values look like options composed of:

  • intrinsic value: a conservative sum of an asset’s future cash flows or consumption value
  • extrinsic value:  the premium in excess of intrinsic comprised of:

    • imagination extrinsic: a premium derived from hard-to-approximate, low probability states of the world that presumably benefit the asset 

    • liquidity extrinsic: a premium built on “networks of confidence” which re-assure that you can convert an asset to cash. Lacking this feature an asset would burden your liquidity profile

Asset Value = Intrinsic + (Imagination Extrinsic + Liquidity Extrinsic)

The Perspective Of The Marginal Buyer

With our elements defined, we can now discuss setting the price for an asset. Price is a prerequisite for liquidity. Think of it this way, the value of an asset, for example, shelter exists independent of price. If there is zero bid for your house, but it keeps you dry, it still has value to you. Pricing is what allows an asset to find liquidity. Price is just the bridge between buyer and seller.  A volatile market, with prices ripping in every direction without continuity, is illiquid by definition.

The question of who sets the price is really “who gives the asset liquidity?” Let’s imagine a hypothetical order book. We will fill in the bid stack with a taxonomy of players, with decreasing bid price, just like a real order book.

Mapping the bid stack to the elements of value

Let’s map the investor type to the liquidity they provide. We will start with the lowest bid and work our way to the highest.

  • Distressed investors

    Focus on the book value portion of intrinsic.  Distressed investors are using the assets comprising the book value as collateral for their liquidity.

  • Value investors

    Focus on the full intrinsic value. Value investors are using the earnings power of the company’s management + the assets as a basis for their liquidity

  • Growth investors

    Focus on imagination extrinsic. Growth investors are willing to speculate on future paths that may lie over the hills. Their liquidity underwrites the potential for an unchallenged blue ocean.

  • Magical Thinking Investors

    These investors are somewhere in between LSD levels of imagination and playing hot potato. The entire bid is contingent on the belief that someone else might pay more. It’s pure liquidity extrinsic. It’s GME. It’s DOGE. It’s intentionally buying ZOOM instead of ZM or SIGL when Signal is actually private. 

    This is not entirely ridiculous. Holding currency for its liquidity value, can be thought of as magical thinking. This is not derogatory. If you believe unpegged fiat is a “shared story” then it’s a monument to human cooperation. (Of course, trying to pay your taxes in anything other than USD will lead to knocks on your door by men in ill-fitting suits and sunglasses…so maybe I’m discounting military coercion too much.)

Liquidity Extrinsic and The Bid Stack

  • Liquidity premiums can exist anywhere and everywhere across the bid stack.

    Faith in liquidity increases the demand for an asset since it is easily convertible back to the fiat your obligations are denominated in. If you did not trust liquidity, you would need to hold more fiat in reserve just in case. This would reduce your demand for assets.

  • Liquidity extrinsic becomes a higher proportion of the extrinsic as you ascend the stack.

    We already saw that the marginal “magical thinking” bid is entirely made of liquidity premium. It can be reasonable as in the case of fiat currency, or wildly speculative like Black Lotus Magic cards. What happens at the distressed end of the stack where there is no liquidity extrinsic? 

    This is the zone where fundamentals are fully central. In a recent interview on Corey Hoffstein’s Flirting With Models, volatility manager Cem Karsan explains:

    In the very long term, all that matters is cash flows. At some point you’re gonna have a liquidity crisis and when the liquidity is not available, companies have to create their own liquidity and that’s where fundamentals matter…they matter, to the extent that they are necessary for purchasing their own stock or buying other companies.

    I’ve used this analogy before, it’s kind of hokey, but I can’t think of a better one. If you’re on an airplane, 30,000 feet off the ground, that 30,000 feet off the ground is the valuation gap. Valuations are really high, but those engines are firing. Are you worried up in that plane about the valuations or are you worried about the speed and trajectory of where you’re going, based on the engines, based on the flows? The flows are what matter for where you’re going.

    But when all of a sudden those engines go off, how far off the ground you are is all that matters. And so, [valuation] is more of a risk management tool, and ultimately it really matters when you have a liquidity crisis.
    It also matters if rates were to go back to 8, 9, 10%. Something crazy again, where nobody can borrow money, and there is no liquidity. Cash flows are all that matters again and we have a world where fundamentals are all that matters. So I want to be clear. It’s not that fundamentals don’t matter at all, it’s that they don’t matter in a world of massive liquidity. 

    Read the boldfaced words again. You should be uneasy. The textbooks, with their dogmatic models of DCF and valuation techniques, appear to be preaching a style of investing that gets lost in the liquidity. We’re going to need a closer look.


  • We have defined our elements of value: 

    • Intrinsic (this is not just book value but includes a sum of reasonably visible future cash flows)
    • Imagination Extrinsic and Liquidity Extrinsic

  • We have identified our “bid stack” of distressed, value, growth, and “magical thinking” investors

  • We have mapped the bid stack to the elements of value

  • We know that as we get to higher marginal bids, liquidity premiums dominate the price.

How An Asset Flows Through Tiers Of The Bid Stack

The liquidity an asset receives depends on which class of marginal buyer is setting the price. Flows are a response to how the top bid perceives changes in the element of value they are focused on.

We’ll look at 2 examples.

1. When Intrinsic Value Goes Up, And The Stock Falls

If distressed or value investors represent a stock’s marginal liquidity there is a limit to how lofty the valuation can get. While we have allowed our version of intrinsic value to include a multiple that multiple has a speed limit. The limit isn’t a hard number on a street sign, but something on the order of the inverse of the discount rate which accounts for both risk and cost of money. Even if we use a 0% interest rate, there’s still a risk premium. If we are aggressive and say that’s only 3% we are talking about the intrinsic multiple in the realm of 33x. The exact number doesn’t matter, but subjectively speaking, this would be on the expensive side of intrinsic.

To break into a higher gear of valuations, the marginal bid has to come from imagination extrinsic focused investors.  The multiple that rests on is effectively unbounded (AMZN traded at egregious multiples in its early years and in hindsight they were not egregious enough). But this also works in reverse. If a stock’s imagination extrinsic is offensively large, its success can actually lead to poor returns.


The intrinsic value increases as it makes profits, but its extrinsic value declines. The number of forked paths ahead of it evaporates faster than its fundamentals could ever make up for. It’s the same feeling you’d have if you bought a put option on a stock, and lost money even if the stock fell. You overpaid for the extrinsic which receded more than stock’s decline.

Turning to another episode of Infinite Loops, here’s @maxarb colorfully explaining:

Somebody said to me once, a smarter, older business guy, a board member that I know is like, “If you have a fast blind growth kind of company, the last thing you want to do is really get revenue. Once you get revenue, the last thing you want to do is get profit.”

I was younger then. I didn’t understand what he
was saying. And he was just like, “You don’t understand. There’s multiples that they sell at. And once there’s EBITDA, nobody cares.” And now you’re getting multiples of EBITDA.

He’s like, “I want multiples of shit. I want
multiples of magic.” And I asked, “Why?”

He goes, “Because once people have something they can poke
holes at, then you have a really big problem there. Then you have to play defense.” And everybody knows that once somebody casts a stone and there’s a crack in the window, playing defense becomes really, really difficult. If you’re throwing a stone at Space X or Tesla, it’s like, all right, well go ahead. What are you  throwing it at? There’s nothing to throw it at. It’s not there yet.

Your marginal liquidity rolled down from a price invariant buyer to one that uses Excel to justify its bid.

2. When Liquidity Is The Only Element Of Value

Suppose you think the upcoming earnings matter. Your tacit assumption is that the best bid cares about intrinsic or possibly imagination extrinsic. You must believe value and/or growth investors are in control. It’s comforting to think so. Although it’s not perfectly clear whether that’s reality. It could also be the case, that enough people think that value and growth investors are driving the flows, so it’s safe to focus on what they might focus on. That world would not look different if you just observed news and prices. But it is different. It underestimates how much liquidity itself drives price.  

Recall how DOGE and GME were being driven entirely by liquidity.  Here’s Alameda’s Sam Bankman-Fried on The Odd Lots podcast:

A beautiful moment was the moment that Robin Hood banned buying a Gamestop. [It was beautiful] because of what happened next…[when] GameStop crashed because they could only sell [and people]  couldn’t buy but they had money. Instead they bought what is, in retrospect, the only possible answer to this question, as soon as you hear it  you’re like “Oh, of course that’s what they bought”.

They bought Doge.

So, as soon as Gamestop started crashing Dogecoin 10x’d. And it’s like absolutely beautiful [because] Gamestop and Dogecoin are like very, very similar products.

As you realize that liquidity alone can drive value, it starts to feel that it totally swamps the sensible stuff that textbooks talk about. One day business considerations are driving price, the next day WSB shows up. Even if they help you it’s unnerving. Like making money on a trading error.

Other favorite examples of liquidity being the sole driver of value:

  • Archegos levered longs that imploded in March 2021. Viacom dropped >50% from its high and never recovered.
  • Amaranth blew up on a long March/April gas futures bet, which ultimately collapsed from over $3 to zero.

There is a commonality between these trades. The peak prices were built entirely on the outsize liquidity it required to drive them there. But liquidity is an unpredictable mistress. The legend I’ve heard is Brian Hunter offered to sell the spread back to Centaurus, pleading that he would offer a discount from the $3 price. 
Allegedly Centaurus founder John Arnold bid him a mere 50 cents. Offended, Hunter pleaded, “but it’s trading $3!”

Arnold replied: “Because you put it there. It’s worth $.50” 

[This is all lore from my cheap seat…if anyone knows the real story, I’d love to update this post with it!]

If liquidity is driving price, but people are talking about fundamentals, it’s like being on a plane to Calgary but everyone’s talking about how fun it’s going to be when we touch down in Vegas. Somebody packed the wrong clothes.

The Most Practical Takeaway: Know Your Game

These 2 examples highlight regime changes when the category of marginal buyer changes and with it the focus on intrinsic or extrinsic.  If you are playing the extrinsic game, your dashboard needs to be concerned with liquidity and flows. Momentum investors don’t cite fundamentals. Vol traders might not even know what the underlying even does. Their inputs match the game they are playing.

Returning to Cem Karsans interview:

[If] you’re betting on something that doesn’t, in the short term, have anything to do with the outcome, you are in a really dangerous situation…Until the liquidity situation changes, other than the fact that other participants are playing the same game and affecting those flows, [fundamentamentals are] not what’s ultimately driving price.

Ask yourself, is the asset moving from one part of the bid stack to another? You may have started shorting GME last year based on valuations but once it turned into a virus you were still using a telescope when you needed a microscope. There’s a reason famous short-sellers like Chanos or Cohodes are not known for playing the valuation game from the short side. Instead, they are hunting for frauds. The reason is there is no limit to arbitrage on the short-side (see Shorting In The Time of ShitCos) , so they are playing a game with a catalyst. With a visible horizon for price and truth to converge.

How about investors who drift into calling bubbles? If you want to profit from bubbles imploding, you must identify when the focus of an asset moves from its extrinsic to its intrinsic. From our framework, it’s clear that it is a question of liquidity. Many investors already understand this leading to an obsession with macroeconomics and central bank balance sheets. [When I read about those topics I feel as overwhelmed as when I first started learning options. As a 21-year old, I’d need to stop every few moments, “ok, so if I short a put, and puts make money when stocks go down, then I must be…long!”. Nowadays it’s, “ok, so if the Fed injects liquidity, it’s balance sheet decreases. Wait, I mean increases. Wait…ahhh, make it stop!” This hasn’t stopped a bubble in macro gurus…I guess the tourists who would have went to Vegas in 2020 found a new club to hit.] Making money from bubbles is diabolically difficult even if you become an expert in M2 or Japan. There are creative approaches that do not take them head on.

The main point is to match your tools and horizon to your game.

Wrapping Up

Between stock valuations, crypto returns, and a headlong embrace of risk within months of an economy-halting pandemic, the role of finance as manifested by investing looks like a farce. Market watchers are asking themselves:

  • Is the bulk of what we are taught about investing poorly matched for the timelines we buy and sell on?
  • Is a 5 or even 10-year track record noise if liquidity regimes delay any verdicts? It feels like the betting windows at the track have never been busier, but we never see the result of a race. 

As I’ve listened to interviews, read, and thought about what the hell is happening, I’ve come to believe that markets are not absurd. It’s our illusions about how tidy they are which is absurd. By asking ourselves meta-question about who the marginal buyer is and what their focus is we can tranche the investing world into different games. Not every tranche is driven by the same inputs. Some layers in the stack are concerned with extrinsic and others intrinsic.

Surviving within each tranche demands its own set of tools to furnish bids. To give liquidity to the assets it targets.  On the low end, cash flows matter because they create their own liquidity. On the high end, external liquidity drives most of the value. Imagine a new set of greeks for this segment. ∂ Extrinsic / ∂ Liquidity. The second derivative of that sensitivity would tell you that the sensitivity itself is changing. That’s what happens as you move from one tier of the stack to the next.

The conventional finance education omits so much of how the practice of investing manifests. Ultimately, your goal is to have the outcomes of your bets have something to do with your rationale. To do this, go ahead, read the glossary of corporate finance terms. Finance is totally real. But skip the investing sections. They present the practice of finance as being built up from the glossary. Instead, bind Matt Levine’s daily columns into a book, and work backward from the fact that markets are made of humans. Investing is about behavior and that is closer to horoscopes than balance sheets.

Darrin Johnson On Flirting With Models

Independently Shorting Volatility with Darrin Johnson (Podcast)
Corey Hoffstein’s Flirting With Models

Darrin Johnson is an options trader and the first independent trader Corey’s had on the pod. Considering Corey’s show focuses on institutional and cutting edge investment professionals, it says a lot that he had Darrin on the show. I’m not surprised, I’ve been following Darrin on Twitter for years and impressed by his understanding of options trading. I have always believed that option trading is an apprentice activity. I cannot imagine how difficult it would be to learn the game with the guidance of masters. Darrin has managed to cobble together that guidance from a variety of sources including Euan Sinclair’s books, Twitter, hiring grad students to walk him through the academic math, running countless simulations, and detailed reconstructions of financial products.

Here are some of my favorite aspects and insights from the interview (with my commentary):

  • Darrin’s entrepreneurial path before he even found his way to trading is worthy of an interview of its own.
  • The importance of building sims instead of backtesting as a way to get more samples. For those of us who trade for firms, we benefit from the collective osmosis of many traders discussing trades and situations in detail. All those morning huddles and afternoon meetings help us build a mental library of counterfactuals. Darrin did the next best thing…build simulations, knowing that a backtest is a single version of what could happen. This is crucial to get a fingertip feel for how positions behave.
  • The idea of pricing out financial products to the penny. Darrin called it “back-office” kinda stuff that retail traders don’t do. Corey said he does this too. This is exactly what you do at a mm/arb shop. As a clerk I remember building giant spreadsheets to price fair value for ETFs. This is not optional work. You will use those skills to attack new products and understand the frictions to arbitrage.
  • At around the 40:00 minute mark Darrin explains why he concentrates his selling on at-the-money or meaty options not the wings. He makes the correct insight: when you sell tails, you need to capture the entire premium. The hit ratio of selling tails is high but when you lose you lose many multiples of the premium. If you fail to collect the full premium, it will not make up for the losing trades. The difficulty of selling tails is even trickier yet. Darrin explains how betting against longshots leaves you uncertain if you have an edge in the first place. In my words: good luck differentiating between a 50-1 shot vs a 100-1 shot. That’s the difference of 1 probability point but it’s massive in payoff space. I discuss further in Tails Explained.
  • Here’s a more subtle insight from the interview. Darrin tries to find the structure that has the best payoff to his vol forecasts or thesis. Notice the subtext. If there’s a “best” there must be a “worst”. This is the basis of relative value trading — buy the best payoff and sell the worst payoff contingent on the vol forecast coming true. For example, if you thought skew was cheap in the oil complex compared to macro backdrop, you could buy the cheapest puts across the oil and products suite. You could buy some ratio of oil puts and selling RBOB or HO puts depending on how how you think the macro stress plays out. Now you might want to be outright long the vol forecast coming true so you might not want to turn this into a basis trade (the advantage of a basis style trade is you can likely do it bigger). Or you could choose to buy oil puts and say sell puts on an equity index where the stress has been priced in. Because you’d be taking an even larger basis risk than staying within the oil complex, you would size the trade smaller than the oil basis trade, but perhaps larger than an outright long oil vol position. The point is there is a lot of creativity on trade expression that balances edge and basis risk.

Since the interview was so good, it got passed around quite a bit on Twitter. In one of the ensuing discussions, I offered my down-to-the-studs view of what options trading really is:

There’s nothing magical about options trading. Paraphrasing Darrin, the intellectuals who are drawn to it prolly need a more blue collar view. Step back and think about what the market needs. What risks doesn’t it want to hold? Obsess over the who and why, not moments [of a distribution]… For years the “job to be done” in vol was be willing to pay theta The marketplace was bidding for that role and vol folks that filled it did well. The market “bids” for different roles all the time in vol-land and the job of a vol trader is to fill it. Simple not easy.

@TheSpeculator0, who trades for a firm, astutely observes: It’s not easy to catch the regime change that switches up the roles.

My response:

That’s why risk management is key. The nature of market-making, even if you don’t explicitly have that title, is you lose on the regime change. So you adjust and hope the next regime lasts long enough to pay you for the [money-losing] transitions.

If you want a fuller discussion for the raison d’etre of vol trading, you probably won’t do better than Corey’s podcast with QVR’s Benn Eifert who describes the job as “bringing balance to the force”. I took full notes for you…Flirting With Models: Benn Eifert (Link)

Interviewing Candidates

With the school year rapidly coming to a close, I was reflecting on how fortunate we were to find such an amazing woman to teach our pod comprised of our boys and two of their friends who are matched in age. I feel fortunate because this woman who we entrusted 40 hours a week of exposure to our kids was chosen on the basis of 2 hours of interviews and some reference checks. She was selected from just 4 possible candidates, sourced mostly from There’s no way to objectively feel other than lucky.

If our odds were improved in any way, it was because of the other set of parents in our pod. I was blown away about how good they were at asking questions and reading the candidates. Yinh, who has now spent countless hours both screening and interviewing podcasts guests, felt the same. This couple is masterful in finding efficient questions to cut to the core of the candidates. It gave me so much appreciation for that skill especially when we consider the stakes.

Well, this week I came across Graham Duncan’s outstanding post about interviewing job candidates. It was one of those posts I added to my list of influential readings and re-factored for my own future reference. It’s full of practical advice but philosophically it really starts with the idea that interviewing is really a narrow application of a broader art.

From the intro:

The philosopher Kwame Appiah writes that “in life, the challenge is not so much to figure out how best to play the game; the challenge is to figure out what game you’re playing.”

When I try to figure out what game I’m playing, I see that for the last 25 years I have been playing a game of strategy applied to people, a game where over and over I try to answer the question “what’s going on here, with this human?”  In this essay, I make recommendations about candidate selection based on thousands of assessments I have made and my somewhat obsessive interest in the topic.

My goal in this essay is to help others make better decisions on a potential hire, business partner, or even life partner as quickly and as accurately as possible.  It’s made up of suggested action steps and some of the ruminations that underlie them. At the end I include my own assessment of different personality assessments and some of my go-to interview and reference questions.

My single favorite line is an idea I take seriously:

One of the greatest gifts we have for each other, for our children and spouses, for our teammates, is the positive feedback loop we can put someone into purely by believing in them, by seeing their genius and their dysfunction clearly and then helping them construct conditions for the former to flourish.

That emphasis is mine. I consider this to be one of the cheapest forms of human capital and this essay is ultimately about directing that capital.

Towards the end of the post you get a nice primer on personality tests as well as guides for conducting interviews and calling references.

Continue to my own takeaways and the link directly to Duncan’s post, Graham Duncan’s “What’s Going On Here, With This Human?” (Link)

Interviewing Engineers

I enjoyed tech founder Slava Akhmechet’s “super secret proprietary no-nonsense guide on how to interview engineers.” I am unqualified to know how valid it is, but it was fun to read. Find the full post here.


This guide is for interviewing very talented people.

It’s applicable if you’re building an extraordinary team at a hard technology startup. If your startup is technology-enabled, or you’re designing an interview process at a large company, or you’re hiring for well-established roles to do specialized tasks, this guide isn’t for you. You will not find references to “junior vs senior” or “front-end vs back-end” here. From the perspective of what we’re trying to accomplish, specialization is for insects.

There are three things you need to determine about a candidate: talent, judgement, and personality.

Think of hiring an engineer as if you’re buying a race car. The first thing you must look for in a race car is horsepower, because without horsepower the car is useless for racing. The horsepower of engineers is talent. Without talent, engineers are useless for building products, so it’s the first thing you must look for in a candidate. It doesn’t matter how nice the person is, or how hard-working. No horsepower, no race.Talent alone is insufficient. The world is filled with talented people who never get anywhere for a myriad reasons. Laziness, anxiety, fragility, impulsivity, egotism, victimhood, just to list a few. So once you’ve identified talent, you have to determine the shape and quality of its vessel. Where will the person direct their talent? And are they well-adapted to the demands of the external world?


  • Talent is a combination of speed, working memory, taste, knowledge of the toolchain, understanding how computers work, and ability to program. It’s IQ, but specialized for engineers. IQ is 50-80% heritable, impossible to improve, normally distributed, and strongly correlated with success in fields like science and engineering.
  • This matters for candidate selection because someone can improve within their talent band, but they can’t jump talent bands. A person with IQ of 145 (σ=3) is dramatically better than a person with IQ of 115 (σ=1). If you watch both people work, it’s like they’re from different galaxies. So your job as an interviewer is to find out the candidate’s talent band.


  • Judgement tends to be weakly correlated with talent, and comes down to this: there is a difference between a tinkerer and an engineer. They’re close, but they aren’t the same thing. Tinkering is building a Rube Goldberg machine for the sheer delight of building it. Engineering is discovering and satisfying (often unintuitive) constraints. The tinkerer works for the machine. The engineer makes the machine work for him.
  • Most engineers aren’t tinkerers, they’re in it for the money. Don’t hire those because they have no soul and hanging around them will slowly poison your own soul by osmosis. Conversely, many tinkerers aren’t engineers. Don’t hire those either, because they’ll build beautifully complex structures that serve no purpose other than their own existence. You want people who take great delight in building Rude Goldberg machines, but balance it with a broader sense of what they’re trying to accomplish.
  • Another way of thinking about it is that talent is a combination of general aptitude and programming tactics. Judgement is programming strategy.


  • The easiest way to think about it is in terms of the big five personality traits. These are kind of like Myers Briggs, except real. The three traits you especially care about are conscientiousness, agreeableness and neuroticism. Psychologists have precise technical definitions for these terms, but in plain language you’re trying to find out (a) whether the candidate is lazy or hard working, (b) are they an asshole, and (c) are they going to be stuck in analysis paralysis and invent life emergencies for themselves all the time instead of working.
  • The bad news is that you can’t find any of this information out until after you’ve hired the candidate. You can set up a low pass filter that might trap a few bad apples, but almost everyone is on their best behavior during interviews. Personal flaws rarely come out until long after the person is working for you. My sixth sense for picking out talent and judgement is pretty good. But for personality it’s only slightly better than random. So unless you have magic powers in this area, set up a low pass filter and later fire bad personalities as they reveal themselves.

Random observation

I’ve now noticed the respect for the Big 5 Personality Traits in multiple places. They’re beloved in tech world.  Slava said the Big 5 “are kind of like Myers Briggs, except real.” Marc Andreesen focuses on ‘conscientiousness’ trait in his interview on education (my notes here). And as we saw earlier, Duncan wrote “Within psychology, it’s the equivalent of gravity, and at this point, nearly everyone in academia finds it a useful mental model for personality.”

Personally, I scored around average for neuroticism, extraversion, and openness. I scored over the 90th percentile in conscientiousness (yay, allegedly) and agreeableness. Of course, as a trader I find agreeableness to be a backhanded compliment (see my post Being a Disagreeable Investor).

At any rate, when I hear the words “Big Five” I still think of going on safari.

More useful posts on interviewing:

  • Cedric Chin’s Using Head Fake Questions To Achieve Your Career Goals (Link)
  • First Round’s 40 Favorite Interview Questions from Some of the Sharpest Folks We Know (Link)