Trading firms are Rand-pilled cloisters of libertarianism.
Is it a self-serving post-hoc rationalization of meitrocracy that allows rich traders to not only enjoy wealth but virtue? Ha ha, sorry folks, not today. I’m ain’t gonna bait myself into this discussion.
I’m just going to leave you with a couple thoughts to turn over at your own pace.
When I was a trainee I remember an argument by a senior colleague who, as was typical, a market-maximilist who argued that teachers are probably overpaid, not underpaid as a fixed price will weed out everyone who knows they are worth more and therefore you structurally select for those worth less on average. Your best case scenario is the price and talent are exactly matched. It’s basically the same argument for why buffet restaurants are bad business. It only selects for eaters who see the price as a good value.
To be honest, I think I’m giving the colleagues’ argument some grace. I don’t remember it being as cosmetically coherent as mine. His argument gestured in the general direction of “markets are right”. That the price of teachers is not set by a free market doesn’t seem to have found its way into the discussion. Details, details. This person is very rich today and extremely sharp on topics like trading and business, so you know, just another reminder that high aptitude in one area doesn’t easily transfer (whether it reflects natural cognitive silo-ing or motivated reasoning is yet another question.)
I’ve heard that a stereotypical view of wealth in many parts of the world is that if you’re rich you must have been corrupt or left a trail of bodies in your wake to amass wealth. In the US, wealth is virtue. Capitalism victory points. Evidence that you gave people something they wanted. A ledger of value creation.
My view is directionally American with wide error bars. There are a lot of rich people whose profit has been nothing but an unaccounted for externality. They got the benefit without bearing the cost. Tobacco is giving people what they want. But pardon me if I think gains from trying to get teenagers to become early addicts should not become wealth. I think even the oncologists who treat those “customers” would be willing to sacrifice the 5th bedroom in their house to not have this “value created.”
Markets are downstream of politics. Markets and law are inseparable constructs and US law is the product of either pure mob democracy (the proposition system in CA) or representative government, whereby a centralized agent, like a senator, is entrusted to, umm… do what they want, subject to the constraint of “get re-elected.”
If law is not a free market, neither are the markets that it rests on, notwithstanding the platonic inventions of libertarian fever dreams. My favorite example of this today is college athletes. They were always creating tremendous value. But one day they weren’t allowed to extract their share and the next they were swimming in NIL money. With the stroke of a pen, their bargaining position changed.
Wealth is not just a function of value creation. Its value creation times some bargaining position factor. And that factor is often political. From FCC spectrum to land to labor laws to unions to IP laws, from subsidy to censure, from Spotify to artists, from accredited investor laws to bank charters, from casino to prediction markets…it’s all infused with law which creates centralized nodes of outsize power to influence or corrupt.
This has always been my concern with wealth inequality. It’s not a normative or moral concern so much as an acknowledgement of social physics. Wealth is power and nobody believes anyone’s power should be unlimited. We watch as individuals’ wealth continues to climb to those of city-states distracted by talk of “greed” or “fair share”. That discourse travels well because it’s smoke. The fire is deeper in the walls.
The future is going to require more transparency than ever. Which should be available in the age of broadband, compute, and video. And yet we don’t trust our eyes and when we do, we disagree about what we see. The line between info and info hazard is blurring every day. It’s ironic that so much wealth has been created by liberating information, but that same wealth will be used to selectively control it.
Switching gears to wrap up…
As a practical matter, when you think about the work you do and how it improves people’s lives, recognize that it’s within a path-dependent, arbitrary system-level backdrop. You may create lots of value, but the rules have limited your bargaining position.
You can choose to make peace with it, fight to change the rules, find a way to express your talents in a more advantageous industry/company. But crying over it or arguing with the smug who say the invisible hand is giving you what you deserve will rot your heart. Face reality to deal with it.
I had a chance to join legends Jeff Ma and Rufus Peabody thanks to John Reeder! If you don’t already listen to Bet The Process, you might remember Jeff as the protagonist of Ben Mezrich’s Bringing Down The House (later adapted to the film 21). I Having the ringleader of the famous MIT blackjack team ask me a question about Catan strategy is not something I had on my podcast bingo card!
Money Angle
On Thursday was the first session of the Investment Beginnings Class I spun up locally.
Identify 5-10 companies in 3 industries and report on what their margins are and the average margins in the industry based on your research. The open-endedness of this question is a feature not a bug. Let’s see what they come up with.
⭐I strongly recommend playing with the spreadsheet to explore the lender and equity investor results if we had rolled “bankruptcy”. Stepping through the formulas is a valuable exercise!
This introductory lesson opens with a question:
What can you do? What can go wrong? What’s your best-case scenario?
Then pose a new question…
From there, the lesson begins…
There were 18 youths, mostly 12-17 years old, and a bunch of interested parents as well.
The next session will be in a few weeks, I’ll share the materials as we go along and consolidate it all on this page:
In the spirit of spaced repetition, I published The Gamma of Levered ETFs as an article on X. Seemed relevant given silver’s 30% selloff on Friday.
Here’s the short version of the math of levered ETFs. To maintain the mandated exposure the amount of $$ worth of reference asset they need to trade at the close of the business day is
x(x - 1) * percent change in the reference asset * prior day AUM
where x = leverage factor
examples of x:
x=2 double long
x=-1 inverse ETF
x= 3 triple long
x= -2 double inverse
Applying this to silver:
AGQ, the ProShares Ultra Silver ETF, is 2x long. It had ~$4.5B in assets at the close on Thursday.
For the underlying swap to maintain the mandated exposure, at the close of Friday (assuming no redemptions) the swap provider must trade silver. How much of it?
2(2-1) * -30% * $4.5B
or -60% of $4.5B.
-$2.7B worth of silver in forced flows. Negative = sell.
There’s an UltraShort 2x ETF, ZSL, that had about $300mm of AUM going into Friday.
Rebalance trade:
-2(-2-1) * -30% * $300mm = –$540mm
Assuming no redemptions, these levered ETFs needed to sell ~$3.25B worth of silver into the close.
In a typical environment, silver volumes are mostly split between London’s spot market (LBMA) and COMEX futures (NY deliverable) with Shanghai (SHFE), India (MCX) and SLV (London deliverable, US traded ETF) combining for less than 10% of total volumes.
At the NY close, SLV and COMEX represent all the liquidity that’s open.
Claude
COMEX futures traded nearly $150B of volume Friday and SLV traded ~$50B which is on the order of 10x the dollar volumes silver used to trade a year ago at lower prices. Still, those forced sales, if they are happening in the few hours of trading may represent something like 5-10% of the liquidity.
I’m guessing readers who are actually on metals desks have a better guess.
Silver futures margins, after being raised again this week, are about 15% of the contract value (although your broker may ask for more. IB asks for twice that, which was prescient!)
If Shanghai futures, which were closed, have a similar requirement, that means the exchange doesn’t have enough collateral to cover the 30% move if Shanghai futures match the COMEX move.
I don’t know how that exchange works (many exchanges have an insurance pool where some of the losses are socialized across clearing members), but one thing that would be interesting is if Shanghai exchange officials have the authority, balance sheet, and ability to have sold COMEX futures as a hedge. I doubt that, it’s just a speculative musing, but if such a thing did happen, their Sunday evening unwind trade would be to buy back COMEX futures as they liquidated Shanghai holders. Again, this is just a ridiculous musing, but I look forward to seeing how it all shakes out.
In any case, I think a useful takeaway from all this could be to add expected levered rebalancing flows to your dashboards (of course, this is a recursive problem because the price at any point in time reflects some people’s knowledge of these flows. Pre-positioning always opens the door to backfiring if enough arbs think the same way).
In the spirit of spaced repetition, I published The Gamma of Levered ETFs as an article on X. Seemed relevant given silver’s 30% selloff on Friday.
Here’s the short version of the math of levered ETFs. To maintain the mandated exposure the amount of $$ worth of reference asset they need to trade at the close of the business day is
x(x - 1) * percent change in the reference asset * prior day AUM
where x = leverage factor
examples of x:
x=2 double long
x=-1 inverse ETF
x= 3 triple long
x= -2 double inverse
Applying this to silver:
AGQ, the ProShares Ultra Silver ETF, is 2x long. It had ~$4.5B in assets at the close on Thursday.
For the underlying swap to maintain the mandated exposure, at the close of Friday (assuming no redemptions) the swap provider must trade silver. How much of it?
2(2-1) * -30% * $4.5B
or -60% of $4.5B.
-$2.7B worth of silver in forced flows. Negative = sell.
There’s an UltraShort 2x ETF, ZSL, that had about $300mm of AUM going into Friday.
Rebalance trade:
-2(-2-1) * -30% * $300mm = –$540mm
Assuming no redemptions, these levered ETFs needed to sell ~$3.25B worth of silver into the close.
In a typical environment, silver volumes are mostly split between London’s spot market (LBMA) and COMEX futures (NY deliverable) with Shanghai (SHFE), India (MCX) and SLV (London deliverable, US traded ETF) combining for less than 10% of total volumes.
At the NY close, SLV and COMEX represent all the liquidity that’s open.
Claude
COMEX futures traded nearly $150B of volume Friday and SLV traded ~$50B which is on the order of 10x the dollar volumes silver used to trade a year ago at lower prices. Still, those forced sales, if they are happening in the few hours of trading may represent something like 5-10% of the liquidity.
I’m guessing readers who are actually on metals desks have a better guess.
Silver futures margins, after being raised again this week, are about 15% of the contract value (although your broker may ask for more. IB asks for twice that, which was prescient!)
If Shanghai futures, which were closed, have a similar requirement, that means the exchange doesn’t have enough collateral to cover the 30% move if Shanghai futures match the COMEX move.
I don’t know how that exchange works (many exchanges have an insurance pool where some of the losses are socialized across clearing members), but one thing that would be interesting is if Shanghai exchange officials have the authority, balance sheet, and ability to have sold COMEX futures as a hedge. I doubt that, it’s just a speculative musing, but if such a thing did happen, their Sunday evening unwind trade would be to buy back COMEX futures as they liquidated Shanghai holders. Again, this is just a ridiculous musing, but I look forward to seeing how it all shakes out.
In any case, I think a useful takeaway from all this could be to add expected levered rebalancing flows to your dashboards (of course, this is a recursive problem because the price at any point in time reflects some people’s knowledge of these flows. Pre-positioning always opens the door to backfiring if enough arbs think the same way).
Trading firms are Rand-pilled cloisters of libertarianism.
Is it a self-serving post-hoc rationalization of meitrocracy that allows rich traders to not only enjoy wealth but virtue? Ha ha, sorry folks, not today. I’m ain’t gonna bait myself into this discussion.
I’m just going to leave you with a couple thoughts to turn over at your own pace.
When I was a trainee I remember an argument by a senior colleague who, as was typical, a market-maximilist who argued that teachers are probably overpaid, not underpaid as a fixed price will weed out everyone who knows they are worth more and therefore you structurally select for those worth less on average. Your best-case scenario is the price and talent are exactly matched. It’s basically the same argument for why buffet restaurants are bad business. It only selects for eaters who see the price as a good value.
To be honest, I think I’m giving the colleagues’ argument some grace. I don’t remember it being as cosmetically coherent as mine. His argument gestured in the general direction of “markets are right”. That the price of teachers is not set by a free market doesn’t seem to have found its way into the discussion. Details, details. This person is very rich today and extremely sharp on topics like trading and business, so you know, just another reminder that high aptitude in one area doesn’t easily transfer (whether it reflects natural cognitive silo-ing or motivated reasoning is yet another question.)
I’ve heard that a stereotypical view of wealth in many parts of the world is that if you’re rich you must have been corrupt or left a trail of bodies in your wake to amass wealth. In the US, wealth is virtue. Capitalism victory points. Evidence that you gave people something they wanted. A ledger of value creation.
My view is directionally American with wide error bars. There are a lot of rich people whose profit has been nothing but an unaccounted for externality. They got the benefit without bearing the cost. Tobacco is giving people what they want. But pardon me if I think gains from trying to get teenagers to become early addicts should not become wealth. I think even the oncologists who treat those “customers” would be willing to sacrifice the 5th bedroom in their house to not have this “value created.”
Markets are downstream of politics. Markets and law are inseparable constructs and US law is the product of either pure mob democracy (the proposition system in CA) or representative government, whereby a centralized agent, like a senator, is entrusted to, umm… do what they want, subject to the constraint of “get re-elected.”
If law is not a free market, neither are the markets that it rests on, notwithstanding the platonic inventions of libertarian fever dreams. My favorite example of this today is college athletes. They were always creating tremendous value. But one day they weren’t allowed to extract their share and the next they were swimming in NIL money. With the stroke of a pen, their bargaining position changed.
Wealth is not just a function of value creation. Its value creation times some bargaining position factor. And that factor is often political. From FCC spectrum to land to labor laws to unions to IP laws, from subsidy to censure, from Spotify to artists, from accredited investor laws to bank charters, from casino to prediction markets…it’s all infused with law which creates centralized nodes of outsize power to influence or corrupt.
This has always been my concern with wealth inequality. It’s not a normative or moral concern so much as an acknowledgement of social physics. Wealth is power and nobody believes anyone’s power should be unlimited. We watch as individuals’ wealth continues to climb to those of city-states distracted by talk of “greed” or “fair share”. That discourse travels well because it’s smoke. The fire is deeper in the walls.
The future is going to require more transparency than ever. Which should be available in the age of broadband, compute, and video. And yet we don’t trust our eyes and when we do, we disagree about what we see. The line between info and info hazard is blurring every day. It’s ironic that so much wealth has been created by liberating information, but that same wealth will be used to selectively control it.
Switching gears to wrap up…
As a practical matter, when you think about the work you do and how it improves people’s lives, recognize that it’s within a path-dependent, arbitrary system-level backdrop. You may create lots of value, but the rules have limited your bargaining position.
You can choose to make peace with it, fight to change the rules, find a way to express your talents in a more advantageous industry/company. But crying over it or arguing with the smug who say the invisible hand is giving you what you deserve will rot your heart. Face reality to deal with it.
Today is about option execution. It’s a blanket response to a host of misunderstandings I find in talking to investing practitioners who don’t come from the market-making side.
Before that we’ll cover a couple things I found interesting.
If you’ve been paying attention to the options world, you know that the last 5 years have seen both a massive increase in retail participation which coincided with the very successful product launch known as 0dte.
A friend with a senior role at a MM has described the last few years as “money raining from the sky”.
In fact, I’m going to be meta and write about this post because of its pedagogical value. Rob saw a situation in the wild, turned it into a real-life word problem, and solved it. We’re going to step through what was unsaid because that process would be helpful to learners who want to get better at recognizing the nature of a problem and constructing a solution.
Excerpt from the intro:
There has been some controversy on X/Twitter about ‘pay to play’ prop shops (see this thread and this one) and in particular Raen Trading. It’s fair to say the industry has a bad name, and perhaps this is unfairly tarnishing what may pass for good actors in this space. It’s also perhaps fair to say that many of those criticising these firms, including myself, aren’t as familiar with that part of the trading industry and our ignorance could be problematic.
But putting all that aside, a question I thought I would try and answer is this – How hard is it to actually pass one of these challenges?
The rules of the Raen challenge are this:
You must make 20%
You can’t lose more than 2% in a single day. There is no maximum trailing drawdown. So if you lose 1.99% every day forever, you’re still in the game.
You must trade for at least 30 trading days before passing the challenge
It costs $300 a month to do the challenge. This isn’t exactly the same Raen which charges a little more, but as a rounder number it makes it easier to directly see how many months we expect to take by backing out from the cost per month. I assume this is paid at the start of the month.
His post is totally free. You should read it. But I want to branch from this point where he laid out the rules of the challenge.
The first thing you need to recognize
To even begin answering the question of how it is to pass the challenge you need to state it in terms of “how hard is it to pass given some [expected daily return] and [volatility]?”
Since the variables of concern are return and volatility, or reward vs risk, the concept of a Sharpe ratio immediately comes to mind.
If you have an expected daily return of 20% with 0% volatility, then your chance of success is obviously 100%. That’s an infinite (undefined?) SR.
If you are even remotely near the investing world you probably have some sense that the SP500 has something like a .5 SR and an SR of something like 2 would be very high. If SP500 is 15% vol, then you are talking about an investment with SP500 vol but gets you 30% per year. You do that for an extended period of time and everyone knows your name.
We can make a reasonable matrix of values for our 2 values of interest.
Since giving a go at trading involves work and buying SPY does not, then having a SR greater than .50 to warrant the effort sounds table stakes. Any number from 1.0 to 2.0 feels like an appropriate starting point, even if it’s arbitrary. Rob starts with 1.5. Fine.
very sophisticated table
Restating the problem:
If you have a Sharpe Ratio of 1.5 and trade with 15% annual volatility, what’s your chance of passing a funded trader challenge that requires:
Hitting 20% profit
Without any single day losing more than 2%
While paying $300/month
Rob recognizes that this is best solved with a simulation, but that’s actually an enlightened reflex. Let’s not take it for granted.
Could you solve this with math in a closed-form way?
Let’s try to solve this with formulas. What we can assume:
Daily returns ~ Normal(μ, σ) where:
μ = (SR × Vol) / 252 = (1.5 × 0.15) / 252 = 0.0893% per day
σ = Vol / √252 = 0.15 / √252 = 0.945% per day
Question 1: How long to reach 20%?
Simple approach: 20% / 0.0893% = 224 days
Hmm. This seems wrong for several reasons:
You don’t go straight up
The bust-out rule: any day < -2% resets you
We need to bring volatility and path dependency into consideration. We ask another question.
Question 2: Probability of hitting -2% on any given day?
Question 3: What’s the probability of reaching 20% before hitting -2%?
The lyrics to Steppenwolf’s Pusher come to mind:
tombstones in my eyes
I have no idea how you solve this analytically.
Fortunately, this question comes to mind 5000 years since Indian mathematicians invented Arabic numerals and 3 years since Anthropic released the tireless teacher known as Claude.
It (he? she? they?) says:
This is a “gambler’s ruin” problem with two absorbing barriers: +20% (win) and one day at -2% (lose), but after bust-out, you reset to 0% and try again!
He goes on to explain that solving this problem analytically requires:
Estimated Learning Time: 1-2 years of graduate-level probability theory
Oh.
It’s gonna take more effort than watching a Veritasium at 2x speed? Bruh, I don’t have cave time on my hands here.
I assume Rob reacted to this trading challenge word problem like a linebacker diagnosing pass vs run in a split second. This is a problem for simulation.
Anyway, I just thought it would be helpful to explicate the unsaid.
And one las thing. Since Rob was generous enough to post his code, I made Claude work overtime for no pay (inner monologue: does this mean I would’ve owned slaves 400 years ago?). Claude’s yield:
While stock execution is a vast topic depending on how finicky you want to be about HFT, microstructure, game theory, counterfactuals, lit vs dark, block trading, etc etc, most institutional algos coalesce around some concept of VWAP or TWAP where the goal is to minimize market impact by making sure you are not an outsize percentage of the volume.
Option execution has no equivalently popular Schelling point benchmark such as a VWAP. This is partly because option premiums are themselves moving targets depending on the interplay of time, implied volatility, and moneyness. This is not a big issue, you could harmonize measurements in any number of ways including by the greeks. You’ll get some sense of how we can do that below. But the fact that you can pay more for an option but be purchasing a lower IV is hint enough that VWAP-ing according to premium is incoherent.
The biggest issue is that the intent of an option order has a different time horizon from a typical stock order. If you are an investor, you probably don’t care that it takes 3 days to accumulate your position as long as there are no catalysts in the execution window. But options, when used as they should be, with a basis in volatility assessment (in other words, discernment of the magnitude of a move over a certain period of time), naturally require more time-sensitive execution.
Options are also less liquid, especially outside the top 50 names or so. Given the sheer number of expiries, strikes and symbols, it is far more likely you are selling the 62 DTE, .24 delta call against a market-maker rather than someone else who woke up that morning thinking they’d like to invest that particular option. This means, you want to minimize your encounters with the order book so even if you could VWAP your order, if the counterparty is a MM you are far more likely to be leaking info that you have an order big enough to make piecing it out worthwhile. This information can and will be used against you.
The best you can do with respect to option execution is not be stupid. Your order is easy to spot. It’s the one whose limit doesn’t tick with the stock (we’ll address counters to this below!). You are always going to lose to your execution in expectation. You can tattoo that on your face. We’ll shed some light on what’s happening on those screens.
Edge functions
At any snapshot in time, market-makers have a fair value for what an option is worth. They stream a bid/ask whose width depends on an “edge function”. The general specification for this function is “how many cents of edge to I need to compensate me for hedging the delta and the vol risk”?
Delta risk
If I believe that buying 100,000 shares of stock XYZ will push it up 8 cents from the current stock offer, then I need to pad my option offer in the .25 delta call by $.02 just to breakeven on expected slippage on selling 1000 options. Note that the offer I’m streaming is not using “last sale” or “mid-market” as the S in the option model. It’s using “stock ask”. The call bid I’m streaming, is using the “stock bid” since I will be selling shares to hedge if I buy calls. You can step through this exercise yourself for put bids and put offers.
Vol risk
Let’s say this same option has a vega of $.10 meaning if IV increases by 1 point, the option premium, all else equal, goes up by $.10.
If this is an asset whose IV moves about 1 point per day, I might be fine accepting something like 1/2 a vol point of edge or $.05 cents to open a position. If the IV moves 10 points a day I’ll demand $.50 per contract to compensate me for the vega risk.
So at the very least, the bid/ask spread reflects the market maker’s willingness to warehouse the vol risk and there cost to hedge at the point of sale. Of course, a multitude of dealers with differing fair values and leans creates a tighter market than if there is only a handful.
If the market is more volatile, then slippage assumptions increase not just becasue the underlying shares are wider, but because there will be less liquidity at each price level. The consumer should expect wider spreads. Volatility itself will also more volatile. Again, wider spreads.
Edge functions are a tax on all option-related strategies when markets get crazy. Including strategies that are biased long vol but generally takers. They still need to trade. Edge functions are like COGs. Market-makers’ costs, including their funding spreads, are passed on to everyone else.
Order types
Like stocks, there are limit and market orders in options. But there is a class of contingent orders that makes sense in light of option premiums being moving targets.
Delta-adjusted orders
A delta-adjusted order may take the form of:
“If the stock is $100.50 bid or higher, I’m willing to offer the 99 put as low as $.50”
You can even peg the offer to the stock bid so that it keeps cancel/replacing according to its delta (so if it is .25 delta, every time the stock drops 4 cents your offer increases a penny) down to some ultimate low premium you’d accept.
You can even “auto-hedge” this type of order. So if you get filled on the puts, it triggers an order to sell or short shares on the bid subject to some tolerance. If the stock moves lower quickly after you sell the puts the auto-hedger will have parameters that you set about how far to “chase”. This is important because you should expect to get filled on the puts when the stock drops quickly and a market-maker snipes your stale offer before your broker has a chance to pull.
In other words, your fills are constant reminders of adverse selection. I’ve explained this in the broader discussion of limit orders:
My Bayesian analysis of being filled on a limit order vs market order
Imagine a 1 penny-wide bid/ask.
If you bid for a stock with a limit order your minimum loss is 1/2 the bid-ask spread. Frequently you have just lost half a cent as you only get filled when fair value ticks down by a penny (assuming the market maker needs 1/2 cent edge to trade). But if you are bidding, and super bearish news hits the tape (or god forbid your posting limit orders just before the FOMC or DOE announce economic or oil inventory), your buy might be bad by a dollar before you can read the headline.
If you lift an offer with an aggressive limit (don’t use market order which a computer translates at “fill me at any price” which is something no human has ever meant), then your maximum and most likely loss scenario is 1/2 the bid-ask spread.
Do you see the logical asymmetry conditional on being filled?
Passive bid: best case scenario is losing 1/2 cent
Aggressive bid: worst case scenario is losing 1/2 cent
This is why exchanges offer rebates for posting bids/offers — the payment incentivizes liquidity which nobody would ever offer otherwise because of adverse selection concerns. When you are not a market-maker you have the luxury of “laying in the weeds” until you spot the “wrong” price and then strike.
Vol-adjusted orders
This is an order that pegs your option bid or ask to a model implied vol. So if you are 25% vol offer in that 99 put your offer will adjust upwards if the stock goes down, or lower as the stock rallies. It sounds like a delta-adjusted order but it’s slightly different in that the delta adjusted order has no concept of theta embedded in it.
For example, the vol-adjusted offer will automatically accept a lower price at the end of the day vs the start of the day since a 25% vol option is worth less after time passes.
The delta-adjusted order relies on some underlying model’s delta for price adjustments but it’s not affected by the passage of time (well, technically there is some modest charm effect as time passing infuences delta). A delta-adjusted offer will tend to drift away from being marketable as time passes and theta kicks in, as you are effectively offering a higher IV. Likewise, a delta adjusted bid will become more marketable as time passes which effectively means you are bidding a higher volatility. The vol-adjusted order solves this, but lets the premium float (although these order types can sometimes allow additional constraints).
In general, these types of orders try to limit the adverse selection you are guaranteed when you place an ordinary limit order in options, where you only get filled when the stock moves against you. In fact these are the order types market makers themselves use for streaming logic.
More advanced considerations: “Mark to cross section”
This is one I’ve never seen anyone talk about but it’s obvious once I point it out.
Suppose you are working a large bid using a vol order. You want to pay 25% IV for the 40 strike in XYZ. It’s chipping away little by little and then suddenly you are filled on the entire thing at an average of 24.9% vol.
How do you feel?
Like you always feel when you get filled fast. Like the position is what your one-night stand partner looks like in the morning light. You can’t chew your own arm off fast enough to get out of it.
The first thing you’ll check is whether you got picked off because the stock gapped. But you find the stock hasn’t done anything weird. And then you notice a different chart on your dashboard…
The VIX futures have collapsed in the last 30 minutes.
The reason you got filled on your vega is that vol is much lower across the market. And this doesn’t show up in conventional execution metrics like mark-to-arrival. In fact, you got filled better than your vol limit of 25%.
Your order was recognized and when it was clear that vol was much lower, that any number of vols across the market were a good relative buy compared to what you were bidding, the market maker said “Yours”.
In other words, you wish you could mark your fills to the cross-section of other vols in the marketplace (or at the very least maybe VIX or SPY vol).
This is a whole other layer of attribution. If you sold a basket of vols but SP500 vol was down far more than your basket, do you feel good about your vol-picking skills?
It’s the same issue in active investment management. It’s a waste of time to earn beta. You need to outperform on a risk-adjusted basis to justify effort and identify skill.
Discussion
There isn’t so much a solution to execution as there is an understanding of the levers to think about what approaches work best for you.
At the end of the day, there is a price to entice someone else to warehouse a risk they didn’t wake up asking for. You are trying to execute at the lowest price that satisfies that threshold. Every cent you pay above that threshold is additional surplus to the market-maker above the minimum they require.
You can put out feeler orders on small size to probe how far into the bid-ask they are willing to execute. You are sussing out their edge function. It’s not foolproof. They understand that it’s not worth it to give up that information for small size. They may allow a high stale bid to sit because if they hit it they make a negligible amount of expectancy but what if they leave it there?
Let’s make this concrete with a simple, highly stylized example. An option is worth $1.00, and there’s an opaque distribution around where the next bid might come in, centered at $1.00 ± $0.04. If a one-lot bid comes in for $1.01, the market maker earns one cent in expectancy by hitting it.
But now there’s some chance that the next bid is higher than $1.01. And while that probability is below 50%, the expected bid conditional on waiting may actually be higher than it would have been had the $1.01 bid never appeared. And it might be for a larger size. Depending on what that distribution looks like, the market maker may have more “pot equity” in letting the market remain framed as-is rather than pasting a bid for a single contract.
The more liquid a name is, the less room there is for such games. If it’s highly liquid, there will be enough mm or customer flow to just whack that one lot stray.
The question is always, will I get a better average price in vol terms* if I hit or lift, vs going slowly and giving away info so that the screens mold to me. If trading against your order increases a market-maker’s inventory, they will pad their edge functions even more. If it decreases their inventory, then you probably want more market participants to see it so that it hastens their built-in desire to trade against you. If you want a bidding war for your flow, then you want to make sure everyone sees it. Be more inclined to “advertise” it by showing it as opposed to using electronic eyes (delta orders that are hidden and snipe when a marketable order appears against it).
[*Again, practice proper benchmarking. If I get a good price on my order to buy calls, it could be because the stock fell over the window when I was accumulating them, but on a delta-adjusted basis I could have been getting worse fills on the way down. In other words, I paid more in IV terms.]
Improving execution, to find the minimum edge that someone will accept to trade with you, is a hard problem. At a minimum, I’m trying to help you conceptualize the problem better with respect to adverse selection and the basic hygiene of benchmarking aspects of your fill due to vol changes vs delta. Execution is a classic domain where people do “resulting” where they let their outcomes adjudicate whether they made good decisions. The problem is hard enough without inviting that particular mistake to dinner.
My wife Yinh pinged Khe to see if he’d host a seminar for people interested in getting more mileage out of AI. He agreed (and texted me separately with “I’m sure you know this already, but your wife is a force of nature”…Oh, I’m quite aware).
She emails 60 friends and associates, inviting them to this session. She got 40 affirmatives by the next time she checked her email. As she told me by text, “everyone feels like a boomer”.
I’m not going to spend time speculating on AI futures but it’s hard to not realize that sources of value are shifting beneath our feet. AI could have written a lot of my technical posts. It wouldn’t have been in my voice, and insofar as my written voice has some entertainment or organic attraction, it’s not the same quality. But it would convey much of the instrumental information content and at far lower cost.
To paraphrase a tweet I can’t find anymore (I gave Grok 2 chances but no dice) from a lifelong software developer: I used to pride myself on solving tricky problems and finding elegant solutions and watching LLMs do this instantly has rattled my sense of self-worth.
A lot of value-added work in the past is commoditized. Without speculating on futures, I only invite you to prompt yourself, “how much of the work I do is truly unique?”
There’s an ongoing whole layer of AI-enabled automation creep that we’ll embrace, I’m not talking about that.
Aside: The latest one I’ve appreciated is the Gemini summaries that sit on top of long email threads:
I’m talking about the increasing automation of formerly complex tasks that we actually hang our hats on. My voice is the organic part of the writing. But what’s that even worth relative to the content? A doctor’s job is a mix of inference and bedside manner. What’s the relative value of these things? If you are in sales, how much of your cycle has to do with trust and a firm handshake versus data persuasion and storytelling. What will AI lower the cost of, not just for you, but for competitors? It’s the Innovator’s Dilemma in homine.
You squeeze one part of the balloon and the air bulges into another part. It’s like the “commoditize the complement” thinking in product strategy.
This article by Jon Matzner is a good example of updating your models hard in the face of re-structured inputs:
The Only Cost I Want to Go Up
Where does the value go? What are your sunk costs? What is a trapped asset or idea that is now tenable? These types of questions were always relevant, but the speed at which they are coming at us in a wide-open frontier is only precedented at major inflections of general-purpose technology. A relatively recent example on the timeline of innovation is Netflix knowing long before it became a streaming-first company that streaming was the future, but broadband needed to catch up. The AI inflection is a confusing sandstorm rapidly covering old monuments while revealing new spaces to build. Anyone paying attention can feel it. Hence, the FOMO response to Yinh’s email.
I can write a description of a bug in Linear or Jira (who am I kidding — I upload a screenshot with a blurb and have AI write a detailed bug spec complete with testing protocol) and assign it to…”Claude bot”. A dev approves the change. Push to prod.
Tools I use
Claude Code with Opus 4.5 on a Max plan ($100/m)
Gemini Pro ($16/m)
ChatGPT Plus ($20/m. This is really Yinh’s but I use it sometimes. Don’t tell.)
NotebookLM when I want an audio summary of lengthy text. Sometimes I will give it a bunch of notes and have it generate a podcast conversation about them which can help me find connections or through-lines that outlining doesn’t. Something about hearing vs hearing I guess. I could get to the same place sparring with a text-based LLM but this way I can do it while walking or in a less taxing way. Or sometimes because I need to just let some material wash over me.
A service (in stealth at the moment) that connects to any data source including the moontower options database that’s hyper-tuned for inference. An example I’m messing with now is something I call VCR or Variance Contribution Ratio. What percentage of the realized variance in a list of assets in some window came from N% of days. You can ask it a question like that and it will come back with all kinds of ideas, charts, insights. It’s an intern that skips the photosynthesis→food→brain power+senses drivetrain altogether and just runs on sending electricty through a recipe trained loop that our ancestors have run through many times before. Progress. Suicide. Both. I don’t know, I’m just an ape with a lever.
Comments
I was using Terragon as an agent that can talk to my github repos as well as deploy to vercel but Claude has replaced all this workflow. Similarly, Claude has replaced my usage of Copilot in VSCode.
I find the native MSFT Copilot in Excel to be trash. I haven’t used Claude for Excel yet. I have found the Claude Chrome extension in the browser to be helpful with Google sheets.
More broadly, Claude and Gemini browser tools are still clunky in some contexts (“port this substack post to my wordpress site”) and useful in others especially within your email. “Give me a list of all the people who reached out asking about XYZ” or “go find the loan agreement document with entity X and compute the accrued interest according to its provisions through today”.
Silo’d projects I’m currently using AI for
As a matter of procedure, I use Projects folders within Claude to compartmentalize initiatives. You can upload lots of files to the project for context and then have a limitless number of chats within the project itself all dealing with different aspects. I like to tell Claude to consolidate what I’ve accomplished or learned from individual sessions and then I feed that back into a living document in the files section so its always handy to the bot for future chats. These documents also include feedback about directions Claude took that I didn’t like. I don’t know what reinforcement learning is mathematically but the process feels like manual training.
Here’s a few things I’m working on:
Investment Idea Generation
Agent reads investment letter email, generate a bullish/bearish template that considers the author’s sentiment, timing, etc, which can automatically be fed another agent connected to moontower.ai infra to see how it accords with option surfaces. Another agent then presents the output. In an advanced form this is becoming part of the product itself, capable of generating watchlists and so forth. (I’m more interested in the pipeline at the moment. The business end of it would be more complex since there’s author IP involved).
Status: very early…need to get email agent running
Mooncoin Option Trading game [skunkworks name for now]
This is less agentic and more LLM conversation about gameflow. However, Claude Code was integral to helping me style.
Status: Ready for a second round of playtesting to pin down the concept. Long way from a final product but can start playtesting over Zoom!
Current screenshots:
Trading Quizzes
One of my projects is setup as a RAG with about 70 articles. I’m having Claude devise interactive quizzes that give learners a chance to practice their option knowledge. Varies from beginner to more advanced.
Status: early and promising. A few rounds of iteration so far on a tranche of concepts where I’m training the LLM to know what I consider a good question. From there I will extend it to more tranches of material and if that goes well I know have a custom quiz maker for any material I give it. I’ve been heartened by some of the angles it’s taken on questions — it definitely comes up with stuff I wouldn’t have. The median quality can be higher, so still more to do. I’m not sure how much of the meta of making a good question I’m going to succeed in relaying but that’s part of the fun.
Money Angle
In the late aughts, one of my family members had a side-hustle while getting his Masters where he’d post ads on Craigslist offering to help people with their Excel work. People were willing to pay a lot more for this than I expected.
He told me why.
It was people who somehow ended up with Excel-heavy jobs without knowing how to use Excel. He was quite literally doing their jobs for them. In finance terms, he was the layoff account where his client was a bank trading desk arbing their customer (the employer) and he was picking up the juicy scraps.
Claude in Excel is an add-in that integrates Claude into your Excel workflow. It’s designed for professionals who work extensively with spreadsheets, particularly in financial analysis and modeling.
With Claude in Excel, you can:
With Claude in Excel, you can:
Ask questions about your workbook and get answers with cell-level citations
Update assumptions while preserving formula dependencies
Debug errors and identify their root causes
Build new models or fill existing templates
Navigate complex multi-tab workbooks seamlessly
Money Angle For Masochists
Today is for the younger masochists (and their overseers).
I’m going to start an investment beginnings class locally. There’s a few things at the end of this section you can use. If it inspires you to do something similar or have ideas, let ‘er rip!
Around 15 people signed up. I’ll see how the experiment goes and report back as it evolves.
This is the email I sent to the families:
We recently opened up a brokerage account for our 12-year-old, Zak so he could start investing in some stocks he’s interested in. I want to give him a more structured foundation and since this scales easily to a group, I figured I’d open it up to family and friends.
What it is: A hands-on class where we learn by doing – looking up real securities, building spreadsheets, understanding how markets work, and developing the kind of financial instincts that serve you for life. The goal is to make sure participants aren’t suckers and start with good financial hygiene.
The approach: Participants will be treated as capable people who can figure things out. We will get comfortable working at the edge of what we know how to do, wherever that may be – Googling, LLM’ing, excel formulas (and we can get into heavier automation/coding if there is appetite), troubleshooting, and being resourceful. If this inspires ambition, we can go further. Other than building an object-level understanding of investing, the dual goal is to earn the type of confidence that only comes from competence and its prerequisite — persistence. This will feel harder than school.
Format: Sessions in front of a room with a projector. Each participant will need a laptop to follow along. We’ll use real tools and real data. (I’ve asked a company to sponsor this by giving us free licenses to their tools, but we’ll see if that comes through. There are plenty of open-source resources that will work.)
Who it’s for: Anyone 12 and up – young people and adults welcome. No prior knowledge needed. Participants will get maximum mileage if they have a brokerage account, but it’s not required.
Cost: Free. I’m doing this for Zak anyway.
Location: [redacted]
Schedule: TBD
Note: I will record sessions to share with remote friends who are interested by uploading as unlisted (undiscoverable but public) YouTube videos. Participation is implied consent to this.
Action items
If you’re interested or have questions, just reply. I’ll follow up once I have a sense of the group.
This is a very loose draft of the plan. I will prepare a lesson before each session (this week is the first) and update this document. As always, work-in-progress.
From My Actual Life
I’ve mentioned before that I coach both my boys CYO basketball teams (4th and 7th grade). The highlight of my past week was Zak’s (7th grade) game so I just want to share it.
Zak had a cold and a headache but we gave him some Advil and said to come root his team on. We were only going to have 5 players without him. He wore his uniform anyway in case he felt good enough to go and in pre-game shooting he said he could play.
The game was neck and neck. One of our players scored an unlikely basket off an offeensive rebound as the clock expired to send the game to overtime. It was shocking, everything about the rebound itself and making the layup from directly under the rim was unlikely.
We’re in OT, down by 2 with 5 seconds left. We intentionally foul. Our opponent misses both free throws. I was prepared to call timeout but Zak ripped the rebound and took off.
No point in calling the timeout since it wouldn’t advance the ball from our backcourt. Instinctually I liked our admittedly very slim chance better with him one on one against a chaser.
Well, he makes it to the 3-pt line, the chaser jumps pass him as he hesiatated for moment, and just put the shot up as the clock is expiring.
Swish.
We win by 1. The team mobs him. Because it’s an overtime game and these things are on tight schedules all the people there for the following game are watching and the whole place jumps.
It’s a meaningless 7th grade CYO game but it was a unique moment. We joked that it was his Jordan flu game.
Anyway, that win happened to clinch 1st place in our division but we had already clinched a playoff spot so it wasn’t integral. We wrap the regular season today and have playoffs in 2 weeks.
(I’ve already went to watch the team will most likely draw from the other division. They have a kid that’s 5’9 and one that’s 6’0. Zak is 5’4 and one of our bigger kids 🫣)
One of the best reasons to write online, which I hadn’t anticipated when I started, was to “find the others”. The people who make you feel less alone in your thoughts. The ones taking the same crazy pills as you, whose minds wander the same alleys.
David Fu is one of those people for me. We bump into each other at the intersections of education, games, and the type of idealism we should have long outgrown. He pings me last week with an email subject:
watched this pod and thought of mathlete vs mathematician
If we live in a world that hyper awards those with power and those willing to cut out their humanity and hyperfocus on the explicit measure (win math competitions, win status and prestige games like getting into Stanford) then we should expect to get a world in which the people who have the most power to communicate and control things are the people who have been most willing to slash out their humanity and hyperfocus
Sociopaths are running the asylum and I’m still stuck on how we got here, so ok, you got my attention. I open the YouTube link.
Dork f’n Christmas.
It’s an interview with C. Thi Nguyen!
Nguyen is a philosophy professor at the University of Utah with a focus on games. Not game theory but theorizing on games. His first book Games: Agency as Art (my notes) is amazing, but I don’t recommend it unless you are in the market for an academic treatise on the philosophy of games.
Nguyen’s interview with Sean Carroll 5 years ago is still one of my favorites (my notes), so I was stoked to settle in to this one.
It delivers.
Turns out he has a new book and if that wasn’t self-recommending enough, I was delighted to see Dan Davies write:
If you liked “The Unaccountability Machine” and you got a book token for Christmas, spend it on “The Score” by C Thi Nguyen. I haven’t seen an advance copy or anything, but I met the author at a conference and he’s extremely funny and clever. I will be trying to promote the book to as many business podcasts as possible, because I very much think that this is a case in which the dead hand of academic analytical philosophy may have robbed the world of one of its greatest management consultants.
Dan’s another author whose powers of observation are galactic, so I’m getting a lot of convergence on healthy brain food.
I’ll leave you with some of my favorite excerpts:
Hobbes, Power, and Defining Reality
What Hobbes says is that the ultimate power is not military or economic power. It is the power to define terms and control language. If you control language and define terms, you control people from the inside.
Games are like artificial governments. They’re things where we play around with incentives and rules and constraints to shape people’s action.
When someone says, ‘Here’s a watch. It measures your health,’ and if you accept that, you’re letting somebody else define what health means for you—typically in what’s easy for one of their devices to measure cheaply.
Value Capture (Core Concept)
Value capture is any case where your values are rich or subtle or in the process of developing that way and you get put in an institutional setting and that institutional setting offers you a simplified—typically quantified—version of that value, and then that simplified version starts to take over your conception of good…It’s not just an incentive. It’s when you start to care about the metric as the thing itself.
Law School Rankings and the Death of Deliberation
Before rankings, colleges described their missions in totally different languages—money, research, activism, community. Students had to deliberate about what they cared about.
The moment U.S. News and World Report started issuing rankings, students stopped talking about what they wanted and started assuming that ‘best’ was whatever the ranking said.
You’re outsourcing not just your values, but the process of deliberation about your values.
Bernard Suits and what a game actually is
Bernard Suits defines a game as the voluntary attempt to overcome unnecessary obstacles. In ordinary practical life, the outcome is valuable on its own, so you try to get it as efficiently as possible. But in games, the value is inseparable from the obstacles themselves.
If the goal of basketball were just to pass the ball through the net, you’d use a ladder at night with no opponents. But that’s stupid — because the value of making a basket is intrinsically tied to dribbling, jumping, shooting, and resistance. Whatever the value is, it’s in the process, not the outcome… And when you hyper-optimize for winning, you destroy the spirit of the game.
Why metrics are fun in games — and dangerous elsewhere
The articulation of a metric has clarity, and that clarity is incredibly powerful over us. The best way to talk about this is to explain what metrics do for us in games — and then why that’s okay in games and not okay elsewhere… Games are this incredibly interesting art form where someone designs a new self for you. A game designer tells you what to want, how to pursue it, and what constraints you have, and suddenly you become a different kind of being — a being of feet, or balance, or precision.
What makes games so beautiful is their simplicity and clarity. We all have the same goal. It’s blissfully clear what a good move is… But that same clarity lets us outsource a complicated judgment about ourselves. The system says: I will let you know when you’re doing great. And the danger is that the clarity of a metric can keep us playing even when it makes us miserable.
Goal vs purpose
One of the most important distinctions in thinking about games is the difference between the goal of a game and your purpose in playing the game. The goal is the target you’re trying to hit. The purpose is why you play at all… For some people, the goal and the purpose collapse into one thing — winning. I call these achievement players. But for a lot of us, there’s a deep difference.
The easiest place to see this is party games. In party games, the goal is to win, but the purpose is to have fun. You have to try to win for the game to work, but if everyone had a great time and you lost, you’d be ridiculous to feel bad about it… The larger purpose has clearly been fulfilled.
Rock climbing is another good example for me. I love rock climbing. I am a terrible rock climber. I am mediocre beyond belief… The goal of rock climbing is to get up the rock. But the purpose, for me, is the beauty of movement and the clarity of mind it gives me. It’s one of the only things that actually gets my brain to shut up.
What’s interesting is that I cannot get that feeling without trying to win — without genuinely trying to complete the climb. But it also doesn’t matter if I fail all day. I leave feeling good. My body feels good. My mind feels cleansed.
When you have the right attitude toward games, you keep goal and purpose separate. The game tells you the goal. You choose the game for your own purposes… And that separation is a huge dimension of freedom that we often don’t have with metrics.
The gap between what matters and what’s measurable
The thing to get really interested in is the gap between what’s really important and what’s easy to measure institutionally. ‘Likes’ claim to represent communicative value. Steps and VO₂ max claim to represent health. And when those representations are too thin, they don’t just miss what matters — they actively change it.
Qualitative understanding is rich, subtle, and context-sensitive, but it travels badly. Quantitative knowledge works by isolating a context-invariant kernel — something everyone can understand — and stripping away nuance so it can move easily between institutions. The problem isn’t that data is bad. It’s that we reach for it compulsively, even when it’s inappropriate.
Recipes, accessibility, and the loss of judgment, and the “facade of objectivity”
The facade of objectivity as well that this folds into. It’s this notion that we are also being sold this actively sold this by tech companies as well as our governments as if this metric data-driven system is also democratizing, it is populist it is access expanding… but what you’re describing is the thing that I think I have felt and have been frustrated by which is the decline in the value of expertise of editorial judgement of human decision
Old recipes don’t say “two cups of flour.” They say things like “add water until it feels just under sticky.” That’s actually a very good recipe — if you know what you’re doing… Modern recipes give you accessibility. Anyone can follow them. But what they take away is the cue to adapt and use judgment.
Metrics are that for values. They tell you something anyone can use and understand. And accessibility isn’t bad — but there’s a price. And the price is expertise.
When data is genuinely good — and when it turns on us
Large-scale data is really good at optimizing for things that are easy to count. It’s why I am alive and why my child is alive. Not dying of an asthma attack is a very clear target, and data is incredibly good at that.
It’s also incredibly good at debiasing. If an institution is convinced it isn’t biased, numbers are often the only thing that can knock the door down. You can point and say: look, women are getting the same scores, but you’re hiring men nine times as often… That clarity is powerful.
But then you move decades forward. And what you start to see is those same data-driven approaches getting thinned down into numerical quotas and proxies that miss the heart of what they were meant to fix… The system that was good at breaking down the door becomes the system everyone optimizes against.
Data-based approaches are very good at the blunt stuff. And then, over time, they tend to miss the subtle stuff — while capturing everyone’s attention. People start gaming the metric. Institutions start optimizing the proxy. And the thing that actually mattered quietly slips out of view.
Metrics are best at targeting what everyone can count easily together. And the uncomfortable question is how much of what makes life meaningful is actually easy to count together… Because if power accrues to those willing to hyperfocus on the explicit measure and cut out everything else, then we should expect a world run by people who have been willing to slash away parts of their humanity in order to win.
Metrics, Shame, and Modern Power
Historically, the guardrail was shame—‘you’re not fun to play with.’…Shame has never felt less effective than it does right now. We live in a system where the green arrow going up and to the right is the only thing that matters.
…and then there’s this little exchange with a very 90s thought. Where “sell-out” was an insult instead of the goal of a person’s life.
Pablo:When I was growing up, obviously, I knew there were like popular things, but it was not as if I read an article or read a book and had my view of it informed by how many other people simultaneously were doing that…We all feel the way in which stuff is worse. It’s hard for me to say that it’s disconnected from the entire conversation we’ve been having.
One of my takes that I have for the new year, popularity will become uncool. And I say that just because we are all watching the mechanisms of what it is to get all of the views and all of the likes and all of the retweets, right? And I just think we’re due for a movement that we’ve seen before, by the way, in which pop culture becomes uncool. And I just think that that is it’s just one of these things that feels like we’re ripe for.
Nguyen (shooting it down): Yeah. Unless that gets captured and large-scale forces successfully gain this sense of uncoolenness and manage to [garbled]. Like punk points. What happened with punk? It became pop punk, right? Some people resisted and were like screw popularity and then large-scale forces figured out how to game that, market that, and we got, you know, “top” alternative radio.
[Random bit I just noticed: Nguyen teaches at University of Utah. Another one of my favorite thinkers and conversation partners, Robert Wuebker, teaches there. I may need to make a field trip to this Utah place.]
In Thursday’s paid subs post, embedding spot-vol correlation in option deltas, I buried this story but I thought worth sharing since it’s broadly suggestive of what happens when you list options on an investments touted as worth being in your asset allocation:
I started in commodity options just before the listing of electronic options markets. When I first stepped into the trading ring, many market-makers were still using paper sheets. We had spreadsheets on a tablet computer, but heard of a fledgling software called Whentech. Its founder, Dave Wender, was an options trader who saw the opportunity. I demo’d the product, and despite it being a glorified spreadsheet, it centralized a lot of busy work. It had an extensive library of option models and it was integrated with the exchange’s security master so its “sheets” were customized to the asset you wanted to trade.
I started using it right away. Since it was a small company, I was able to have lots of access to Dave with whom I’ve remained friends. I even helped with some of their calculations (weighted gamma was my most important contribution). I was a customer up until I left full-time trading. [Dave sold the company to the ICE in the early 2010s. It’s been called ICE Option Analytics or IOA for over a decade.]
The product evolved closely with the markets themselves. Its nomenclature even became the lingua franca of the floor. Everyone would refer to the daily implied move as a “breakeven” or the amount you needed the futures to move to breakeven on your gamma (most market-makers were long gamma). Breakeven was a field in the option model. Ari Pine’s twitter name is a callback to those days. Commodity traders didn’t even speak in terms of vols. They spoke of breakevens expanding and contracting.
What does this history have to do with a spot-vol correlation parameter?
This period of time, mid-aughts, was special in the oil markets. It was the decade of China’s hypergrowth. The commodity super-cycle. Exxon becoming the largest company in the world. (Today, energy’s share of the SPY is a tiny fraction of what it was 20 years ago.)
Oil options were booming along with open interest in “paper barrels” as Goldman carried on about commodities as an asset class. But what comes with financialization and passive investing?
Option selling. Especially calls.
Absent any political turmoil, resting call offers piled on the order books, vol coming in on every uptick as the futures climbed higher throughout the decade.
A little option theory goes a long way. Holding time and vol constant, what determines the price of an ATM straddle?
The underlying price itself: S
straddle = .8 * S *σ√T
If the market rallies 1%, you expect the straddle price at the new ATM strike to be 1% higher than the ATM straddle when the futures were lower. Since the “breakeven” is just the straddle / 16, you expect the breakeven to also expand by 1%.
But that’s not what was happening.
The breakevens would stay roughly the same as the market moved up and down.
If the breakevens stay the same, that means if the futures go up 1%, then the vol must be falling by 1% (ie 30 vol falling to 29.7 vol)
It dawned us. Our deltas are wrong.
If we are long vol, we need to be net long delta to actually be flat.
When your risk manager says why are you long delta and you explain “I need to lean long” to actually be flat, you can imagine the next question:
“Ok then, how many futures do you need to be extra long for this fudge factor?”
We need to bake this directly into the model because it’s getting hard to keep track of. Every asset and even every expiry within each asset seems to have different sensitivities between vol and spot. The risk report can’t be covered in asterisks detailing thumb-in-the-air trader leans.
Whentech listened. Whentech introduced a new skew model that allowed traders to specify a slope parameter that dictated the path of ATM IV. Their approach was simple and numerical…
I want to expand briefly on Wednesday’s HOOD: A Case Study in “Renting the Straddle”because HOOD’s implied volatility that contains earnings actually declined for the rest of the week and disentangling that is a good chance to reinforce your understanding.
On Wednesday, Feb 13th HOOD vol (which encompasses earnings on Feb 10) lifted a bit from when I wrote the post. We’ll call it 68% IV.
To make 68% IV fit smoothly with the non-earnings vols from the preceding expirations, we need to assume an earnings move that allow the ex-earnings vol to be ~56%
That corresponds to about a 9.5% earnings move (a bit higher than the average move of 8.55% for the past 8 quarters).
This table shows implied trading day IVs net of various-sized expected earnings moves.
Let’s tie this idea back to theta or option time decay.
A one-day move of 9.5% corresponds to a single-day implied vol of ~119%
9.5% / .80 = 119%
This comes from remembering that an ATM straddle is 80% of the implied vol
As you approach the earnings day, the implied vol of the option will be dominated by the fact that the stock is expected to move 9.5%. Therefore, we know the implied vol is going to increase.
We think of theta as “how much value the option loses as time passes” but because we know that vol is going to steadily rise, we can conclude that the actual experience of theta is going to be much less than the model says. The model doesn’t “know” the implied vol is going to increase, but you do.
As vol increases, the option will gain value that offsets some of the theta. It won’t offset all the theta. If it did, then you would just buy all the options today, have free gamma for a month, and sell them right before earnings.
So much of the theta will be offset?
We can answer this if we hold our assumptions constant:
trading day IV is 56%
earnings move is 9.5%
(I added the assumption that the earnings date is also the expiration date. It’s stark that all the theta we defer happens on the last day.
You can see how the vega offsets part of the theta.
Just like with any option, the theta still accelerates as you approach expiry but at a slow rate (theta is left axis).
All the theta happens at the end.
Oh, as a matter of pragmatism, I should add that HOOD option markets are wide. And yet there’s millions of contracts of open interest! Amazing for market makers. To quote Alanis…isn’t that ironic?
1) You can do anything if you put your mind to it” is a lie.
If your last name is McCaffery, you have a chance of engineering elite athletes. If you are an Abdelmessih, you’ll be waiting for the metaverse for the sensation of what a 4.3 40 feels like.
2) You are currently very far from your ceiling.
You can drive a truck through the gap between these 2 ideas so they are not really in conflict.
To let the first disappoint you is to let perfection thwart the good. The cost of this pedantically true statement is self-defeat. It’s the kind of victory only an intellectual would recognize because it’s familiar territory — an unnatural use of technicalities to excuse failure because they define success as adherence to fine print. It’s a strange inversion of “It’s better to be roughly right than precisely wrong”. They are precisely right but roughly wrong, but the wrongness touches their life ceaselessly and in the most material ways.
To let the second statement disappoint you is known as a “start”. Congratulations. Recognition is the first step. This should be obvious, but the path to improvement starts by realizing there’s room for it. In you. Not in the world changing such that your conditions are improved, but for you to improve your station, with a smiling indifference to a world you can’t control anyway.
But I stay “start” because beginnings are sensitive to expectations. If you start anything expecting it to be easy, you will likely not finish. It’s such a simple observation, but it bears a life-changing load. It means that anything you are serious about doing should start with the expectation that it will test your resolve, so when the moment comes, you are not hit with the double indignity of difficulty but also surprise.
And one of those negative surprises always comes from others. Haters. But haters also come from people who don’t actually hate you. They may even love you. But this is how they deal with being disappointed in themselves.
This is not an easy subject. It’s at the root of how everyone relates to everyone else. It’s wrapped up in status, luck, a sense of narrow justice when it has to do with the promotion at work, and global justice in the sense of being born on third (or America…although whether the runner is heading home or to second is today’s “dress” debate).
It’s not as easy as saying “ignore everyone else”. There’s a scammer in jail or even just a common internet grifter who dismissed sober advice from someone they respect who they dismissed as speaking behind a veil of risk-aversion. Or less scandalous scenarios like “I’m dropping out of school to pursue acting”.
It’s a good idea to consider the judgement of those you are certain love you. But even then you need to grade them on a curve based on their own risk bias which takes some judgement of your own. Parents want to see their adult children on solid ground. If you win an Oscar and they get to walk the red carpet, that’s just gravy. That will never be in their calculus. But it might be in yours. They’re running a max-min strategy, you want to win the tournament.
So if you should consider the judgment of loved ones and even then with skepticism, you know who you should definitely ignore? Randos and water-cooler friends. There’s just too much at stake.
I posted this on X in a thread where Ryan was parrying haters.
When it comes to haters its useful to remember that the correct retaliation is nothing but apathy which if the detractor was smart in the first place, they would realize that themselves. What’s that line about hate being like drinking poison and expecting the other person to die?
Hate seems like ultimate confession of weakness.
It’s very rare that anyone changes anyone else’s mind. Unlearning hurts.
The internet fools us because when life’s most important moments happen, your world shrinks. The volume on everything turns down, and you are left with a few people. The hater? Might as well be an atom in another galaxy. Why would they occur to you?
Attention is everything. Lots of people on here give you the gift of permitting yourself to ignore them. Accept it gratefully
Scott Adams, the Dilbert cartoonist, died this week after a battle with prostate cancer. He’s a politicized figure (Scott Alexander’s memorial post is a bizarre mix of tribute and psychoanalysis). But like many others, I’ve read his work on career advice and even the thought experiment book “God’s Debris” which I remember precisely nothing about. But I did see a quote from it this week, which I strongly agree with:
“People think they follow advice but they don’t. Humans are only capable of receiving information. They create their own advice. If you seek to influence someone, don’t waste time giving advice. You can change only what people know, not what they do.”
1) You can do anything if you put your mind to it” is a lie.
If your last name is McCaffery, you have a chance of engineering elite athletes. If you are an Abdelmessih, you’ll be waiting for the metaverse for the sensation of what a 4.3 40 feels like.
2) You are currently very far from your ceiling.
You can drive a truck through the gap between these 2 ideas so they are not really in conflict.
To let the first disappoint you is to let perfection thwart the good. The cost of this pedantically true statement is self-defeat. It’s the kind of victory only an intellectual would recognize because it’s familiar territory — an unnatural use of technicalities to excuse failure because they define success as adherence to fine print. It’s a strange inversion of “It’s better to be roughly right than precisely wrong”. They are precisely right but roughly wrong, but the wrongness touches their life ceaselessly and in the most material ways.
To let the second statement disappoint you is known as a “start”. Congratulations. Recognition is the first step. This should be obvious, but the path to improvement starts by realizing there’s room for it. In you. Not in the world changing such that your conditions are improved, but for you to improve your station, with a smiling indifference to a world you can’t control anyway.
But I stay “start” because beginnings are sensitive to expectations. If you start anything expecting it to be easy, you will likely not finish. It’s such a simple observation, but it bears a life-changing load. It means that anything you are serious about doing should start with the expectation that it will test your resolve, so when the moment comes, you are not hit with the double indignity of difficulty but also surprise.
And one of those negative surprises always comes from others. Haters. But haters also come from people who don’t actually hate you. They may even love you. But this is how they deal with being disappointed in themselves.
This is not an easy subject. It’s at the root of how everyone relates to everyone else. It’s wrapped up in status, luck, a sense of narrow justice when it has to do with the promotion at work, and global justice in the sense of being born on third (or America…although whether the runner is heading home or to second is today’s “dress” debate).
It’s not as easy as saying “ignore everyone else”. There’s a scammer in jail or even just a common internet grifter who dismissed sober advice from someone they respect who they dismissed as speaking behind a veil of risk-aversion. Or less scandalous scenarios like “I’m dropping out of school to pursue acting”.
It’s a good idea to consider the judgement of those you are certain love you. But even then you need to grade them on a curve based on their own risk bias which takes some judgement of your own. Parents want to see their adult children on solid ground. If you win an Oscar and they get to walk the red carpet, that’s just gravy. That will never be in their calculus. But it might be in yours. They’re running a max-min strategy, you want to win the tournament.
So if you should consider the judgment of loved ones and even then with skepticism, you know who you should definitely ignore? Randos and water-cooler friends. There’s just too much at stake.
I posted this on X in a thread where Ryan was parrying haters.
When it comes to haters its useful to remember that the correct retaliation is nothing but apathy which if the detractor was smart in the first place, they would realize that themselves. What’s that line about hate being like drinking poison and expecting the other person to die?
Hate seems like ultimate confession of weakness.
It’s very rare that anyone changes anyone else’s mind. Unlearning hurts.
The internet fools us because when life’s most important moments happen, your world shrinks. The volume on everything turns down, and you are left with a few people. The hater? Might as well be an atom in another galaxy. Why would they occur to you?
Attention is everything. Lots of people on here give you the gift of permitting yourself to ignore them. Accept it gratefully
Scott Adams, the Dilbert cartoonist, died this week after a battle with prostate cancer. He’s a politicized figure (Scott Alexander’s memorial post is a bizarre mix of tribute and psychoanalysis). But like many others, I’ve read his work on career advice and even the thought experiment book “God’s Debris” which I remember precisely nothing about. But I did see a quote from it this week, which I strongly agree with:
“People think they follow advice but they don’t. Humans are only capable of receiving information. They create their own advice. If you seek to influence someone, don’t waste time giving advice. You can change only what people know, not what they do.”
Money Angle
I want to expand briefly on Wednesday’s HOOD: A Case Study in “Renting the Straddle”because HOOD’s implied volatility that contains earnings actually declined for the rest of the week and disentangling that is a good chance to reinforce your understanding.
On Wednesday, Feb 13th HOOD vol (which encompasses earnings on Feb 10) lifted a bit from when I wrote the post. We’ll call it 68% IV.
To make 68% IV fit smoothly with the non-earnings vols from the preceding expirations, we need to assume an earnings move that allow the ex-earnings vol to be ~56%
That corresponds to about a 9.5% earnings move (a bit higher than the average move of 8.55% for the past 8 quarters).
This table shows implied trading day IVs net of various-sized expected earnings moves.
Let’s tie this idea back to theta or option time decay.
A one-day move of 9.5% corresponds to a single-day implied vol of ~119%
9.5% / .80 = 119%
This comes from remembering that an ATM straddle is 80% of the implied vol
As you approach the earnings day, the implied vol of the option will be dominated by the fact that the stock is expected to move 9.5%. Therefore, we know the implied vol is going to increase.
We think of theta as “how much value the option loses as time passes” but because we know that vol is going to steadily rise, we can conclude that the actual experience of theta is going to be much less than the model says. The model doesn’t “know” the implied vol is going to increase, but you do.
As vol increases, the option will gain value that offsets some of the theta. It won’t offset all the theta. If it did, then you would just buy all the options today, have free gamma for a month, and sell them right before earnings.
So much of the theta will be offset?
We can answer this if we hold our assumptions constant:
trading day IV is 56%
earnings move is 9.5%
(I added the assumption that the earnings date is also the expiration date. It’s stark that all the theta we defer happens on the last day.
You can see how the vega offsets part of the theta.
Just like with any option, the theta still accelerates as you approach expiry but at a slow rate (theta is left axis).
All the theta happens at the end.
Oh, as a matter of pragmatism, I should add that HOOD option markets are wide. And yet there’s millions of contracts of open interest! Amazing for market makers. To quote Alanis…isn’t that ironic?
Money Angle For Masochists
In Thursday’s paid subs post, embedding spot-vol correlation in option deltas, I buried this story but I thought worth sharing since it’s broadly suggestive of what happens when you list options on an investments touted as worth being in your asset allocation:
I started in commodity options just before the listing of electronic options markets. When I first stepped into the trading ring, many market-makers were still using paper sheets. We had spreadsheets on a tablet computer, but heard of a fledgling software called Whentech. Its founder, Dave Wender, was an options trader who saw the opportunity. I demo’d the product, and despite it being a glorified spreadsheet, it centralized a lot of busy work. It had an extensive library of option models and it was integrated with the exchange’s security master so its “sheets” were customized to the asset you wanted to trade.
I started using it right away. Since it was a small company, I was able to have lots of access to Dave with whom I’ve remained friends. I even helped with some of their calculations (weighted gamma was my most important contribution). I was a customer up until I left full-time trading. [Dave sold the company to the ICE in the early 2010s. It’s been called ICE Option Analytics or IOA for over a decade.]
The product evolved closely with the markets themselves. Its nomenclature even became the lingua franca of the floor. Everyone would refer to the daily implied move as a “breakeven” or the amount you needed the futures to move to breakeven on your gamma (most market-makers were long gamma). Breakeven was a field in the option model. Ari Pine’s twitter name is a callback to those days. Commodity traders didn’t even speak in terms of vols. They spoke of breakevens expanding and contracting.
What does this history have to do with a spot-vol correlation parameter?
This period of time, mid-aughts, was special in the oil markets. It was the decade of China’s hypergrowth. The commodity super-cycle. Exxon becoming the largest company in the world. (Today, energy’s share of the SPY is a tiny fraction of what it was 20 years ago.)
Oil options were booming along with open interest in “paper barrels” as Goldman carried on about commodities as an asset class. But what comes with financialization and passive investing?
Option selling. Especially calls.
Absent any political turmoil, resting call offers piled on the order books, vol coming in on every uptick as the futures climbed higher throughout the decade.
A little option theory goes a long way. Holding time and vol constant, what determines the price of an ATM straddle?
The underlying price itself: S
straddle = .8 * S *σ√T
If the market rallies 1%, you expect the straddle price at the new ATM strike to be 1% higher than the ATM straddle when the futures were lower. Since the “breakeven” is just the straddle / 16, you expect the breakeven to also expand by 1%.
But that’s not what was happening.
The breakevens would stay roughly the same as the market moved up and down.
If the breakevens stay the same, that means if the futures go up 1%, then the vol must be falling by 1% (ie 30 vol falling to 29.7 vol)
It dawned us. Our deltas are wrong.
If we are long vol, we need to be net long delta to actually be flat.
When your risk manager says why are you long delta and you explain “I need to lean long” to actually be flat, you can imagine the next question:
“Ok then, how many futures do you need to be extra long for this fudge factor?”
We need to bake this directly into the model because it’s getting hard to keep track of. Every asset and even every expiry within each asset seems to have different sensitivities between vol and spot. The risk report can’t be covered in asterisks detailing thumb-in-the-air trader leans.
Whentech listened. Whentech introduced a new skew model that allowed traders to specify a slope parameter that dictated the path of ATM IV. Their approach was simple and numerical…
From My Actual Life
I definitely have more couch potato tendencies in the winter. I’m currently watching Mad Men (for the first time!) I’m almost finished with Season 2 which means I like it.
I recommend the movie Eden on Netflix. Go into it knowing nothing. That’s how I went in (Yinh said let’s watch some movie called Eden and I said ok knowing nothing else). I’m so out of touch sometimes, we were a quarter of the way through the movie before I said “Isn’t that Jude Law?”
It’s definitiely one of those movies where right after you finish it, you’re googling “how true were the events in [movie title]?”
Wednesday night was the first time I ever went to a Cal game which is kinda pathetic since I’ve lived less than 20 minutes from Berkeley for over a decade now. But St. Mary’s College usually has a better hoops team, is even closer, and has a much smaller arena. It’s more of a gym than a venue.
Cal was able to hang with the Blue Devils for the first half before Duke started being Duke.
So many nepo babies in the game. Marbury’s son was is a sophomore walk-on for Cal (he’s only played 5 minutes all season though), Justin Pippen is Cal’s starting PG as a sophomore, and the freshman Boozer twins play for Duke (although only the 6’9” one sees the court. 6’4” bro MIA). The taller Boozer is a force. Much savvier than you might expect from a freshman big.
Duke brought out some local celebs. We didn’t see them, but Steph and Del Curry were there with family. We did see these guys one of whom’s life is basically a victory lap. Getting dapped up every 3 seconds, everyone taking selfies with him. You can decide who I’m talking about:
