First order of business…this week moontower.ai launched Workflows.
About Workflows
A quick reminder of how option enjoyyyyers are sorted into 2 camps.
Camp 1: Investors who start with an opinion on a stock. They go to the option chain to express it and accept the posted price as fair. This is the vast majority of option users. Using options for delta or possibly “income” which still maintains a delta.
Camp 2: Vol traders invert the process. They’ll concede the stock is priced about right, since that’s not the skill they bank on. Instead, their discernment goes into the derivatives where they search for relative value of contracts on the volatility surface.
Moontower originates from camp #2, but our new Workflows feature is to serve camp #1.
There’s 3 suites, each one is organized around an intent that drives your screening process married to the Moontower lens for finding value.
Income is for selling covered calls and cash-secured puts.
➡️ Introducing Income Workflows
Defensive is for buying protection, or replacing a long position with calls or spreads.
➡️Introducing Defensive Workflows
Collars is for investors willing to finance protection by selling some of their upside.
➡️Introducing Collar Workflows
You posts explain each suite in more detail but we built them after talking to clients about their specific processes. The interface will be intuitive based on how investors usually screen for these ideas except our opinionated analytics are quickly narrowing and sorting to accelerate your workflow. Hence the name.
“Income”
We use the word “income” only because that’s what the investor community recognizes. File that in the marketing hall of fame next to calling death insurance “life insurance”.
The focus on premium without a consideration for what it gives up is like talking about the price of anything without considering the value received. At worst, an investor sells calls without considering whether the option is cheap or expensive which is understandable. The knowledge and the tooling to answer that question have never been simple. Investors will default to non-vol-aware heuristics like sorting for the highest premium or sorting for the highest implied vol. Sure, you’ll find the option “which option costs the most”, but not “which option is most expensive.”
Most investors understand that a high P/E stock isn’t expensive if the earnings are compounding fast enough to deserve it. They understand that a low P/E stock can be a “value trap”. The options market is capable of the same distinctions with respect to option premiums.
Workflows pull together pieces of the vol surface and the stock’s own behavior to compare the relative value of options across names. The lens is entirely cross-sectional. Whether it’s your watchlist, a sector, or your portfolio of names vol surfaces are scored to one another based on what’s typical and what’s not in the current market in addition to considering the names own history.
Workflows acts like a cheat sheet but if you want more control every screener filters on any column, groups by any column, and carries a long roster of columns beyond the ones we show first. Intersect our scores with whatever your process already leans on : what IV has done in the past week, a correlation limit, how realized volatility is changing, how many standard deviations a stock is from its moving average, and so on.
We’ve preloaded a set of house screens (see the individual posts) but you can build and save your own.
In short, the value prop is whether you invest for your own account, advise clients, or just want to see the options market from the perspective of your intentions, you’ll spend less time assembling the picture and more time deciding what to do about it.
This is the call-to-action part: Sign up
Seriously, it’s bad-ass.
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a talk I gave at a quant bootcamp
I’ve praised Ricki Heicklen’s Arbor trading bootcamp countlessly over the past few years. I’ve recommended it, sent my friend’s son to it as he was entering college, been a student in that room and this past winter, a speaker.
The bootcamp reminds me of how lazy my own thinking can get. That reasoning and decision-making are practices. It also reminds me that I’m a midwit. I’m definitely the dumbest person in the room, but I can hide that behind crystallized knowledge and experience. I have perspective that comes from simply having had a lot more cycles to think about certain topics, and it is from that position that I conjured a talk that could actually get the whizzes in the room’s attention.
The setting is casual and kind so I took the flatteringly favorable feedback with a grain of salt but not so much that I wouldn’t recycle it here.
I hope you enjoy this talk I gave at the Arbor bootcamp (and thanks to the Arbor team for recording it!)
[I expect to be at the next bootcamp Oct 9-12 in SF which btw is my favorite time of year in SF weather-wise. It’s also Fleet Week. Nothing like watching the Blue Angels fly over the marina and all the ships in the Bay. I don’t know if Ricki planned it to sync up but either way it’s a bonus for everyone.]
Transcript
Options Then and Now — Talk at Trade Boot Camp
Kris Abdelmessih, founder of Moontower, speaking to Trade Boot Camp students. AI Transcript lightly edited for readability; phrasing preserved.
Introduction
Host: Kris is one of the most prolific writers I know. He writes posts about markets at a faster rate than I can read posts — even if my full-time job was just reading the stuff he writes. And it is so extremely useful for a person who is wading their feet into trying to understand options and a lot of different markets, to be able to access those things. He goes through examples, he goes through different models of things. He has a blog called Moontower, and also moontower.ai, which has a bunch of useful tools for understanding how options as well as other asset classes can be priced or thought about and reasoned about.
In addition to that, he’s spoken in a bunch of different contexts. And most importantly, he spoke here at Trade Boot Camp a year and a bit ago last November. And on a personal note, he’s been a mentor to me and to Ross over the past year — really helpful on us thinking about both the question of what would be some successful potential business decisions, but also what do we want to do and who do we want to be, being role models to our kids, making decisions and trade-offs when it comes to big numbers of dollars and how we spend our time and education and what really matters in this world.
So if you guys get just a tiny drop of the wisdom that we’ve managed to squeeze out of Kris in the past year and a half of knowing him, then I will feel like you are incredibly lucky, and lucky to have me help facilitate that gift to you. All right Kris, take us away.
Part 1: Options Then and Now
Kris: Thanks to all of you for giving me a little bit of time here, and hopefully I can pass along a little crystallized knowledge to all of your fluid intelligences. That’s about the phase that I’m at right now.
A little about me
I started at SIG in 2000. I went to Cornell for my undergrad, joined SIG as a floor trader, did a lot of different things for them — equity options trading, index options trading, ETFs, market making. I was a specialist on the New York Stock Exchange in ETFs. Then around 2005 I started their floor business for oil options trading on the NYMEX floor. Ran that for about three years, then I left, got a backer, started my own market making group, eventually hiring another partner and a few people. Ran that for about four years.
Then I moved to California in 2012, where I built out the commodity vol trading business for Parallax, which was equity vol trading only at the time. I was sort of like the first alternative strategy they brought on. They’re actually based here in San Francisco. I left in 2021, and since then I’ve been making software and writing a lot more than I used to. I started writing in my Parallax days, but writing a lot more these days. That’s my career in a nutshell.
Four exchanges, colored jackets, and fractions
So the title of this talk on our shared spreadsheet was “Options Then and Now.” I’m going to spend like three minutes on that — which is really just to say thank you, that’s very nice. I also feel like I’m wave one, and you guys are wave two who see all the steps.
When I joined SIG, I started on the floor of the AMEX in 2000. Back then it was four option exchanges only: the AMEX, the PCX (Pacific), the CBOE, and the PHLX. And options were single-listed. What does single-listed mean? It means if you wanted to trade options on QQQ — by the way, QQQ was brand new, SPY was brand new; the first place I clerked was for the guy that made markets in SPY, the stock itself. Like there were people that used to stand on a floor and make markets in the ETF itself. It wasn’t even options. So my first clerking position was for a person who did that. This is how new a lot of this stuff was.
So if you wanted to trade QQQ options, you could only trade them on the AMEX. You could send an electronic order at the time, but a lot of order flow was done through a broker — you call up a broker, the broker’s on the trading floor, runs into the crowd and says, “How’s the 45 calls expiring in January?”
Today, I think there’s 18 or 19 exchanges. Everything is incredibly electronic. Back then, if you just walked around the trading floor, you would have seen probably at least a hundred different colored jackets — all the firms wore these flannel smocks with your badge on them, and each firm had their color. Probably the most obvious thing to me that’s changed over the last 25 years is: if you were to throw all the people who are market makers in options today into a building and make them wear jackets of their firm, there would not be that many colored jackets anymore. The whole industry is massively consolidated.
Back then we traded in fractions. I started in the year they were changing over to decimals. In some ways that’s how long ago it was — but also, this is only a generation ago. Minimum increment was a sixteenth, which means your market was minimum 6.25 cents wide.
When I first started trading, somebody asked for a five-dollar-wide call spread market. We’re going to learn today about options, so if you don’t know what a call spread is, you’re going to learn about that today. If somebody quoted a five-dollar-wide call spread market and you thought it was worth $2.50, your market might have been 2.30 at 2.70. Today you’re 2.49 at 2.51. The business is massively tighter than it was. The margins are way, way thinner.
The skill set has changed
When I got hired, I had to answer probably 10 probability questions in my interviews. I’ll give you an example, and it’s probably going to feel incredibly remedial to you today. A question like:
You’re down by two. You have the ball at the end of the fourth quarter. Your three-point shooter has a 40% chance of making the shot. Your two-point shooter has a 50% chance of making the shot. If you go to overtime, you’re 50-50 to win the game. Who do you give the ball to?
Pretty simple little Markov question. That was the extent of it. I didn’t even know Excel when I got hired. It was a totally different landscape as far as what hiring was like. It was still competitive, but it was largely what I would call a bit of a misfit industry. If you walked around the trading floor, you were equally likely to have met some nepo Italian kid whose father owned a brokerage firm for the last 30 years, or the best chess player in the United States who couldn’t hold down a regular job because they’re just not cut out for a normal job. To become that person, you had to be a bit of a misfit. That was the trading floor — this weird gamut of everybody.
And this was just kind of part of the, whether you think Cornell’s Ivy League or not, I guess I was part of that first crop of people where it was like, “They’re hiring from good schools now.” Totally different landscape from the way it is today.
What else has changed? The pay is up 10x since I got hired. Starting pay — I got paid $37,000 my first year. Starting pay is more than 10x now, I think, for places like Optiver, Citadel Securities, these firms. Trading volumes are up about 20x. I think the average number of daily option contracts traded in 2000 was about 2 million a day. That number is over 40 million today. So volumes are up more than 20x, but like I said, margins are completely crushed. This is a very volume-scale business.
Headcount: when I got hired at SIG there were 800 people. I don’t know how many there are now, but my guess is about 3,000 is reasonable, maybe less. Jane Street is about 3,000. When I was there, I was employee number 1,000 — that was in 2019. My best guess is right now they’re between two and three thousand, but it’s not public information and I left a few years ago. So headcount is up, but not nearly as much as the pay is up.
Software eating the options world
The story of pay being up and the skill set changing — from being tall, loud, and fast at mental math to being able to code and do mathematics properly — the last math class I ever took in my life was Calc BC in high school, so it’s been a while. The skills are totally different now.
What’s happened is it’s a story of technology. It is the same story you see everywhere: software eating the world. The story of what happened in options trading is largely one of firms that basically plowed every dollar back into developing software systems. Those are the ones that you see today. The CapEx required is ultimately a Red Queen race — the CapEx required probably weeded a lot of people out.
Think about it: back then you were making a pretty good living trading options. A lot of people could retire pretty early. But do you really want to bet it all on trying to get to the next rung of the game? A lot of firms did not want to do that. Maybe they sold whatever technology or traders they had to existing firms.
The firms like SIG — a lot of the people I worked for were early Jane Street founders. Chen Dar from Jane Street is an ex-SIG guy. All the mathematics of index dispersion, index options trading, all of that stuff was developed inside SIG. The founder of Five Rings was my eye clerk in 2001. There was a whole — I always think about that era as a little bit like what Bell Labs was in the fifties. There was O’Connor, and SIG, and they kind of germinated all these other firms coming out of them. It was an interesting time to look back on. I had no idea — I didn’t understand it because I was young at the time — where I was. I didn’t understand this game of how technology was going to change, how all this reinvestment into technology was going to matter. The people who ran these firms were able to see the future a little bit and, I think, properly made all those investments.
Today they’re competing for the same talent that OpenAI and Meta and the Magnificent Seven are competing for. It’s the same talent pool. That’s why the pay looks the way it does. That’s why the skill set is what it is. Back then, if you were a top 5% student, you were probably going to do okay in your life. Today, you’re going to have to be a lot better than that to get into one of these firms — unless you’re like the top three people in math at Princeton, I’m not sure how much they care about you.
It’s a very, very different environment today because there’s so much leverage in being at the cutting edge of these things. You’re seeing it across the whole industry — the kind of crazy figures that people are paying at the top end. So it’s really a story about productivity gain. The lever is long. That’s the story of options trading in general.
Part 2: The Beauty of Options
But what I actually wanted to do — because I was looking at the schedule, today really is a full day of options stuff — is talk a little bit about the beauty of options.
I’m not an academic person. I came to my understanding of options through crazy amounts of experience. I’ve traded an outrageous number of options. When I was at Parallax, at one point I was trading 100,000 options a day — and that’s not even high frequency. The number of expirations I’ve been through, everything I’ve traded, it was all learning by doing. I have no formal background that should have said I could do any of this.
Having said that, having gone through the experience, it’s interesting to me to see options as a beautiful lens to look at all of finance. I’m almost retrofitting an academic lens to it, a language that’s not familiar to me but I’ve kind of come up with.
The Bridge of Asses
There’s a guy named James Somers. I don’t know if he’s still at Jane Street — you probably didn’t know him. He’s a coder who was at Jane Street and is also a fantastic writer. He sometimes publishes in The New Yorker.
A couple of years ago — November 2023, I don’t have it in front of me — he wrote a great article in The New Yorker called “A Coder Considers the Waning Days of the Craft.” This must have been the early days of LLMs, where he was starting to see what automation would look like. In the article he talks about his own learning paths arriving to becoming a developer, and he has this passage:
“Medieval students called the moment at which casual learners failed the pons asinorum — the Bridge of Asses. The term was inspired by Proposition 5 of Euclid’s Elements, the first truly difficult idea in that book.”
The proof in Proposition 5 is that in an isosceles triangle, the base angles are equal — and that if you extend the two equal sides downward, the exterior angles beneath the base are also equal.
Those who cross the bridge of that proof, you would be capable of going on to learn the more difficult stuff in geometry. Wikipedia defines pons asinorum as a metaphor for a problem or challenge that acts as a test of critical thinking — it separates the capable from the incapable reasoner.
As I read this, I thought to myself: what is the pons asinorum in finance? And I believe it’s arbitrage pricing theory. I basically think it’s options theory. To understand options theory is a passage into an entirely different way of seeing the world.
It might be an overdriven way of saying this, but Jeff Yass has said that you cannot actually understand decision making if you do not understand options theory. That’s a very pointy statement, but I’m just pointing out that there is probably something magical about thinking about options theory broadly — beyond just the formula in the context of it.
What I’m getting at is this: the conceptual rails of looking at a web of branching future payoffs, seeing how it can be replicated, and measuring the cost of that replicating portfolio today is the reasoning thing I’m talking about. It is the formalization, I think, of finance’s deepest truth: you cannot eradicate risk. You can only transform its shape. That is the lesson you will deeply get out of understanding options theory — the formalization of trade-offs.
Concept 1: Value Over Replacement
There are a few concepts inside options trading that are very interesting and extend beyond options. One is the formalization of opportunity cost — or as I sometimes think of it, Value Over Replacement. If anybody’s ever played fantasy sports, you’re familiar with VOR. It’s “what’s the replacement level cost, and how much value added is in the choice I’m making?”
Options theory deals with this very formally, because the cost of funding parameter in a replicating portfolio — the risk-free rate we use in Black-Scholes — is effectively a hurdle. In fact, the discovery that the risk-free rate is the right rate to use to discount your portfolio is an incredibly clever innovation.
The puzzle goes back to the early 1900s. The innovation Black and Scholes brought was this: if I can replicate an option, what is the right discount rate for the cash flows? Their answer was that it should be the risk-free rate, because the replicating portfolio for an option contract is going to be some amount of stock and some amount of bonds. If you price that portfolio’s cash flow at expiration and it should be the same as the option at expiration, there should be no risk in owning one (the option) and being short the other (the portfolio). If there’s no risk, the right discount rate for that combined position is the risk-free rate. That was the puzzle that people hadn’t figured out.
They’d been asking, “What is the right discount rate for a stock?” If you think about the Capital Asset Pricing Model, CAPM is a completely different framework. It says the right discount rate for a stock is a function of its volatility — if the stock moves twice as much as the S&P, it should offer twice as much return. There’s no grounding in that at all.
Arbitrage pricing is a completely different way of approaching the world. It says: what is the cost of the replication? And that is the right price for anything. The right price for a futures contract in one year is not what I think the price of the asset is going to be in one year. It’s simply: what’s the cash flow if I bought the asset today, stored it, and promised to deliver it in a year? The cash flow that falls out of that is the fair value of that future — nothing related to expectations. There’s nothing in here that requires me to have an opinion or a prediction about the future.
This concept of the replicating portfolio is so endemic to options theory, and it’s important.
Concept 2: Explore–Exploit and Optimal Stopping
Another interesting concept is the explore–exploit problem. The fun version is: how do you get a mate? You may have heard the rule of 37 — you have a sampling period where you say, “I’m going to date around and meet 20 people, figure out who the best was in that sample, and then I’m going to date around again, and the first person who comes along who is at least as good as the best person in my sample, I commit to them.” You basically use the 37th percentile as your cutoff. Of course, you don’t know how many people you’re going to date afterwards, so it’s not a very practical solution. I don’t recommend this if you’re in the market for a mate. But it’s an attempt to solve what’s called an optimal stopping problem.
How do you know when to stop exploring and commit? Where does this show up in options? It’s the optimal exercise of an American call. European-style options can’t be exercised until expiration, but American-style options — all our US equity options — can. Sometimes it’s optimal to exercise early. When? When the cash flow from doing so, in expectation, exceeds the value of the thing you’re giving up.
When you exercise a call on the strike, you’re giving up the put — the protection embedded in owning that same strike. If you think of a deep in-the-money call, if the stock goes to zero you eventually stop losing if you own a deep in-the-money call — you don’t participate all the way down. There’s a put embedded in your length from owning that option.
This decision of what you’re giving up and what is the right time to exercise is embedded very formally in options theory. That’s kind of interesting — the explore–exploit problem is right there. I’m no scholar on that problem, but what I’ve heard is that the problem is considered so complicated that they used to snipe their engineers from working on it instead of making bombs during the war.
Concept 3: Distributions
The third thing about options is the way they tell us about distributions. Here’s my example:
Two stocks are both trading at $100. All you see is that they’re both $100. But they’re $100 for two completely different reasons.
- Stock A is $100 because it’s 50% to be $80 and 50% to be $120.
- Stock B is $100 because it’s 90% to be $0 and 10% to be $1,000.
Think about a biotech stock before some FDA ruling. Both stocks have a binary distribution. The second has a very skewed distribution and is clearly higher volatility than the first.
If you’re looking at both of them as investments, how do you size them? How do you distinguish them? Well, if there were options listed on both, look at the 200 call.
- In Stock A, the 200 call is worthless. Zero bid at a penny.
- In Stock B, what’s the value of the 200 call? There’s a 10% chance that call is $800 in the money. So that call is worth $80.
(On review of my example — $80 expected value; the point stands.)
Despite the fact that both stocks are $100, the biotech stock’s 200 call is trading way above the other one’s. That is information. You now know something much more about Stock B that was not presented to you in the two-dimensional view of just the stock price.
Consider all the strikes and expirations — the options price starts to feel like the options market is actually the underlier. It’s the truth about the stock. It’s giving you a very rich picture of what the risk of this stock is and what its properties actually are — in a way you will not get from the stock price itself.
Formally: the mean of the stock is the first moment of the distribution, volatility is the second, skew is the third, kurtosis (heaviness of the tails) is the fourth. You’re getting a much more textured picture of the risk of the asset by looking at the options market than just by looking at the stock. I call it the 3D view versus the 2D view.
Part 3: Complete Markets and Why Options Matter
Let’s take a detour.
Arrow’s Impossibility Theorem
There’s a famous economist named Kenneth Arrow. He had a celebrated idea called the Impossibility Theorem. It’s about how to organize and coordinate collective human decision-making.
If you’re trying to understand how a government or any collective decision-making process can take individual preferences as inputs and produce a final action, we think about democracy as a solution. Dictatorship works too — a dictator can do this with ease; he just says “this is what we do.” Another way is voting, per capita, equal weight.
Back in the 1700s there was a super progressive math genius named the Marquis de Condorcet. Condorcet was a prodigy when he was young, and what he effectively demonstrated was that there’s no necessary coherence in preferences generated by voting. You can prefer A to B and B to C, but still prefer C to A — which is incoherent. There’s no ranked ordering that necessarily resolves itself.
Kenneth Arrow proved this formally: there is no procedure that respects the preferences of all and at the same time produces a coherent decision. This is actually important because it is the justification for markets as a completely different way to organize consensus.
Complete Markets
Markets are another way to organize ourselves beyond democracy or dictatorship. Arrow talks about an agenda that “completes markets.” What’s a complete market? A complete market would be that every asset in every possible state of the world has a price. It’s the ability to exchange risk based on finer and finer definitions of state.
This sounds abstract. I actually think this idea is as important as refrigerators and airplanes. It is a financial innovation, a financial idea, and it’s incredibly important. Here’s why.
If you think about this idea of state-contingent claims — what is the price of something in various states — think about the market for a firearm. You have a price for a firearm right now. But imagine you could trade the price of a firearm conditional on zombies walking down Telegraph Avenue. You’d have a completely different price. If you can consider the price of all things in every state of the world, you start to get this idea of a full surface of possibility — parlays everywhere — where you can make finer and finer assessments about risk.
This is very similar to how you think about options as a full surface of possibility. It is a step toward completing a market. It is a step toward the idea that risk should be held by its most efficient holder. The person who can bid the most for risk is the one best equipped to manage it — and that is a net benefit to all of us.
A simple example is insurance. The price of your car or home insurance, if you go out to a marketplace and buy it, is probably cheaper than you trying to self-insure. That’s because of economies of scale for the provider — laws of large numbers, underwriting over populations. They can provide insurance at a relatively low cost.
That benefit is real. How would you be able to buy a home — current times notwithstanding, but go back to when we were sane about this — when buying a home might cost 20%, 25%, 30% of your income or assets? That’s a significant risk. Would you buy a home if you could not insure it, especially in a place that has fire risk, like out here? It would be very difficult. The fact that home insurance exists is of net benefit to you.
Absorbing risk at the right price lowers everybody’s cost of capital. That is very important, because it is exactly the thing that enables specialization. It allows you to trade your skills with somebody else’s. Instead of figuring out how to grow my own food and do everything I need to support existence, I can just study X and offer my services there, and use money to fill in all the other things I need.
All of this innovation is very real. The benefits of trade are very real, and complete markets are incremental improvements to that entire structure. When I look at options, what I’m seeing is that there is a beauty to what’s actually happening here — we have enabled somebody to be able to isolate their risks, because then you can make better decisions for the rest of your life.
An Ed Thorp tangent
Side note. Some of you may have heard of Ed Thorp. Ed Thorp is in some ways the father of quant trading. If you’re not familiar with him, strongly recommend reading his biography, A Man for All Markets. One of the most amazing minds of the 20th century. Besides figuring out card counting and blackjack, his list of achievements is absolutely amazing. He also figured out how to price options before Black and Scholes did. He figured it out before their paper was published and used that to make lots of money.
Thorp ended up meeting Warren Buffett. He was a professor at UC Irvine and was about to start accepting outside money. A finance professor at UC Irvine was interested in investing in Thorp but didn’t know if Thorp was a quack. This professor happened to know Buffett. He tells Buffett, “I need you to come out, let’s go to dinner, kick the tires — is this guy a quack?” Buffett was 38 at the time, Thorp was 36.
They go out to dinner. Thorp and Buffett immediately recognize that the other is a genius — both see it immediately, despite the fact that they think about investing completely differently. Buffett isn’t thinking about things in terms of arbitrage the way Thorp is. But both saw the absolute merit in how the other saw the world. Thorp came back and told everybody he knew: “Give that guy all your money. He’s going to make you very, very rich — and your children very, very rich.”
At that dinner, they went back to Thorp’s house, and Buffett was a bridge enthusiast. Buffett showed Thorp one of his favorite possessions: non-transitive dice — basically A beats B, B beats C, C beats A. Rock-paper-scissors in dice form. He showed Thorp because he was fascinated by it. If you read Charlie Munger, Buffett’s long-time business partner, Munger will tell you that Buffett had basically figured out options pricing theory himself as an adolescent and had a very deep understanding of options.
I always think it’s amusing because Warren is also the guy who comes out and talks about weapons of mass destruction and rails against derivatives — and yet there are very few people in the world who probably understand derivatives as well as Warren. Behind that hokey exterior, as I always say, is an absolute shark.
Mainstreaming
Today, options are super mainstream. There are buffered ETFs. There’s the VIX, people know what the VIX is — your mom or dad might know what the VIX is by this point. There’s an ETF called BOXX that has $10 billion in assets under management, which basically invests in box spreads. That itself has spawned an entirely new market.
What’s a box spread? We can walk through it later today if you’re interested, but a box spread is a way to get T-bill-like returns from a combination of options structures. It’s effectively riskless and earns you a yield that tends to be a little bit higher than treasuries.
BOXX is an ETF sub-advised by some ex-Susquehanna guys that basically buys box spreads. When you buy a T-bill, your interest is imputed as a taxable ordinary gain. When you buy a box spread in an ETF, you do not have a gain until you sell the ETF. So you’re effectively investing at the risk-free rate — slightly better, actually — and not paying taxes every year. Very clever invention, but it’s using options. When it first came out people were like, “What dark arts are going on here? You’re investing in options?” I had to write about it because I’m like, no, no, no, this thing is super benign. Options traders have been using box spreads for as long as I’ve been in business.
An interesting follow-on: that ETF is basically a lender, earning the yield. There’s now a company called Syntheticfi that Y Combinator backs. Syntheticfi is like, “Wait a minute — can I borrow at box rates?” Borrowing at slightly better than the risk-free rate is better than getting a mortgage for your house. Mass affluent people are now, through Syntheticfi working with financial advisors, using the options market as a sort of API between the options market and advisors to borrow money to buy their house.
I’m not pointing this out to shill box spreads. I’m pointing it out because this mainstreaming of options is happening right in front of my face. I used to talk about things in options and nobody would know what the hell I’m talking about. Today the vocabulary of options is everywhere. I see it everywhere. I’ve seen it change in the last 25 years — it’s almost tiresome. Everyone’s talking about “maximizing my upside,” “capping my downside,” “keeping my options open,” “keeping future paths open,” side hustles as optionality, social networking as optionality. This language has become very mainstream.
The pushback
I’ll close with my necessary pushback against the whole options-thinking-as-life-advice thing. Options are beautiful. But the option mindset I see everywhere has done this thing where it assumes that money is the ultimate option — it’s pure optionality to make lots of money — and people become obsessed with this, basically hoarding options.
I will tell you that the exchange rate between options and time is imperfect. Time is not money. There are many activities in your life — how you spend your time, like seeing your children — that are exclusionary goods. The exchange rate between money and time is discontinuous at various limits like those.
It’s important to recognize this, because when you’re young and obsessed with this option-hoarding mentality, you forget that the best things in life come from exercising the damn options. Your courage and commitment — that’s how you exercise an option. I don’t know how those dating apps flip honestly, but you don’t swipe left on everything. Sometimes the right thing to do is swipe right, commit, and go deep on the thing. Stop hoarding the damn options.
Nobody’s going to talk at your funeral about all the options that you hoarded. They’re going to talk about the options you ultimately exercised.
A Good Will Hunting moment
I always love that movie. I kind of had to write this one:
Of course, that’s your take. You just started trading options. You read one thread about gamma, probably from some ex-market-maker with a Greek in his bio, so now everything’s “dealers are short gamma” and you’re convinced that explains the entire market. That’ll last until next month when you discover Vanna, and suddenly you’re explaining every 10:30 move as systematic flows and vol control rebalancing. Then next year you’ll be here regurgitating Taleb, talking about convexity and antifragility, telling everyone that options are really about epistemology, not P&L — until you blow up selling puts in a low-vol regime and decide that the real edge was just in carry all along.
That was a one-shot. Good.
Anyway, that’s all I’ve got to say about options this morning. I don’t want to talk any more directly — any Q&A, we can do whatever.
Q&A
Q1: Zero-DTE and gambling
Student: You’re talking about how options are becoming more commonplace, and with that maybe comes gambling — zero-DTEs and everything. As someone who’s seen the progression and understands pricing very well, do you think those products are pushing markets forward? And when you look at them, do you trade them in a systematic way, or are they just there for thrill?
Kris: I think it’s generally a good thing whenever I see a new way to do things. I’m not too nanny or nudgy about “hey, you shouldn’t do this.” Something like this is a good thing that exists. If you want to make a bet and have some reason to think you have an edge, it’s pretty cool that there’s something there to take advantage of.
I think what zero-DTE is about, ultimately, is that you are effectively trading delta, and it’s expensive to do so. If you’re trading a 40-delta option and you pay a penny through fair value, you are paying 2.5 cents through on the underlying, because the market maker is charging you for the delta risk they have to take on the other side.
That penny is true on any option you trade — you are paying for the delta in the option. However, there’s a very large percentage of the premium when you’re trading a zero-DTE. The vig is very big on a zero-DTE, even though optically it looks like a penny.
Student: Can you explain what the vig is?
Kris: The vig is your slippage cost to trade — bid-ask as a percentage. If your option is 50 cents and you’re paying a penny through, you’re paying 2% of the option premium just to get executed. That’s not including your brokerage’s costs, direct or indirect. Maybe your broker doesn’t charge you to trade the option, but in that case, in expectation you are paying a vig, because that flow has been sold to somebody you’re trading against.
All those pennies add up. That’s why those firms make billions of dollars — these are not unrelated phenomena. You’d need to overcome that penny. But because edge is optically small and slightly negative, I always say this is a feature, not a contrivance. It’s a feature almost by accident: you wouldn’t go borrow money from the mob because you know it’s a bad deal. But you don’t really think it’s a bad deal when it’s just a penny. In a repeated game, this is a very bad deal.
Are zero-DTEs a good idea? It’s a question I turn back: what is the edge that tells you that you think this is a good idea? In absence of a great story for that, it’s probably a bad idea.
The other thing we can talk about as the day goes on — there are interesting aspects of zero-DTEs. Implied vol is really a meaningless number in a zero-DTE, basically because of how little time there is to expiration. Implied vol is a function of your option model and how much time there is to expiration. With a zero-DTE, we can have a real difference of opinion about how much time is to expiration — because you don’t care about wall time, you care about vol time. And vol time and clock time are not the same. So we can disagree about how much vol time remains to expiration, and that’s what drives the price of the option.
The actual option model’s output is basically garbage. I never traded zero-DTE — it became popular after I stopped trading — but I’ve traded many times in my life an option with one day to expiration, which is effectively zero-DTE. I could trade that stuff without a model. I could do it in my head.
You get a feel over time for how time passes, how vol time passes throughout the day. You build up a history: you understand that in the middle of the day an option barely decays, but it decays a lot from 9:30 to 10 AM. That’s only half an hour out of a 6.5-hour day, and yet the option might lose 30% of its value in that first 30 minutes. It’s not a smooth function.
It’s also not smooth when you think about Thursday at the close with expiration Friday at the close. How much do you think your option decays overnight? There’s a real debate to be had. Where does that option open tomorrow morning? What influences the price at tomorrow’s open?
On one hand, zero-DTE from first principles is probably a bad idea if you don’t have edge. On the other hand, if you want to be analytical about pricing them, most of the discourse on the internet is completely missing the things that matter. Nobody hawking these things is actually talking about vol time. So yeah — it’s a long convoluted answer. It’s cool that it exists. You probably shouldn’t trade them.
Q2: The transition from shouting to software, and 24/7 markets
Student: Two questions. First, what was it like to transition from the old shouter-trader model to the new math-quant-software model? Second, NASDAQ and NYSE have announced moving to a 23.5-hour model and eventually 24/7. Who do you think will be the big winners and losers of that, and for people interested in trading as a career, what do you think the second-order effects are?
Kris: Let me start with the second question. Right off the cuff: my first instinct is that not much is going to change initially. Liquidity is a network effect. There’s an inertia to the way liquidity behaves. Futures are already open around 24/7, but where are the big bumps in volume? The London open, the US open. There’s a human element behind how we aggregate liquidity. My 10-year view — all bets are off. There’s a funny Matt Levine bit about “how would it be affected if we had trading open only five minutes a day?” How much is just around shelling points, “these are the times we’re going to show up, those are the times that matter”?
I would actually feel very much like a mean by the way on this — but I think they can shorten the hell out of trading hours. I’d go the exact opposite direction. I’m very suspect — and again, I was never in HFT land — but I’m generally pretty negative on the fact that we fragmented all this liquidity. People will make arguments that it’s for consumer choice. I’m like, put it all on a central limit order book and let all the liquidity come to one place. I’m very much of the “put sunshine on everything” mindset.
This movement toward more frequent trading is stretching liquidity over a longer period. My gut is that it’s probably bad — especially because my prior was that if you shortened hours, that would be good, and if you centralized flow on a single order book, that would be good. This is moving in exactly the opposite direction.
One random thing: maybe it’s not a big deal, maybe it makes it a little easier for a young person to get a job. Night shifts suck. They’ve been documented as bad for your health. If you’re willing to bear that — nobody wants to work the night shift, and you’re going to need more night shifts. So maybe the opportunity set opens for somebody aggressive.
But yeah, I think it’s a step in the wrong direction. Crypto is already 24/7 and more international, so hours are more than just market hours. I don’t know the breakdown of volume between US hours and other hours.
What was the first question? Transition.
The transition wasn’t abrupt. Every year a new innovation was kind of happening. I think — path dependence, luck, whatever — I benefited from the way the transition happened. Compared to somebody who graduates college today, I’m a dinosaur as far as knowledge. But it’s kind of funny — I said I didn’t know Excel coming in, but on the quant spectrum of trading, I was closer to the quant side. I mean, I had the joke — when I came into the business, there were a lot of idiots. So I was relatively ahead of the curve.
I learned Excel very quickly, became very proficient. My front end in Excel looked like software, was super interactive. Within four or five months at SIG, I was rewriting spreadsheets for most of the people on the trading floor. I’d go there and be like, “Yeah, can I make this look better, blah, blah, blah.” To me this was something where I could make my boss’s life better.
Broader life lesson: I was in a cohort of about 60 market makers in the New York SIG office. I had a morning one day where I was late. Everybody was already at their desks, which is a little embarrassing — you’re walking in, everyone’s sitting down. Somebody stopped me and asked, “Which was higher — your verbal SAT or your math SAT?” The whole room was waiting. I said, “Verbal.” Half the room erupts. Turns out the market was 3 or 4 on how many people in the room had verbal higher than math, and I was the fourth — and I was the last person to walk into the room. So they did a great job making the market.
I was definitely not on the quantitative spectrum of aptitude of the people. Many people in my cohort got an 800 on the math SAT. A lot of MIT people. I understood where I was in the horsepower pecking order — on the lower end. So I needed to be better in other ways. I’m the short guy on the basketball court — you figure out how to be better. This Excel thing, I’m going to figure it out, get obsessed with it.
Being ahead there allowed me to be self-sufficient. If you weren’t good at using a computer — and there were traders who weren’t — you depended on others. If you were happy to use the computer, you could experiment more, write your own models. I have hundreds of files of just me trying to figure something out by brute force — horrible looping, things that would look absolutely primitive to you. But the person you become doing that is really a destiny. You’re progressing to do all that, and you get a real feel for: “If I sell an option at 30 vol and it realizes 29 vol, what are the error bars around my result?” You need to plug in stuff and get your hands dirty to figure this out. I think that helped me leapfrog a lot of people just by doing more work.
When I think about the transition — from yelling to more quantitative — we at SIG were pretty early on figuring out vol time. That was a big innovation. It wasn’t me that figured it out; somebody at SIG did. That person ended up completely transforming Citadel Securities’ options desk in the mid-2010s. He was a bit of a runt-of-the-litter kind of guy who turned out to be one of the best people they ever hired. Using the Yahoo Finance API, within Susquehanna — not even using their resources — he had basically figured out vol-time calculations, which they ended up deploying to their market-making software.
I was over at NYMEX, and we were like, “What are the equity options people doing over there?” We started looking at it — oh, this is pretty neat. It gives us way better insight into what the price of a calendar spread should be. We adopted this lens, and I felt like we adopted it before the larger market understood it. It looked like there was edge everywhere. The heat map was just blowing up — money to be made everywhere.
I was a discretionary trader — that’s the other thing I should say. Systematic trading is on the much higher-Sharpe end of the spectrum, and competition is way more difficult there. Right now in the marketplace there is a lot of brainpower and capital pointed at predicting the next tick, predicting today. There’s a very good Flirting With Models podcast interview with the guy who runs AI at Hudson River Trading. Reading between the lines: there’s probably going to be more opportunity at medium-frequency and longer-frequency trading, because all the brains are pointed where the Sharpe is highest.
There’s no way a person like me could ever compete in that high-frequency part. I don’t have the skill set, and it requires tremendous resources. But thinking about further-out time frames is absolutely an opportunity. When I speak to guys still doing the job the way I did it, at the frequencies I traded at, I don’t see that it’s actually changed very much. That makes sense — big data, basically looking at the market like an ad-targeting problem, which is what HFT firms are effectively doing, has nothing to do with mid-frequency trading. The HRT guy says there is no realm of “big data” happening past the day. That’s not where these tools work.
There’s still an area for understanding markets, understanding gamesmanship, and all these things that lend themselves to being able to trade in those parts. The broader lesson is: figure out where you fit in. I thought by now this would be completely over — it doesn’t seem to me it actually is. And it may be over in five or ten years, I don’t know. Right now it still doesn’t feel like it’s over. I feel like I could go back to my job, fire up the computer, and be right where I was before.
The transition is about understanding which front of the battle you’re on, how fast innovation happens on that front, and what the surface area of that innovation is. If innovation is happening in big data and you’re in a part where it doesn’t really lend itself to that, you’re probably a little safer a little longer.
There’s a large trading firm, founded by another guy in my cohort, based in Chicago — they’re recently getting into options in the last couple of years. From what I understand, they’re not even thinking about options in terms of vol. That’s crazy to me — I don’t even understand what you’d think about. From the little I know, they’re really about predicting the next tick, even in options. Completely different approach. But it reinforces this idea: big data is what’s happening at the front end. Depending on where you are, the innovation is always happening, but you can have some awareness of it and try to put yourself where you fit.
Q3: Why haven’t options taken off in crypto?
Student: Thank you for being here — I’m here because of you, I follow you on Twitter, you’re a great storyteller. Why do you think options haven’t picked up in crypto the way they have in traditional markets? In traditional markets they seem to have the majority of volume, but in crypto they seem stuck below a threshold even though many platforms offer them. I used to think it was just that they only traded in certain places, but now the big platforms all have options and they still seem to be a minority of volume. Why?
Kris: I suspect it’s just a matter of crypto adoption. Even though crypto has grown a lot as an asset class and it’s kind of big, it doesn’t feel like it’s that widespread. I did a survey that hit my Substack at the end of the year. Based on the sample, 60% of people who had taken the survey had never owned crypto. I thought that was kind of low given that my population — 50% of my readership is in finance, and of that 50%, maybe 30% is in trading, prop trading, etc. You’d think there was more adoption. I thought it would be higher than that. Sixty percent never owned crypto seems kind of crazy. That’s very high financial acumen people.
Adoption probably isn’t as far along as it needs to be. Options are a subset of a subset of a subset. You have people trading the underlying, then people in futures for leverage, then options. And crypto itself has a UX that isn’t as nice or as familiar to the average person as traditional brokerage — which is a hurdle. Then you can’t trade it in the US easily. All these things add up. IBIT was exactly what the market needed.
Options are already relatively niche — even though we’re talking about it in this big way today, in the grand scheme it’s still somewhat niche despite its growth. Crypto is also a niche. So your niche on niche on niche — it doesn’t surprise me that it’s not super liquid and hasn’t expanded beyond a certain point. Options inherit from the liquidity of the underlying. That’d be my guess. But again, I’ve never even owned crypto, so I’m not in the nuts and bolts of it. I’ve done some LP stakes through Coinbase, but I’m not super deep in crypto.
Q4: First principles pricing — does it exist in options?
Student: In a normal equity market, there might be some trader who decides from first principles or fundamentals, “This is how I’m going to price X, irrespective of what the rest of the market thinks,” and they trade in that and hopefully make money. Does that kind of exist in options — where someone from first principles thinks about every eventuality and creates the curve or surface irrespective of what the surface currently is, and then trades in that direction? Or is the surface always just an emergent property of thousands of people making markets?
Kris: It is an emergent property. A surface is a consensus. But anybody with a very strong opinion that the distribution is wrong can trade against it, and they will influence the consensus if they trade big enough.
To me, that’s the definition of what you should trade. Here’s the thing about options: they are surgical tools. You are highly levered to being right.
An option is interesting because it’s both a statement about magnitude and direction — which together suggests volatility. We talk about volatility formally, but in crayons, we’re really talking about magnitude and direction within a certain time frame — which together imply volatility.
The more surgical your opinion — the finer your opinion — the more options are probably the right tool for the job, because you’re very levered to getting all of those things correct.
As options traders, we use this to say: if somebody knows something, we’re sitting ducks. We’re using heuristics to price the surface. We’re getting some intelligence from consensus — but at the end of the day, we’re pricing this very specific thing without that knowledge. Our knowledge that informs our pricing could be missing something critical that you may be positioned to own. This is also why insider traders and criminals go to the options market first. One of the first things you learn early in SIG days is that crime shows up in the options market first — that’s where the highest reward for ill-gotten information is. You’re highly levered.
That lesson cuts both ways. People geek out on options and want to think about Greeks and volatility and all that. But there have been a lot of very successful options traders who have an intuitive understanding without this formal language. Think about the guys from The Big Short — those two who were out here in Berkeley, the ones who ended up talking to the Brad Pitt character. They were trading options — way-out-of-the-money calls. They were looking and going, “The distribution in the options market is smooth, and this asset does not have a smooth distribution whatsoever,” because they actually understood the asset and the accounting. The options looked like a giant mispriced asset, and they placed their bet.
Did they think in terms of implied vol, the straddle, all that? No. They were saying, “These are my scenarios, and given the expected value of the scenarios, this contract makes no sense at that price.” That is probably one of the best ways to approach options — come to the market from a very deep fundamental understanding.
I always like to say: when you throw a punch, the fist just delivers it — all the energy comes from the hips. The upstream work, the research, understanding the distribution — that’s the hips. The option is just the final expression, the contact point. If you came to me and said, “This is my thesis, here’s all the work I did,” I’d say, “I can help you do the options part.” That’s the easiest part of the whole problem. You could probably train an LLM to do that. All the work before is really the magic. The option is just the weapon of choice.
Q5: Edge in illiquid markets
Student: When you see illiquid markets today — crypto options, small-cap stock options, or prediction markets — do you think market makers there are still using techniques from your early career? Or is something totally different going on? Are there still niches where more primitive models can work, or is it new techniques at smaller scale?
Kris: More primitive techniques might work, because one, if it’s a small illiquid market, it’s a lot less likely that Jane Street is quoting it. It doesn’t make sense to devote resources to quoting a market where there isn’t a lot of money to be won. So if you’re a relatively small trader looking to make good bets, you probably want to look where the big firms aren’t. That’s where things are most likely mispriced.
The trade-off is markets will also be wider — you’ll have to overcome a bigger spread. But you always have the option to not trade. So it’s always fine to look. Nobody in this room has any edge trading SPY.
The only place there could possibly be an edge is going to be in trading something that is not looked at and machined to death — maybe you catch somebody off guard.
I can recommend blogs. There’s an ex-SIG trader who retired and writes an amazing blog about prediction market betting. He was a great SIG trader, and he is completely obsessed with prediction market stuff. On his blog he walks through lots of trades and explains his reasoning. When you read it, you get a sense of the kinds of thinking that can go into making a bet. In one sense it’s primitive — he’s really doing a judgment layer mixed with some Markov chain math. Nothing especially sophisticated, but it does take work.
Your instinct is right that you’d probably have more edge going where people aren’t looking.
Host: Awesome. On that note, thank you so much for everything. From the chatter in the staff Discord, my staff members’ minds were blown, and looking around, it seems like that’s probably true for a bunch of students here too. We’re now going to go immediately into trading options.