pitchfork CLAWback

You can’t swing a cat these days without hitting a prediction of what AI means for humanity. Insofar as it’s possible for someone writing for a wide audience, I’ll share what amounts to some half-baked thoughts that I keep coming back to.

“YOU GET A UI, YOU GET A UI”

I say this as someone who feels some dissonance building an analytics product with charts and tables. The future is just APIs talking to each other. In the future, Zillow’s UI is a mere suggestion. You want the data in a different format? You want inference beyond what Zillow decided goes into a Zestimate? All of that is getting cheaper and accessible to non-technical people.

You’ll go to a site. Maybe. Instead it wil be Siri or Jarvis or Alexa or whatever “I want to see XYZ” and your client-side listener will construct it but it’s going to need access to API that has the data. The data is increasingly all the value while rigid presentations become pointless.

Again, the future is APIs talking to each other. Data becomes increasingly locked down.

On Data Lockdown…

Scarce or exclusive data’s value increases as its complement, inference, gets cheaper. The big futures and stock exchanges are some of the original 2-sided platform businesses. Can see them flexing their quasi-monopolistic might on the data side.

…which might get dark

The fight over data will intensify as well. If you place a bid, the exchange claims that’s their data. But is it yours? Well, it’s of little value to you but whose gonna galvanize the white-collar movement around “hey AI trained on all this data that had little value in isolation, but so much value in aggregate then used it to disrupt US”. It started with the Hollywood writers guilds, but is it crazy to imagine rolling protests as automation eviscerates industry by industry? To see picketers with dystopian slogans like “my data, my choice”.

It’s a different argument than p(doom) objections to AI. It’s not “you shouldn’t have built this” but you had no right to cut me out. It seemed like a bargain when we got “free” email or “free” social media. The tone deaf tech mogul will undoubtedly claim it was fair at the time and maybe that can fly intellectually. But it’s not the clawback by court that will decide. That one happens by pitchfork.

AI Immune

As SaaS gets wrecked, we wonder retains value in the singularity. My working model is:

trust and accountability

Maybe AI can sell my house but realtors have survived fee compression and technology far longer than anyone expects. I think this hints at a still-valid truth. People want to have someone to yell at, appeal to, or simply talk to when it comes to lumpy, rarely repeated transactions.

It’s the “shit umbrellas” theory. The human’s value is not in doing the work but in retaining liability. AI can read the tax code, but my accountant will stand by his work in court.

If you travel extensively for work your relationships are hard-earned. The proof of work is miles traveled or other exclusionary behavior where there was no substitute. Relationships are repos of accumulated, unfakeable work.

The more you can position yourself as accountable the more value you can retain. Being trustworthy and reliable don’t go out of fashion. They will get even more valuable as so much else can be faked.

A strange corollary to this:

Things that were always fake but valuable will stay that way. Like astrology.

A final thought in this thread:

Anyone burning their reputation to the ground thinks either the world is ending or the tides won’t ever turn. Hmm, how would you act if you couldn’t afford for the tides to ever turn?

Art

Art is a big question. There’s will always be a positional scarcity component of it and there will always be genius. The question of whether there will be a surplus of robot genius around as well. We may finally get an answer to would a million monkeys write Shakespeare.

Live performance and sports will stay important. At least until everyone over the age of 10 today is dead. Then all bets are off. I never thought watching people play video games would be popular. I’m now open to the possibility that future people may perfectly prefer robots playing video games or anything for that matter over people playing.

 

I leave you with this interview with the creator of Open Claw. Listen specifically from 8:30 to 10:17

107 seconds and I quote, “Holy fuck”

If you are hanging your hat on cleverness for its own sake or rigid definitions of intelligence, your time is over. I’m not saying intelligence is losing value, but that its truest definition will become obvious — the ability to get what you want out of life. This is the only definition that will matter and the bright side of that is that its more inclusive than whatever school thinks it is.

I was at a local book fair last week where you dump as many books as you can fit into brown shopping bag for $8. It was an epic haul and a great incentive to just snag boogs that seem even remotely interesting.

I picked up this 1957 classic by C. Northcote Parkinson. I was familiar with his eponymous law, which states “work expands so as to fill the time available for its completion”.

Image

This entire book is an extraordinary, laugh-out-loud, pull-no-punches satire. Parkinson would have been an absolute master at Twitter. The law itself is satire wrapped around a specific observation. The way he formalizes the argument is pure art, even ending with an insane equation (he constructs hilarious equations throughout making the book feel like a tongue-in-cheek treatise on social physics).

Satire, notwithstanding, it sure feels like the very thing Parkinson’s Law pokes fun also holds the key to our salvation if AI just does all the work. So that’s where I am now. Placing humanity’s hope on a joke by a British naval man whose skill with the pen is such that I want to vibecode a Parkinson writing voice app.

Moontower #306

Friends,

You can’t swing a cat these days without hitting a prediction of what AI means for humanity. Insofar as it’s possible for someone writing for a wide audience, I’ll share what amounts to some half-baked thoughts that I keep coming back to.

“YOU GET A UI, YOU GET A UI”

I say this as someone who feels some dissonance building an analytics product with charts and tables. The future is just APIs talking to each other. In the future, Zillow’s UI is a mere suggestion. You want the data in a different format? You want inference beyond what Zillow decided goes into a Zestimate? All of that is getting cheaper and accessible to non-technical people.

You’ll go to a site. Maybe. Instead it wil be Siri or Jarvis or Alexa or whatever “I want to see XYZ” and your client-side listener will construct it but it’s going to need access to API that has the data. The data is increasingly all the value while rigid presentations become pointless.

Again, the future is APIs talking to each other. Data becomes increasingly locked down.

On Data Lockdown…

Scarce or exclusive data’s value increases as its complement, inference, gets cheaper. The big futures and stock exchanges are some of the original 2-sided platform businesses. Can see them flexing their quasi-monopolistic might on the data side.

…which might get dark

The fight over data will intensify as well. If you place a bid, the exchange claims that’s their data. But is it yours? Well, it’s of little value to you but whose gonna galvanize the white-collar movement around “hey AI trained on all this data that had little value in isolation, but so much value in aggregate then used it to disrupt US”. It started with the Hollywood writers guilds, but is it crazy to imagine rolling protests as automation eviscerates industry by industry? To see picketers with dystopian slogans like “my data, my choice”.

It’s a different argument than p(doom) objections to AI. It’s not “you shouldn’t have built this” but you had no right to cut me out. It seemed like a bargain when we got “free” email or “free” social media. The tone deaf tech mogul will undoubtedly claim it was fair at the time and maybe that can fly intellectually. But it’s not the clawback by court that will decide. That one happens by pitchfork.

AI Immune

As SaaS gets wrecked, we wonder retains value in the singularity. My working model is:

trust and accountability

Maybe AI can sell my house but realtors have survived fee compression and technology far longer than anyone expects. I think this hints at a still-valid truth. People want to have someone to yell at, appeal to, or simply talk to when it comes to lumpy, rarely repeated transactions.

It’s the “shit umbrellas” theory. The human’s value is not in doing the work but in retaining liability. AI can read the tax code, but my accountant will stand by his work in court.

If you travel extensively for work your relationships are hard-earned. The proof of work is miles traveled or other exclusionary behavior where there was no substitute. Relationships are repos of accumulated, unfakeable work.

The more you can position yourself as accountable the more value you can retain. Being trustworthy and reliable don’t go out of fashion. They will get even more valuable as so much else can be faked.

A strange corollary to this:

Things that were always fake but valuable will stay that way. Like astrology.

A final thought in this thread:

Anyone burning their reputation to the ground thinks either the world is ending or the tides won’t ever turn. Hmm, how would you act if you couldn’t afford for the tides to ever turn?

Art

Art is a big question. There’s will always be a positional scarcity component of it and there will always be genius. The question of whether there will be a surplus of robot genius around as well. We may finally get an answer to would a million monkeys write Shakespeare.

Live performance and sports will stay important. At least until everyone over the age of 10 today is dead. Then all bets are off. I never thought watching people play video games would be popular. I’m now open to the possibility that future people may perfectly prefer robots playing video games or anything for that matter over people playing.

 

I leave you with this interview with the creator of Open Claw. Listen specifically from 8:30 to 10:17

107 seconds and I quote, “Holy fuck”

If you are hanging your hat on cleverness for its own sake or rigid definitions of intelligence, your time is over. I’m not saying intelligence is losing value, but that its truest definition will become obvious — the ability to get what you want out of life. This is the only definition that will matter and the bright side of that is that its more inclusive than whatever school thinks it is.

I was at a local book fair last week where you dump as many books as you can fit into brown shopping bag for $8. It was an epic haul and a great incentive to just snag boogs that seem even remotely interesting.

I picked up this 1957 classic by C. Northcote Parkinson. I was familiar with his eponymous law, which states “work expands so as to fill the time available for its completion”.

Image

This entire book is an extraordinary, laugh-out-loud, pull-no-punches satire. Parkinson would have been an absolute master at Twitter. The law itself is satire wrapped around a specific observation. The way he formalizes the argument is pure art, even ending with an insane equation (he constructs hilarious equations throughout making the book feel like a tongue-in-cheek treatise on social physics).

Satire, notwithstanding, it sure feels like the very thing Parkinson’s Law pokes fun also holds the key to our salvation if AI just does all the work. So that’s where I am now. Placing humanity’s hope on a joke by a British naval man whose skill with the pen is such that I want to vibecode a Parkinson writing voice app.

 

 

Money Angle

As an example of “everyone gets their own UI” I whipped up a Dashboard page where I can add modular tools.

The first tool I added is something I call the “Financial Analyzer”. The seed of the idea came from an education POV. I’m teaching this Investment Beginnings Class, but I myself am a novice at reading balance sheets and income statements.

Pre-AI I would want a teacher sitting next to me explaining what sticks out to them. In minutes I was able to make a site where I give it a ticker and range of years and it pulls the filings from the SEC’s Edgar database. But the best part is Claude can act as the teacher and write its own summary of what it sees from year to year. I’m not saying this is going to be human expert level analysis but that is not the bar. I’d just like to pull up a stock and get a quick orientation through the years.

I could even feed the analysis back into an LLM to have it explain it to me even simpler.

I happened to pick up Neal Stephenson’s Diamond Age from that book fair I went to. You can build your own “Young Lady’s Illustrated Primer” now. It’s a bull market for learners out here.

The video below shows how the tool works. I’m not sharing the tool publicly because the analysis layer uses Anthropic tokens but this description is from Claude and is probably a good enough prompt to make it yourself:

A browser-based tool that pulls structured financial data for any US public company directly from the SEC’s EDGAR XBRL API — the same data companies are required to submit with their 10-K and 10-Q filings. No third-party data providers, no API keys.

  • Enter a ticker, pick a year range, and get collapsible income statement, balance sheet, and cash flow tables going back to 2005.
  • Toggle between annual and quarterly views.
  • Every line item shows the exact XBRL concept tag it maps to, so you can trace any number back to the original filing. A “Raw XBRL Data” tab exposes the complete set of concepts the company filed — not just the ~40 our template covers — with search and filtering. Remainder rows flag where our template’s sub-items don’t sum to the reported total, so nothing silently disappears.
  • An AI-generated analysis summarizes trends across the full time series.

Stack

  • Single HTML file (no framework, no build step)
  • Vercel serverless functions for the SEC proxy and Claude API calls, hosted on Vercel’s free tier.

Data endpoints

  • www.sec.gov/files/company_tickers.json for ticker lookup
  • data.sec.gov/api/xbrl/companyfacts/ for filing data.

 

Money Angle for Masochists

My new podcat series with Outlier Trading is up. The first is a short one just to set the stage for what to expect from weekly episodes.

We released a second one on Friday because, well, oil is interesting.

Visual Derivations

This week I re-published a foundational option post on X articles.

🔗👿The MAD Straddle👿

It’s a beast of a post that I orginally published in the format of a Socratic homework but in the X format you can basically read straight through it.

It covers:

☑️The relationship between MAD (mean absolute deviation) and standard deviation
☑️how to approximate a straddle value without a model
☑️a visual derivation of the approximation
☑️see how the straddle is the MAD
☑️gain an intuition for how skew and fat-tailed distributions distort the relationship between straddle prices and volatility
☑️see practical situations where ATM straddles and therefore volatility misrepresents risk

Sometimes these learning posts go over a lot of material so I think it’s helpful to point out what parts of them are most interesting to me personally. In this post it’s the section Lessons from a Skewed Coin and how standard deviation and in turn straddles are deeply misleading representations of risk when a distribution is highly skewed such that the mean is balancing many frequent events in one direction verse rare but large events in the other. I talk about how this shows up in familiar investing scenarios.

The other concept in here I like to emphasize, in no small part, because it’s legit fun is the visual derivation of the straddle approximation that states the straddle is 80% of the vol.

The derivation:

The mean of the distribution

We want to estimate the straddle. The mean of the underlying stock distribution is centered around the forward price not the at-the-money price.

We will estimate the at-the-forward (ATF) straddle.

This means we are estimating the straddle struck at the ATF strike.

The ATF strike occurs at the ATF price:

Approximating the ATF call option

This is the meat of the work.

[It requires no more than pre-algebra.]

Let’s go.

While we want the straddle, let’s start with the ATF call option.

 

Image
Image

We established 3 identities that occur at-the-forward:

Image

Now we just plug these back into the B-S formula for the call.

Image

Hmm, this looks fairly docile. Stare at it hard. The next section will feel good if you like geometry!

The underlying distributions for B-S is that stock prices are lognormal. The prices are lognromal but logreturns are normally distributed.

This is handy because normal distributions are familiar to work with.

d1 and d2 are like Z-scores on a Gaussian (bell) curve of logreturns!

The probability density function (PDF) for a bell curve:

 

The center of our distribution is an expected logreturn of 0 corresponding to the forward Seʳᵗ

The peak of a bell-curve at that forward price corresponding to a logreturn of 0. For the standard normal curve we can assume σ = 1

Plug 0 into x of the PDF:

 

Let’s bring this all together into a picture:

Image

 

Understanding the picture

The value of the ATF call is the integral of the PDF between d1 and d2 but we can estimate it!

height x base x forward price

 

 

Note: This will slightly overestimate the value of the call (see the overestimated region in the picture

To go from call price to the straddle, we remember that at-the-forward strike the call and put are equal because of put-call parity!

The rest is easy:

Image

The straddle is the MAD!

The volatility, which is computed just like a standard deviation, gives large moves extra weight. But the straddle is a better reflection of what move size we typically see.

It will cost you .80 of the standard deviation to buy a fairly priced straddle. Let’s plug that into a normal curve’s cumulative distribution function:

Image

💡Theoretically, if the straddle is fairly priced:

  • it will expire in-the-money ~ 42% of the time
  • despite the low “hit rate”, it’s fairly priced because the payoff on larger moves balances the expectancy

 

Stay groovy

☮️

Moontower Weekly Recap

Posts:

useless NOISE

This is what ZeroHedge posted after NVDA earnings:

and now NVDA is flat. straddles were pricing in 4.4% move. options worthless, dealers win.

Huh?

Earnings were priced cheap and you think the dealers were… short?

And by what mechanism are they engineering a short pin? Texas hedging their gamma scalps?

The dealers were probably sitting there lamenting how smart the rest of the market to stuff straddles down their throats after the earnings announcement being a nothingburger (at least based on the early reaction).

From a birdie, I pinged who knows a tad about trading — ya know, because they sling thousands of options a day for a living, instead of ragebaiting conspiracy theorists with conspiracies that aren’t even coherent on their face:

Idk- nvda was up four %, then unched, now down 4%. I’d guess you’d be long earnings gun to your head. I doubt dealers were smoking a 4% nvda earnings move. In var space I think that looks rough. What I will say- is given the print- market was long nvda and now just exiting into a good print and excess liquidity if I had to guess.

This brings me to a rant I need to pop off maybe once a year or so before the tank fills up again.

Look, I don’t know shit about most stuff. But watching takes on options from popular channels reminds me that the standards of knowledge one is willing to meet when their game is to have an opinion on everything is embarrassingly low. Which, in turn, discredits that channel on everything. When they are right…it’s accidental.

This is the f’ing definition of NOISE. Pure static. Hanging around, blathering. Like we all know someone like this in person — ugh, enough, aren’t you tired of wasting spectrum yet, jfc.

It reminds me of an old Farnam Street post about Batesian mimicry. Several species of snakes mimic the appearance of the venomous coral snake.

Image

This is a common defense in nature. And a common offense on Twitter/X to gain clout.

The more impressive the “model,” the more effective its mimics can be in convincing people they too are impressive, and in all the same ways. But for every Warren Buffett (just one by our count), there has been many “future” Warren Buffett’s. For every Steve Jobs, there have been many “next” Steve Jobs’.

In fact, sometimes even just appearances can be quite convincing: now-disgraced Theranos founder Elizabeth Holmes was very fond of wearing a very Steve Jobsian black turtleneck outfit.

It seems almost a law of nature that success will be copied, sometimes in a very disgraceful way.

And who can best tell the difference between a coral snake and its mimics? The coral snake itself. The Munger quote:

“It’s very hard to tell the difference between a good money manager and someone who just has the pattern down. If you aren’t a good money manager yourself, rather than trying to pick one, you’re probably better off with a low cost index fund. It takes one to know one.”

Example of “measurement not prediction” in the wild

A reader replied enthusiastically to my 2-week-old post when logic and proportion have fallen sloppy dead giving me credit for calling that a strike on Iran would lift oil prices 14%.

He wants to know what I think now.

Slow down. This is a great example to clarify:

I don’t know anything material about geopolitics, military strategy, the supply/demand response function for light, sweet crude slated for delivery at Cushing, Oklahoma. I don’t have an opinion now or when I wrote the post.

I only have eyes to see the present. To look at a price and try to reverse engineer how it could make sense. The details are in that post, but the specifics matter less than the approach. In fact, I even mention why my approach is probably exactly wrong, but what a more correct one could look like.

This cuts to the heart of what I think trading is. It’s something pretty light on “opinions”. That’s for VCs and crystal ball investors, me, I’m a donkey.

I try to invert prices to reason about what the point spreads are, then try to find a contradiction. The whole “measurement not prediction” thing*. Measurement is hard enough. Prices tell you things if you can measure. You can separate probabilities from magnitudes. You can know what the consensus is for how correlated assets are to each other. You can divine when the market thinks we will attack Iran. This is all just sitting there.

You can protest that prices are dumb and wrong, but you are only allowed to make such pronouncements from your private jet otherwise, I can’t hear you.

So as oil goes, I have no opinion, but I can pull up a few screens and tell you what one of the smartest, most efficient markets in the world might think. Maybe there are prices in dumber or less liquid or harder-to-access corners of the world that disagree. Trading means different things to different people. I think it’s the art of turning contradictions into cash.

*Related:

I was listening to Citrini chat with Risk of Ruin’s John Reeder when John said:

I have heard Citrini repeat something that George Soros says, which is, I’m not predicting, I’m observing. Paying attention to what’s happening.

You’ll discover Citrini’s key to observing is how he filters, a skill that is increasingly difficult but always growing in value.

the math of investing

As I’ve shared here before, I spun up an investing class for middle and high school kids locally. I am teaching my 12-year-old as it is, so I figured if I formalize it a touch so others could learn as well.

The materials for all the classes live here:

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

There are a few weeks between each session since there’s a fair amount of prep even with AI helping with:

  • Claude in PowerPoint was released recently so I gave it a spin. I gave it a stylesheet of colors and fonts as well as an unformatted draft of the lecture, and let it cook. You can see the result below.
  • The interactive spreadsheet has a bunch of JavaScript behind it

The class we did this week was a lot of fun. There’s even a video to prove it below (I masked any faces. There were 16 kids in attendance). Most importantly, the kids learned a ton. Parents were texting me with their feedback and it felt good to hear their kids’ gears were turning.

For what it’s worth, I think there was a lot of material in here that parents don’t know either but I’ll leave you to guess what some of that might be.

Investment Beginnings — Class 2: The Math of Investing

Class 1 was about building a business.

Class 2 flips the perspective — you’re the investor now.

Someone is asking you for money. What should you pay for shares? What’s the lowest rate you’d lend at? How do you know if it’s a good deal?

This session covers the foundational math that underpins every investment decision you’ll ever make.

What we covered:

✅ The power of compounding (FV = PV × (1 + r)^n)
✅ The lily pad riddle: why most of the action happens at the end
✅ Early Bird vs Late Starter: why starting 10 years earlier beats investing 3x more money
✅ Warren Buffett: 99% of his wealth came after age 50
✅ Total Return vs CAGR: why doubling your money in 10 years is ~7%/yr, not 10%
✅ The Rule of 72: quick trick to estimate how long to double your money
✅ P/E ratio (multiple) and earnings yield (the reciprocal)
✅ The two levers of stock returns: earnings growth vs multiple expansion/contraction
✅ Zoom case study: great earnings, terrible return — how you can pay too much
✅ The asymmetry of losses: why losing 50% requires a 100% gain to recover

Hands-on:

🕹️ Live bidding exercise: students not only bid on shares of Lamorinda Sneaker Co knowing only that it earns $10/share, but quoted the lowest rates they’d lend at.
🕹️ P/E guessing game: guess the real-world multiples for Tesla, Chipotle, Shake Shack, Lululemon, Nike, and more

Homework:

🔨 Inflation Scavenger Hunt — look up prices from the year you were born vs today🔨 Fee Impact Calculator — compare 0.03% vs 1% fees over 40 years
🔨 P/E Return Decomposition — Pick 5 stocks. For each, look up the price and EPS 5 years ago vs today. 1) How much of the total return came from P/E multiple change vs EPS growth? 2) Then compute the current earnings yield (E/P). Compare it to the trailing 5-year CAGR. 3) Using the Rule of 72: if the 5-yr CAGR continued, how long to double your money? If you earned the earnings yield instead, how long to double?
🔨 Compounding Frequency — calculate FV compounded annually vs semi-annually

Resources:

📊 Slides
📈 Spreadsheet (File → Make a copy to get your own editable version; scripts may trigger a security warning — just advance through it)

Full video:

Money Angle For Masochists

Junior Masochists

Let’s review 2 examples from the class that demonstrate how markets are hard because prices are already forward-looking.

The kids learned how to decompose returns into change in earnings vs change in multiple. Or “what happened” vs “the future” or what I sometimes referred to as “sentiment”.

When I asked the class what stock would have been all the rage during Covid (when many of these kids were only 6 years old 🥹), one boy immediately and correctly responded, “ZOOM!”

I pulled up ZM’s price chart:

I asked…”what do you think happened?”

Kids suggested that less people used Zoom as people went back to offices. I explained that ZM’s earnings actually did skyrocket for the past few years so that’s not the culprit behind the horrible return.

Look at the revenues from this Twitter post:

It’s not just the revenues that are up (although you can see how revenue growth has slowed). EPS has also skyrocketed.

The multiple just got hammered. Great business, but investors just paid too much for it.

Earnings were up >35x, but the multiple is down 99%.

A handy decomposition:

Price return = (1+ percent change in EPS) * (1 + percent change in multiple) – 1

The point of the formula is that your return depends on changes in fundamentals (actual earnings) AND change in sentiment around future growth prospects.

A quick caveat. This is not complete. Imagine a situation where a company is $5/share and EPS of $1 for a P/E of 5. Over the next year, the company’s earnings don’t grow and the stock price doesn’t change. The price return is zero. But the company did earn $1. It’s assets have grown by 20%. You are economically richer by 20% but if they don’t distribute it by other paying a dividend or buying back shares (which would raise EPS) then the formula above did not account for a more holistic total return.

You could estimate:

Total return = (1+ percent change in EPS) * (1 + percent change in multiple) + earnings yield – 1

That would capture the idea that you are economically better off even if it’s not paid out, although management’s allocation decisions are a matter of concern.

As a class, we stumbled into a situation on the opposite side of the spectrum. A boy mentioned he bought Delta Airlines 5 years ago for ~$35. I pulled up the chart and noticed the stock doubled.

First of all, great teaching moment as we covered rule of 72 minutes earlier so I immediately asked the class, what the annual return must be? Proud dad moment as Zak is the first one to say 14.4% which I know he figured by thinking “72 divided by 10, times 2” which is better than I would have done as I would reach for 70/5.

Mental math aside, I asked our young investor, “Why did Delta do well, did the earnings increase or the multiple?” With zero hesitation, he responds that the earnings haven’t grown. So a perfect anti-Zoom example for the class. Delta Airlines coming out of Covid years had sour vibes but even if the earnings didn’t grow, you could make a nice return on the sentiment and therefore multiple improving.

I did go back after the class to see DAL earnings and stock history and I think it makes more sense that the kid bought the stock just 2 years ago, since that is the point in time where the earnings were about the same to now and the stock was about $35.

A crap business that investors sold too cheap.

For our regular Masochists

Since we are talking fundamentals, a mutual on X pointed out that HRB (H&R Block) has recently gotten trashed and that its shareholder yield is ~15%.

Shareholder yield is dividends + net share repurchase + debt reduction as a percent of market value.

News flash, HRB is not a growth business. It doesn’t re-invest much of its earnings versus just distributing the cash. I do find it amusing that the stock could be trashed along with other AI disruption stories when it has already survived the transition from brick & mortar to the internet, the popularity of TurboTax, and the growth of the standard deduction, relieving a wider proportion of the population from filing. With a P/E of 7 and a management that pays out the earnings you make ~15% if its already crap business stays the same.

Shedding 1/3 of its market cap since the start of the year, the implied vol is unsurprisingly jacked. I’m a little nuts and decided this was enough to launch some puts with the “I’ll take the shares if I’m wrong”. I normally don’t like this mentality, but part of the vol selling attitude is that the stock probably doesn’t have a lot of upside which reduces the regret possibility from “I was right on this stock and all I collected was some put premium”. In other words, if the upside is abridged, that’s a statement about the vol of the stock being lower.

Selling puts for yield is pretty aligned with what I’m trading the stock for in the first place — yield. I’m just taking it in the form of options intead of buying the stock because the option market is giving me that, but if the price falls a lot further well, I’ll have to go for that yield in the form of assigned shares.

Never financial advice, I’m just sharing my thinking aloud. As options go I’m currently short covered calls in silver and short cash-secured puts in HRB and long options on TSLA and IBIT. Overall, vols are on the higher end of their range across the market (outside of bond vols), but there’s always relatively cheap and relatively expensive in any market cross-section.

Moontower #305

In this issue:

  • The math of investing
  • moontower as a “bridge”

Friends,

The money sections are full of education today, so I’ll be short up here again.

Permission to Chase Work You Love | 12 min read

In prior years, I’ve shared Bill Gurley’s excellent talk Runnin’ Down A Dream. It was so popular with audiences that he spent years turning it into a book with additional research. It came out this week so he’s been promoting it everywhere. Check out David’s interview with him. It’s a book I’ll be picking up for son and sharing with the kids I have in the class I discuss below.

Child’s Play: Tech’s New Generation and the End of Thinking | 34 min read

There’s no blurb suitable for this article. It hurts my head. Like, I think I’m sad. Or I’m crazy. Or the world is ruled by crazies and I’ve stayed the same. I can’t tell anymore. It was definitely entertaining.

Money Angle

As I’ve shared here before, I spun up an investing class for middle and high school kids locally. I am teaching my 12-year-old as it is, so I figured if I formalize it a touch so others could learn as well.

The materials for all the classes live here:

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

There are a few weeks between each session since there’s a fair amount of prep even with AI helping with:

  • Claude in PowerPoint was released recently so I gave it a spin. I gave it a stylesheet of colors and fonts as well as an unformatted draft of the lecture, and let it cook. You can see the result below.
  • The interactive spreadsheet has a bunch of JavaScript behind it

The class we did this week was a lot of fun. There’s even a video to prove it below (I masked any faces. There were 16 kids in attendance). Most importantly, the kids learned a ton. Parents were texting me with their feedback and it felt good to hear their kids’ gears were turning.

For what it’s worth, I think there was a lot of material in here that parents don’t know either but I’ll leave you to guess what some of that might be.

Investment Beginnings — Class 2: The Math of Investing

Class 1 was about building a business.

Class 2 flips the perspective — you’re the investor now.

Someone is asking you for money. What should you pay for shares? What’s the lowest rate you’d lend at? How do you know if it’s a good deal?

This session covers the foundational math that underpins every investment decision you’ll ever make.

What we covered:

✅ The power of compounding (FV = PV × (1 + r)^n)
✅ The lily pad riddle: why most of the action happens at the end
✅ Early Bird vs Late Starter: why starting 10 years earlier beats investing 3x more money
✅ Warren Buffett: 99% of his wealth came after age 50
✅ Total Return vs CAGR: why doubling your money in 10 years is ~7%/yr, not 10%
✅ The Rule of 72: quick trick to estimate how long to double your money
✅ P/E ratio (multiple) and earnings yield (the reciprocal)
✅ The two levers of stock returns: earnings growth vs multiple expansion/contraction
✅ Zoom case study: great earnings, terrible return — how you can pay too much
✅ The asymmetry of losses: why losing 50% requires a 100% gain to recover

Hands-on:

🕹️ Live bidding exercise: students not only bid on shares of Lamorinda Sneaker Co knowing only that it earns $10/share, but quoted the lowest rates they’d lend at.
🕹️ P/E guessing game: guess the real-world multiples for Tesla, Chipotle, Shake Shack, Lululemon, Nike, and more

Homework:

🔨 Inflation Scavenger Hunt — look up prices from the year you were born vs today🔨 Fee Impact Calculator — compare 0.03% vs 1% fees over 40 years
🔨 P/E Return Decomposition — Pick 5 stocks. For each, look up the price and EPS 5 years ago vs today. 1) How much of the total return came from P/E multiple change vs EPS growth? 2) Then compute the current earnings yield (E/P). Compare it to the trailing 5-year CAGR. 3) Using the Rule of 72: if the 5-yr CAGR continued, how long to double your money? If you earned the earnings yield instead, how long to double?
🔨 Compounding Frequency — calculate FV compounded annually vs semi-annually

Resources:

📊 Slides
📈 Spreadsheet (File → Make a copy to get your own editable version; scripts may trigger a security warning — just advance through it)

Full video:

Money Angle For Masochists

Junior Masochists

Let’s review 2 examples from the class that demonstrate how markets are hard because prices are already forward-looking.

The kids learned how to decompose returns into change in earnings vs change in multiple. Or “what happened” vs “the future” or what I sometimes referred to as “sentiment”.

When I asked the class what stock would have been all the rage during Covid (when many of these kids were only 6 years old 🥹), one boy immediately and correctly responded, “ZOOM!”

I pulled up ZM’s price chart:

I asked…”what do you think happened?”

Kids suggested that less people used Zoom as people went back to offices. I explained that ZM’s earnings actually did skyrocket for the past few years so that’s not the culprit behind the horrible return.

Look at the revenues from this Twitter post:

It’s not just the revenues that are up (although you can see how revenue growth has slowed). EPS has also skyrocketed.

The multiple just got hammered. Great business, but investors just paid too much for it.

Earnings were up >35x, but the multiple is down 99%.

A handy decomposition:

Price return = (1+ percent change in EPS) * (1 + percent change in multiple) – 1

The point of the formula is that your return depends on changes in fundamentals (actual earnings) AND change in sentiment around future growth prospects.

A quick caveat. This is not complete. Imagine a situation where a company is $5/share and EPS of $1 for a P/E of 5. Over the next year, the company’s earnings don’t grow and the stock price doesn’t change. The price return is zero. But the company did earn $1. It’s assets have grown by 20%. You are economically richer by 20% but if they don’t distribute it by other paying a dividend or buying back shares (which would raise EPS) then the formula above did not account for a more holistic total return.

You could estimate:

Total return = (1+ percent change in EPS) * (1 + percent change in multiple) + earnings yield – 1

That would capture the idea that you are economically better off even if it’s not paid out, although management’s allocation decisions are a matter of concern.

As a class, we stumbled into a situation on the opposite side of the spectrum. A boy mentioned he bought Delta Airlines 5 years ago for ~$35. I pulled up the chart and noticed the stock doubled.

First of all, great teaching moment as we covered rule of 72 minutes earlier so I immediately asked the class, what the annual return must be? Proud dad moment as Zak is the first one to say 14.4% which I know he figured by thinking “72 divided by 10, times 2” which is better than I would have done as I would reach for 70/5.

Mental math aside, I asked our young investor, “Why did Delta do well, did the earnings increase or the multiple?” With zero hesitation, he responds that the earnings haven’t grown. So a perfect anti-Zoom example for the class. Delta Airlines coming out of Covid years had sour vibes but even if the earnings didn’t grow, you could make a nice return on the sentiment and therefore multiple improving.

I did go back after the class to see DAL earnings and stock history and I think it makes more sense that the kid bought the stock just 2 years ago, since that is the point in time where the earnings were about the same to now and the stock was about $35.

A crap business that investors sold too cheap.

For our regular Masochists

Since we are talking fundamentals, a mutual on X pointed out that HRB (H&R Block) has recently gotten trashed and that its shareholder yield is ~15%.

Shareholder yield is dividends + net share repurchase + debt reduction as a percent of market value.

News flash, HRB is not a growth business. It doesn’t re-invest much of its earnings versus just distributing the cash. I do find it amusing that the stock could be trashed along with other AI disruption stories when it has already survived the transition from brick & mortar to the internet, the popularity of TurboTax, and the growth of the standard deduction, relieving a wider proportion of the population from filing. With a P/E of 7 and a management that pays out the earnings you make ~15% if its already crap business stays the same.

Shedding 1/3 of its market cap since the start of the year, the implied vol is unsurprisingly jacked. I’m a little nuts and decided this was enough to launch some puts with the “I’ll take the shares if I’m wrong”. I normally don’t like this mentality, but part of the vol selling attitude is that the stock probably doesn’t have a lot of upside which reduces the regret possibility from “I was right on this stock and all I collected was some put premium”. In other words, if the upside is abridged, that’s a statement about the vol of the stock being lower.

Selling puts for yield is pretty aligned with what I’m trading the stock for in the first place — yield. I’m just taking it in the form of options intead of buying the stock because the option market is giving me that, but if the price falls a lot further well, I’ll have to go for that yield in the form of assigned shares.

Never financial advice, I’m just sharing my thinking aloud. As options go I’m currently short covered calls in silver and short cash-secured puts in HRB and long options on TSLA and IBIT. Overall, vols are on the higher end of their range across the market (outside of bond vols), but there’s always relatively cheap and relatively expensive in any market cross-section.

[Dons marketing tie]

I sent this to our moontower.ai list this week:

If you run a trading or investment book that uses options but don’t have or need the weapons-grade (and weapons-cost) infrastructure that options market-makers have, then you are in our position. We built moontower.ai for us, which means it’s for you.

The various dimensions of options across expiries, strikes, and symbols are impossible to make sense of without the right lens.

Moontower is a bridge.

Everything we build is designed to be “opinionated” — pulling things together the way a vol PM sees them. Not a sea of contract premiums. A coherent picture of what’s typical and, critically, what’s not. What we call “analytics with a point of view”.

Explore Moontower Plans

“Hey, this looks expensive compared to its own history, but cheap relative to prevailing volatility surfaces across the market.”

If you understand that options are about volatility, then that is the type of statement you can make with this lens.

Take It With Your Coffee

We launched the Today’s Markets page in the past few weeks to be the first stop when opening your option view.

Your watchlist loads and the metrics snap to that universe.

  • Volume List shows what’s trading.
  • Trade Ideas classifies tickers by vol surface signatures into preset ideas.
  • Skew Extremes shows 25 delta calls and puts at extreme percentiles
  • Filters can exclude earnings and illiquid names to clean the cross-section.

Sector Performance can flag when vol moves against expectations.

Today, the Sector Performance surfaced an unusual dynamic. Crypto implied vols are up on the rally, while SLV vols are down on an up day. Opposite of what you’d expect for both!

The numbers on the bar show the price change in standard deviations;at the number on the end of the bar shows the change in implied strike vol for 1-month options.

Most option users are not dyed-in-the-wool vol traders first. If you are a professional manager refining your option expressions, reach out to hello@moontower.ai or visit us online.

From my actual life

Just some content stuff. We finished Mad Men. It’s immediately canon for me. One of my favorite shows ever. The writing, the character, the arcs, the costumes, and the period piece-ness of it. Straight into my veins.

Joining the rest of you in this decade we watched both the Anaconda reboot and Nuremberg this weekend.

Anaconda has 2 scenes that had the 4 of us howling. There’s nothing better than watching your kids cry from laughter. It’s a preposterous movie that turned out to be all upside.

I enjoyed Nuremberg on the whole, even if I found Kelly’s character forced and frankly silly (bruh, it took the film evidence to finally wake you up?). Russell Crowe and Michael Shannon carried. Although with Mad Men still in our RAM, I couldn’t take John Slattery’s character in the movie seriously. He is Roger Sterling forever.

Stay groovy

☮️

Moontower Weekly Recap

Posts:

the moontower bridge

I sent this to our moontower.ai list this week:

If you run a trading or investment book that uses options but don’t have or need the weapons-grade (and weapons-cost) infrastructure that options market-makers have, then you are in our position. We built moontower.ai for us, which means it’s for you.

The various dimensions of options across expiries, strikes, and symbols are impossible to make sense of without the right lens.

Moontower is a bridge.

Everything we build is designed to be “opinionated” — pulling things together the way a vol PM sees them. Not a sea of contract premiums. A coherent picture of what’s typical and, critically, what’s not. What we call “analytics with a point of view”.

Explore Moontower Plans

“Hey, this looks expensive compared to its own history, but cheap relative to prevailing volatility surfaces across the market.”

If you understand that options are about volatility, then that is the type of statement you can make with this lens.

Take It With Your Coffee

We launched the Today’s Markets page in the past few weeks to be the first stop when opening your option view.

Your watchlist loads and the metrics snap to that universe.

  • Volume List shows what’s trading.
  • Trade Ideas classifies tickers by vol surface signatures into preset ideas.
  • Skew Extremes shows 25 delta calls and puts at extreme percentiles
  • Filters can exclude earnings and illiquid names to clean the cross-section.

Sector Performance can flag when vol moves against expectations.

Today, the Sector Performance surfaced an unusual dynamic. Crypto implied vols are up on the rally, while SLV vols are down on an up day. Opposite of what you’d expect for both!

The numbers on the bar show the price change in standard deviations;at the number on the end of the bar shows the change in implied strike vol for 1-month options.

Most option users are not dyed-in-the-wool vol traders first. If you are a professional manager refining your option expressions, reach out to hello@moontower.ai or visit us online.

links between options and event prediction markets

Oil vols and calls skews were up a lot this week as the expectation of the US striking Iran increases. A few pictures:

Polymarket implies only 38% chance that the U.S. does NOT strike Iran by March 31.

Risk reversals, which measure the premium of puts to calls, in USO have shot sharply negative this month.

USO vols are elevated and strongly inverted across the term structure.

Implied vols until late March are ~53%.

You already know to use the free event volatility extractor to compute trading day volatility by removing an expected earnings move from an expiration. Let’s use the calculator in reverse. If we assume a typical trading day volatility of 30%, then if we were certain a strike were to occur, we guess-and-test our way to an 11.3% move size to make the term vol fair at 53%

But this is not earnings. We don’t know if the “event” will occur. We can use the Polymarket probability of 62% that an attack will occur before the end of March. We’ll need to expand the equation we normally use to account for p.

We recall the basic identity:

Term variance = expected event variance + accumulated daily variance.

In math:

where:

DTE = business days til expiry =26

p = probability of strike = 62%*

TermVol = ATM IV from March 27 expiry = 53%

EventVol = annualized vol of strike day = 224%

DailyVol = annualized vol of regular business day = ❓

*Notice in the case where P =1, the equation would be exactly the same as the one behind the calculator.

Solving for DailyVol:

DailyVol = 40.7%

But, wait, we want to fix the DailyVol to be 30%. We need the event vol that generates a DailyVol of 30% assuming that event only happens 62% of the time, not 100%, as our first calcs assumed.

It turns out to be 14.4% or 285% annualized

💡Annualizing a move to a vol

  • 14.4% x 1.25 x √251
  • Why 1.25? Because a straddle or move size is only 80% of the volatility or standard deviation. See The MAD Straddle

In sum, if we treat an Iran strike that satisfies Polymarket’s definition AND we believe the Polymarket odds AND we think it manifests as one large single-day move, then 53% IV suggests that oil will move as normal at ~30% vol but have a single-day shock of ~14%.

This is a highly skewed way of decomposing 53% vol. To assume there’s a bunch of variance concentrated in just a single day. But that 53% vol is also not the market assuming we move ~ 3.25% per day either. It’s some mix of:

  • “realized vol is elevated right now because there’s uncertainty”
  • “at some point in the near-ish future there’s going to be a lump of variance as oil either relaxes lower (which could easily be 10%) or much higher. The current price of oil is a compromise between 2 states of the world but it’s not the right price in either of them and we don’t know which state it’s going to be”

Thoughts on the Polymarket price

Here’s a more up-to-date snapshot (Substack has a Polymarket integration!)

 

I have zero insight on geopolitics so I’m just going to offer thoughts on prices:

EDIT: The Polymarket prices updated from when this email post sent (a Sunday) and when I wrote it (Friday night)

  • The market thinks a strike is coming soon. March 31 is 64% and June 30 is only 68%. Conditional on a strike happening, the market implies 64/68 ~94% chance it happens before the end of March. You can buy June, sell March and only risk $4.
  • The dollar volume on these things is small but there are many papers supporting the “marginal trader hypothesis” that it only take a handful of active, well-informed traders to make a market more efficient. This is not suprising. If we played a mock trading game for even zero stakes it wouldn’t take long for you to see how quickly a market converges to a reasonable fair value.
  • The volatility risk premium across many liquid markets isn’t abnormal. The market either doesn’t care what oil and Polymarket says or a strike on Iran is not expected to have a material effect on the volatility of equity shares. However, defense names have implied vols in high percentiles (while PLTR vols are tanked btw)

Here’s my off-the-cuff impression of the 64% price:

The real odds are probably higher. If this contract were trading for say 10% I’d guess it was overestimating the true probability because of lotto-ticket bias but also because there needs to be a healthy risk premium for seller to enter a highly negative skew trade.

I wouldn’t guess that a bunch of yolo-punting puts a price to 64% for lolz. When someone bids 64%, they are laying odds. Betting nearly $2 to win $1. The price of this contract has doubled in a week…it’s the buyer who likely brings more caution to the order book now.

I could imagine someone buying these as part of a relative value trade against selling oil options but the dollars available means it would need to be retail size and that kind of trade (oil vega vs prediction market?!) doesn’t seem like the kind of thing that would excite the class of trader who expects 20x leverage on crypto perps to get them outta bed in the morning.

If Polymarket depth was big enough to influence stock markets, there’d probably be some interesting scenarios of incinerating a few million bucks, maybe less, to influence the Poly price so you can influence the price of defense stocks where you could make tens of millions. The informational and liquidity linkages between prediction markets and traditional markets will be fascinating (appalling?) to watch as they continue to grow.

 

a downside of trading careers

Ex-SIG quant trader, friend of the Moontower, fellow Substacker Whirligig Bear and prediction market enjooooyer Andrew Courtney went on the Odds On Open with Ethan Kho.

(Ethan’s pod is totally catching fire with his great guests and interviews. He works hard as hell on this project as well as school so I’m stoked he’s getting such traction).

Not surprisingly, it’s a terrific conversation, but I want to zoom in on an idea that resonated deeply for me and easy to overlook for aspiring traders.

Ethan: You left the firm with I think you said only around 40 or so real professional connections. You said that that was one of the other defining things of being a trader — you’re with the same group of people, obviously making lots of money, but it’s not the place for someone who wants to be wants to have this insane network of a lot of different people. Talk to me a bit about the culture.

Andrew: Let’s frame it as who might this fit or not fit. Let’s contrast it with some other high leverage elite type careers. Say you’re a consultant and you’re meeting C-suite people from all different kinds of clients, you know, and you’re only a year out of college. Or you’re an investment banker and you’re doing deals with all these different firms. You’re gathering this wide network of people, a

lot of different information sources. You are working with many people versus my primary relationships were my co-workers. These were fantastic people but that was the most of my network. When you’re a quant trader, you’re not out there at conferences telling people what you’re doing or networking. You’re not talking to anybody about what you’re doing.

So I had a pretty tight network and and good relationships with a lot of these people, but it’s not it’s not like I can the C-suite or get career advice or something like that. It was much more narrow and concentrated and dense network. So it’s a different type of career definitely.

This is very rarely talked about. But the trader career will not leave you with much of a usable business network if you change careers compared to a more sales-oriented job (I say sales because high leverage careers only fall into 2 camps — being on the road selling/deal-making or being a 99.5 percentile solo-player in front of a computer. And the latter is very much under threat right now).

I am always urging early career traders to take the effort to be outward before they need to. You have to overcompensate for the narrow network. After all, you’re going to make a lot of money, right? Well, you want to have people to invest with or raise money from if you decide to become an entrepreneur one day (if you’re trading for a living, there’s a misfit inside you that probably doesn’t want to be an employee forever).

I was fortunate to be on the trading floor which does expose you to lots of people. That network was critical. It led to my next job after SIG, it created most of my broker connections when I left the floor, and it has helped me connect people with firms. But my network didn’t really ramp until I became far more outward. Reaching out on Twitter to learn, starting this letter, and adopting a more sharing posture in general. There is a zero-sumness in trading that leaks into your mindset. It has its purpose to be sure, but don’t let it creep beyond its usefulness.

One last bit that Andrew alludes to…if you want a lunch break or lunch meetings, trading isn’t for you. You never get your full attention. Want to code or do any deep work without one eye scanning screens? Tough luck. Even your basic needs take a backseat.

I forget which comedian made the joke about the weird life of pro athletes. They are rich and influential. But they still have to chase a ball around.

There is no self-aggrandizing story to tell about trading. You serve money. If you’re not there to pick it up when it presents itself why’d you even come in?

Moontower #304

In this issue:

  • white rabbit
  • a downside of trading careers
  • oil options, Iran, Polymarket

Friends,

I’ll be short up top here today as the Money Angle sections are longer than usual. This is just something fun.

My adult ensemble band played a short set at Norm’s in Danville on Thursday night for “rock band karaoke”. Our set list was High and Dry from Radiohead, You’re Love by The Outfield, and finally White Rabbit via Jefferson Airplane and written by Grace Slick.

White Rabbit is one of my favorite songs because of how it builds, a signature feature of just one of its many eclectic influences, the Spanish bolera. If you’re into song origins this was a great watch.

Apparently, Slick wrote the song after listening to a Miles Davis record for 24 hours during an acid trip. The lyrics reference Alice in Wonderland:

One pill makes you larger
And one pill makes you small
And the ones that mother gives you
Don’t do anything at all
Go ask Alice
When she’s ten feet tall

And if you go chasing rabbits
And you know you’re going to fall
Tell ‘em a hookah-smoking caterpillar
Has given you the call
He called Alice
When she was just small

When the men on the chessboard
Get up and tell you where to go
And you’ve just had some kind of mushroom
And your mind is moving low
Go ask Alice
I think she’ll know

When logic and proportion
Have fallen sloppy dead
And the White Knight is talking backwards
And the Red Queen’s off with her head
Remember what the dormouse said
Feed your head
Feed your head

Money Angle

Ex-SIG quant trader, friend of the Moontower, fellow Substacker Whirligig Bear and prediction market enjooooyer Andrew Courtney went on the Odds On Open with Ethan Kho.

(Ethan’s pod is totally catching fire with his great guests and interviews. He works hard as hell on this project as well as school so I’m stoked he’s getting such traction).

Not surprisingly, it’s a terrific conversation, but I want to zoom in on an idea that resonated deeply for me and easy to overlook for aspiring traders.

Ethan: You left the firm with I think you said only around 40 or so real professional connections. You said that that was one of the other defining things of being a trader — you’re with the same group of people, obviously making lots of money, but it’s not the place for someone who wants to be wants to have this insane network of a lot of different people. Talk to me a bit about the culture.

Andrew: Let’s frame it as who might this fit or not fit. Let’s contrast it with some other high leverage elite type careers. Say you’re a consultant and you’re meeting C-suite people from all different kinds of clients, you know, and you’re only a year out of college. Or you’re an investment banker and you’re doing deals with all these different firms. You’re gathering this wide network of people, a

lot of different information sources. You are working with many people versus my primary relationships were my co-workers. These were fantastic people but that was the most of my network. When you’re a quant trader, you’re not out there at conferences telling people what you’re doing or networking. You’re not talking to anybody about what you’re doing.

So I had a pretty tight network and and good relationships with a lot of these people, but it’s not it’s not like I can the C-suite or get career advice or something like that. It was much more narrow and concentrated and dense network. So it’s a different type of career definitely.

This is very rarely talked about. But the trader career will not leave you with much of a usable business network if you change careers compared to a more sales-oriented job (I say sales because high leverage careers only fall into 2 camps — being on the road selling/deal-making or being a 99.5 percentile solo-player in front of a computer. And the latter is very much under threat right now).

I am always urging early career traders to take the effort to be outward before they need to. You have to overcompensate for the narrow network. After all, you’re going to make a lot of money, right? Well, you want to have people to invest with or raise money from if you decide to become an entrepreneur one day (if you’re trading for a living, there’s a misfit inside you that probably doesn’t want to be an employee forever).

I was fortunate to be on the trading floor which does expose you to lots of people. That network was critical. It led to my next job after SIG, it created most of my broker connections when I left the floor, and it has helped me connect people with firms. But my network didn’t really ramp until I became far more outward. Reaching out on Twitter to learn, starting this letter, and adopting a more sharing posture in general. There is a zero-sumness in trading that leaks into your mindset. It has its purpose to be sure, but don’t let it creep beyond its usefulness.

One last bit that Andrew alludes to…if you want a lunch break or lunch meetings, trading isn’t for you. You never get your full attention. Want to code or do any deep work without one eye scanning screens? Tough luck. Even your basic needs take a backseat.

I forget which comedian made the joke about the weird life of pro athletes. They are rich and influential. But they still have to chase a ball around.

There is no self-aggrandizing story to tell about trading. You serve money. If you’re not there to pick it up when it presents itself why’d you even come in?

Money Angle For Masochists

Oil vols and calls skews were up a lot this week as the expectation of the US striking Iran increases. A few pictures:

Polymarket implies only 38% chance that the U.S. does NOT strike Iran by March 31.

Risk reversals, which measure the premium of puts to calls, in USO have shot sharply negative this month.

USO vols are elevated and strongly inverted across the term structure.

Implied vols until late March are ~53%.

You already know to use the free event volatility extractor to compute trading day volatility by removing an expected earnings move from an expiration. Let’s use the calculator in reverse. If we assume a typical trading day volatility of 30%, then if we were certain a strike were to occur, we guess-and-test our way to an 11.3% move size to make the term vol fair at 53%

But this is not earnings. We don’t know if the “event” will occur. We can use the Polymarket probability of 62% that an attack will occur before the end of March. We’ll need to expand the equation we normally use to account for p.

We recall the basic identity:

Term variance = expected event variance + accumulated daily variance.

In math:

where:

DTE = business days til expiry =26

p = probability of strike = 62%*

TermVol = ATM IV from March 27 expiry = 53%

EventVol = annualized vol of strike day = 224%

DailyVol = annualized vol of regular business day = ❓

*Notice in the case where P =1, the equation would be exactly the same as the one behind the calculator.

Solving for DailyVol:

DailyVol = 40.7%

But, wait, we want to fix the DailyVol to be 30%. We need the event vol that generates a DailyVol of 30% assuming that event only happens 62% of the time, not 100%, as our first calcs assumed.

It turns out to be 14.4% or 285% annualized

💡Annualizing a move to a vol

  • 14.4% x 1.25 x √251
  • Why 1.25? Because a straddle or move size is only 80% of the volatility or standard deviation. See The MAD Straddle

In sum, if we treat an Iran strike that satisfies Polymarket’s definition AND we believe the Polymarket odds AND we think it manifests as one large single-day move, then 53% IV suggests that oil will move as normal at ~30% vol but have a single-day shock of ~14%.

This is a highly skewed way of decomposing 53% vol. To assume there’s a bunch of variance concentrated in just a single day. But that 53% vol is also not the market assuming we move ~ 3.25% per day either. It’s some mix of:

  • “realized vol is elevated right now because there’s uncertainty”
  • “at some point in the near-ish future there’s going to be a lump of variance as oil either relaxes lower (which could easily be 10%) or much higher. The current price of oil is a compromise between 2 states of the world but it’s not the right price in either of them and we don’t know which state it’s going to be”

Thoughts on the Polymarket price

Here’s a more up-to-date snapshot (Substack has a Polymarket integration!)

 

I have zero insight on geopolitics so I’m just going to offer thoughts on prices:

EDIT: The Polymarket prices updated from when this email post sent (a Sunday) and when I wrote it (Friday night)

  • The market thinks a strike is coming soon. March 31 is 64% and June 30 is only 68%. Conditional on a strike happening, the market implies 64/68 ~94% chance it happens before the end of March. You can buy June, sell March and only risk $4.
  • The dollar volume on these things is small but there are many papers supporting the “marginal trader hypothesis” that it only take a handful of active, well-informed traders to make a market more efficient. This is not suprising. If we played a mock trading game for even zero stakes it wouldn’t take long for you to see how quickly a market converges to a reasonable fair value.
  • The volatility risk premium across many liquid markets isn’t abnormal. The market either doesn’t care what oil and Polymarket says or a strike on Iran is not expected to have a material effect on the volatility of equity shares. However, defense names have implied vols in high percentiles (while PLTR vols are tanked btw)

Here’s my off-the-cuff impression of the 64% price:

The real odds are probably higher. If this contract were trading for say 10% I’d guess it was overestimating the true probability because of lotto-ticket bias but also because there needs to be a healthy risk premium for seller to enter a highly negative skew trade.

I wouldn’t guess that a bunch of yolo-punting puts a price to 64% for lolz. When someone bids 64%, they are laying odds. Betting nearly $2 to win $1. The price of this contract has doubled in a week…it’s the buyer who likely brings more caution to the order book now.

I could imagine someone buying these as part of a relative value trade against selling oil options but the dollars available means it would need to be retail size and that kind of trade (oil vega vs prediction market?!) doesn’t seem like the kind of thing that would excite the class of trader who expects 20x leverage on crypto perps to get them outta bed in the morning.

If Polymarket depth was big enough to influence stock markets, there’d probably be some interesting scenarios of incinerating a few million bucks, maybe less, to influence the Poly price so you can influence the price of defense stocks where you could make tens of millions. The informational and liquidity linkages between prediction markets and traditional markets will be fascinating (appalling?) to watch as they continue to grow.

 

Stay groovy

☮️

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