the singularity trade

Not to deter any stubborn bears, but just understand your history. In 1999, the Nasdaq returned 86%.

If we ignore the small 3.2% down year in 1994, that run looks even crazier and capped with an insane blow-off top.

The 1999 blow-off top is pretty interesting from a how-do-I-reconcile-option-pricing-with-real-world lens.

I’ve written a bunch on how volatility measures are sensitive to sampling periods.

See:

Volatility scaling can feel unintuitive.

If an asset’s annual standard deviation (ie volatility) is 16%, then its daily standard dev is ~1%

Well, from that, it’s clear that you can have say a 10 sigma move in a day, but not in a year. That alone seems to point to a weakness in how we scale volatility through time.

But this is mostly resolved by measuring distances in lognormal space correctly. When you do that, you find that +86% is MUCH closer than -86%.

Just screenshot the formula in the post and treat Gemini like a calculator:

This explains why calls that are 50% OTM calls are worth more than puts that are 50% OTM (even if the spot and forward were the same).

To consolidate knowledge, it’s why collars can look so attractive in high vol stocks:

“Stock pickers market”

I’m old enough to remember when investment managers complained that the Fed drove the market, everything was correlated, and there was little reward for discerning between companies.

Well, we’re in the opposite world.

This is showing put skew falling and call skew rising in QQQ:

moontower.ai 5/29/26

This is front-and-center to the options market:

There’s a record disconnect unfolding in the trading pits right now

A chart from the article shows the spread between the weighted avg stock vol in the SPX vs the index vol. It’s another proxy for cross-correlation as the index vol is dampened relative to the stock vols because the stocks are doing a great job diversifying each other.

A stretched relationship can get more stretched. But as it stretches, there is a mathematical reason why the spread would revert. Think of the limit. If 1 company achieved singularity and ate all the other companies, its weight would increase relatively as each dollar it made was a dollar less for the others until it was the index. This is NOT a tradable idea. That is a make-believe world. I’m only being pedantic to help you move the pieces around in your brain to help you see how they fit together.

But the price action of anything related to AI ripping vs everything else is a giant singularity trade, and from that context, the low correlation makes superficial narrative sense for now…a handful of companies are expected to eat the rest.

But I’ll pose this one…if instead this handful of companies are becoming the COGS of all other companies, wouldn’t that look more like the stories we’ve heard that I had Claude reconstruct by asking it to describe the circular revenue phenomena in bubbles:

Company A buys ads on Company B’s site. Company B uses that revenue to buy servers/software from Company C. Company C buys ads on Company A’s site. Everyone books revenue, everyone’s growth numbers look great, valuations rip higher — but no net new money is entering the system from outside customers. It’s just the same dollars chasing themselves around a closed loop, with each pass inflating reported revenue.

The poster children were the late-90s telecom and dot-com names. Global Crossing and Qwest got nailed for swapping fiber capacity with each other and booking both sides as revenue (”capacity swaps”). AOL was accused of round-tripping ad deals. A lot of dot-coms were essentially selling ads to each other, with VC money funding the ad budgets — so the “revenue” was really just recycled venture capital.

The concern isn’t fake deals today, but the circularity possibility means index vol will have its revenge. Good luck with timing though.

SpaceX

It’s interesting to hear Mitchell step through the numbers of how much day 1 shares need to be absorbed and how unprecedented this is. Recall in PTJ’s interview on Invest Like The Best:

2000 was the easiest bear market I’ve ever seen in my whole life. It’s got so many similarities to right now, in the sense that the bear market of 2001 and 2002 were a consequence of all the IPOs in ’99 and 2000. And then as they unlocked, you just had this never-ending cascade of selling, that’s a great way of putting it. And we’re getting ready – I want to say that the contemplated IPOs for next year are going to be five or six percent of market cap. So why are we where we are right now? Because we’ve been retiring two or three percent of market cap, probably a little less than 2% of market cap, every year without fail for the past 10 years [through buybacks.]

And so now all of a sudden, you’re gonna completely reverse that math. And so, I don’t think it necessarily happens instantaneously with the IPOs, but then there’ll be the unlocks. So you can see a situation where, okay, maybe we go through some kind of rolling top. And then 18 months from now – six months, we’ll have to look at the unlock schedule. But you’re going to want to watch those because that’ll just be adding equity supply. And you’ve already gonna be diminishing the buybacks because of all the commitment to capex from the hyper-scalers. They’re already gonna be eating into their cash flow.

The current set-up feels very strange. It seems too easy to think it’s going to be a local top right? But it’s a hard idea to resist. It feels like it’s a negative for gross returns and then under the hood, possibly chaotic for sector flows (like to absorb the IPO do people rebalance out of what went up the most recently? That feels like a pretty natural idea).

You have pockets of extreme bullishness manifesting in options with cheap put skew and risk reversals and left-for-dead implied correlations but the bearish factors are also common knowledge:

  • IPO issuance
  • Midterms (assuming Dems are the bear choice)
    polymarket on 5/29/26
  • elevated bond yields 

In other words, current prices are NET of everyone knowing about these factors. By the way, this is always the problem with markets. If you see something on the horizon and think it’s bearish, whose to say the current market wouldn’t just be higher if that thing you’re latching on to is observable by others.

What’s the more contrarian position right now, to be bullish or bearish?

The option point spreads have shifted in a way that suggest bullishness is consensus.

Moontower agent

The moontower agent has been in the wild for a month now, and it’s been an awesome companion to help you reason through trading questions. It’s connected to the data we buy and process, and it’s tuned and under ongoing reinforcement learning for trading contexts.

=> 🤖Ask the agent a question

It’s powered by AI harnesses, of course, so the output is non-deterministic, so it’s helpful to report back on what it does well and poorly so we can keep course-correcting.

a delightful conclusion to the Investment Beginnings Series

This week I taught Class 5 of the Investment Beginnings series I’ve been doing with the 12+ year olds.

my little guy helping me set-up

It’s the last class in the series before we do “labs” in July. During lab, we’ll convene when the market’s open and I will give each kid individual attention as they execute an investment. I want to make sure they know how to read the screen, navigate their broker site, see the confirmation of the execution etc.

This last class was special. I’ve been posting all the materials online and there are families following along remotely. One dad sent me an app that consolidated and vibecoded the slides and games. He and his son worked on the project together:

https://investment-class.vercel.app/

And this next part blew people’s minds in the class, not to mention my own. A mom brought her son from Miami because he’s been obsessed with the class and wanted to be here in person with the other kids. I’m speechless. Supermom and superkid.

We took them to dinner with my family and brought along my son’s good buddy so our visiting friend would know a few people before stepping into the class. I can’t gush enough about how nice this all was.

When Class 5 ended, a lot of parents came to talk to me and said all this kind stuff and gave me totally unnecessary, generous gifts (I would have done the same so I get it but also just feels like too much). The most important thing is how all these kids’ gears are turning. It feels like a no-brainer to really clean this up (I learned a lot from doing it and know how I’d mod it in the future) and turn it into something. Maybe a well-produced YT thing, but I’m stretched pretty thin. We’ll see, I guess. Famous last words.

Anyway, here’s the outline of class 5 and link to all the materials from the classes.

Class 5 — Making Trades & Reading Markets

  • Different kinds of auctions and how markets are continuous auctions
  • The order book: bids, asks, spread, and what “depth” actually looks like
  • Price discovery as consensus — the price aggregates what everyone knows
  • Market hours, plus what pre-market and after-hours really are (and why beginners should avoid them)
  • Public vs. private markets, with real estate as the bridge example
  • How an IPO turns a private company into a publicly traded one
  • Why baskets exist: the easy button for diversification (callback to Class 4)
  • Three kinds of baskets — index, themed/sector, manager-picked
  • ETF vs. mutual fund: same idea, different checkout (auction all day vs. one daily NAV)
  • Index construction math: cap-weighted vs. equal-weighted, with four real stocks
  • Why SPY and RSP — the same 500 names — can produce materially different returns
  • 🔨 Homework: talk to parents about a brokerage account, ahead of the July lab where students place their first real trades

We spent much of the class doing a mock trading game:

 

How the game worked

There are 16 kids.

  • Each gets 2 cards — that’s private info
  • There are 3 “stocks”: Hearts, Spades, and Red
  • At the end of the game, each stock settles to the sum of the cards held collectively in that category across all 32 dealt cards
  • Card values run 1 to 13 (ace to king)

Kids bid, offer, and trade with each other based on what they think final settlement will be. They log transactions on index cards they carry.

Every few minutes, news hits — I reveal some of the remaining 20 cards. These are cards that will NOT contribute to the value of the 3 stocks.

The Teaching Moments

Basic valuation

  1. What’s the maximum value of each of the 3 stocks? (Also a fun way to teach someone to quickly compute the sum 1 to N.)
  2. What is the fair value of the stocks at the start of the game, when no common information has been revealed?

Information and private signals

  1. What is the fair value of Hearts if you’re holding the 9 of Hearts?
  2. Ask the kids: what’s a good hand to be dealt, and why? (A very simple exploration of what “information” actually is.)
  3. After news is revealed, how do you update fair value? Walk through the exact math.

Reading flow

  1. Your fair value is always subject to adjustment based on flow. What is Alice’s bid generally saying about Spades? What is Mike’s offer suggest about Red?
  2. At the end, computing P/L is a big exercise — marking trades to settlement.

We didn’t go into crazy depth on any of these. Just getting a basic understanding easily takes a group of 16 kids an hour, and even then some are lost. Totally expected. Honestly, many adults are too.

It’s super interesting to see who gets it very quickly though.

The origin of the game

This was the first trading game I remember doing as a trainee at SIG. All the new hires in NYC played while the trainees who had been around for 3-9 months traded options on these “stocks.” Their hedge orders would get sent into our trainee market!

Moontower #317

Friends,

In this issue:

  • streetlight effects
  • Investment Beginnings Class 5 was a delight
  • thoughts on the current market cycle and options

I’ll be short up here with one rec since the investing sections are a little longer. Just have extra exhaust since last week’s graduation issue skipped finance stuff.

everything is a nail, or at least it ought to be | 5 min read

This is a short book review by Dan Davies of The Irrational Decision by statistician Ben Recht.

Recht argues that if a hammer is genuinely your best tool, it’s actually smart to look for nail-shaped problems or reshape problems them so they’re more hammer-friendly.

In Recht’s case, the hammer is mathematical optimization (especially linear optimization). The book traces how, over the past century, people haven’t just used optimization to solve problems, they’ve restructured problems to fit optimization’s strengths. He gives the example of the feedback loop between chip design and optimization algorithms where better chips enable better optimization, which enables better chip design, repeat.

If you recall, in my post slashing away parts of their humanity, Davies plugs C.Thi Nguyen’s book The Score (which I bought as I enjoyed Nguyen’s first book about games). Davies’ latches on to the manner in which metrics ultimately create “streetlight” effects by optimizing not necessarily for what really matters but for what’s easy to measure.

Well, as you might expect from any self-respecting James C. Scott fan, Davies praises Recht for resisting the profitable route of hyping this trajectory into AI singularity cheerleading. Instead, Recht asks: what do we lose when we reshape problems to make them algorithmically manageable? Once you’ve defined what to measure and set a success metric, an optimizer will always confess an answer. But all the real judgment happens upstream, in choosing what counts as success in the first place. That same process that advances chips is a convenient way to persuade overly left-brain, ahem, “data-driven” decision-makers.

Recht’s book ends with a thoughtful chapter on how we should make decisions, but Davies also flags an argument that knocks you a bit off balance. He makes the case that randomized controlled trials are better understood as a regulatory tool than a scientific one. I found that a bit haunting. It’s a dark thought that also casts a shadow on our accepted standards of rigorous epistemology.

Recht, Nguyen, and Davies are all quantitatively minded scholars converging on nuanced skepticism of data in what I’d describe as a next-gen version of How To Lie With Statistics. In the first gen, inferences were distortions of what the data told us (i.e. sleights of hand like substituting causation for correlation), but is the new deception to do inference honestly but use proxy measures that, to use a trading term, have a lot of basis risk to the thing we actually care about. And then the bigger question is how much of that is laziness vs trying to manipulate the terms of discourse.

Money Angle

This week I taught Class 5 of the Investment Beginnings series I’ve been doing with the 12+ year olds.

my little guy helping me set-up

It’s the last class in the series before we do “labs” in July. During lab, we’ll convene when the market’s open and I will give each kid individual attention as they execute an investment. I want to make sure they know how to read the screen, navigate their broker site, see the confirmation of the execution etc.

This last class was special. I’ve been posting all the materials online and there are families following along remotely. One dad sent me an app that consolidated and vibecoded the slides and games. He and his son worked on the project together:

https://investment-class.vercel.app/

And this next part blew people’s minds in the class, not to mention my own. A mom brought her son from Miami because he’s been obsessed with the class and wanted to be here in person with the other kids. I’m speechless. Supermom and superkid.

We took them to dinner with my family and brought along my son’s good buddy so our visiting friend would know a few people before stepping into the class. I can’t gush enough about how nice this all was.

When Class 5 ended, a lot of parents came to talk to me and said all this kind stuff and gave me totally unnecessary, generous gifts (I would have done the same so I get it but also just feels like too much). The most important thing is how all these kids’ gears are turning. It feels like a no-brainer to really clean this up (I learned a lot from doing it and know how I’d mod it in the future) and turn it into something. Maybe a well-produced YT thing, but I’m stretched pretty thin. We’ll see, I guess. Famous last words.

Anyway, here’s the outline of class 5 and link to all the materials from the classes.

Class 5 — Making Trades & Reading Markets

  • Different kinds of auctions and how markets are continuous auctions
  • The order book: bids, asks, spread, and what “depth” actually looks like
  • Price discovery as consensus — the price aggregates what everyone knows
  • Market hours, plus what pre-market and after-hours really are (and why beginners should avoid them)
  • Public vs. private markets, with real estate as the bridge example
  • How an IPO turns a private company into a publicly traded one
  • Why baskets exist: the easy button for diversification (callback to Class 4)
  • Three kinds of baskets — index, themed/sector, manager-picked
  • ETF vs. mutual fund: same idea, different checkout (auction all day vs. one daily NAV)
  • Index construction math: cap-weighted vs. equal-weighted, with four real stocks
  • Why SPY and RSP — the same 500 names — can produce materially different returns
  • 🔨 Homework: talk to parents about a brokerage account, ahead of the July lab where students place their first real trades

We spent much of the class doing a mock trading game:

How the game worked

There are 16 kids.

  • Each gets 2 cards — that’s private info
  • There are 3 “stocks”: Hearts, Spades, and Red
  • At the end of the game, each stock settles to the sum of the cards held collectively in that category across all 32 dealt cards
  • Card values run 1 to 13 (ace to king)

Kids bid, offer, and trade with each other based on what they think final settlement will be. They log transactions on index cards they carry.

Every few minutes, news hits — I reveal some of the remaining 20 cards. These are cards that will NOT contribute to the value of the 3 stocks.

The Teaching Moments

Basic valuation

  1. What’s the maximum value of each of the 3 stocks? (Also a fun way to teach someone to quickly compute the sum 1 to N.)
  2. What is the fair value of the stocks at the start of the game, when no common information has been revealed?

Information and private signals

  1. What is the fair value of Hearts if you’re holding the 9 of Hearts?
  2. Ask the kids: what’s a good hand to be dealt, and why? (A very simple exploration of what “information” actually is.)
  3. After news is revealed, how do you update fair value? Walk through the exact math.

Reading flow

  1. Your fair value is always subject to adjustment based on flow. What is Alice’s bid generally saying about Spades? What is Mike’s offer suggest about Red?
  2. At the end, computing P/L is a big exercise — marking trades to settlement.

We didn’t go into crazy depth on any of these. Just getting a basic understanding easily takes a group of 16 kids an hour, and even then some are lost. Totally expected. Honestly, many adults are too.

It’s super interesting to see who gets it very quickly though.

The origin of the game

This was the first trading game I remember doing as a trainee at SIG. All the new hires in NYC played while the trainees who had been around for 3-9 months traded options on these “stocks.” Their hedge orders would get sent into our trainee market!

Money Angle for Masochists

Not to deter any stubborn bears, but just understand your history. In 1999, the Nasdaq returned 86%.

If we ignore the small 3.2% down year in 1994, that run looks even crazier and capped with an insane blow-off top.

The 1999 blow-off top is pretty interesting from a how-do-I-reconcile-option-pricing-with-real-world lens.

I’ve written a bunch on how volatility measures are sensitive to sampling periods.

See:

Volatility scaling can feel unintuitive.

If an asset’s annual standard deviation (ie volatility) is 16%, then its daily standard dev is ~1%

Well, from that, it’s clear that you can have say a 10 sigma move in a day, but not in a year. That alone seems to point to a weakness in how we scale volatility through time.

But this is mostly resolved by measuring distances in lognormal space correctly. When you do that, you find that +86% is MUCH closer than -86%.

Just screenshot the formula in the post and treat Gemini like a calculator:

This explains why calls that are 50% OTM calls are worth more than puts that are 50% OTM (even if the spot and forward were the same).

To consolidate knowledge, it’s why collars can look so attractive in high vol stocks:

“Stock pickers market”

I’m old enough to remember when investment managers complained that the Fed drove the market, everything was correlated, and there was little reward for discerning between companies.

Well, we’re in the opposite world.

This is showing put skew falling and call skew rising in QQQ:

moontower.ai 5/29/26

This is front-and-center to the options market:

There’s a record disconnect unfolding in the trading pits right now

A chart from the article shows the spread between the weighted avg stock vol in the SPX vs the index vol. It’s another proxy for cross-correlation as the index vol is dampened relative to the stock vols because the stocks are doing a great job diversifying each other.

A stretched relationship can get more stretched. But as it stretches, there is a mathematical reason why the spread would revert. Think of the limit. If 1 company achieved singularity and ate all the other companies, its weight would increase relatively as each dollar it made was a dollar less for the others until it was the index. This is NOT a tradable idea. That is a make-believe world. I’m only being pedantic to help you move the pieces around in your brain to help you see how they fit together.

But the price action of anything related to AI ripping vs everything else is a giant singularity trade, and from that context, the low correlation makes superficial narrative sense for now…a handful of companies are expected to eat the rest.

But I’ll pose this one…if instead this handful of companies are becoming the COGS of all other companies, wouldn’t that look more like the stories we’ve heard that I had Claude reconstruct by asking it to describe the circular revenue phenomena in bubbles:

Company A buys ads on Company B’s site. Company B uses that revenue to buy servers/software from Company C. Company C buys ads on Company A’s site. Everyone books revenue, everyone’s growth numbers look great, valuations rip higher — but no net new money is entering the system from outside customers. It’s just the same dollars chasing themselves around a closed loop, with each pass inflating reported revenue.

The poster children were the late-90s telecom and dot-com names. Global Crossing and Qwest got nailed for swapping fiber capacity with each other and booking both sides as revenue (”capacity swaps”). AOL was accused of round-tripping ad deals. A lot of dot-coms were essentially selling ads to each other, with VC money funding the ad budgets — so the “revenue” was really just recycled venture capital.

The concern isn’t fake deals today, but the circularity possibility means index vol will have its revenge. Good luck with timing though.

SpaceX

It’s interesting to hear Mitchell step through the numbers of how much day 1 shares need to be absorbed and how unprecedented this is. Recall in PTJ’s interview on Invest Like The Best:

2000 was the easiest bear market I’ve ever seen in my whole life. It’s got so many similarities to right now, in the sense that the bear market of 2001 and 2002 were a consequence of all the IPOs in ’99 and 2000. And then as they unlocked, you just had this never-ending cascade of selling, that’s a great way of putting it. And we’re getting ready – I want to say that the contemplated IPOs for next year are going to be five or six percent of market cap. So why are we where we are right now? Because we’ve been retiring two or three percent of market cap, probably a little less than 2% of market cap, every year without fail for the past 10 years [through buybacks.]

And so now all of a sudden, you’re gonna completely reverse that math. And so, I don’t think it necessarily happens instantaneously with the IPOs, but then there’ll be the unlocks. So you can see a situation where, okay, maybe we go through some kind of rolling top. And then 18 months from now – six months, we’ll have to look at the unlock schedule. But you’re going to want to watch those because that’ll just be adding equity supply. And you’ve already gonna be diminishing the buybacks because of all the commitment to capex from the hyper-scalers. They’re already gonna be eating into their cash flow.

The current set-up feels very strange. It seems too easy to think it’s going to be a local top right? But it’s a hard idea to resist. It feels like it’s a negative for gross returns and then under the hood, possibly chaotic for sector flows (like to absorb the IPO do people rebalance out of what went up the most recently? That feels like a pretty natural idea).

You have pockets of extreme bullishness manifesting in options with cheap put skew and risk reversals and left-for-dead implied correlations but the bearish factors are also common knowledge:

  • IPO issuance
  • Midterms (assuming Dems are the bear choice)
    polymarket on 5/29/26
  • elevated bond yields

     

In other words, current prices are NET of everyone knowing about these factors. By the way, this is always the problem with markets. If you see something on the horizon and think it’s bearish, whose to say the current market wouldn’t just be higher if that thing you’re latching on to is observable by others.

What’s the more contrarian position right now, to be bullish or bearish?

The option point spreads have shifted in a way that suggest bullishness is consensus.

Moontower agent

The moontower agent has been in the wild for a month now, and it’s been an awesome companion to help you reason through trading questions. It’s connected to the data we buy and process, and it’s tuned and under ongoing reinforcement learning for trading contexts.

=> 🤖Ask the agent a question

It’s powered by AI harnesses, of course, so the output is non-deterministic, so it’s helpful to report back on what it does well and poorly so we can keep course-correcting.

Thursday webinar

Been a lot of recent chatter about volatility funds as a strategy and as a business. There’s a lot of misconceptions about them. Which makes sense, it’s an opaque world.

I’ll host a live webinar on Thursday for paid subs to share some thoughts on the topic.

Details to follow this week.

This Week In The Options Trench

 

 

Stay groovy

 

☮️

Moontower Weekly Recap

 

phantom zone

This is a straight-up rant.

If you are anywhere near financial or tech twitter you’ve seen Deedy’s tweet and the reactions to it. Here’s a reprint:

The vibes in SF feel pretty frenetic right now. The divide in outcomes is the worst I’ve ever seen.

Over the last 5yrs, a group of ~10k people – employees at Anthropic, OpenAI, xAI, Nvidia, Meta TBD, founders – have hit retirement wealth of well above $20M (back of the envelope AI estimation).

Everyone outside that group feels like they can work their well-paying (but <$500k) job for their whole life and never get there.

Worse yet, layoffs are in full swing. Many software engineers feel like their life’s skill is no longer useful. The day to day role of most jobs has changed overnight with AI.

As a result,
1. The corporate ladder looks like the wrong building to climb.
Everyone’s trying to align with a new set of career “paths”: should I be a founder? Is it too late to join Anthropic / OpenAI? should I get into AI? what company stock will 10x next? People are demanding higher salaries and switching jobs more and more.

2. There’s a deep malaise about work (and its future).
Why even work at all for “peanuts”? Will my job even exist in a few years? Many feel helpless. You hear the “permanent underclass” conversation a lot, esp from young people. It’s hard to focus on doing good work when you think “man, if I joined Anthropic 2yrs ago, I could retire”

3. The mid to late middle managers feel paralyzed.
Many have families and don’t feel like they have the energy or network to just “start a company”. They don’t particularly have any AI skills. They see the writing on the wall: middle management is being hollowed out in many companies.

4. The rich aren’t particularly happy either.
No one is shedding tears for them (and rightfully so). But those who have “made it” experience a profound lack of purpose too. Some have gone from <$150k to >$50M in a few years with no ramp. It flips your life plans upside down. For some, comparison is the thief of joy. For some, they escape to NYC to “live life”. For others still, they start companies “just cuz”, often to win status points. They never imagined that by age 30, they’d be set. I once asked a post-economic founder friend why they didn’t just sell the co and they said “and do what? right now, everyone wants to talk to me. if i sell, I will only have money.”

I understand that many reading this scoff at the champagne problems of the valley. Society is warped in this tech bubble. What is often well-off anywhere else in the world is bang average here.

Unlike many other places, tenure, intelligence and hard work can be loosely correlated with outcomes in the Bay. Living through a societally transformative gold rush in that environment can be paralyzing. “Am I in the right place? Should I move? Is there time still left? Am I gonna make it?” It psychologically torments many who have moved here in search of “success”.

Ironically, a frequent side effect of this torment is to spin up the very products making everyone rich in hopes that you too can vibecode your path to economic enlightenment.

 

The speed and magnitude of the wealth creation is like a black hole. The envy and accompanying anxiety that AI will devour future paths to wealth for anyone who doesn’t already have it has a gravitational pull in the Bay Area from which no light can escape. The metaphor writes itself. The event horizon is the singularity moment where capital is the only thing that matters.

Stanford senior, author Theo Baker’s recent NY Times editorial What A.I. Did to My College Class indicates the black hole is growing at one of the world’s leading universities. Pardon another long excerpt, but it’s worth it:

Cheating has become omnipresent. I don’t know a single person who hasn’t used A.I. to get through some assignment in college, yet the school was at first slow to realize how widespread this would become. As freshman year went on, some professors suggested that the “nuclear option” might be called for: allowing faculty to proctor in-person exams, a practice banned at the university for over a century to demonstrate “confidence in the honor” of students.

In our tech-enabled, newly A.I.-powered world, students were increasingly fudging just about everything. They would embezzle dorm funds to spend on their friends and lie about having Covid to get the UberEats credits that the school offered to those in quarantine. Some kids I knew published a paper that claimed a groundbreaking new A.I. advancement. Online sleuths quickly pointed out that it appeared to be just a stolen Chinese model, to which the two Stanford co-authors responded by blaming the plagiarism on the third author.

In junior year, 49 percent of the 849 computer science majors who responded to an annual campus survey said they would rather cheat on an exam than fail. A friend of mine captured the school’s ethos while we were discussing the tech hardware and other items our student club neglected to return to corporate sponsors. It was all, I recall her saying, “just a little bit of fraud.”

About halfway through freshman year, some coding classes started requiring students to sign a declaration — “I did not utilize ChatGPT” — to submit each assignment. During the first term these attestations began to appear, I watched a freshman I knew sign the declaration that he’d done his homework without A.I. as ChatGPT was still open in the next window — while on the deck of a yacht party financed by venture capitalists. The incentive structures were not aligned toward honesty. One could get ahead, quickly, by cutting corners, by focusing on self-presentation.

The money is a big part of it. A.I. has merely accelerated a trend that was already underway at Stanford and has been reflected by many of the country’s most corporatized universities: Education itself can be seen as a secondary goal to enabling future success, frequently defined as a future windfall.

The article then goes on to talk about the student body’s fascination with getting rich as they watch peers and recent alum hit the equivalent of the lotto in this hockey-stick environment. And even if it’s not the lotto, there’s the constant reminder that any obsession not having to do with money is carrying an increasing opportunity cost:

Next to me, one student scribbled on a branded notepad from Hudson River Trading, a quantitative trading firm where fresh graduates can earn upward of $600,000 a year.

This is scrambling people’s brains. Here’s Educated Guess:

I would think that tech people have had plenty of practice coping since this has been going on for awhile even if the numbers are bigger now. Being in finance and watching more than a fair share of idiots get rich has given me plenty of perspective. But it’s exactly too not think of the idiots getting rich, but of all the great people who didn’t.

Think of the people you know who haven’t had your luck and who you know are better than you. This immediately shifts your mind to gratitude. There are a million moments in a day to recognize how lucky you are. If you’re so f’n “agentic” why are you unable to choose to see that reality.

I wouldn’t be surprised if the most anxious people, the ones described in Deedy’s post, are the ones who are the most imposter. The ones who massively outperformed and in their hearts know it. They are not as self-reliant as they outwardly show and they hope their bank account will save them from ever having to face the truth that they are stunted in broad ways. They are less adaptable than they appear. They are specialized and therefore hostage to an environment that may well be artificial and, feeding their deepest fear, fleeting.

The deranged psychology in Deedy’s description isn’t about greed. Maybe for a few. It’s really about being fragile. These are rich but fragile people. And it’s even more twisted than this. The permanent underclass meme isn’t a nightmare. It’s a fantasy. If you’ve lucked into being “post-economic” by age 30, where even the most conservative compouding assumptions mean being able to throw out your alarm clock forever, you’ve secured never having the discomfort of testing your character and resilience.

But this fantasy is just that. A fantasy. And a poorly thought-out one. What’s a world where the United States has a permanent underclass? That’s what Egypt is today.

How do you get from where we are today to that arrangement?

  1. We really do achieve capital singularity and pre-existing wealth becomes the only meaningful input to flourishing and class mobility. This might be a foregone conclusion to many, but I also think it’s short-term profitable to promote this view so it’s not a fully honest position.
  2. This new order becomes common knowledge. The government and its wealthy owners use media and propaganda, supercharged by the tech they own, to pacify the unwashed (ie most of us.)
  3. The dam eventually breaks. You know the scene already: The powerful will be ripped from their decadent nests and cast into the cold world the rest of us have known and endured.
  4. This aggression will not stand, man. The oligarchs respond. The ensuing authoritarianism in this country is unprecedented. Welcome to Egypt’s corrupt system of favor-trading and hopelessness, except it’s secured by the most dystopian sci-fi technology.

So let’s see, you’re rich but not as self-reliant as you want others to believe, and this world is your salvation? What you’ve secured is a boot-licking future. At least you’ll still be able to afford DoorDash.

If you’re going to be a piece of shit, at least be evil and accountable instead of swallowing and boosting anxiety-porn because you either lack the imagination to see why either it’s wrong or how little your bag will matter in the world where it’s not.

Get over yourself. Show some gratitude. Do you hear what you sound like? If you’re fucked, then everyone else is dead. Do you really believe this? If so, while not redirecting your energy towards a remedy, is to admit being a rich coward. Enjoy your enclave while it lasts. It’s a life raft to nowhere.

I find being in finance and from NY, but building a life and family in the Bay Area makes it hard to avoid comparing the locations. The Bay Area really struggles to reconcile its identity with profound wealth. It’s not surprising given the velocity of change. The legacy of hackers, iconoclasts, and nerds who happened into insane riches bred a more institutionalized capital formation ecosystem. Like the kind that NY has always been known for.

But the cultures cannot thoroughly mix without paradox. The unabashed but honest avarice of NY capitalism meets the idealism of artists who, at some point, cannot resist turning in their bicycle for a Pagani and fuel-guzzling jet. But they also don’t wanna see themselves as “that guy”. So we endure this moralizing hypocrisy. Watching them strain to serve a master they haven’t checked in with since the days of eating ramen in a garage.

I kind of appreciate the Stanford story. For most kids, school was always about “is this gonna be on the test?” not skill-building. It’s a place to demonstrate the “right” mix of aptitude and conformity to keep the “right” options open. The “right” options being a white-collar gig with either enough prestige to please your parents or enough money to shut them up.

Instead of “Is this gonna be on the test?”, it’s ”Is this gonna make me rich?” It sounds crude, but given the cost of college and its role for many people as a way to break out of the lower class, it is what many people are already thinking. It’s the next logical step in the progression because money is prestige and prestige without money ain’t gonna get you into a Great Schools 10 zone to perpetuate the cycle with your own kids.

If there’s a devil, he doesn’t want to kill you. He wants you to live, but be obsessed with yourself. That scales. That is a cycle that goes deeper than the radiation from a one-time nuclear cloud. To stay alive, with your insecurity trapping you in a 2-D rhombus projecting its phantom zone on your bloodline for eons.

The upper bound of being obsessed with yourself is survival. That’s a strange peak ambition for people who are free of material constraint.

Perhaps they are anything but free?

high implied vol can work for or against you

Here’s how high vol works against you

It’s too expensive to buy puts to trade directionally once an asset has already made a giant move higher.

When you are 100+ vol, it’s not surprising the market puts your odds of getting cut in half at 1 in 3 proposition.

It’s hard to make money in a reasonable risk-adjusted away once an asset is already high vol since it’s hard to size it without risking your neck.

It is well within the meat of the distribution for SNDK to get cut in half this year. That’s just a good baseball player’s chance of getting a hit or a typical NBA player hitting a 3 in a game (or missing a 3 in practice).

How high vol works for you

The high vol is a gift to the natural holders. Millennial employees can lock in their unborn grandkids’ inheritance.

A non-technical way to appreciate how high vol creates this opportunity in upside call vs downside put differentials:

Imagine a stock starts at $100. It gets to $125. From $125 to $150 is only 20%

But if the stock fell to $75 the distance from $75 to $50 is 33%

Both $50 and $150 are 50% from the initial price, but in a compounding sense 150 is much “closer” to the starting value than $50. The higher the vol the less “distance” a fixed dollar move represents. As implied vol increases OTM calls grow faster in value than OTM puts. This is the source of the attractive pricing you see in the risk reversal (ie option collar).

That tweet comes from Dean Curnutt of The Alpha Exchange Podcast. He’s a partner in an option brokerage firm I’ve known for a long time. I told him he needs to buy an SF realty company, since risk reversal-financed $10mm SF Victorian pipeline is unmanned!

Speaking of, if you wanted to bet on AI without access to private shares, real estate on leverage would have worked. See Redfin economist Daryl Fairweather’s Is the Bay Area in an AI Housing Bubble?. I hear from locals who own a bunch of SF RE that the bid is mostly in single-family and multi-family rental units are not getting the hockey stick treatment. The rents have been exploding higher, however. And to think coming out of COVID, you couldn’t give away an SF condo. Super high vol asset. They need options!

“a collection of tradeoffs”

Thursday’s post what I want my kids to know struck a nerve with readers for different reasons. A close friend noted that it seemed pretty male-centric. Having grown up with only a brother himself, he probably wouldn’t have noticed if it wasn’t for raising a daughter now. He wrote me a thoughtful email about it, analogizing between seeing the world as a mountain to climb (male-coded lens) vs a more sea-like horizontal interconnectedness where you are bombarded by both supportive and punishing waves. A line he wrote that resonated:

women are more in-tune or more impacted by the reality there may not be a peak to this mountain. That the mountain itself is just a projection of a higher-dimensional reality and the “peak” is really just a collection of tradeoffs.*

*You can find my immediate response to this further below but it’s secondary to the message front-and-center

I think seeing a “collection of tradeoffs” does several things.

First of all, it immediately flattens the idea of a peak or at least places them as narrow spires on a plateau. You can be the greatest in the world at XYZ, but you haven’t conquered life. Elite performers don’t usually sugar-coat the cost of these conquests. Sometimes the public sees the price they pay when their lives crumble and wonder if it’s because they are stunted in every other domain than the one they dominate. The self-aware ones are effusive in acknowledging the support of their families in enabling what is ultimately a pursuit of glory and even posterity.

Secondly, seeing a “collection of tradeoffs” loosens the creativity muscles. If you view life as a race to some mountaintop, you will restrict the routes your life can take. That artificially narrowed menu will be written by your immediate surroundings, which is already a skinny slice of human experience.

I want to pause on that for a moment. The narrowness of the menu we choose flows from the most tyrannical source: random path dependence. Where you were born, in what time, and to whom? It’s probably adaptive to ignore that perspective and trudge forward, but I admit it’s a thought that intrudes just enough to bug me.

I was watching videos of people covering songs I like on YouTube the other night. I will often wander to the long tail of videos that have very low view counts. It feels like you are watching something vulnerable and isn’t really intended for your eyes except for that they posted it publicly. I watch and I wonder. Who is this person? What’s their life like? I’m getting an energy from their performance but they have no idea who I am, where I am, and that I’m watching this a decade after they posted it.

I’m several of the 34 views of this vid:

It’s not a nice voice. The man looks unwell. But it’s extremely expressive. The way he performs it. The instrumentation he chose. The fact that he looks enigmatically young and old at the same time.

Futurism and space travel represent adventure and vastness. Sheer wonder reminds us how small we are. But I see vastness in a simple video like this. This individual is made of the same stuff I am, but we are aliens to each other. Maybe or maybe not. But that’s the point. The mystery creates a sense of vastness. It is the wonder, that right here on Earth, the lyrics of the song hold:

See the animal in his cage that you built
Are you sure what side you’re on?
Better not look him too closely in the eye
Are you sure what side of the glass you are on?
See the safety of the life you have built
Everything where it belongs
What if everything around you
Isn’t quite as it seems?
What if all the world you think you know
Is an elaborate dream?
And if you look at your reflection
Is it all you want it to be?
What if you could look right
Through the cracks?
Would you find yourself
Find yourself afraid to see?

Shortly after that vid, the YT algo served me Trent Reznor’s speech when he inducted The Cure into the Rock and Roll Hall of Fame. He eloquently transmits the idea that their music and way of being spoke to so many people who didn’t feel like they belonged. People who likely saw something besides life as a “mountain”. When Trent first heard The Cure he thought they were making music directed at him.

Trent is gesturing at the thing every great artist or artisan understands. The skeleton key is to connect with others authentically. To give people something they deeply want because you understand the yearning yourself. Artists express and artisans solve. One has fans, the other has clients. Sometimes the artisan is so good the clients are fans. In both cases, the relationship is deeply empathetic. I call it a skeleton key because that thing is different for everyone but it unlocks the same door.

The door to thriving.

*As promised, this was my reply back to my friend:

I see what you mean and yes I agree its gendered. I think underneath it all, my sense of how the world operates is probably from a biological place — women are default valuable (their overt subjugation in much of the world is a demented response to this…like a male attempt to take back power that biology confers) whereas a man is entire worth depends on what he can provide. Modernity changes the calculus to a meaningful extent (in doing so trades off against novel considerations) but I don’t think it has created a new calculus. At the end of the day, there is a competition and as with any competition, there are niches that will provide a better harbor for some individuals to strive within based on their unique traits and views.

Insofar as my writing is narrow, it is written from the perspective of being subsumed by one of these niches. I’m swimming in the “water” in the David Foster Wallace sense of the word. But of course, the audience is self-selected and therefore assumed to be in the same water.

The beauty of travel is to be able to look back home and see the water for what it is. Something that has a particular pH balance that nourishes parts of our souls and sickens other parts.

Moontower #315

In this issue:

  • racing to a mountaintop or just another “collection of tradeoffs”
  • how high implied vol can work against you or for you
  • the greatest intern class of all time?

Thursday’s post what I want my kids to know struck a nerve with readers for different reasons. A close friend noted that it seemed pretty male-centric. Having grown up with only a brother himself, he probably wouldn’t have noticed if it wasn’t for raising a daughter now. He wrote me a thoughtful email about it, analogizing between seeing the world as a mountain to climb (male-coded lens) vs a more sea-like horizontal interconnectedness where you are bombarded by both supportive and punishing waves. A line he wrote that resonated:

women are more in-tune or more impacted by the reality there may not be a peak to this mountain. That the mountain itself is just a projection of a higher-dimensional reality and the “peak” is really just a collection of tradeoffs.*

*You can find my immediate response to this further below but it’s secondary to the message front-and-center

I think seeing a “collection of tradeoffs” does several things.

First of all, it immediately flattens the idea of a peak or at least places them as narrow spires on a plateau. You can be the greatest in the world at XYZ, but you haven’t conquered life. Elite performers don’t usually sugar-coat the cost of these conquests. Sometimes the public sees the price they pay when their lives crumble and wonder if it’s because they are stunted in every other domain than the one they dominate. The self-aware ones are effusive in acknowledging the support of their families in enabling what is ultimately a pursuit of glory and even posterity.

Secondly, seeing a “collection of tradeoffs” loosens the creativity muscles. If you view life as a race to some mountaintop, you will restrict the routes your life can take. That artificially narrowed menu will be written by your immediate surroundings, which is already a skinny slice of human experience.

I want to pause on that for a moment. The narrowness of the menu we choose flows from the most tyrannical source: random path dependence. Where you were born, in what time, and to whom? It’s probably adaptive to ignore that perspective and trudge forward, but I admit it’s a thought that intrudes just enough to bug me.

I was watching videos of people covering songs I like on YouTube the other night. I will often wander to the long tail of videos that have very low view counts. It feels like you are watching something vulnerable and isn’t really intended for your eyes except for that they posted it publicly. I watch and I wonder. Who is this person? What’s their life like? I’m getting an energy from their performance but they have no idea who I am, where I am, and that I’m watching this a decade after they posted it.

I’m several of the 34 views of this vid:

It’s not a nice voice. The man looks unwell. But it’s extremely expressive. The way he performs it. The instrumentation he chose. The fact that he looks enigmatically young and old at the same time.

Futurism and space travel represent adventure and vastness. Sheer wonder reminds us how small we are. But I see vastness in a simple video like this. This individual is made of the same stuff I am, but we are aliens to each other. Maybe or maybe not. But that’s the point. The mystery creates a sense of vastness. It is the wonder, that right here on Earth, the lyrics of the song hold:

See the animal in his cage that you built
Are you sure what side you’re on?
Better not look him too closely in the eye
Are you sure what side of the glass you are on?
See the safety of the life you have built
Everything where it belongs
What if everything around you
Isn’t quite as it seems?
What if all the world you think you know
Is an elaborate dream?
And if you look at your reflection
Is it all you want it to be?
What if you could look right
Through the cracks?
Would you find yourself
Find yourself afraid to see?

Shortly after that vid, the YT algo served me Trent Reznor’s speech when he inducted The Cure into the Rock and Roll Hall of Fame. He eloquently transmits the idea that their music and way of being spoke to so many people who didn’t feel like they belonged. People who likely saw something besides life as a “mountain”. When Trent first heard The Cure he thought they were making music directed at him.

Trent is gesturing at the thing every great artist or artisan understands. The skeleton key is to connect with others authentically. To give people something they deeply want because you understand the yearning yourself. Artists express and artisans solve. One has fans, the other has clients. Sometimes the artisan is so good the clients are fans. In both cases, the relationship is deeply empathetic. I call it a skeleton key because that thing is different for everyone but it unlocks the same door.

The door to thriving.

*As promised, this was my reply back to my friend:

I see what you mean and yes I agree its gendered. I think underneath it all, my sense of how the world operates is probably from a biological place — women are default valuable (their overt subjugation in much of the world is a demented response to this…like a male attempt to take back power that biology confers) whereas a man is entire worth depends on what he can provide. Modernity changes the calculus to a meaningful extent (in doing so trades off against novel considerations) but I don’t think it has created a new calculus. At the end of the day, there is a competition and as with any competition, there are niches that will provide a better harbor for some individuals to strive within based on their unique traits and views.

Insofar as my writing is narrow, it is written from the perspective of being subsumed by one of these niches. I’m swimming in the “water” in the David Foster Wallace sense of the word. But of course, the audience is self-selected and therefore assumed to be in the same water.

The beauty of travel is to be able to look back home and see the water for what it is. Something that has a particular pH balance that nourishes parts of our souls and sickens other parts.

 

Money Angle

🔗 How to Short a Bubble | 10 min read

Outstanding post. Alexander Campbell on why shorting the thing going vertical is the worst possible expression of being bearish. As something goes parabolic your exposure grows with it (I have a collection of posts on why shorting is complicated).

The vol that accompanies a bubble renders the puts useless (more on that in the Masochists section). Instead, Campbell proposes a better risk-adjusted approach by identifying:

  • the wedge: the thing that kills it the bubble. He suggests if AI is the bubble, rates are the wedge, and inside every bubble there’s a weakest link that needs the bubble to keep accelerating just to survive a pause
  • the victim: the cheap-vol neighbor that gets dragged down such as airlines pre-COVID, BAC instead of housing CDS in ‘08.
  • confirmation: wait for a trend to break then press specific shorts

 

🎙️PTJ on Invest Like The Best | podcast link

Patrick O’Shaugnessey interviewed legendary macro trader Paul Tudor Jones. It’s self-recommending, but here are the 2 parts that stayed with me:

From contraction to expansion on the issuance side

PTJ: If I think of some really, really big accidents, most of them have the same underlying reason, the same underlying foundation, which is some too much leverage somewhere. Most of the leverage, most of the time – if I think of the big ones – were derivatives inspired. Either futures or options.

1987, that crash was 100% portfolio insurance. A hundred percent. Had they had limits, which they didn’t, it would’ve been 10%, maybe 15% max. But that was a hundred percent derivatives. If I think about 1998, Long-Term Capital, big derivatives. They had a huge balance sheet with a lot of derivatives they were offsides on.

2000 was a little different. 2000 was the easiest bear market I’ve ever seen in my whole life. It’s got so many similarities to right now, in the sense that the bear market of 2001 and 2002 were a consequence of all the IPOs in ’99 and 2000. And then as they unlocked, you just had this never-ending cascade of selling, that’s a great way of putting it. And we’re getting ready – I want to say that the contemplated IPOs for next year are going to be five or six percent of market cap. So why are we where we are right now? Because we’ve been retiring two or three percent of market cap, probably a little less than 2% of market cap, every year without fail for the past 10 years [through buybacks.]

And so now all of a sudden, you’re gonna completely reverse that math. And so, I don’t think it necessarily happens instantaneously with the IPOs, but then there’ll be the unlocks. So you can see a situation where, okay, maybe we go through some kind of rolling top. And then 18 months from now – six months, we’ll have to look at the unlock schedule. But you’re going to want to watch those because that’ll just be adding equity supply. And you’ve already gonna be diminishing the buybacks because of all the commitment to capex from the hyper-scalers. They’re already gonna be eating into their cash flow.

This one sticks with me because I’m a “the market is just positions and flows”. There’s nothing magical about historical rates of return, margins and so forth. You have tradeable capital in the form of stocks and bonds. Issuance is the supply. Demand comes from savings. If savings increase faster than paper prices go up. And this is not linear because the marginal propensity save one’s millionth dollar is higher than one’s thousandth dollar.

Prices have gone up a lot so it makes sense for a narrow base of supply owners should dump it on the wider marketplace. I’m quite curious if the public markets will value these companies as highly as the illiquid private markets do, but since the issuance was be low float, I assume the owners share my curiosity and wanna feel things out before trying to realize their god-wealth.

Life advice

At the end of the interview PTJ (emphasis mine)

We can humbly devote ourselves to finding the kindness within ourselves and the goodness within ourselves, and transmit that to somebody else during that day.

I think that’s the secret to happiness. You don’t have to worry about yourself. You have to worry about, “How am I going to brighten someone else’s day?” And with that attitude, one, you’ll always be happy. I’m just gonna spend this one day doing this one outward act. And if you repeat it enough pretty soon you take “I should” and they will become “I ams”.

So if you take that mentality, that I want to do this wonderful act of kindness for someone else, pretty soon you become an incredibly kind person. It becomes natural. It becomes instinctive and organic. And it’s gonna brighten your day. You’ll have such a positive outlook on life.

I’m in the camp that happiness is a self-effacing end. You never get it if you aim at it. You’ll probably get more mileage from the definition of humility that it’s not about thinking less of yourself but thinking about yourself less (I don’t know who said that. There’s debate over whether it was C.S. Lewis. For all we know it was Mark Twain. Either way, it’s public domain.)

Money Angle for Masochists

Here’s how high vol works against you

This echoes Campbell’s thought about using puts to trade directionally once an asset has already made a giant move).

When you are 100+ vol, it’s not surprising the market puts your odds of getting cut in half at 1 in 3 proposition.

It’s hard to make money in a reasonable risk-adjusted away once an asset is already high vol since it’s hard to size it without risking your neck.

It is well within the meat of the distribution for SNDK to get cut in half this year. That’s just a good baseball player’s chance of getting a hit or a typical NBA player hitting a 3 in a game (or missing a 3 in practice).

How high vol works for you

The high vol is a gift to the natural holders. Millennial employees can lock in their unborn grandkids’ inheritance.

A non-technical way to appreciate how high vol creates this opportunity in upside call vs downside put differentials:

Imagine a stock starts at $100. It gets to $125. From $125 to $150 is only 20%

But if the stock fell to $75 the distance from $75 to $50 is 33%

Both $50 and $150 are 50% from the initial price, but in a compounding sense 150 is much “closer” to the starting value than $50. The higher the vol the less “distance” a fixed dollar move represents. As implied vol increases OTM calls grow faster in value than OTM puts. This is the source of the attractive pricing you see in the risk reversal (ie option collar).

That tweet comes from Dean Curnutt of The Alpha Exchange Podcast. He’s a partner in an option brokerage firm I’ve known for a long time. I told him he needs to buy an SF realty company, since risk reversal-financed $10mm SF Victorian pipeline is unmanned!

Speaking of, if you wanted to bet on AI without access to private shares, real estate on leverage would have worked. See Redfin economist Daryl Fairweather’s Is the Bay Area in an AI Housing Bubble?. I hear from locals who own a bunch of SF RE that the bid is mostly in single-family and multi-family rental units are not getting the hockey stick treatment. The rents have been exploding higher, however. And to think coming out of COVID, you couldn’t give away an SF condo. Super high vol asset. They need options!

Interestingly, home prices locally in the burbs have been dead money since around 2023 although having a step-function increase from the Covid era. I can think of at least one person who rebalanced, selling their burb home, moving to a cheaper state but plowing some of the proceeds of the sale into a depressed SF condo.

Geniuses

This is just fun.

My son is in 7th grade. This is Scott Wu in 7th grade. But it doesn’t matter what grade. Tough day for the genius girl standing next to him. It’s just a 1 minute vid, watch it before you read ahead:

I just wanted to share the trick I think Scott did to do 255² – 245² so quickly.

You have to immediately recognize that a difference of squares is the same as the sum of the 2 numbers times their difference. You’ve all done this in school:

a²-b² = (a+b) (a-b)

My guess is Scott quickly reasoned:

255 + 245 = 500

255 – 245 = 10

500 x 10 = 5000

If you are regularly practicing math I’d guess converting “difference of squares” which is a canonical form into its factored form is quite natural.

From there, the particular numbers chosen make this problem quite easy to compute but yea he’s fast as hell. And for the final question, you witness insane reading speed.

This Week In The Options Trench

We talk about greeks in understandable ways (I hope!)

Stay groovy

☮️

Moontower Weekly Recap

Moontower #314

In this issue:

  • smart vs wise
  • adverse selection when landing a senior role
  • cost of carry as a conviction hurdle
  • KenKen

Friends,

Happy Mother’s Day!

It’s a nice day for an enjoyable read. I loved this post from Adam Mastroianni:

Infinite Midwit | 12 min read

The essay is insightful and typical of Adam. It’s just so fun to read. Which is itself an exhibit of his thesis.

I stitched together these excerpts, but I encourage a full reading.

The opening

The better AI has gotten, the less anxious I’ve become.

A few years ago, when the computers first started talking, it was reasonable to believe that we would soon be in the presence of omnipotent machines. For someone like me, whose job is to produce words on the internet, it seemed like only a matter of time before I would have to fill my pockets with stones and wade into the sea.

Two intelligences

Some problems have clear boundaries and verifiable solutions, like “What’s the cube root of 38,126?”. These problems require objective intelligence. Other problems are vague and squishy and it’s not clear whether you’ve solved them, or whether they exist at all, like “How do I live a good life?”. These problems require subjective intelligence. Objective intelligence can be trained, reinforced, and validated. Subjective intelligence cannot.

[Kris: smart vs wise]

It’s unfortunate that people use one word to refer to both of these capabilities, when in fact they have nothing to do with each other. It is also, ironically, a case of objective intelligence overshadowing subjective intelligence: these skills are obviously and intuitively different, but a century of psychological research has “proven” that only one of them exists. Over and over again, psychologists have found that all intelligence tests correlate with one another, even when you ostensibly try to test for “multiple intelligences”. Numbers don’t lie, and they all say that there’s only one intelligence, the so-called g-factor.

The problem is that any test of intelligence is only ever a test of objective intelligence. “How do I live a good life?” is not a multiple-choice question. “Discovering” the g-factor again and again is like being surprised that you find the same patch of sidewalk every time you look under the same streetlight.

The Catan fantasy

The promise of artificial superintelligence is based on the idea that objective intelligence is the only intelligence. Or, even if there are multiple forms of intelligence out there, that they are fungible. To be an AI maximalist is to believe we are playing under Settlers of Catan rules, where if you have enough of any one resource, you can trade it for any other resource. If you have infinite objective intelligence, then you have infinite everything.

It’s not just that objective intelligence can’t be transmuted into “emotional” intelligence or social savvy or whatever we want to call it. It appears to be very difficult, if not impossible, to transmute objective intelligence into any other cognitive ability.

When you meet a human who can do quadratic equations in their head but can’t hold onto a job or a relationship, you know they’re missing something upstairs.

Nerds

When I was growing up, this paradox was an endless source of sitcom plot lines—if you’re so smart, nerds, why don’t you figure out how to make yourselves popular? The entrepreneur/essayist Paul Graham took up this question 20 years ago and came to the conclusion that the nerds must not want to be popular. They’re too busy with their Neal Stephenson novels and their D&D campaigns to spend a single brain cycle figuring out how to keep their heads out of the toilet.

I disagree. The nerds I knew in high school—myself included—were always hatching harebrained schemes to increase our social status. They just didn’t work. (”All the girls will want to go to the Homecoming dance with me once they see how many state capitals I’ve memorized!”) We couldn’t use our smarts to make ourselves popular because we had the wrong kind of smarts.

For example, I went to college with a guy who was super smart, but he also couldn’t do anything on time. He would be late to exams. His grades would tank because he would finish his essays but forget to turn them in. He would set meetings with his professors to sort everything out, and then never show up.

I always used to wonder: why doesn’t this guy just use his big brain to make himself more conscientious? Isn’t life one big role-playing game, and isn’t intelligence just experience points that you can assign to any of your Big 5 skills?

Why AI writing vaguely sucks

It’s cool that AI can fold proteins, create websites, fact-check journal articles, etc. but it can’t write anything that I am interested in reading. The problem isn’t that it hallucinates or makes mistakes. It’s that everything it writes vaguely sucks. I drag my eyes across the words and I feel nothing. That’s not quite right, actually—I feel like, “I would like this to be over as soon as possible.” …

Words themselves don’t contain feelings—they are a recipe for creating that feeling inside your own head, to assemble the right set of emotions out of the experiences you have at hand. If I do a good job, the subjective experience that results inside you might resemble the one that originated inside me, but it will never be identical, because we’re working with different ingredients.

The computer doesn’t know any of this. It can’t know any of this. It can only read the cookbook; it can’t taste the meal. Objective knowledge can make your sentences true, but it can’t make them alive. Without access to subjective knowledge, you quickly hit a wall. And unlike all previous walls that AI has surmounted, you can’t overcome this one by scaling—either in the literal or metaphorical sense—because it’s a wall with a width you cannot describe and a height you cannot see.

Money Angle

I unlocked this older post, which found a lot of agreement from senior professionals who have transitioned from a pure trading job to building a business or strategy for asset managers. The target audience is seasoned practitioners. It’s written specifically for option traders but the feedback is that its warnings extend well beyond that market.

We know that there is adverse selection when hiring but this is about avoiding a lemon when getting hired.

Enjoy: adverse selection in the option job market

Money Angle for Masochists

Brent and Alf have a regular macro podcast. This episode from late 2025 has a number of evergreen trading concepts.

On carry costs

Alf: In our fund, we’ve recently added an alert before you put a trade on. It looks at how much it’s going to cost you to own this position in a relatively vol-adjusted way if nothing happens for the next 30 days. It’s essentially like some sort of carry-to-vol screener.

[Kris: notice how naturally this forces a “thinking in bets” discipline on your opinions]

“Am I really sure this is going to happen or not?”

A Hungarian Forint Example

We had this example where we had all this theory on Hungary. We looked at Hungarian forint and said, “Okay, Orbán is going to go nuts, win the elections, spend money, and the market will punish the Hungarian forint.” Sure, you can be right. You can be wrong.

So how do you trade this? Well, you buy the euro and sell the Hungarian forint. You do the trade, then you look at the carry differential between the two currencies. It’s about 4% yearly carry differential in the forwards. That comes down linearly to about 30 basis points a month.

You think: “30 bips? That’s nothing. I can pay 30 bips in a month. No problem.”

But then you look at the monthly volatility of this thing. It basically doesn’t move. So at some point you realize: the static ex-ante Sharpe ratio of this thing for the next month is like -0.6 Sharpe against me. Holy crap. I need to be not only right—I need to be right with a high Sharpe ratio just to start offsetting the negative carry adjusted for volatility in this trade.

Analogizing to options where the costs are framed more explicitly

A lot of trades are very expensive to own. With options, I think sometimes you fool yourself because you pay for the vol once, and then you say, “Okay, I paid for the vol. That’s what it is. Now I can go long, and this thing can drop to zero, but I did pay for the vol.”

But if you buy 50 options in a year, you pay for the vol 50 times. In options, people do it very lightly but in linear trades, people don’t sometimes think about this, but I think it’s important.

[Kris: I’d broaden this discussion to be a reminder that the cost of carry in addition to opportunity cost is hurdle that your conviction must clear. If it’s not explicit in your in your process consider making it so]

Extending to Hard-to-Borrow Stocks

Brent: It’s a different but similar situation where normally you’re dealing with a very high-vol instrument, but you’re paying a crazy amount of money to borrow the stock.

There’s quite a bit of research showing that hard-to-borrow stocks do tend to go down—they’re hard to borrow for a reason. Someone knows a secondary is coming, or it’s a really bad company. There’s usually a reason why it’s hard to borrow and why everyone’s short.

But functionally, the cost to borrow negates the negative return of the stock almost perfectly in aggregate. If you short all the hard-to-borrow stocks, you’ll make money on the shorts and lose about exactly the same amount on the borrow.

A CoreWeave Example

Take CoreWeave—there’s no borrow right now, but there has been off and on, and the borrow was like 150%. Even if you catch a pretty decent move, if you’re not catching it instantaneously, you’re probably not making money.

One simple thing I’ve been doing: when there is a borrow, just selling it at 9:30 AM and buying it back at 4:00 PM. You actually made more money being short that way than holding it—not even counting the borrow—because CoreWeave has a little bit of positive drift in the overnight session.

 

Extending to currency roll costs

Even buying EUR/GBP today, I bought some at 0.8573 and rolled it to September 17th. It was 17 pips to roll it. For six weeks on a currency that’s moving 20-30 pips a day, you’re paying 17 pips of roll. That’s not very fun.

 

Spurious Correlations: When Copper Takes Down Silver

Here’s something huge: spurious correlations. Copper tariffs were actually removed. All of a sudden there are no tariffs on copper, and copper goes down like 30% in two days.

Then, do you know what happens to any other high-beta metal? Doesn’t matter what it is—palladium, silver, you name it—goes down 3-4-5 percent. It’s just cascading risk and basically some exogenous event hitting you, not even directly, but laterally, and you lose money.

The Sympathy Trade Strategy

Brent: Generally, I feel like there’s a lot of good trades like that. Being short silver when copper collapses—but these sympathy trades tend to be very short-lived.

For me, it’s always like: if you’re looking at AppLovin and The Trade Desk, they’re similar companies. When AppLovin craters 50 bucks on earnings, you can sometimes sell The Trade Desk and make four bucks in 20 hours.

But like you said, there’s really no economic reason for the correlations a lot of the time. Sometimes with earnings there is, but with copper and silver, it’s just that a lot of the same people who have that sort of inflation and debasement trade are long copper, long silver, long gold, long Bitcoin. When one part of the portfolio gets a nuclear bomb, they’re forced to liquidate the other stuff.

I do those trades as sympathy trades, but I go in knowing: most of the time, there’s no economic sense to this. It’s more of an endogenous unwind story. So you got to be quick.

 

This Week In The Options Trench

Erik has a soft spot for GME so in light of Ryan Cohen’s bid for eBay, we talk about GME options. A fun thing about this casual weekly podcast format is, while we have a loose calendar of discussion topics, we might just talk about whatever grabs our attention. This week was one of those.

📺GameStop and eBay Acquisition What the Options Markets Say

 

From My Actual Life

My 4th grader loves the KenKen puzzles his teacher gives. KenKen is a Sudoku-style puzzle invented in the early 2000s.

In this 4×4, grid each row and column must contain each of the digits 1,2,3,4.

The digits in the bold cages must satisfy the arithmetic operation in the cage’s upper left. For example, in the cage with “5+”, the only valid combinations are (4,1) and (3,2).

In this example, I know the bottom right corner must be a 2 because the 7+ cage must include (3,4). 2 is the missing number in the column.

We got the kid a KenKen book for his birthday and my mother saw it while visiting and got addicted herself so we sent her a copy as well.

The puzzles can range from easy to hard and they can have larger grids (ie 6×6 or 7×7). My son likes to make them as well. At first, that sounded difficult but brain fart. I asked him how he did it and he said he just fills out the grid so the row/column rules are satisfied and then you simply cherry-pick your cages and display the operation and target that makes the cage work.

Again Happy Mother’s Day, may the simple pleasures pamper.

Stay groovy

☮️

 

Moontower Weekly Recap

appreciating diversification

This week, I hosted class #4 of the Investment Beginnings for local kids aged 12+.

The series’ materials are here:

https://notion.moontowermeta.com/investment-beginnings-course

This is the specific material for class #4:

I also created a web version of the game:

☀️🌧️Sun/Rain Game

While I’ve been doing the series for kids, I think a lot of adults could even benefit. The overall arc of the presentation:

  1. Last class’s game ended with a humbling but common result, hinting at a key pillar of investing.
  2. We use a few facts to dispel the recency bias that all investors carry with them.
  3. They learn what the fundamental nature of stocks predicts about their individual and group behavior.
  4. We widen the meaning of diversification beyond stocks, which was extremely easy to do in light of March 2026.
  5. We play a game that makes the implications for portfolios concrete.

While moontower readers span a wide range of investment experience (although overall quite interested in investing and money), here are a few ideas that I hope are presented in ways that might augment even your understanding or at least help you explain to learners in your life.

The most naive strategy is hard to beat

The kids spent Class 3 picking stocks based on a bunch of variables they could sift through, only for the equal-weight benchmark to beat everyone except the team that contrarily concentrated in the highest momentum company that is very much still an enigma to the market (TSLA).

The equal-weight strategy which I just called a monkey (although it’s not random, just dumb) beat 2/3 of the 15 individual stocks themselves.

The reason you shouldn’t be surprised that the naive strategy is hard to beat

Companies eventually die, but indexes shed them before they are in hospice.

Only 17% of the original S&P 500 companies from 1957 survived 50 years. The average company lifespan on the index was 33 years in 1964 — it’s now under 20. Kodak invented the digital camera in 1975 and buried it because of the innovator’s dilemma.

In a crash, stocks remember they’re all stocks.

Diversification works differently in good years than bad ones. In the class data, stocks spread widely in bull years. Then we looked at Jan 2022 to Jan 2023: 13 of 15 stocks fell together, the spread collapsed.

I didn’t want to lean into the word correlation, but I noticed a different way to convey the same idea. The inter-quartile range (IQR) of annual returns was smallest in the worst years. This chart is rich with insight. Notice the IQR’s visually but also how the equal-weight portfolio performed relative to the individual stock and median stock returns each year:

These observations are non-CAPM ways to arrive at the familiar language of diversifiable risk (company-specific stuff you can eliminate for free) and systematic risk (market-wide stuff you can’t diversify away but do get paid to carry). The crash revealed which was which.

If we zoom out from stocks alone, we see a race where the leaders change each year

The Novel Investor quilt shows 15 years of annual returns ranked best to worst across 9 asset classes. The diversified portfolio, that gray-ish bar, never wins a year nor comes in last. Note commodities, gold and BTC are absent from the series.

How do you think they would influence the gray portfolio?

The Sun/Rain Game

This leads to a game where we can build some intuition about the role of non-stock assets in a portfolio.

If you look at the sheet you can see how the kids actually did (I changed the kids names to letters):

The game’s punchline is that owning the anti-correlated asset despite it having a worse expected return than the “good” asset leads to a better long-term portfolio.

But this is so unintuitive that I got a student’s question wrong during the discussion!

I’ll explain the mistake here.

A student asked if we played the game for 100 years instead of just 20 years, if owning the good asset ONLY would have led to the best return. I initially said no, then corrected myself and said yes because it has the higher expected return.

But I was right the first time. The answer is definitely NO.

It comes down to the fact that the good asset has an expected arithmetic return of +5%, BUT it has a negative expected CAGR or geometric return.

The math:

The company is 50/50 to return+40% or -30% in any given year.

.5 x 40% + .5 x -30% = +5%

But over 2 years, you expect 1 up, 1 down. Compounding math:

1.4 x .7 = 98%

You expect to lose 2% over a 2-year sequence of about 1% per year.

Formally, we compute the expected CAGR by multiplying (note how the arithmetic or single period return is added):

1.4^(1/2) * .7^(1/2) – 1 = .9899 -1 = -1%

[The exponents represent the probability of each outcome. If there were 3 outcomes, you’d have 3 terms and the exponents sum to 1.]

In the long run, the good asset destroys value. So you do not want to concentrate in it despite its superior expected arithmetic return.

The CAGR is being killed by volatility drag, which is the asymmetry of the fact that if you lose 30% you need to return 42.9% to get back to even, but the “up” years only return 40%. You are falling behind over time.

The bad asset returns -10% half the time and +8% half the time. It’s a “worse” asset, but it’s less volatile. Taking this quality to its extreme, isn’t this what cash is?

In arithmetic terms, our average return if we allocate to each asset equally is +2% (50% x 5% + 50% x -1%). But that portfolio is less volatile because one stock zigs when the other zags. The diversification cuts the volatility MORE than it cuts the expected return, leading to a better risk/reward!

If we rebalance each year back to an equal-weight portfolio, we “pull” the expected CAGR closer to the expected arithmetic return. It’s the only way we can get close to eating those expected arithmetic returns. Otherwise, they don’t really exist for you over time.

This table is worth staring at:

Here’s a message one of the dads sent me after the class:

Measure Your Own Diversification

I made you a tool to compute your portfolio vol and see how much the cross-correlations between your holdings have been reducing total vol from the vol that the individual assets contain. You can tinker by adding ETFs of other asset classes to your equities (ie GLD or USO or TLT etc) to see how they affect the volatility.

If you just want inspiration for an idea, use the tool to compare the Mag 10 index (MGTN) realized volatility with the average realized volatility of its holdings. The index is conveniently equal-weighted, 10% in each name.

Two ways to try this on your own portfolio:

🌐To run in your browser

https://colab.research.google.com/github/Kris-SF/data-pipelines/blob/main/portfolio-vol/portfolio_analysis.ipynb

⚠️Just push through the warning it spits off

The output will includes metrics and charts:

 

🖥️To run locally

git clone <https://github.com/Kris-SF/data-pipelines.git>
cd data-pipelines/portfolio-vol
pip install -r requirements.txt
jupyter lab portfolio_analysis.ipynb

Either way, edit the WEIGHTS dict and the START / END dates, then Run All.

Moontower #313

In this issue:

  • The “three pitches” rule and a lazy man’s framework for getting in shape
  • Things that popped from the Investment Beginnings Lesson #4 — Risk
  • Made you an easy online tool to see how much diversification benefit you get from your holdings

Friends,

A couple of good articles that stood out before we get to Money stuff.

How to Apply Pixar’s “Three Pitches” Rule | 3 min read

David Epstein spent a lot of time with Ed Catmull in researching his recent book Inside the Box. He shares a neat practice from Pixar. Directors aren’t allowed to bring one idea, they must develop three. We often fixate on our first idea even though it’s usually not our best (the “creative cliff illusion”). Epstein applied this in writing the new book by writing three different openings for every chapter. Nine of twelve chapters ended up using attempt #2 or #3. He admits this is tedious, but leads to better quality. I’d add that LLMs can ease some of that burden or augment the process by asking them to consider more ideas beyond the 3 you generate yourself.

The Lazy Man’s Guide to Actually Getting in Shape | 60 min read

Jonathan doesn’t publish often these days, but it’s worth subbing; otherwise, you’ll miss a treatise like this. This is 16,000 words, but Jon tells you upfront that you can just read the bolded sentences for a fast version. It’s a moneyball lens on fitness with a decision process that generalizes to any wicked domain, wellness, of course being one of the most wicked. A lot of examples of “think in probabilities”, “make +EV bets with limited downside”, “via negativa”, and toggling confidence when multiple lenses validate an idea (ie personal experience, expert track record, math, what works empirically, science).

Money Angle

This week, I hosted class #4 of the Investment Beginnings for local kids aged 12+.

The series’ materials are here:

https://notion.moontowermeta.com/investment-beginnings-course

This is the specific material for class #4:

I also created a web version of the game:

☀️🌧️Sun/Rain Game

While I’ve been doing the series for kids, I think a lot of adults could even benefit. The overall arc of the presentation:

  1. Last class’s game ended with a humbling but common result, hinting at a key pillar of investing.
  2. We use a few facts to dispel the recency bias that all investors carry with them.
  3. They learn what the fundamental nature of stocks predicts about their individual and group behavior.
  4. We widen the meaning of diversification beyond stocks, which was extremely easy to do in light of March 2026.
  5. We play a game that makes the implications for portfolios concrete.

While moontower readers span a wide range of investment experience (although overall quite interested in investing and money), here are a few ideas that I hope are presented in ways that might augment even your understanding or at least help you explain to learners in your life.

The most naive strategy is hard to beat

The kids spent Class 3 picking stocks based on a bunch of variables they could sift through, only for the equal-weight benchmark to beat everyone except the team that contrarily concentrated in the highest momentum company that is very much still an enigma to the market (TSLA).

The equal-weight strategy which I just called a monkey (although it’s not random, just dumb) beat 2/3 of the 15 individual stocks themselves.

The reason you shouldn’t be surprised that the naive strategy is hard to beat

Companies eventually die, but indexes shed them before they are in hospice.

Only 17% of the original S&P 500 companies from 1957 survived 50 years. The average company lifespan on the index was 33 years in 1964 — it’s now under 20. Kodak invented the digital camera in 1975 and buried it because of the innovator’s dilemma.

In a crash, stocks remember they’re all stocks.

Diversification works differently in good years than bad ones. In the class data, stocks spread widely in bull years. Then we looked at Jan 2022 to Jan 2023: 13 of 15 stocks fell together, the spread collapsed.

I didn’t want to lean into the word correlation, but I noticed a different way to convey the same idea. The inter-quartile range (IQR) of annual returns was smallest in the worst years. This chart is rich with insight. Notice the IQR’s visually but also how the equal-weight portfolio performed relative to the individual stock and median stock returns each year:

These observations are non-CAPM ways to arrive at the familiar language of diversifiable risk (company-specific stuff you can eliminate for free) and systematic risk (market-wide stuff you can’t diversify away but do get paid to carry). The crash revealed which was which.

If we zoom out from stocks alone, we see a race where the leaders change each year

The Novel Investor quilt shows 15 years of annual returns ranked best to worst across 9 asset classes. The diversified portfolio, that gray-ish bar, never wins a year nor comes in last. Note commodities, gold and BTC are absent from the series.

How do you think they would influence the gray portfolio?

The Sun/Rain Game

This leads to a game where we can build some intuition about the role of non-stock assets in a portfolio.

If you look at the sheet you can see how the kids actually did (I changed the kids names to letters):

The game’s punchline is that owning the anti-correlated asset despite it having a worse expected return than the “good” asset leads to a better long-term portfolio.

But this is so unintuitive that I got a student’s question wrong during the discussion!

I’ll explain the mistake here.

A student asked if we played the game for 100 years instead of just 20 years, if owning the good asset ONLY would have led to the best return. I initially said no, then corrected myself and said yes because it has the higher expected return.

But I was right the first time. The answer is definitely NO.

It comes down to the fact that the good asset has an expected arithmetic return of +5%, BUT it has a negative expected CAGR or geometric return.

The math:

The company is 50/50 to return+40% or -30% in any given year.

.5 x 40% + .5 x -30% = +5%

But over 2 years, you expect 1 up, 1 down. Compounding math:

1.4 x .7 = 98%

You expect to lose 2% over a 2-year sequence of about 1% per year.

Formally, we compute the expected CAGR by multiplying (note how the arithmetic or single period return is added):

1.4^(1/2) * .7^(1/2) – 1 = .9899 -1 = -1%

[The exponents represent the probability of each outcome. If there were 3 outcomes, you’d have 3 terms and the exponents sum to 1.]

In the long run, the good asset destroys value. So you do not want to concentrate in it despite its superior expected arithmetic return.

The CAGR is being killed by volatility drag, which is the asymmetry of the fact that if you lose 30% you need to return 42.9% to get back to even, but the “up” years only return 40%. You are falling behind over time.

The bad asset returns -10% half the time and +8% half the time. It’s a “worse” asset, but it’s less volatile. Taking this quality to its extreme, isn’t this what cash is?

In arithmetic terms, our average return if we allocate to each asset equally is +2% (50% x 5% + 50% x -1%). But that portfolio is less volatile because one stock zigs when the other zags. The diversification cuts the volatility MORE than it cuts the expected return, leading to a better risk/reward!

If we rebalance each year back to an equal-weight portfolio, we “pull” the expected CAGR closer to the expected arithmetic return. It’s the only way we can get close to eating those expected arithmetic returns. Otherwise, they don’t really exist for you over time.

This table is worth staring at:

Here’s a message one of the dads sent me after the class:

 

Money Angle for Masochists

I made you a tool to compute your portfolio vol and see how much the cross-correlations between your holdings have been reducing total vol from the vol that the individual assets contain. You can tinker by adding ETFs of other asset classes to your equities (ie GLD or USO or TLT etc) to see how they affect the volatility.

If you just want inspiration for an idea, use the tool to compare the Mag 10 index (MGTN) realized volatility with the average realized volatility of its holdings. The index is conveniently equal-weighted, 10% in each name.

Two ways to try this on your own portfolio:

🌐To run in your browser

https://colab.research.google.com/github/Kris-SF/data-pipelines/blob/main/portfolio-vol/portfolio_analysis.ipynb

⚠️Just push through the warning it spits off

The output will includes metrics and charts:

 

🖥️To run locally

git clone <https://github.com/Kris-SF/data-pipelines.git>
cd data-pipelines/portfolio-vol
pip install -r requirements.txt
jupyter lab portfolio_analysis.ipynb

Either way, edit the WEIGHTS dict and the START / END dates, then Run All.

 

An Explicit Solution to Black-Scholes Implied Volatility | Wolfgang Schadner

For the past 50 years, implied vols were calculated from option prices and other option inputs numerically. Simple versions use Newton-Raphson or bisection searches. The idea is to “guess” what the implied vol is, call that g*, see what option price that produces, split the difference, and repeat the recipe until you arrive at a price that is within a fraction of a cent of the market price. This method is used because there’s no closed form going from price → vol, only vol → price.

This SSRN paper came out this week and made the rounds quickly. It offers a closed-form approximation, alleging it recovers IV to machine precision ~3.4x faster than the current best-in-class. If it holds up under wider testing in the wild, it’s the kind of thing that ends up in textbooks.

From My Actual Life

My youngest turned 10 yesterday. I wrote him a letter just as I did for my eldest when he turned 10. It can be hard to remember what your kids are like at every phase. But also, it can be hard to remember where you’re at mentally at those ages. You hope the letter becomes a gift they cherish when they are older and can relate to being an adult writing to their child. But looking back at the letter myself will be a time capsule gift for my future self too.

This is an instance of a belief I have come around to as they’ve gotten older. A lot of what I think I do for them I really think is for me. I want to be around them selfishly more so than I think my presence is as important as I’d like to believe.

The possibility that kids do more for you than you for them is better left as a self-effacing end to having children rather than something to weigh before having them. Don’t tell the optimization maxxers.

This Week In The Options Trench

📺Convexity vs Leverage

This week Eirk and I disentangle the source of amplified profits and losses

Stay groovy

☮️

 

Moontower Weekly Recap