The Beauty of Option Theory

This past weekend, I cloaked myself in the robe of imposter syndrome and gave a talk to a small group of sophisticated investors. I don’t consider myself a great investor, my core portfolio is a simple asset allocation model in the vein of a permanent portfolio. The point of it is to preserve wealth so I have the slack to take shots using my human capital which I have more faith in than the meanderings of a drunk market.

That wasn’t going to be interesting to a group like this (although it’s a topic worth plenty of discussion for the average saver). Instead, I decided to talk about the beauty of options. It fails the test of giving a directly actionable investment idea, but if it helps extend an investor’s mental toolbox it would at least be worthwhile. Plus, I’m a hedgehog. Options are probably the only thing I’m justified to pontificate on. A pathetic, dull boy in 99% of contexts, but hopefully value-added here.

I started with the practical before wandering into the aesthetic.

A Practical Option Consideration

    1. The directional use of options is trivial because most of the work is upstream of the option expression. If you have a divergent view of an asset’s distribution from what the volatility surface implies, trade expressions are often obvious. Any decent option broker or junior level option trader could probably help.
    2. So-called “vol trading” is irrelevant to 99% of the investing world  — it’s a low-margin business relying on the law of large numbers while also being capacity-constrained. In the bigger picture, it’s chess-boxing — nerds fighting. If you want to be really rich, find a way to get paid on beta.
    3. If directional trading is the most common use of options, then covered calls and hedging are the next most common. We can use a “replication mindset” to understand that even when you sell covered calls (or hedge) you are, regardless of how promoters sell the idea, engaging in a volatility trade.Consider my logic:
      • The alternative to selling a 20d call monthly: you can sell 20% of your position instead.
        1. Call selling: You get called away on your position about 1 in 5 months
        2. Selling the stock: you are out of your position in 5 months
      • The false accounting that the call seller uses to rationalize: “I get called away on my position less than 20% of the time so actually selling the calls is better”
      • Reality: You are failing to account for the times when the stock dives where you don’t get assigned on your short calls, but you would have been better off to have sold 20% of your position.

The spread between the false accounting and reality is a function of the volatility that was realized vs the IV you sold 1

When you sell covered calls, whether it was a better choice than just selling the equivalent fraction of your position depends on what vol is realized vs what vol you sold.

If you sell calls too cheap you are better off just selling a fraction of your position and that’s why you shouldn’t sell calls indiscriminately for “income”. You need to consider whether the price is right.

Stop thinking of options through the lens of directional trading — you are still just trading volatility.

The Beauty of Options

I don’t actively encourage investors to trade options. In “Do You Even Trade Bro?” I offer a framework for deciding if you should bother. That said, learning about options and portfolio theory is worthwhile in both an appreciative sense — options are a “bicycle for the mind” and because it’s a useful lens for decision-making. Decisions are options.

The beauty of options theory and arbitrage pricing, in general, is in its replication mindset. Pricing derivatives is an exercise in finding and valuing a portfolio that would mimic the derivative’s payoff. If we combine the derivative with its replication, we have constructed a risk-free portfolio. The Black-Scholes formula prices an option by showing (under faulty but useful assumptions) that its cost should be equal to a trading strategy that rebalances a mix of cash and underlying shares until expiration. The rebalance between cash and shares depends on the probability of the underlying going through the strike price and by how much. That probability depends on the volatility of the asset and its distance from the strike, all normalized by time.

By studying the concept of replication (ie arbitrage pricing theory) you gain a new mental tool for approaching decisions.

Examples

  1. In How Much Extra Return Should You Demand For Illiquidity?, I provide an options-based approach to thinking about how much extra yield you might require to hold a bond (like an EE bond or annuity-type investment) that you cannot sell. The key is to price the illiquid asset like the liquid version of the investment (ie Treasury bond) as the illiquid plus the option to rebalance. The higher the volatility, the more the rebalance option is worth. This confirms your intuition — the more volatile the world becomes, the more we should value liquidity.

If there is a large discount to buy an illiquid version of an investment, you are being offered a “deal” to effectively short volatility by abandoning the option to rebalance. When illiquid investments (ahem PE) argue that the illiquidity is an advantage for behavioral reasons (”protect yourself from selling during periods of stress”) they are standing in defiance of financial theory.

If you understand options conceptually, you can inoculate yourself from such motivated sales pitches. As an investor, if the stock market drops 25% and PE is not marking itself down, then you’d want to liquidate your PE investment at the nonsense mark and rebalance into the public markets. Of course, you can’t do that because the PE mark is not tradeable and you have forgone your option to rebalance. By not understanding options, you are the mark.

  1. Understanding when a typical situation now has an option embedded

In Options on USO when oil went negative, I show how a popular oil ETF became an option. It began trading at a significant premium to its NAV — but thinking this was wrong was a fool’s trade. USO had turned into an option instead of a futures or “delta one” equivalent and the premium to NAV represented the volatility value of the option. (An easy way to see that USO had turned into an option is to realize you could have bought USO and shorted CL oil futures to structure a riskless trade — USO cannot go below zero but futures can!)

  1. A final example comes from portfolio theory in general.

Portfolio theory shows us that if we have 2 assets that are only loosely or perhaps negatively correlated, a portfolio comprising a mix of both assets can have a better risk/reward than either of the components. In You Don’t See The Whole Picture, I give a simple math example to demonstrate this principle.

This principle has a deep implication — it means you don’t get paid for taking diversifiable risks. If I own a sunglasses company, I am the most “efficient bidder” for an umbrella company because I can diversify my weather risk. If markets are liquid, transparent, and the world transmits information cheaply then I should only expect to get paid for risks that are systematic, not idiosyncratic. Idiosyncratic risks are the types that can be diversified by being held by a party who owns the opposite type of risk (like the sunglasses/umbrella example).

A real-world example of this is the vol premium in oil puts when Pemex conducts its annual “Hacienda” hedge. Pemex, Mexico’s national oil company, hedges its forward production by buying puts and put spreads on oil futures. Typically this increases the value of the puts, enticing risk capital and arbitrageurs to sell the puts at a price that they believe exceeds their replication value.

However, I remember a year when Delta Airlines sold them the puts at a relatively fair price. This was a win for both Pemex and Delta. Delta is happy to sell the puts because they are “natural buyers” of oil via jet fuel (Delta also owns a refinery!)

This is a great example of markets doing their job. A risk that could be diversified was paired off between natural counterparties. However, from another perspective, this is bad news for investors who expected to earn the “sell expensive puts” risk premium. If a risk premium exists but it diversifies another party’s exposure, then that party can afford to pay more for it than the standard speculator. So the efficient frontier for speculators is just the set of investments that contain systemic risks that cannot be hedged.

The most obvious example is the equity risk premium in general — the corporate world is levered to financial growth. Corporations are owned by people in the population. Once all risks are netted, there is no stakeholder remaining who benefits from economic collapse. Therefore the only carrot to entice someone to invest in corporations, effectively doubling down on their reliance on economic growth, is a yield in excess of the risk-free rate. That’s an undiversifiable risk premium.

I’ve given more examples in *Why You Don’t Get Paid For Diversifiable Risks, but like any model or theory it’s not water-tight. It’s useful. This one is a reminder to consider if the risk you are being asked to underwrite should command a premium. If it was hedgeable by someone else more cheaply, why did it show up on your doorstep labeled “excess return”?

Allison Bishop On The Growth From Failure Podcast

My wife Yinh’s podcast Growth From Failure is in its 5th year. Her guests are extremely wide-ranging and rarely found on “the circuit”. Many of you know her and would agree — her multi-standard deviation superpower is a genuine interest in people’s individual stories. It’s a power that is not simply recognized by people she meets — it’s felt. You feel like she’s listening to you because she listens with her whole self. Some may wish for an invisibility cloak or a crystal ball. I’d take her ability to listen (and for every keto dude working on his abs — I’d be willing to bet that this listening skill is the OP aphrodisiac — the problem is it’s rarer than a six-pack.)

She doesn’t need me promoting her pod but yea you should check it out if you want to break out of your normal pod routine especially if you get the awkward sense that you’ve slotted too many quarters into the same dudes-who-use-business-idioms-like-open-the-kimono merry-go-round.

That said, if I promoted every episode I’d dilute my recommendations. I restrain unless the interview is:

☑️ too compelling to not share. Examples: Elizabeth Shaughnessy, founder of the Berkley Chess School (one of my favorite humans) or T-Vu, engineer and rapper (maybe my favorite GFF episode).

☑️if they intersect with quant finance. Past in this category include interviews with my former colleagues Kelly Brennan, partner at CitSec, and options trader Tina Lindstrom or power trader Noha Sidhom.

Today, I’m boosting her latest episode because it checks both boxes.

🎙️ALLISON BISHOP – COMPUTER SCIENTIST, WRITER, COMEDIAN. PRESIDENT AND CO-FOUNDER, PROOF TRADING (Growth From Failure)

Yinh’s intro:

This is the story of Allison Bishop, president and co-founder of Proof Trading, an institutional equities execution platform. In this episode, we cover Alison’s journey from aspirations in creative writing, which had a rejection and led her down a path that was much more quantitatively oriented than she thought. That led her to Masters and PhDs, in math, computer science, and cryptology.

I learned so much from her like the branch of math called combinatorics, which I’ve never heard before. And also the practical applications of cryptology and computer science and for the first time, finally, understanding how those were actually used.

But more importantly, I learned about controlling how you set people’s expectations and reclaiming that power, either emotionally or physically. Allison literally changed the way she moved in the world.

Select excerpts:

On her transition into math after being rejected from the hallowed Princeton Creative Writing path, her entire reason for choosing Princeton in the first place:

I was devastated, it was the entire point that I was here. And at the time, I was also supposed to be just getting rid of my general distribution requirements. One of those was to take a math course. And I refused to take calc, which was what most people are taking. I’d taken calc AB in high school, and I find it kind of boring. And so they’re like, you could just take Calc II.

Meh, what else you got?

I ended up taking number theory because I thought it was the “physics for poets” of math. It is not. It’s a foundational course in cryptography. And it was a course math majors were taking and it set me on this very different path of learning that I liked math and that math could be creative. But it happened because of this simultaneous confluence of events that I got rejected from Creative Writing, and I refused to take calculus.

I also did take the “physics for poets” version at Princeton. I thought it was great. It was really philosophical and insightful, and I quite enjoyed it. But yeah, the math class was not at all that. It was a serious math class and I also had no conception of what Princeton math is. What the Department was or what that meant. And I’m really glad I didn’t know because I think I would have found it very intimidating. I got pretty deep into this process as a math major before people started, like telling me, you do know, this is one of the best math programs in the world. Oh, no, I didn’t know that. You know, the guy teaching linear algebra is a Fields medalist. What’s the Fields Medal? And it was just very perplexing to the people around me how I got there because there are usually about 60 to 100 people every year applying to Princeton for math and in my year, only 15 graduated with that major. I ended up being like this wild card person who did not know what was going on, but was in for the ride.

What she found creative in math

It was the first time I actually got to write proofs. This concept of using math not as a vehicle to just calculate something, but as a way of reasoning about the world. That was new to me because I feel we lose so many opportunities in the way we teach math at the elementary, middle school and high school level. Here’s the procedure and you do it. If we’re lucky — “here’s what that means”.

But there’s not “here’s how people came up with it. Here’s the history of it, or here’s the question from first principles, and have you come up with the procedure?” So the first time having these open-ended questions be asked, and then having to reason about it myself, assemble proofs out of the building blocks that we’ve seen in the class.

The one that I think fascinated me at first, which is actually a relatively simple one that you can teach at the middle school level, is a proof that there are infinitely many prime numbers. The fact that you could prove there are infinitely many of something as complicated as prime numbers. What’s fascinating to me, and the creativity that goes into this, okay, how do I reason about this? How do I create a procedure to always produce a new prime outside of the set of primes that I produced so far? That constructive building process was very appealing to me.

But when you’re writing a proof and realize how creative it is, but then you’re going through it again and it’s still the same answer does it then feel black and white, and then QED?

Not really. And I think this is something that mathematicians are at varying degrees of denial about, because there is this process of peer review that happens when we prove new theorems and people put them out. And it’s highly nontrivial to go through and check someone else’s proof and make sure everything makes sense. And in some sense, when we can reduce each little step to this logic axioms, then you can check that we mostly gain confidence. But the process of putting those things together really shapes the theorems that you’re proving. So it’s not really that there’s this a universe of facts. And then there’s these proofs that get attached to the facts. And then as long as we have a proof attached to the fact that we can check we can move on. There’s so many different things that we could reason about, or relationships between objects that we could try to prove theorems about so much more of the interesting stuff goes into the human process of what do we find worth studying? What questions do we ask?…I think mathematicians are a little bit reticent to admit how subjective the process of curating what’s important and what things we study is, because the process of checking a proof is already nontrivial, but is solvable in some sense. But the process of deciding which proofs are worth doing, and which questions are worth investigating is where most of the fun stuff happens.

From math to computer science

Math separates into two sub-fields. For me, at least the way I think about it, some of them have very complicated objects, and then you prove relatively simple theorems about them. So all the complication goes into the objects themselves. And so there’s things like topology, which is about shapes in the world, and things like that. And algebraic geometry. And combinatorics is more like the objects are pretty simple. Graphs, you’ve got dots, and you’ve got lines connecting the dots are things but then the theorems and the patterns that you study on them are complicated, which is much more aligned with computer science.

I ended up wandering from math to computer science. So as an early PhD student at Austin, I would go around to the different mathematicians in the department and try to learn about their research, I would always ask them, “What is the application of this in the world?” And I got a range of answers from there aren’t any applications of this in the world to tons of applications to other areas of math. And so I was pretty underwhelmed by the potential impact of the things that were being studied. And there’s a lot of fundamental research that happens. And we don’t know yet how it’s gonna get applied. And it eventually gets applied. And I think this stuff is really cool. But from the perspective of I have one life, and I like being very people-facing and doing things that impact people directly, it wasn’t really compelling enough to me. So I started wandering over to the computer science department.

It’s always a joke I make with mathematicians, “what are you guys doing over here?” It’s all the same stuff. But it’s got much better research grants in computer science, and it’s much more potentially impactful and relevant, pretty directly. So I ended up switching halfway through my PhD to be in the computer science department, which meant doing all of their requirements, again from scratch. So I basically did two PhDs and left with one of them. Totally the wrong way to do it. But I ended up in a good place sort of finishing my PhD with an emphasis in cryptography in the computer science department.

[Skipping over a discussion of the 2 major branches of cryptography which solve the same problems with different tools but remain silo’d for complex reasons as well as her human interest in the field]

While I’ll also skip how she started working with IEX before starting Proof Trading I found the transition story useful:

Cryptography and finance are similar fields — they both try to scare people away with enough acronyms. So I was somewhat comfortable at that point, being the person who just asked everyone questions all the time. And so my strategy on the trading floor was just sitting in the middle of all these people and whenever they their take their headphones off, I would ask them a question. “Hey, I’m wondering what this graph means. Can you come over here?” I was just shameless about asking questions. But I think also just having that prior experience of learning a jargon-heavy field, knowing that the fact that I didn’t know what the things were, didn’t mean I was stupid. And it didn’t mean it was going to be hard. It just meant that I had to ask, although I do think finance makes it unusually tough.

I’ve also been documenting some of my process. Proof has put out a market structure primer, which is basically my writing down the things that I didn’t know, and therefore asked and putting that into a form that hopefully helps other people. Because we do think that, unlike cryptography, where there are textbooks and there are public facing things and surveys that are helpful, in finance, you’re piecing this together from different people’s memories. I’m in the middle of the trading floor asking “What does this four-letter code mean on this trade flag?” There are no public references for so much of this. So I do think as a field, we need to do a better job of giving people friendlier entry points, but the people on the trading floor at IEX, around me were great at just having the patience to answer a million questions.

What problem is Proof Trading trying to solve?

The biggest surprise to me learning about the stock trading system was that the entire purpose of stock trading is to provide public information about prices. That’s the whole reason for being of the stock market. And yet, absolutely, every structure around that is completely opaque, which I just think is ludicrous. I will make the same argument with people about pay transparency, we need better insight into where these prices are coming from, for exactly the same reasons that we need public price discovery for stocks, but taking it specifically to the broker layers.

What we saw from our seat at IEX, was that we were trying to build tools that would ultimately help long-term investors on the buy side, but we didn’t have direct access, because that’s not who IEX is — its customers are brokers. And every time we’d ask a question, well, why are brokers doing this? Or why are brokers acting this way? There’s no insight available into that because brokers are this black box.

Thinking about this coming from cryptography, cryptography is all about keeping secrets, but they are much less secretive than this. Because fundamentally, whenever somebody comes to the cryptography community and says, I have a cool new way of encrypting data but I can’t tell you how it works, we laugh at that person, then we break their system immediately. Usually, “I can’t tell you how it works” means it’s not going to stand up to scrutiny. And the reason we believe in the encryption algorithms that we have is that they’ve been exposed to decades of people trying to break them and improving them and all these things. So it seemed crazy to me that the science of electronic trading algorithms of how to round certain ways or how to build or design a schedule, or how to optimize to certain goals for order performance, that that was all individualized inside these black boxes, instead of benefiting from an open science culture. It seemed completely handicapped to me as a scientific field and completely unnecessary.

There are things that need to be protected and confidential, like, what stock are you trading and when are you trading it. But if I’m claiming to you that I have a way of taking big trades and breaking them up into pieces in the market, so that they blend in with the noise, if they really blend in, then I should be able to tell you my mechanism, and it should still work. And if I’m forced to expose that mechanism, it should open up all of the surface for public science and collaboration that should help us get much better outcomes. So I’m a big believer in making science public, whenever there’s not a great reason to do otherwise, rather than secrecy being the default.

So one of the main things we wanted to solve for as a broker was to make as much of our decision-making process public as we could. So to make us more accountable, to open that up as a surface for collaboration with our clients that if we tell them what we’re doing, they can say, Oh, well, that’s not aligned with our goals in this case. And that’s a much more rich surface for communication and improvement than just saying, Here’s the box, you can use it or not. So it’s kind of our hope that bringing a scientific process into the open in this area would really jumpstart progress toward better solutions.

[Skipping a balanced discussion of the challenges they face as a remote-first company]

Can you give me an example of what Proof Trading does for a client? (I highlighted the refreshingly honest part of the answer)

Once a client has decided they want to buy a large amount of stock or sell a large amount of stock, our job is to figure out how to split it over time and space into pieces, so that the market doesn’t disproportionately react. How do we make their total activity blend in with the random activity of the market in such a way that we can get done what they want to get done without the price going up, because they’re buying or going down, because they’re selling so it’s reducing impact relative to getting the trade that you want? That is the value that we’re looking to add.

One thing that’s very tricky about this process is that the market is very noisy. So there’s a lot of noise in the data performance. And it’s very hard to compare two algorithms, apples to apples, because they get different kinds of orders and different market conditions, huge sample sizes. So it’s a very tough sales position. I can’t point to a single order. “Look, this is the amount of money we saved you.” And people seem to expect that, which seems super weird. When we go into the sales call it’s “explain to me how many basis points your algorithm is going to save me versus my competitors.” One, your competitors won’t tell me anything about their performance. So how would I know that? And two, I can’t even measure my own performance cleanly, because it’s a function of all this noise. And so I get a lot of befuddled expressions on the other side, it’s like, well, then what are you selling?

We think we’re better. We just also think this is really hard to show and I’m not going to show you some half-baked thing.

Addressing her recovery from a deeply personal trauma:

As a growth moment, it was pretty significant because I was having symptoms of depression and PTSD as a young faculty member. And what was strange to me about it was that my ability to function and do my job was the last thing to go. I was not sleeping, I was not eating well, everything was off. And yet, I was still publishing papers and teaching classes on paper, everything looked fine. And I had to convince myself that it was bad enough to heal, just give myself permission to heal.

And I think one of the things that surprised me about that process was it was less of the growth — it was more, almost shedding a limb, just completely resetting. And that was actually the time a lot of people have asked me about. I started dyeing my hair, blue and purple, and I started getting tattoos that were meaningful to me and changing my appearance. I felt like I was walking through the world looking like this person that I wasn’t able to be anymore. And having people react to her the same way they used to react to her was stopping me from healing, people would expect things in me and I would do them because that’s what I’d always done. And so I needed to find a way to change what people expected of me. And so I think one of the biggest things was reclaiming my physical presentation and space. That was also when I started learning, boxing, and just changing the way I move in the world.

So for me, I think the biggest growth moment was realizing that sometimes you need to reset, and you need to reclaim some of the things that are in the way of that progress and giving myself permission — also to quit, as a faculty member and not say it is a failure. I think a lot of academics think of leaving academia is always intrinsically a failure. It was a continuation of my journey, the willingness to be seen as a failure. And that sense, I think was really important.

And I loved this part:

Realize that we have more control over setting people’s expectations for us. And I think it takes a certain amount of separation from people’s reaction to you just realize that that lever is there to some extent. And for me, it really came out of a place of necessity. And from feeling it in myself, I had to wake up in the morning and look in the mirror and see this person that I didn’t feel existed anymore. And that was this weird, disconnecting feeling.

This was always the biggest thing I tell people thinking about public speaking or comedy, is that if you make yourself laugh, it’s contagious. If you’re getting on stage, and you want to convey an emotion, or you’re pitching your startup or whatever, if you feel it, the audience will feel it. And so it’s getting to the point where you feel good about what you’re doing, or you feel excited about what you’re doing is 90% of it. And the rest is just icing on the cake.

Check out the full episode to hear about how Allison defines success, what she learned from her blunder as an 18-year-old intern working on the Mars Rover with the JPL (Jet Propulsion Lab), her boxing and comedy outlets and how her professor Jordan Ellenberg (my notes on his book) inspired her to embrace her varied interests and her recent acceptance to a creative writing MFA program!

Allison also founded a conference called CFAIL: Failed Approaches and Insightful Losses in Cryptology.

It’s an annual event where we give people a platform to talk about research that didn’t ultimately succeed in whatever they were trying to do. So it’s whether they tried to prove something and they couldn’t, or they tried to build something, and it was broken. And that has been, I think, just one of the funnest and most energizing research conferences that I’ve been a part of people embracing talking about failure.

I’ll leave you with this skit Allison created:

“The MMWF Award” — a fictional award for Men Who Support Men Who Support Women in Finance.

5 Takeaways from Convexitas’ Devin Anderson

Option trader and founder of Convexitas Devin Anderson drops some terrific insights in his interview with Bill Brewster on the Business Brew Podcast. I found them deeply resonant.

Episode link

I added my comments to the following excerpts which were taken from minutes 20-30 in the episode.

“Risk Over Rules”

Risk vs rules-based approach

Risk-based limits are set for every mandate that we monitor throughout the day, every day. For each mandate, we agree on a size and determine the risk limits for the product. We manage within these risk bands for the handful of different products we have. This approach is different from a rules-based approach, which would dictate specific actions based on market conditions or other factors. Instead, we exercise discretion within the risk-based framework.

Example:

  • The market exposure cannot be greater than the notional amount you have hired us for, and it must be negative.
  • We cannot take a leveraged short.
  • There are minimum amounts of convexity that we must maintain at all times
  • [Our size is constrained by] shock scenarios.

There is a set of rules that determines the band of market exposure and the minimum amount of shock and spot convexity we must have, but it is up to us to decide how to implement those rules. We determine which part of the surface looks the most interesting, what the relative value is, and how much of it we should have on at any one point in time. This is a completely different way of thinking than simply investing a set amount and waiting to see what happens in the future.

“All good option trading has to start from biases in the market”

To draw a parallel to value investing. If you don’t believe that you have an edge in some stock, and you don’t believe that there’s a discount, then why should you own this thing? We can apply that same general framework to options trading, thinking about it as one level up. So there’s still the stock or the market or whatever the underlying equity is, that can have value in it. But then the options themselves have their own market, microstructure, flows, and biases. It’s not enough to say, “Well, I have a view on a stock, therefore, I’m going to trade some options.” If you’re going to trade some options, you have to say, “I have a view on the stock. And there’s this interesting thing in the options that makes trading the options worthwhile relative to just trading the stock.”

So in everything that we do, it starts from some biases in the option market. Those biases in the options market take the shape of flows and imbalances that result from forced trading, yield-seeking, or bank hedging. There are actually a bunch of sources of these.

[Kris: this is what Benn Eifert means when he says “disturbances in the force”. If there were no flows all the point spreads would be fairly priced. No “willing losers”, no opportunity.]

In our case, we buy short-dated options that we believe are inexpensive because there’s an avalanche of people selling them, ranging from private banks to other managers that look like us to even big institutions. There’s a depression in a certain part of the short-dated volatility surface, particularly S&P, that we think offers very good value. That’s solely because there are yield-generating programs out there that are pushing the prices down. Then we can go out on the long end of the curve and find really good values there in certain conditions when the market sells off because of the particular dynamics of the way structured products have to be re-hedged. So we look for certain flows after a market sell-off that tells us that that’s happening and we go out and trade those options. But the point is, a good options trading program needs to start from value in the options themselves, not a statement about the underlying. Ultimately, you have to be able to make a statement about the options and a statement about the underlying together.

“Beware of hockey players”

Inevitably you come across a private bank “options expert”, right? And he’s like, “I have my strategy and it works on all underlyings because I’m going to come in and trade my call or whatever it is, right?” But really, what he’s saying is:

“I’m trading options for their payout at expiry, without a lot of regard to whether there is any relative value in the options themselves.”

Just because you can buy a put and reshape the terminal payout of the terminal distribution out that options expiry doesn’t mean that that option is underpriced. It could be overpriced, and in fact, they often are. If I buy hurricane insurance after the rates have already gone up, like Yeah, I guess I’ve mitigated my downside, but what did I pay to buy the insurance?

[Kris: see It’s Not The Merit It’s The Price]

As a general rule, whenever you hear someone giving you a pitch about derivatives that are based on its terminal payoff, and they’re drawing hockey sticks for you, your radar needs to go up.

So we have a joke: “beware of hockey players.”

[Kris: think buffered ETFs or structured products]

On breakeven arguments

The only place where I have consistently seen breakeven arguments work is in biotech or pharma, where there are very specific events. If you have knowledge about the likely outcome of an event, you can look at the breakevens and determine whether it’s a good value. I have seen this strategy work in those industries.

[Kris: I’ve seen this in nat gas as well — what’s the common link? These are all special sits types of scenarios where the distributions vary greatly from lognormal or bell-curve shapes, often having 2 more modal outcomes.]

However, during my time on an institutional dealing desk for over a decade, I only met two people who could consistently trade options for direction without paying attention to biases and make money. Even then, I’m not convinced they were making that much money trading the options.

[Kris: See my discussion of path vs destination]

Options or re-size the position?

And then you need to ask the question: why these options? What is the mispricing or value in the derivative itself? if someone comes to you and is like, well, I you know, you should get long whatever sector in the option space they need to have a really good reason for why those sector options are mispriced.

What is special about the option pricing itself that makes doing this an option better than just re-sizing the position?

Kris: this is an absolute money question!

It relates back to how options are priced with specificity:

You are paying for specificity via options because they are priced with a particular vol to a specified expiry. The offsetting benefit is you are highly levered to being right.

From If You Make Money Every Day, You’re Not Maximizing:

The beauty of options is how they allow you to make extremely narrow bets about timing, the size of possible moves, and the shape of a distribution. A stock price is a blunt summary of a proposition, collapsing the expected value of changing distributions into a single number. A boring utility stock might trade for $100. Now imagine a biotech stock that is 90% to be worth 0 and 10% to be worth $1000. Both of these stocks will trade for $100, but the option prices will be vastly different.If you have a differentiated opinion about a catalyst, the most efficient way to express it will be through options. They have the most urgent function to a reaction. If you think a $100 stock can move $10, but the straddle implies $5 you can make 100% on your money in a short window of time. Annualize that! Go a step further. Suppose you have an even finer view — you can handicap the direction. Now you can score a 5 or 10 bagger allocating the same capital to call options only. Conversely, if you do not have a specific view, then options can be an expensive, low-resolution solution. You pay for specificity just like parlay bets. The timing and distance of a stock’s move must collaborate to pay you off.

Since you pay for specificity, you need a well-formed understanding of your edge. If you’re going to trade options directionally I would want to see the specificity in your fundamental analysis that suggests these particular options are the right options to buy or sell.

It’s so easy to lose on timing or changes in vol even if you get the direction right. See:

Moontower #191

I have a beautiful book recommendation today:

Math Games With Bad Drawings by Ben Orlin

The big, bright hardcover will grace any coffee table but even better — it’s meant to be used.

notion image

From the description:

From beloved math popularizer Ben Orlin comes a masterfully compiled collection of dozens of playable mathematical games.

This ultimate game chest draws on mathematical curios, childhood classics, and soon-to-be classics, each hand-chosen to be (1) fun, (2) thought-provoking, and (3) easy to play. With just paper, pens, and the occasional handful of coins, you and a partner can enjoy hours of fun—and hours of challenge.

Orlin’s sly humor, expansive knowledge, and so-bad-they’re-good drawings show us how simple rules summon our best thinking.

The book has five sections:

  1. Spatial Games
  2. Number Games
  3. Combination Games
  4. Games of Risk and Reward
  5. Information Games

For each game you are given the rules, the “tasting notes” for the game, why the embedded math matters and how it relates to your life more broadly.

There are 3 games I bring special attention to because they relate easily to the topics discussed in Moontower.

A Game of Risk and Reward

Outrangeous

This is a multi-player version of a game that helps you tune your confidence calibration. We do a version of this when we onboard applicants to PitBulls because in trading you rarely know the “right” answer. A key meta-skill is to handicap how the odds that your proposed answer is right or wrong.

If you are overconfident in trading you make your markets too tight. That means you’ll get all the market share and find yourself sad for selling $1 bills for 95 cents.

If you are too conservative (ie too wide) in your markets or ranges you’ll never trade. You’re the person bidding 15 p/e for the SP500…go away, nobody cares about your irrelevant bid.

Calibration is a learned skill. Nobody comes out of the womb a great bettor. This is a foundational belief of training programs in trading and books like Superforecasting (see notes) or Thinking In Bets. You learn by practicing. Outrangeous is a way to practice with friends whether you’re on a long road trip or standing in line at Six Flags (a good question might be “what was the avergae number of people that visitied the theme park daily in 2022).

From Orlin:

  • What’s the goal?
    • Each answer is a number. You’ll guess a range of values. trying to make it as narrow as possible while still including the true answer.
  • What are the rules?
    • One player — the judge for the round — announces the trivia question. The other players act as guessers, each secretly writing down a range of values.
    • When everyone has committed their answer to paper, the guesses are revealed. The goal is to capture the true value, while keeping your range as narrow as possible.
    • The judge reveals the true answer. Anyone who missed the answer- no matter how painfully close they came-receives 0 points. Instead, the judge receives 1 point per wrong guess, as a reward.
    • Then, among the players with the correct answer, order them from the narrowest range (i.e., most impressive guess) to the widest range (i.e. least impressive guess.)
    • These players receive 1 point per guesser that they beat. Note they all beat anyone who missed the answer
    • Play enough rounds so that each person has an equal number of turns as judge. In the end, whoever has the most points is the winner.

Games of Information

  • Bullseyes and Close Calls

    A CLASSIC CODE-BREAKING GAME

    Under the name Mastermind, this became one of the biggest board games of the 1970s, selling as many units as The Godfather sold tickets (about 50 million, if you’re keeping score). But the game didn’t begin with those colorful plastic pegs. For a century beforehand, it was played using pen and paper, under the earthy name Bulls and Cows. Now, as an ardent bovine feminist, I reject the idea that bulls are better than cows, so I’ve renamed the former as Bullseyes and the latter as Close Calls. But feel free to use whatever words you wish. This code game, under any code name, remains a stone-code classic.

    [Kris: I’ve recommended Mastermind before. See Fun Ways To Teach Your Kids Encryption]

    WHY IT MATTERS

    Because life is a hunt for information, and humans are lazy hunters. You know this already. Either you’re human yourself, or you’re conversant enough in human culture to enjoy human books like this one. Either way, you’ve seen Homo sapiens spend hours gorging on information, then somehow emerge from the feast without an ounce of nourishment.

    Take a wretched and typical specimen: me. I subscribe to 77 podcasts, follow 600 people on Twitter, and long ago maxed out the number of open in my Wikipedia phone app. Given all this information, how informed am I? The other day my young daughter picked up a pinecone. “That’s a pinecone,” I volunteered. “It comes from a pine tree. It’s… some kind of big seed, I think?” This wasn’t a tough pitch to hit. My daughter had not picked up a quasar, a Tom Stoppard play, or the hard problem of consciousness. The truth about pinecones is definitely out there. I just didn’t know it. Nine words in, I had exhausted my knowledge.

    As a rule, humans don’t seek information in the right places. In a classic psychology study, subjects were shown four cards, each with a letter on one side and a number on the other. Then they learned a rule: A card with a vowel must also have an even number.

    The question: Which cards do you need to flip over to see if the rule has been violated?

    notion image

    Before reading further, think it over. What would you flip? If you prefer to copy off of other people’s homework, here are the most common answers from a typical iteration of the study, conducted in 1971:

    notion image

    See the notes if you want to the answer and the reasoning behind it.

  • Caveat Emptor AN AUCTION GAME

    I’m afraid I can’t teach you how to win at Caveat Emptor. But I can easily tell you the best way to lose: Just win every auction. I mean it. Play a few rounds, and you’ll find that overbidding is all too common. It’s a game marked by Pyrrhic victories, with winners forced to take home prizes for more than they’re worth. This phenomenon-losing your shirt on a winning bid is so pervasive that auction economists have dubbed it “the winner’s curse.”

    Lucky for you, Caveat Emptor offers a lot more information than the typical auction. Will that be enough for you to escape the curse?

    [Kris: See the notes for how to play and why it matters including under which conditions you’d expect to find a “winner’s curse”.

    It also reminded me of Recipe For Overpaying where I note investor Chris Schindler’s intuitive explanation for why high volatility assets exhibit lower forward returns: a large dispersion of opinion leads to overpaying. He points to private markets where you cannot short a company. The most optimistic opinion of a company’s prospects will set the price.

    Fyi, back in 2000 SIG issued all new hires a copy of Prof. Richard Thaler’s Winner’s Curse]

🔗My notes to Math Games With Bad Drawings

💗Give some love to author Ben Orlin — buy the book (I don’t know Ben and this is not even an affiliate link)

Money Angle

  • 15 Ideas From Morgan Housel’s Interview with Tim Ferriss (31 min read)
    Moontower

    This was a great interview from last summer but the content is evergreen. These were my favorite excerpts.

  • Portfolio Theory In The Wild: Funding YouTube Creators (11 min read)
    Moontower

    Business Breakdowns host Ali Hamed interviewed Spotter founder Aaron DeBevoise. Spotter is a private company that provides knowledge and capital to YouTube creators including MrBeast.

    I “spotted” 2 great examples of “portfolio theory in the wild”. I relate them back to where I’ve covered these ideas before and their implication.

Money Angle For Masochists

I introduced masochism posts in January as a separate section (in the past regular Money Angle posts would just veer into masochism without warning — thanks to readers for asking for a street sign).

The “masochism” title is a self-dig because the point is actually to bootstrap the logic of challenging financial concepts with broadly accessible intuition slowly and socratically. I will resume that practice after summer break. If you are interested in catching up:

Commentary or Qualitative Reasoning

Quantitative Reasoning


Socratic Tutorial

Stay groovy ☮️

Learn Investing Without The Brainworms

Here’s Devin from

Paid in Full

on Twitter:

The tweet reminded me of this detailed 2-part takedown of Kiyosaki (who has really expanded his reach, parlaying his fame into the doom grift stratosphere).

Excerpt with the author’s emphasis:

A number of people asked me about Robert T. Kiyosaki and his book Rich Dad, Poor Dad. When I said I didn’t think he was a real-estate guru, they insisted he was. Several told me I would like him, that he preaches a message like mine. Eager to find such a guru, I bought his book, Rich Dad, Poor Dad, in a bookstore.

Rich Dad, Poor Dad is one of the dumbest financial advice books I have ever read. It contains many factual errors and numerous extremely unlikely accounts of events that supposedly occurred.

Kiyosaki is a salesman and a motivational speaker. He has no financial expertise and won’t disclose his supposed real estate or other investment success.

Rich Dad, Poor Dad contains much wrong advice, much bad advice, some dangerous advice, and virtually no good advice.

I decided to crowdsource books that teach real estate without a side-effect of brainworms:

The replies are full of thoughtful suggestions.

Full confession…I do have a strain of contempt for real estate investing in general. I’m a bit of a Georgian at heart I guess (map to this rabbit hole –> this interview with Lars Doucet on the Lunar Society podcast with

Dwarkesh Patel).

It is a peculiar blessing in America to have an intellect so goldilocks mid that you equate being a landlord with being a “man in the arena”. For capitalism to remain a brand worth buying, its apogee cannot literally be seeking rent.

“I Love Individuals, I Hate Groups”

In Wednesday’s Munchies, I shared some “purple pills” from game designer Gabriel Leydon. It’s not warm and fuzzy.

The psychological manipulation he describes feels like fighting over scraps. The scraps might be lucrative as the internet captures whatever attention the pre-online world had a grip on, but it’s not a foundation for wide prosperity any more than a private equity roll-up. Yea, they still increment “GDP” but so did constructing the Death Star (this doubles as a Clerks reference…iykyk).

And I don’t want to fall into the same idealistic trap Leydon describes in 70s futurism to pretend that C does not R.E.A.M

But there’s a non-Shaolin-inspired “C” that also rules everything around me — confirmation bias. It doesn’t roll off the tongue as easily as “cash” but it’s becoming more it’s fungible with it. (FOXA stock price is the exchange rate)

What does that mean?

It’s getting harder to know what’s true today. That’s not news. Everything we read is through a prism. The light we shine through it is our own priors and the refraction is perfectly predictable — the projected image will be the impression that minimizes the surprise between our starting beliefs and the interpretation of the new knowledge. If they hear the word “school shooter”, a liberal auto-presumes a MAGA-hate-pilled domestic terrorist and a conservative suddenly cares about mental health or anything else not starting with the letter “g”. 25 years ago they scapegoated video games and Keanu Reeves in a trenchcoat. The point is that our minds are made up because we are lazy and surprises are cognitively expensive (in the short term).

Your prism is a cope. Or a dishwasher — it saves you time. And because our minds are already inclined to take such shortcuts, the media just needs to keep bringing food to the cell. If horoscopes didn’t already exist, I’d accuse XKCD of leaking the partisan news business model:

I have mixed feelings to report.

It’s possible to fabricate new prisms. Angled to project a wider spectrum of understanding — smarter, more empathetic, courageous. It sounds nice but there’s a problem. The allure of the prisms in front of you now is they make you feel comfortable. Self-righteous. In control.

That means it hurts to have your horizons expanded. Learning is a struggle. If it’s not, it’s just review. You can do elementary math puzzles all day and feel proud but you aren’t growing. (Which is why that “expensive” moment of surprise is so valuable — it is the learning stimulus).

And this is where the storyteller comes in. The best stories, in my unapologetically smug opinion, are the ones that burden your mind with a lack of closure. They whisper “withhold judgment”. Their ambiguity is the most honest reflection of our condition. Their objects endure mistakes, hard choices, triumphs, and redemption. But the best won’t wrap it all up in a lesson (see Roger Ebert’s 2010 review of Lost In Translation). That trains us to stay immature. Fairy tales and parables are for kids because they’re developing a conscience bit by bit.

You can tell when a grown-up hasn’t grown up. They need laugh tracks and characters with face tattoos for hints on how to feel.

After reading The Sympathizer and finishing Ken Burns’ 20-hour Vietnam documentary, I’m again humbled by how complicated and inconsistent we are. Such stories grab us by the face and force us to look at our hands and what they’re capable of. At both extremes. (1 min clip by one of the veterans on war being “finishing school”).

The importance of (good) stories in raising our self-awareness came to me obliquely. I just finished that 4-hour George Carlin documentary on HBO Max. I really enjoyed it but the line that keeps echoing:

People are wonderful. I love individuals. I hate groups of people. I hate a group of people with a ‘common purpose’. ‘Cause pretty soon they have little hats. And armbands. And fight songs. And a list of people they’re going to visit at 3am. So, I dislike and despise groups of people but I love individuals. Every person you look at; you can see the universe in their eyes, if you’re really looking.

It’s a reminder. The best stories are written in our lives. You just have to get together to hear them.

Happy Mother’s Day

 

 

Moontower #190

Friends,

In Wednesday’s Munchies, I shared some “purple pills” from game designer Gabriel Leydon. It’s not warm and fuzzy.

The psychological manipulation he describes feels like fighting over scraps. The scraps might be lucrative as the internet captures whatever attention the pre-online world had a grip on, but it’s not a foundation for wide prosperity any more than a private equity roll-up. Yea, they still increment “GDP” but so did constructing the Death Star (this doubles as a Clerks reference…iykyk).

And I don’t want to fall into the same idealistic trap Leydon describes in 70s futurism to pretend that C does not R.E.A.M

But there’s a non-Shaolin-inspired “C” that also rules everything around me — confirmation bias. It doesn’t roll off the tongue as easily as “cash” but it’s becoming more it’s fungible with it. (FOXA stock price is the exchange rate)

What does that mean?

It’s getting harder to know what’s true today. That’s not news. Everything we read is through a prism. The light we shine through it is our own priors and the refraction is perfectly predictable — the projected image will be the impression that minimizes the surprise between our starting beliefs and the interpretation of the new knowledge. If they hear the word “school shooter”, a liberal auto-presumes a MAGA-hate-pilled domestic terrorist and a conservative suddenly cares about mental health or anything else not starting with the letter “g”. 25 years ago they scapegoated video games and Keanu Reeves in a trenchcoat. The point is that our minds are made up because we are lazy and surprises are cognitively expensive (in the short term).

Your prism is a cope. Or a dishwasher — it saves you time. And because our minds are already inclined to take such shortcuts, the media just needs to keep bringing food to the cell. If horoscopes didn’t already exist, I’d accuse XKCD of leaking the partisan news business model:

I have mixed feelings to report.

It’s possible to fabricate new prisms. Angled to project a wider spectrum of understanding — smarter, more empathetic, courageous. It sounds nice but there’s a problem. The allure of the prisms in front of you now is they make you feel comfortable. Self-righteous. In control.

That means it hurts to have your horizons expanded. Learning is a struggle. If it’s not, it’s just review. You can do elementary math puzzles all day and feel proud but you aren’t growing. (Which is why that “expensive” moment of surprise is so valuable — it is the learning stimulus).

And this is where the storyteller comes in. The best stories, in my unapologetically smug opinion, are the ones that burden your mind with a lack of closure. They whisper “withhold judgment”. Their ambiguity is the most honest reflection of our condition. Their objects endure mistakes, hard choices, triumphs, and redemption. But the best won’t wrap it all up in a lesson (see Roger Ebert’s 2010 review of Lost In Translation). That trains us to stay immature. Fairy tales and parables are for kids because they’re developing a conscience bit by bit.

You can tell when a grown-up hasn’t grown up. They need laugh tracks and characters with face tattoos for hints on how to feel.

After reading The Sympathizer and finishing Ken Burns’ 20-hour Vietnam documentary, I’m again humbled by how complicated and inconsistent we are. Such stories grab us by the face and force us to look at our hands and what they’re capable of. At both extremes. (1 min clip by one of the veterans on war being “finishing school”).

The importance of (good) stories in raising our self-awareness came to me obliquely. I just finished that 4-hour George Carlin documentary on HBO Max. I really enjoyed it but the line that keeps echoing:

People are wonderful. I love individuals. I hate groups of people. I hate a group of people with a ‘common purpose’. ‘Cause pretty soon they have little hats. And armbands. And fight songs. And a list of people they’re going to visit at 3am. So, I dislike and despise groups of people but I love individuals. Every person you look at; you can see the universe in their eyes, if you’re really looking.

It’s a reminder. The best stories are written in our lives. You just have to get together to hear them.

Happy Mother’s Day

Money Angle

Here’s Devin from

Paid in Full

on Twitter:

The tweet reminded me of this detailed 2-part takedown of Kiyosaki (who has really expanded his reach, parlaying his fame into the doom grift stratosphere).

Excerpt with the author’s emphasis:

A number of people asked me about Robert T. Kiyosaki and his book Rich Dad, Poor Dad. When I said I didn’t think he was a real-estate guru, they insisted he was. Several told me I would like him, that he preaches a message like mine. Eager to find such a guru, I bought his book, Rich Dad, Poor Dad, in a bookstore.

Rich Dad, Poor Dad is one of the dumbest financial advice books I have ever read. It contains many factual errors and numerous extremely unlikely accounts of events that supposedly occurred.

Kiyosaki is a salesman and a motivational speaker. He has no financial expertise and won’t disclose his supposed real estate or other investment success.

Rich Dad, Poor Dad contains much wrong advice, much bad advice, some dangerous advice, and virtually no good advice.

I decided to crowdsource books that teach real estate without a side-effect of brainworms:

The replies are full of thoughtful suggestions.

Full confession…I do have a strain of contempt for real estate investing in general. I’m a bit of a Georgian at heart I guess (map to this rabbit hole –> this interview with Lars Doucet on the Lunar Society podcast with

Dwarkesh Patel).

It is a peculiar blessing in America to have an intellect so goldilocks mid that you equate being a landlord with being a “man in the arena”. For capitalism to remain a brand worth buying, its apogee cannot literally be seeking rent.

Ok, enough restrained ranting, let’s brain burn like the masochists Moontower readers are…

Money Angle For Masochists

4 years ago in a short post called Get A New X-Axis I hinted at the concept of “variance time”:

In options trading, models assume time passes linearly but we know market volatility is lumpy. It’s concentrated on business days and even within business days, it’s concentrated near the open and the close. Not all hours are created equal. An option barely erodes on a Saturday but decays off a cliff after a stock reports earnings. Option traders adjust for this behavior by specifying a schedule by which “variance” passes as opposed to time.

If you think of an option as insurance, the value of the contract decays at a non-constant rate. By analogy, imagine having a Carribean travel insurance policy that you secure for a year. The value of that policy will remain fixed for the first 9 months of the year then plummet after the hurricane season. Time passed linearly but the risk that is being insured against decays rapidly as we progress through the storm season.

This week I published a detailed walk-thru of the concept and how to “clean” naive or “dirty” measures of implied volatility. If you use any off-the-shelf software you are looking at a “dirty” volatility. Whether you should take the effort to clean them up depends on why you are ingesting implied volatility data (the market’s consensus about volatility derived from option prices) in the first place.

My experience has been that the topic of “variance time” puts people’s heads in a blender. I use repetition and light Socratic techniques to bootstrap the topic so even a relative novice can at least understand the shape of the problem. A more advanced reader will be able to use this post to build their own model.

The topic is fascinating. And as recently as 15 years ago, comprehending it was a major source of edge. With 0DTEs and options that expire every business day, this concept has never been more important.

I’d deem this post a success if it’s the link pros handed to their trainees or risk support and said “I’m tired of explaining this, here’s a guide so you can re-read at your own leisure”.

For retail traders, this post is nothing more than a nerdsnipe.

Enjoy:

Understanding Variance Time

Life As A Tournament

Let’s start with this single reply in a thread that caught fire.

I encourage you to scroll the thread — it’s like having a listening device inside a confessional. Every living generation’s gripes being aired out. Enough baggage to weigh down an Airbus A380.

If you have been reading Moontower for at least 2 years you know where some of my sympathies lie:

In Adding My .02 To The WSB Insanity, I offered:

A hypothetical.

Suppose there are 15 courses of actions one can take. 5 are illegal, 5 more are unethical. That leaves 5 acceptable actions. It feels like our collective calculus is moving to a rule of “if it’s legal, why not?”

The ethics ozone layer between what’s legal and what we should do is fully depleted. The air is irrevocably polluted. I’m not pointing fingers solely on daytraders who are openly coordinating behavior in ways that stun anyone who has ever sat through securities compliance training. There is a sense that the game is rigged and while I think the specific targets in these trading examples are misdirected, it certainly feels that way in a broader sense. Especially when we consider the runaway examples of inequality I’ve discussed [see Is Social Harmony The Last Collateral?]

The last tweet in the side chat below is an echo of Adam Singer’s tweet at the start of this post.

Browsing Twitter this week I saw an account announce that people have an imperative to make as much money as they want within the confines of the law.

Look, last week I admit I have a fast cringe reflex. Hustlers are quick to say that instead of abstaining from cringey activity, the key to your dreams is killing the cringe reflex. This is reasonable. And that’s why it’s dangerous — it’s written in the same ink as the grift manuals. It’s the raw material for collapsing the firewall known as ethics that runs along the letter of the law and its spirit. It takes but 1 second of second-order reasoning to understand this does not scale. The proverbial picture replacing 1000 words:

Annoyed by the profit-as-religion tweet, I crafted a thread response (because I’m childish) and the janky Twitter app failed to send it. 4x. There was 2 silver linings to my frustration:

  1. I deleted the Twitter app (again)
  2. I hopped on a video call with Dave, Tom and Adam — a group of investors who have been thinking deeply about how we climb out of the collective Molochian quicksand.Here’s the recording:PolyCrisis, Institutional Decay, and AI in Q2 2023: An Update with Dave Nadig (53 min)

There’s a sense that life is increasingly turning into a tournament. There will always be some group of psychopathic wealthy with self-serving comprehensions of evolution and a strain of ambition who would have been warlords in a different era. Today, most of those outliers express their sociopathy in token-collecting.

But there’s a thick layer of grounded rich people who don’t feel rich enough because they see the minimum acceptable life as becoming increasingly unattainable for younger generations and their perfectly rational individual response is to make even more money so they can self-insure their children’s safety nets. This mindset taken to its extreme closes the self-fulfilling behavior loop promoted by the cringe-merchants.

I guess if prisoner’s dilemmas were a cinch to solve we wouldn’t have needed Nash-level minds wasting cycles on them. But alas, it’s still fun to bang your head on such puzzles.

If you are interested, Dave hosted a panel at a conference with Adam, Tom and several finance minds to discuss these topics. I reached out to tell him how much I enjoyed it. Our ongoing conversations on these subjects is what earned my naive role on the video call in the first place — the Straussian inference here is to listen to the panel talk if you only have time for one.

  • Exchange 2023 – The Future of Finance (98 min)

You Think You’re Trading Vol….But Are You Even?

Option amateurs underappreciate the role of funding in pricing derivatives. Professional options traders need to be obsessed with funding costs because they are trading for tiny, often sub-penny, margins.

Here’s a simple example to demonstrate the tyrannical effect of funding on pricing:

What is a 1-year American at-the-forward call option on a non-div paying, 20% implied vol, $100 stock worth?

You need to feed the model an interest rate to get an answer. You look at the yield curve and see a 5% rate (making this up) for 1 year. This yields a forward price of $105 (we can hand-wave simple vs compounded rates for this purpose).

Imagine the bid-ask for this call is 40 cents wide $7.80 – $8.20

If you buy on the bid and sell on the offer you make a .40 profit. Easy-peasy.

Now imagine you buy the bid and hedge the position until expiry. What implied vol did you buy?

The first thing to recognize is that you will be shorting the stock to hedge. Assuming it’s easy to borrow, you are still not going to receive a 5% rate on the cash proceeds. Your prime broker needs to earn its margin. If 5% is the risk-free rate, let’s assume they pay you 4.5% on cash balances. Conversely, the prime broker will lend at 5.5% (this is known as the “long rate” and it’s the rate you finance long positions at). If you sell the call on the offer you will need to pay that rate to finance the shares you buy.

Uh oh.

If you buy the call you need to use a 4.5% rate in the model to back out an implied vol and if you sell the call you need to use a 5.5% rate in the model. You can see where this is going.

  • If you buy the call on the bid you are paying 20.06% implied vol.
  • If you sell the call on the offer you are selling 19.95% implied vol.

(Check the math if you want)

You think you’re trading vol but because of the bid-ask spread on your funding rate, you are basically trading the same implied vol even if you buy the bid and sell the ask. Rho is the sensitivity of the option price for a 1% change in the interest rate. The vega of an option is the sensitivity of its price for a 1-point change in volatility.

The rho of this call option is 46 cents vs a vega of 40 cents.

A 1% difference in funding rate (ie 4.5% vs 5.5%) is an institutional level bid-ask. It can be much worse for retail.

If you are trying to make markets you think you’re trading vol but are you even?

Pricing and carrying longer-dated options is crucially dependent on funding costs and the bid-ask spreads might not even be wide enough to compensate a market maker for their funding spread. Another way of saying this: the market-maker with such a 1% wide funding rate is making a 20% “choice” market in the vol. If the bid-ask was tighter they would be bidding a higher vol than they were offering!

(Again this assumes they hold and manage the position as opposed to spreading the options off by say buying one call and selling another or having the privileged position of just getting ping-ponged on their posted bid-ask all day)

Moontower #189

Friends,

Let’s start with this single reply in a thread that caught fire.

I encourage you to scroll the thread — it’s like having a listening device inside a confessional. Every living generation’s gripes being aired out. Enough baggage to weigh down an Airbus A380.

If you have been reading Moontower for at least 2 years you know where some of my sympathies lie:

In Adding My .02 To The WSB Insanity, I offered:

A hypothetical.

Suppose there are 15 courses of actions one can take. 5 are illegal, 5 more are unethical. That leaves 5 acceptable actions. It feels like our collective calculus is moving to a rule of “if it’s legal, why not?”

The ethics ozone layer between what’s legal and what we should do is fully depleted. The air is irrevocably polluted. I’m not pointing fingers solely on daytraders who are openly coordinating behavior in ways that stun anyone who has ever sat through securities compliance training. There is a sense that the game is rigged and while I think the specific targets in these trading examples are misdirected, it certainly feels that way in a broader sense. Especially when we consider the runaway examples of inequality I’ve discussed [see Is Social Harmony The Last Collateral?]

The last tweet in the side chat below is an echo of Adam Singer’s tweet at the start of this post.

Browsing Twitter this week I saw an account announce that people have an imperative to make as much money as they want within the confines of the law.

Look, last week I admit I have a fast cringe reflex. Hustlers are quick to say that instead of abstaining from cringey activity, the key to your dreams is killing the cringe reflex. This is reasonable. And that’s why it’s dangerous — it’s written in the same ink as the grift manuals. It’s the raw material for collapsing the firewall known as ethics that runs along the letter of the law and its spirit. It takes but 1 second of second-order reasoning to understand this does not scale. The proverbial picture replacing 1000 words:

Annoyed by the profit-as-religion tweet, I crafted a thread response (because I’m childish) and the janky Twitter app failed to send it. 4x. There was 2 silver linings to my frustration:

  1. I deleted the Twitter app (again)
  2. I hopped on a video call with Dave, Tom and Adam — a group of investors who have been thinking deeply about how we climb out of the collective Molochian quicksand.Here’s the recording:

    PolyCrisis, Institutional Decay, and AI in Q2 2023: An Update with Dave Nadig (53 min)

There’s a sense that life is increasingly turning into a tournament. There will always be some group of psychopathic wealthy with self-serving comprehensions of evolution and a strain of ambition who would have been warlords in a different era. Today, most of those outliers express their sociopathy in token-collecting.

But there’s a thick layer of grounded rich people who don’t feel rich enough because they see the minimum acceptable life as becoming increasingly unattainable for younger generations and their perfectly rational individual response is to make even more money so they can self-insure their children’s safety nets. This mindset taken to its extreme closes the self-fulfilling behavior loop promoted by the cringe-merchants.

I guess if prisoner’s dilemmas were a cinch to solve we wouldn’t have needed Nash-level minds wasting cycles on them. But alas, it’s still fun to bang your head on such puzzles.

If you are interested, Dave hosted a panel at a conference with Adam, Tom and several finance minds to discuss these topics. I reached out to tell him how much I enjoyed it. Our ongoing conversations on these subjects is what earned my naive role on the video call in the first place — the Straussian inference here is to listen to the panel talk if you only have time for one.

  • Exchange 2023 – The Future of Finance (98 min)

Money Angle

  • Flirting With Models: Designing the Cockroach Portfolio (55 min)Corey Hoffstein interviews Jason Buck. I’ve hyped the hell out of these guys before (The Most Underrated Finance Channel On YouTube) because I want you to see why I weaseled my way into being their friends. They are brilliant guys who don’t take themselves too seriously. And their investing approaches are highly resonant with the principles I espouse in Moontower.

    It’s very much why I’m an investor in Jason’s cockroach fund and had Mutiny be the first sponsor of this letter. I knew Jason before he ever launched this fund and was honored to be a general sounding board on his ideas. I can’t believe how well he synthesizes and articulates complex trade-offs so the average investor can understand. The whole episode goes down extra-easy because Jason is the Dos Equis guy.

    Don’t miss this one.

  • The Mindful Money Playbook (RadReads)”Reimagine your relationship to money, status and joy”

    I’d like to say I have a hand in this because I’ve been urging Khe to re-factor and package his thoughts about money and life into a book. He thinks and communicates lucidly for laypeople despite a highly professional background (months after we got to know each other I learned that when he was at Blackrock he was on the team that studied the types of strategies I worked in!).

    The book is totally free and built on Notion.

  • How To Get Rich (Netflix)Ramit Sethi is one of the personal finance gurus I recommend (there’s a lot of nonsense out there). Yinh and I started watching these 8 30-minute episodes and I’m struck out how good Ramit is at meeting people where they are in terms of dealing with their finances. He is a perfect mix of tough but compassionate and this is not easy when mass media often selects for a more mono-approach to establish a brand. Instead, Ramit builds his message and therefore brand around the concept of “how to build YOUR rich life” which means questioning conventional wisdom and ruthlessly cutting desires which are not truly yours while doubling-down on what you care about.

    I’ve wrote about him 4 years ago and his message is still the same. See He Will Teach You To Be Rich (2 min read)

Money Angle For Masochists

Option amateurs underappreciate the role of funding in pricing derivatives. Professional options traders need to be obsessed with funding costs because they are trading for tiny, often sub-penny, margins.

Here’s a simple example to demonstrate the tyrannical effect of funding on pricing:

What is a 1-year American at-the-forward call option on a non-div paying, 20% implied vol, $100 stock worth?

You need to feed the model an interest rate to get an answer. You look at the yield curve and see a 5% rate (making this up) for 1 year. This yields a forward price of $105 (we can hand-wave simple vs compounded rates for this purpose).

Imagine the bid-ask for this call is 40 cents wide $7.80 – $8.20

If you buy on the bid and sell on the offer you make a .40 profit. Easy-peasy.

Now imagine you buy the bid and hedge the position until expiry. What implied vol did you buy?

The first thing to recognize is that you will be shorting the stock to hedge. Assuming it’s easy to borrow, you are still not going to receive a 5% rate on the cash proceeds. Your prime broker needs to earn its margin. If 5% is the risk-free rate, let’s assume they pay you 4.5% on cash balances. Conversely, the prime broker will at 5.5% (this is known as the “long rate” and it’s the rate you finance long positions at). If you sell the call on the offer you will need to pay that rate to finance the shares you buy.

Uh oh.

If you buy the call you need to use a 4.5% rate in the model to back out an implied vol and if you sell the call you need to use a 5.5% rate in the model. You can see where this is going.

  • If you buy the call on the bid you are paying 20.06% implied vol.
  • If you sell the call on the offer you are selling 19.95% implied vol.

(Check the math if you want)

You think you’re trading vol but because of the bid-ask spread on your funding rate, you are basically trading the same implied vol even if you buy the bid and sell the ask.

Rho is the sensitivity of the option price for a 1% change in the interest rate. The vega of an option is the sensitivity of its price for a 1-point change in volatility.

The rho of this call option is 46 cents vs a vega of 40 cents.

A 1% difference in funding rate (ie 4.5% vs 5.5%) is an institutional level bid-ask. It can be much worse for retail.

If you are trying to make markets you think you’re trading vol but are you even?

Pricing and carrying longer-dated options is crucially dependent on funding costs and the bid-ask spreads might not even be wide enough to compensate a market maker for their funding spread.

Another way of saying this: the market-maker with such a 1% wide funding rate is making a 20% “choice” market in the vol. If the bid-ask was tighter they would be bidding a higher vol than they were offering!

(Again this assumes they hold and manage the position as opposed to spreading the options off by say buying one call and selling another or having the privileged position of just getting ping-ponged on their posted bid-ask all day)