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.
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.
- What are the odds of each scenario?
- What is the payoff in each scenario?
- 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:
- What are the odds of each scenario?
- What is the payoff in each scenario?
- 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 ).
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:
- “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.
- “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…]
“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.
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.
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.
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.
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).
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:
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
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)
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 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.
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.