The Moontower Volatility Wiki

Many beginners to options ask me and other professionals what they should read to learn options. I’ve seen this question asked enough times that I built a wiki that I can reference instead of needing to come up with an answer every time.

Voila…The Options Starter Pack (Link)

In the process of curating that I figured why not go the extra step…Introducing the Moontower Volatility Resources wiki (Link)

In addition to Moontower trading content, you will find select options content from the rest of the online vol community.

To maximize how useful this wiki there are a 2 important points.

  1. I will be keeping this wiki updated, but it is not open source. At this time, I think readers are best served knowing I’ve pre-screened submissions.
  2.  If you find a blog, book, video, interview, etc that you feel deserves to be here please submit it. I won’t guarantee I’ll include it but the benefit is we can keep this resource high quality and free of spam.

So there’s a tension involved…one side is that in order for this to be useful it can’t be a free-for-all. If you want a free-for-all there’s Reddit and Twitter and upvoting and ‘like’ buttons. This is not that. This is intended to be a reference with evergreen content subject to my standards. Like any manner of gatekeeping, I will miss things and I might let subpar stuff slide in. Sorry in advance. I’m always open to hearing suggestions/complaints. You’ll need to trust that I’m competent and care.

The other half of this tension is it requires engagement even though it’s not open-source. If you come across a source, a tool, a course or anything that fits neatly with this wiki then please share it.

Finally, here’s the excerpt from About This Wiki:
Option strategies range from directional hedging/speculation to the complexity of index dispersion portfolios and exotic structured product books. You cannot learn to trade options from reading. It is a craft and your understanding of it comes much faster when you have a position. When the feedback of the position comes in the form of mark-to-market p/l you learn what the position is sensitive to. Greeks like delta, gamma, and vega are immediately less abstract.

The good news is I believe any numerate, motivated person can learn options.

The bad news is two-fold:

  1. Experience is expensive.
  2. It is a craft best learned as an apprentice.

#1 is unavoidable. Straight talk — you will lose money learning. Guaranteed. Act accordingly. Don’t sell naked options and make sure worst-case scenarios are tolerable. Bid/asks are expensive. Sure, they might only be a few pennies, but 1 cent on a $1 option is 1% slippage. That’s 10-100x the slippage you pay to trade stock. Vast fortunes have been built on that 1% slippage. It will grind you as surely as a blackjack dealer if you play long enough without an edge.

#2 has better news. The internet in the form of blogs, podcasts, electronic brokerage and social media (esp Twitter) has never made it easier for a voracious learner to educate themselves, find mentors, and have meaningful discussions that would have been impossible even as recently as 2000 when I got into options trading.

I was fortunate to discover options trading right as I graduated college. I joined Susquehanna (SIG) and learned how to think about options, risk, and trading from Jedis. Their curriculum and methods for teaching were so comprehensive, tested, and systematized that it was a massive source of competitive advantage. The cared deeply about cultivating talent. They did not care if you knew what an option or interest rate was when they hired you. They looked for drive and aptitude only since they were secure in their ability to teach everything you needed to start managing a portfolio in as few as 18 months out of college.

I am not a math whiz. I was one of the <5% of hires who got a higher score on verbal than math SAT. Options intimidate many people simply because of the Greek letters and the math behind the models. I get it. I’m intimidated by math whizzes too. I have no more than HS Calc BC math education and a single stats course in undergrad. But the truth is, you don’t need to be able to derive Black-Scholes any more than billiards champ needs to know physics. Don’t get me wrong — the intuition behind the models is critical but the bar to acquire that is much lower than a math degree.

Much of my writing is an attempt to bring the reader to an intuition of the math in the same way that I was taught. I hope it’s even more accessible since my own weakness in math makes it easy to imagine being in the average reader’s shoes.

This wiki sits in that sparse space in-between the basics you might learn from the Series 7 and the nerdom that is derivatives structuring at a French bank. This is that mushy practical area in-between sophisticated retail and professional vanilla options user. It is an area, that will become more popular thanks to the boom in retail option activity and r/WSB. The vig and risk of options is going to weed out many of the new tourists but the few who persevere and have a deeper thirst to learn should find this wiki helpful.

And for the finance professionals who use options directionally but do not “trade volatility”, the resources found here might be just the bridge you need to understand volatility surfaces a bit better. This can improve your trade expressions, risk management, timing and ultimately executions.

If you have feedback, my door is always open.


ERCOT Island

Texas power is administered by ERCOT which supplies electricity to 90% of Texas and 25mm people. I actually had a chance to learn quite a bit about power trading in Texas some years ago when I was looking at a fund that just electricity in TX. Coming from listed futures world where you might look at PJM futures, it was interesting to dig into ERCOT. It’s most distinctive property — it is not connected to any other grid in the US. It’s an island.

This fact resurfaces in interesting ways. But before we get to that, 2 bullet points:

  • ERCOT has 85% thermal fuel stack (coal and gas mostly), 5% nuclear, wind/solar <10%
  • In an extreme weather event there are allowances for outages. In other words, they expect some amount of failure. They call it Extreme Generation Outages During Extreme Peak Load. (via @JesseJenkins)

Here is an example of how things become uselessly politicized instantly. As the failures started happening, there were reports that renewables like wind and solar were not doing their job as the turbines had frozen. Well, this is one of those easily manipulated half-truths. Yes the wind and solar were incapacitated, but within the range of what’s expected. At times they overperformed and at times they underperformed.

The real story was how the thermal sources, which comprise most of the capacity anyway, failed due to pipe freezes and fuel shortage. In an extreme case they were expected to lose 20% capacity and they have lost closer to 40%. This says nothing about the relative merits of thermal versus renewables. It’s more to point out how the narratives become twisted.

But political winds blow both ways.

Conservative values faced criticism as the tight budgets were seen as the culprit. A culture of frugality with public funds was painted as insensitive. Capitalist corner cutting that comes back to haunt you in a disaster. I get it. Is the cost-cutting mentality creating value or underpricing benefits? Maybe Texas was penny wise and pound foolish.

But it’s not that simple. Byrne Hobart pulled data that showed that TX pays 20% less than the national average for electricity.

I don’t know what to say. I just have questions:

  • What is driving those savings?
  • Were those savings pulled from measures that might have mitigated the effects of this once-in-a-generation cold streak?
  • Should the state divert some of those savings into a disaster fund?
  • If these events are so rare, why would we expect low-margin energy utilities to underwrite plants that will be stranded assets 99.9% of the time?
  • What does it cost to weatherize plants and fuel sources? Who’s bears that cost?
  • Covid exposed how hyper-optimized our supply chains are. Is there a parallel story here? Do we have too much MBA mentality in places where we need engineering principles like redundancy & points of failure?

Ultimately, will the isolation of ERCOT be proven to have been worthwhile? The history of ERCOT and public works in TX is couched in that southern “don’t tread on me spirit”. No power. Tough luck. Should have had a generator. The tradeoffs and complexity of how public goods was on full display in Texas this past week. John Arnold, probably the most knowledgeable human on energy economics on the planet, frames the debate well here:

The story of the Texas chill is a political story, an engineering story, a weather story, an economics story, but most importantly a human story.

A Former Market Maker’s Perception of PFOF

It feels like payment for order flow controversies flare up every few years. When I see some of the takes I know how marine biologists felt after Jaws hit the cinemas in 1975.

Except they didn’t have Twitter to scream into.

I’m going to assume you already know what payment for order flow is.

If you need the basics, A16’s Alex Rampell and Scott Kupor have you covered. (Link)
If you want the GOAT of high finance’s version, here is the Matt Levine post I shared last week. (Link)

Now if you stop at Levine’s post I’d forgive you. There’s really no following that guy. But now that I’ve said that, you own the downside of reading further and if I say anything useful here I’m in-the-money.

I think my experience qualifies me to hopefully add some perspective to the discussion. I have been trading options for 21 years with the first half of those years on the floor. Even though I’ve been trading prop for the past decade I’m a dyed-in-the-wool market-maker. You can take the dog off the floor, but you can’t take the floor out of the dog. (Full disclosure: I used to work for SIG who was an early payer for order flow, but I had no insight into that side of their business).

An Image Problem

Payment for order flow sounds terrible. It sounds like payola. Greasing the radio DJ to get your record played on-air. That’s a bribe to the regional gatekeeper. There’s widespread misconception that when Citadel pays for flow it’s attempting to use the info to front-run the order. This is a dizzying misconception.

No trader thinks front-running random retail flow makes any sense.

Write that on a chalkboard 50x please.

The Nature of Adverse Selection

Drive it home: no trader thinks front-running random retail flow makes any sense.

In fact, the opposite is true. The entire basis of trading against retail flow is that it is a random mix of buys and sells and not autocorrelated. You want to trade against your drunk uncle Sal who has a good feeling about the Jets this Sunday. We call this “dumb” flow. Sorry, but that’s what it’s called.

On the other hand, we refer to institutional flow as “smart flow”. Not because it knows which direction the stock is going to go, although this can be the case as anyone who has been contra to SAC flow back in the day can attest. The reason we don’t want to trade against the flow is that it’s autocorrelated. 1,000 shares is the tip of an iceberg. Nobody eats just one chip just as nobody buys just 1,000 shares.

The options equivalent is putting someone up on a trade, only to have them reload 5 minutes later. This past fall, Softbank string-raised tech calls every day for a couple weeks. Masa-son is not smart paper, but he has a big stack. Truthfully, the threshold to be an undesirable counterparty is surprisingly low. I remember hearing a SIG trader at a conference a few years after I left. He mentioned that their studies had shown that the adverse selection of an options trade went up dramatically once it was greater than 16 lots.

Let’s understand this. Consider a pro-rata exchange where your limit bid is on equal standing with other limit bids but your fill is proportional to your size. So let’s say you are bidding $1.25 for 100 option contracts and the total bid quantity is 1000. If a retail sized order sells the bid for 10 contracts, you get filled on 1 because your size was 10% of the total displayed size. The pro-rata system (vs maker-taker which is a queue based on speed) incentivizes traders to show far more liquidity than they really want to. They don’t want to get their whole bid hit but they need to show size to be entitled to any reasonable percentage of the incoming orders. When an order sweeps the book, banging out the displayed size on the bid, the market makers are instantly sad. They know they are on the wrong side of a “smart” order.

The possibility that the flow you trade against is adverse, smart, institutional – whatever you want to call it – has a deep implication. You make a wider market than you would have if you could just tell the difference between the adverse flow and the random retail flow.


The brokers have realized they can segment the market between orders that can be facilitated on tighter spreads and those that require wider quotes. Liquidity has a price. Without PFOF, spreads need to be cushioned by the probability that an order is institutional. Instead, PFOF creates a tiered market where the cost of liquidity is proportionally aligned with the risk on a per trade basis. Retail traders get better fills. There’s less deadweight loss.

Institutional traders might complain, but its an illusion that they should have gotten the price that a retail trader should get. The risk business is not the widget business. You don’t get volume discounts.

“The opportunity to trade against random flow” as a source of revenue is a bit abstract. You are already familiar with price discrimination in other domains.

  • Casino’s attracting whales.

    Casinos don’t like card counters, they want customers that have positive LTV in the long run. They like whales and the type of people who buy books titled “The Fool-Proof System To Beating Roulette”. Casinos are paying for order flow when they offer complimentary suites and blacked out SUVs to and from McCarran.

  • Ad tech

    What is the internet but reams of data on customers being sold to the highest bidder so platforms (the brokers in our analogy) and in turn vendors (the Citadels) more can more efficiently convert sales (trades)?

  • Financial products

    Good driver discounts on auto policies. Life insurance physicals. Credit checks for loans. Price discrimination based on risk is the norm not the exception.

  • Retail

    As a broke 20 year old I used to frequently buy and return products at GNC. Yes, you can return a half-used tub of creatine. GNC started keeping tabs as a policy. I get it. The Ponderosa wishes it could turn away Joey Chestnut.


The discourse around PFOF has an air of monopoly sentiment. Maybe not in the Standard Oil sense of the world. There’s more firms than Citadel. You have Virtu, G1 (SIG), Two Sigma, Wolverine. It looks more like OPEC.

But there’s a big difference. These are not natural monopolies or crony handouts. Contrast the dynamic with payola. Payola was a scam that worked because the value of the bribe to the briber (the record label) was very low compared to the payoff of getting radio exposure. Meanwhile the value of the bribe was substantial to the receiving DJ who was paid a conventional salary despite being the caretaker of a government monopoly — airwaves.

I don’t think it’s surprising that high fixed cost industries settle into oligopoly-type hierarchies. The competitive forces are so strong that they double as high barriers to entry. The HFT-firms here are not defending natural monopolies. They are the survivors of the trading game who invested heavily in technology early. @hidenotslide explains in his recent post about another storied traded firm, DRW:

This brings me to my first point – firms who embraced HFT early in its evolution are today’s kings. Of the 10-20 firms that make up the bulk of high frequency trading profits, a large majority were launched before the 2008 financial crisis and many even prior to 2000. Because superior technology leads to direct competitive advantages in HFT, barriers to entry have become insurmountable over the last decade as companies have invested in ever faster exchange connections & market data feeds. A 2017 paper from researchers at Cornell & Penn argues this exact point – newer, smaller entrants that engage in HFT can survive, but they don’t get anywhere near the share of profits that larger, more established firms enjoy.

What’s absent from the narrative is how tall the pile of bodies these firms stand atop. I should know. I used to be able to work five hours a day (NYMEX alum holla) and make a lawyer’s wage. And in some years, a law partner’s carry too. Well, if you were smart you saved your money and realized it wasn’t going to last. The days of “locals” (ie wildcat market-makers) is long gone.

Many of the small firms, who saw the writing on wall and had an appetite for the long game, plowed money back into massive technology capex. Most of them just earned the right to say they lost to the best. In some cases they found small, profitable niches where they play the role of suckerfish. Respect to them, even this was not easy.

How about the remaining firms? The private giants the media likes to call “shadowy”. They were the ones who were most adept at assembling teams of software and hardware engineers working with game-theory geniuses to devise algos in a cat-and-mouse battle with competitors. The ones who stayed step-for-step with the exchanges who themselves were experimenting with matching engine rules, data, product listings and connectivity in their own battles for market share.

The truth is progress is cutthroat.

I remember the days before decimalization where you could make $5 wide verticals 3/8 wide. Today that same vertical is a choice market and the market maker gets paid the equivalent of an inter-dealer broker commission or about 25 cents. On a 3/8 wide market the market maker used to earn nearly $18.75 (or 50% of 3/8)! My business partner and I always marvel at the innovation and how little vig a trader is willing to accept to flip million dollar coins. It’s such a flex for capitalism. So much so that how good these firms are is chalked up to monopoly and not that fact that they are the survivors of the capitalism’s most brutal tournament.

How Survivorship Bias Makes Firms Look Like Monopolies

Perhaps I should not be surprised at the monopoly sentiment. Some of you will nod. “How can they make money every day?” First, I’m not sure they do, but even if they did that’s hardly a red flag. Casinos might make money every day so long as they can open. They’re not monopolies. Worrying that financial firms make money everyday is conflating market makers with investment managers because they traffic in the same products. But one of them is a customer and the other is a supermarket. With tiny supermarket margins per trade. And high fixed costs. If volumes dried up, the losses would show up even if the margins stayed flat.

A stronger, but still naïve argument, that they were monopolies would come from noticing that these shops came of age at the same time as the giant tech firms. This is a hint of how much they have in common. The difference is the size of the relative opportunities, but the tactics are similiar.

It started with skill and luck. The early big bets on talent and technology meant they were bringing guns to a knife fight. SIG wasn’t know as the “evil empire” on the Amex just because of the black jackets we wore. They understood the risk-reward was completely outsized to what it should be 25 years ago. They were amongst the first to tighten markets to steal market share. They accepted slightly worse risk-reward per trade but for way more absolute dollars. They then used the cash to scale more broadly. This allowed them to “get a look on everything”. Which means you can price and hedge even tighter. Which means you can re-invest at a yet faster rate. Now you are blowing away less coordinated competitors who were quite content to earn their hundreds of percent a year and retire early once the markets got too tight for them to compete.

SIG was playing the long game. The parallels to big tech write themselves. A few firms who bet big on the right markets start printing cash. This kicks off the flywheel:

Provide better product –> increase market share –> harvest proprietary data. Circle back to start.

The lead over your competitors compounds. Competitors die off. They call you a monopoly.


Thus far I’ve only pushed back against the idea that PFOF is somehow nefarious. It is a form of price discrimination. The price discrimination is economically sensible when we price liquidity. There is a cost to having someone trade with you at the exact moment you want to trade. If you are a retail trader, that cost is tiny and we can thank technology and the competitive drive of very smart people to undercut one another so they can be the best bid for your business.

If you are an institutional trader that cost is higher. And it should be. Your cost to trade should be compared to your historical cost to trade. Not against what a retail trader’s costs are. I’d be shocked if an apples-to-apples TCA showed that this cost has increased over time. My null is the cost to trade for everyone has collapsed but probably more for retail.

I don’t have any strong opinions as to whether PFOF is the best equilibrium. One could argue we should have a single central order book, but then the exchange would have a monopoly. Plus it’s not obvious to me that the centralization of liquidity serves the heterogenous interests of all economic stakeholders across countries, regulatory regimes, strategies, time zones, and instruments.

We could entertain more incremental tweaks to the current architecture. For example an auction every minute or shorter trading hours to centralize liquidity in time but not venue. There’s probably some efficient frontier of tradeoffs. Nothing about PFOF looks villainous from my understanding of markets so if it lies along that frontier I would not be surprised.

And perhaps now you won’t be either.

V-Day Reminds Me Of Stupid Times

The first time I ever came to Tahoe was exactly 17 years ago. I remember because it was the first Valentine’s Day after I met Yinh and I totally ditched her to fly to SF from NYC to enjoy a ski weekend with my college friends. And I don’t even ski. I also remember bringing poker chips on that trip and being stopped by security who literally flipped through each of the 500 chips. Why so thorough? The TSA agent told me poker chips look like pipe bombs when passed through the scanner. Better than being stripsearched for being an “Abdelmessih” I guess.

[My father was actually stripsearched in a pre-9/11 world and a few men in my family changed their names after 9/11…nevermind the fact my last name is aggressively Christian translating to “servant of the Messiah”. When you consider my first name, I’m a walking recursive loop. Anyway, the men in my family weren’t going to count on racists to split hairs on brown people and the etymology of names.]

I’d say those were stupid times, but we still take our shoes off before we fly which is a comically overfit, closing-the-barn-door-after-the-horse-escaped policy. I’d like to see a risk to cost analysis of the millions of lost minutes due to that one. Anyway, nothing is stupider than me circa Feb 2004.

(I actually thought Yinh avenged me in the most voodoo way…it took 8 hours to drive back to SFO from Incline Village. Of course now we know that is not unusual. It’s just a holiday weekend.)

Progressive Bikeshedding

I’m in Tahoe this long weekend with my extended local family. My in-laws have kids in SF public elementary schools. They are very involved parents in the Richmond district. On Friday night after the kids went to bed we were chatting about school life and the struggles of remote learning in the community.

Deeply regrettable stuff. I learned of the hotline where parents can call in to vent for 60 seconds. Seriously, 1 minute. It’s a desperate outlet. Parents feeling that “they are unfit to be parents”. Totally overwhelmed by the demands of holding down jobs, guiding their kids 24/7, being short with their kids, and their kids becoming distant, troubled, sad or any other strain of negativity you can imagine exacerbating the parents’ dire year even further. A vicious cycle.

Then there’s the clinically tragic. Consider the alarming reason why SF is suing the schools for remaining closed:

UCSF Benioff Children’s Hospital has seen a 66% increase in the number of suicidal children in the emergency room, and a 75% increase in youth who required hospitalization for mental health services, the lawsuit said, quoting pediatricians, child psychiatrists and emergency room doctors.

Last month, UCSF Children’s Emergency Department at Mission Bay reported record high numbers of suicidal children seen and treated, according to the legal filing which did not provide detailed numbers of cases and hospital visits. It also quoted doctors citing an increase in anxiety, depression and eating disorders among children, consistent with national data. (Link)

Now this is all quite bad (after using a thesaurus to find the right word I rejected all the candidates. “Bad” wins.)

But it’s not shocking. If Covid revealed how our economic supply chains were globally optimized to the penny, we should not be surprised to discover that a typical household was already driving on a spare.

What was shocking was what I read about the SF Unified School District, coincidentally, just before the conversation with my in-laws. After they told me their stories, I simply read aloud what I learned in Bob Seawright’s Better Letter earlier that day:
The school board of the San Francisco Unified School District recently voted to move ahead with a plan to change the names of more than 40 schools. The plan called for removing from schools names of those who “engaged in the subjugation and enslavement of human beings,” who “oppressed women,” who committed acts that “led to genocide,” or who “otherwise significantly diminished the opportunities of those amongst us to the right to life, liberty, and the pursuit of happiness.” Among those to be excluded are Abraham Lincoln, George Washington, Thomas Jefferson, Theodore Roosevelt, Franklin Roosevelt, John Muir, Robert Louis Stevenson, Paul Revere, and Dianne Feinstein.

[pause for family to grok the irony of reading this together on President’s Day Weekend]

The board eliminated Lincoln’s name because of his policies toward Native Americans; Washington’s and Jefferson’s names were struck because they held slaves. The Paul Revere Elementary School will be renamed because of Revere’s role in the Penobscot Expedition of 1779, a Revolutionary War naval assault on a British fort from the Penobscot Bay that the committee assumed, bizarrely and wrongly, was intended to colonize the Penobscot people.

Perhaps it will become Robespierre Elementary and the school board will offer instruction in Maoist constructive self-criticism. 

Robert Louis Stevenson, an important area literary figure, is having his name removed because the poem, “Foreign Children,” from his famous collection, A Child’s Garden of Verses, used the rhyming word “Japanee” for “Japanese.” James Russell Lowell was wrongly claimed to have opposed allowing Black people to vote. It was enough to cancel Lowell. The name of James Lick was ordered removed because his legacy foundation funded an allegedly racist art installation nearly two decades after his death.

Clarendon Elementary, named for Clarendon Avenue, on which it sits, will lose its name because, as the Board of Education explained, the name “can be traced to a county in South Carolina, one of the 13 Colonies named for Edward Hyde Earl of Claredon [sic] impeached by the House of Commons for blatant violations of Habeas Corpus.”

[I was reading all this aloud and decided to take a let-that-sink-in pause. They would need a moment to collect themselves before the crazy train picked up speed again]
Gabriela López, the head of the San Francisco Board of Education, defended the overall decision along with the decision not to consult any historians during the process because she doesn’t want to “discredit the work that this group has done” despite their questionable judgment and glaring use of false information. In her view, those pointing out even obvious errors are “trying to undermine the work that has been done through this process.” 

López insisted that people are “up in arms” because they “have a problem with the discussion of racism.”

Oh, and “Lincoln is not someone that I typically tend to admire or see as a hero.”

In general, any breach of political purity precluded a name from fronting a school irrespective of countervailing good works. There was one exception, however. When a member questioned whether Malcolm X Academy should be renamed because Malcolm was once a pimp, and therefore subjugated women, the committee decided that his later deeds redeemed prior errors. Lincoln, Washington, Jefferson, the Roosevelts, and the others did not receive similar forbearance.

In other San Francisco school news, the school board has deemed acronyms racist, and SFUSD’s vice president, Alison Collins, asserted that the concept of merit is also racist. Just this week, after two hours of debate, the board rejected a gay dad of mixed-race children from volunteering for one of several empty seats on a parent advisory group that didn’t have any gay members or men. Their problem was that he’s white and doesn’t bring diversity to the group. Really.


Let me stop here for a moment. I don’t especially like bringing attention to the most ridiculous and therefore straw version of progressivism. Doing so undermines progressive ideas that actually deserve attention (Moontower readers might be surprised that I almost agree with “meritocracy is racist”. In fact, the reason I don’t agree, is because that statement is an object level instance of my meta belief that meritocracy is largely “besides the point”. Maybe I’ll discuss this at some point when I’d feel less bad about a flock of unsubscribes. Like right before there’s enough readers to shove me into the paid tier of Mailchimp.) But also, I couldn’t help but share the insanity as it collided with what my family was telling me.

I’ll let Bob’s pragmatic sentiment be the outro…

Meanwhile, the SFUSD has no plan to reopen its schools despite the weight of scientific authority establishing that reopening can be done safely and that remote school is bad for kids. Priorities, people.

While nearly half (48%) of San Francisco’s residents are white, only 15 percent of public-school students are white. It’s hardly a coincidence that San Francisco’s private school are open, all but conclusively establishing that the city’s care for “the least of these” is far more symbolic and performative than real. As the Apostle James made clear, believing the right things without action on them is worthless.

How Options Confuse Directional Traders

2017 was a historically low-vol year, rewarding options sellers despite selling lower option premiums as the year progressed. Like they found a broken slot machine at the Cosmo. It wasn’t until the Feb 2018 “volmageddon” in exchange-traded VIX products, that retail discovered the dangers of selling options.

In the past year, retail, led by r/WSB, is back in the deep end of the options pool. This time they brought swimmies — they are only buying options. This limits their losses to the premiums.

As opposed to professional vol traders, most people use options as a way to bet on direction. You buy a put to bet on a stock going down and you buy a call to bet on a rally (or an “up” — a term coined by my doctor friend who always used to make fun of us finbros who talked about “puts and ups” all the time when we were in training). I tend to dissuade people for messing with options unless they have a very specific risk to hedge or if their speculative thesis is well-defined. Since options expire you need to be right not just on direction but timing as well. There’s a lot of ways to lose, get lured into trading more, and generally chop yourself up.

I’m going to demonstrate how you can lose money despite being very “right”. For good measure, we’ll extend the conversation to how hedging can actually increase your risk. Let’s jump in.

An Option Lesson

The recent action in GME justified the cigarette warning label I put on options. If the option user doesn’t appreciate the role implied volatility plays in an option price, then Benn’s tweet is mystifying:

Put options increased in value as the stock went up.

Then, with the stock on the way down @mark_dow tweets:

Put options lost value as the stock collapsed.

My kids would chalk this up to “opposite day” (apparently a modern holiday where kids wear pajamas to school). Alas, there is a more boring explanation:

Implied volatility increased as the stock price increased and fell as the stock price fell.

Pro Version

If you are eager, we can drill down a bit.

  • The option’s “vega” dominated its delta in both cases. The vega tells us how much the option’s price will change as the volatility rises or falls.
  • “Vanna” represents the sensitivity of the option’s delta to volatility — a second order effect. As the vol increased, the OTM option deltas increased. This is notable because it is a positive feedback loop. As the stock and vol both increase on the way up, market makers have to buy more stock to hedge. On the way down, it is stabilizing as the vol decreasing means the option delta decreases and market makers need to be “less short” to hedge the puts…it’s stabilizing because this offsets the negative gamma effect from being short puts in the first place. This one is tricky because the vanna effect is dampening the vanilla gamma effect.
  • Then there’s “volga” which is how the option’s vega changes with respect to vol. This is yet another second order effect of vol (I’ve written about that here). It feeds right back into vanna and acts as a reinforcer on the way up and a stabilizer on the way down (since spot and vol are positively correlated. We’ll get to this correlation later).
  • There are higher order Greeks than “vanna” and “volga”. Ironically, they are only known by the French. Don’t ask.

Vol traders care about these cross-currents because of how they accelerate or dampen the price of options. These effects alter hedging flows which change buying and selling pressures. Outputs become inputs so each sub-cycle in the process looks like a foreshock to something bigger, or the aftershock to something dissipating.

This might sound theoretical or academic but it’s the nuts and bolts of managing volatility portfolios. An option book with many names, maturities, and strikes looks like an amorphous blob until you use these concepts to give it shape. Once it has shape you can recognize what kind of animal it is. You can predict how it might respond to different scenarios. The measurable risk is how it will react to the market’s movements. The stock is going to do stuff. That’s a given. You are not allowed to be surprised by that fact.

The real concern is if the portfolio, this animal under your care, acts outside your range of expected behavior.

Normie Version

Rest easy. That was utter overkill for investors or even casual option punters. To understand why puts got cheaper on a selloff, you just need this picture:

It is a beautiful and simple visual intuition constructed by @therobotjames.

  • The purple bell curve is the distribution of GME stock when it’s trading for 600% vol and $200.
  • The green bell curve is the distribution of GME stock when it’s trading for 400% vol and $90.


Despite the higher stock price, the purple curve imputes a higher probability of the stock going below $20 because the distribution is much wider at 600% vol than at 400% vol. The impact of the vol totally dominates the moneyness, or distance, the stock is away from the strike. Another way to say this is “the $20 strike is closer to $200 than it is to $90” if the volatility is that much higher when the stock is $200. This is easier to understand if we simply make the volatility disparity wider. Imagine a govt bond that trades for $100 par and a stock that trades for $200. Nobody would be shocked if the 50 strike put for the stock was worth more than the 50 strike put for the bond.


I can see you scratching your head. In GME, we are talking about the same exact asset at 2 points in time with a contradicting proposition: namely that the probability of the stock dropping below $20 when the stock is $200 is higher than when the stock is $90!

This paradox is an illusion that happens whenever you have the benefit of hindsight. You don’t know which of these prices is the true odds. You can only trade with the information you had at the time. You cannot arbitrage the relative pricing between the 2 states of the world that we have the luxury of seeing in the rearview. Looking back you can say that the stock’s chance of going below $20 was underpriced when it was trading $90 or that it was overpriced when it was trading $400 but you couldn’t make those claims at the time. They only seem paradoxical when compared to each other.

At this point, I suspect retail traders, curious as to why they won to buying puts on the rally and lost to buying puts on the selloff, developed some understanding of vol dynamics.

Hopefully the tuition wasn’t too steep. Not all lessons are as cheap as a defined option premium.

The Expensive Option Lesson Pros Learn

Professional option traders adjust option greeks for spot-vol correlation. In the GME-case the correlation is positive just as it is in agricultural commodities. As the price increases, the vol increases. Most markets have a negative spot-vol correlation. The VIX falls when the SPX rallies. This is also true in the oil market. A supply of options hits the market during rallies as large hedgers overwrite calls.

To adjust for this, option traders will model a negative spot-vol correlation or “vol beta”. For example, suppose your ATM call option typically has a 55% Black-Scholes delta. you might model a 50% delta only, knowing that if the future goes up $1, your call option probably won’t increase by $.55 since implied vol will fall. (In fact, one of the ways to know if the counterparty you are quoting was a bank or not was by the delta the broker wanted to use on delta-neutral structures. Banks often quoted with Black-Scholes deltas while prop shops used deltas which incorporated vol betas, effectively lowering all call deltas).

When you model vol beta you are usually making a trade-off between hedging local behavior of common moves versus more unusual sized moves which will break the spot-vol correlation, in turn upending calibrated deltas. If a skirmish broke out in the Strait of Hormuz and oil ripped 10% higher I would not expect volatility to fall. Therefore, you also need to consider a matrix of outcomes.

(This is a hypothetical picture which tells us if oil rallied 10% and vol increased 50% we would lose money. Note that if vol fell in accordance with a vol beta we would have made money).

Even with respect for local and jump spot-vol correlations, you can still be caught off-guard. In nat gas, I’ve underestimated just how GME-like its vol surface can change. I’ve seen put prices not budge despite a 20% selloff in an underlying. If you are running a hedged book and have any long futures against the puts you enjoyed the full drawdown in futures without any offset from the puts. Enough to make a burly man cry.

The idea that “you only risk your premium” when you buy options is only true if you do not hedge. It’s diabolical to get crushed on a supposedly neutral position. Why? Because, you thought you were hedged. This tricked you into buying more puts than you would have if you didn’t hedge.

(All basis trades have this dangerous property. The illusion of being hedged induces you trade bigger or use leverage to push a small edge.)

Qualitative Appreciation For Spot-Vol Correlation

The GME put holder who lost money on a sell-off now understands how the change in implied volatility explains the loss. Regrettably, this is like being told you missed a flight because you were late. It’s just a mechanical explanation. What you really want to know is why did volatility come in as much as it did? In option trader terms, “why did the vol beta outperform or underperform in the first place?”

The beta itself will have quite a bit of variance since a price can follow many paths to a destination. Those paths will each be a sample of unique realized volatility. Did the price grind to X or did it gap to X? The realized beta will vary from your projected one depending on the path and the market’s interpretation of that path. If the stock gaps down due to a specific bit of news (for example news that a big short is done covering or the company issuing more shares) the gap can actually be vol-reducing as the market interprets the news as “stabilizing”. If the gap comes with no explanation, then the market might interpret this data point as another mystery piled on an already burning heap of confusion. The market will presume that the crazy stock might just rip back up again. In this case, the vol might hold up better on a sell-off that occurs without a reason in contrast to the the prior case where the reason had the narrative effect of curtailing the upside.

So in the GME case, most of the reasons the price can go down are stabilizing. We expect options to be sold in response to a sell-off, and for the vol to decline. But “most of the reasons” does not mean 100% of the reasons so there is a probabilistic distribution to what the realized spot-vol correlation could be. And that’s why we still have surprises.

The Beauty Of Options

Ultimately, options help to “complete” a market. A simple stock price is just the expected value of a stock (equity risk premia and arbitrage pricing theorists are welcome to have a cage match over that statement. I’ll be out back selling beer). By imputing more information than a one-dimensional expected value, option surfaces give us a richer picture of expectations. What’s considered stabilizing, and what’s considered unthinkable are encoded in options markets.

There’s a silver lining to the WSB obsession with options. Some of these people who showed up for a thrill will stick around to learn how to listen to how a vol surface whispers.

Sparking My Kid’s Interest In Coding

My niece is learning to code using pygame. Pygame is a Python based module for writing games. When she told me, I hopped on to YouTube to watch a tutorial with Zak (7) to see if we can learn together. Hmm. It was quickly clear. He was going to need some basics first.

After he went to bed, I decided to script a simple text-based game that might enjoy. It also had the oblique purpose about teaching him the basics of business math. You’ll recall I planted this seed with Zak and his podmate back in the fall. I described the process in A Socratic Money Lesson for 2nd Graders.

I’ve shared the game with cousins and his friends, and it gives them a quick little competition. It encourages them to read, reason, and do basic arithmetic. After they played it for awhile, I told him I wrote it. Now I can’t really code but it was just enough for the desired effect — he would think “whoa, we have the power to make a game!”. Now he is interested in at least messing with Python and trying to learn some basic syntax.

Share it with your kids and see how much money they can make at the Ice Cream Shoppe. (game)

Here’s the code. It’s not pretty but it should be easy enough to spot how to change it. (code)

The game takes less than 2 min to play. And it will introduce you to Trinket, a great site for writing and running programs in a browser.

The 4-year-old wanted to play a game too. He’s learning basic addition and loves chess so I wrote him an even simpler game. It encourages arithmetic by adding the values of chess pieces. He can’t read but his bro wrote a cheatsheet on a piece of paper so he can match the words on the screen with the word on the paper. Over time, he is figuring out that the word that starts with “p” is “pawn”.

Play it here. (chess piece game)

The Return of Slatestarcodex

Slatestarcodex Is Back

Last summer, the NY Times threatened to reveal pseudonymous blogger Scott Alexander’s identity.

His response was to blow up any basis for a story:

I deleted my blog of 1,557 posts.

I wanted to protect my privacy, but I ended up with articles about me in New Yorker, Reason, and The Daily Beast. I wanted to protect my anonymity, but I Streisand-Effected myself, and a bunch of trolls went around posting my real name everywhere they could find. I wanted to avoid losing my day job, but ended up quitting so they wouldn’t be affected by the fallout. I lost a five-digit sum in advertising and Patreon fees. I accidentally sent about three hundred emails to each of five thousand people in the process of trying to put my blog back up.

I had, not to mince words about it, a really weird year.

The story of his year is remarkable in many ways. From the outpouring of supporters to behind the scenes intrigue. The reasons behind his response range from practical concerns specific to his work to the philosophical discussion of power and privacy. Something that matters the world to you is vulnerable to being obliterated by some journalist’s “Tuesday”.

Check out the full homecoming post: Still Alive. (Link)


Trevor McKendrick on Slatestarcodex:

If you were a fan of Slate Star Codex you undoubtedly already heard the news, but let me use this moment to sell everyone else on Scott’s writing.

The only person who writes well enough to describe why Scott’s work is so good is Scott but I’ll try my best anyway: his writing makes me feel alive, explains complex topics with rigor yet approachable language, and is regularly laugh-out-loud funny.

It’d be one thing if he were merely rewriting published papers to make them easier to read, or doing groundbreaking research in normal dense language, or only occasionally going deeper on the most important topics of the day.

Somehow he does all of these things, regularly, and better than anyone else I’ve found.

A Twitter thread about Scott’s return that’s worth reading.

One part that describes what makes him so good: “Scott asks big questions across a wide variety of domains and doesn’t rest until he has clear answers. No, he doesn’t rest until he can explain those answers to you lucidly. No, wait, he doesn’t rest until he can do that and also make you laugh out loud.”

Some of his best work you could start with:

I Can Tolerate Anything Except the Outgroup – probably the most important piece you can read during our current political times

Beware the Man of One Study – in which Scott describes why I find e.g. nutrition to be a fuzzy science at best

Book Review: Albion’s Seed – Scott’s book reviews are often better than the books themselves. After reading this review you might think about the book every day…

Slatestarcodex has revealed himself to be Bay Area psychiatrist Scott Siskind. He’s not taking new patients but he started a new practice and the website is worth a visit. This post talks about the difference between prescription drugs and supplements and includes a list of his favorite supplements for various conditions. (Lorien Psychiatry)

As the meme goes, men will read Scott’s blog instead of going to therapy.

Adding My .02 To The WSB Insanity

r/WallStreetBets. GME. AMC. Citadel. Ken Griffin. Steve Cohen. Melvin. Matt Levine.

Wait, Matt Levine?

Yes, Matt Levine. Just read everything he wrote this week for staging this entire topic.

My work here is done.

…Ughh fine. I’ll address a few subtexts.

Feedback Risk

The simplest observation from the hedge fund Melvin’s plight is their bet size was too large. They underestimated both volatility and liquidity. These are not uncommon mistakes.

Morgan Housel explains by analogy:
Forecasting when a species might go extinct is hard because whatever is causing a species to die off rarely progresses at the same rate. It can speed up in the blink of an eye in ways that surprise people.

Say an elephant is being hunted for its tusk. The rate of hunting often massively speeds up over time, cascading into a frenzy that pushes a mildly at-risk species into quick extinction.

It’s simple: As the number of elephants declines, tusks become rare. Rarity pushes prices up. High prices make hunters excited about how much money they can make if they find an elephant. So they work overtime. Then fewer elephants remain, tusk prices rise even more, more hunters catch on, they work triple-time, on and on until the number of hunters explodes as everyone chases the last herd of elephants whose super-rare tusks are suddenly worth a fortune.

Forecasting models that don’t appreciate how frantic the last-minute hunt can become “give a false sense of security when managing large harvested populations,” the researchers wrote. A species’ endangerment starts slow, then picks up, gets a little faster, then boom … spirals into a disaster seemingly overnight. Supply and demand are intuitive; realizing how quickly supply and demand can go from linear to exponential is not.

Feedback loops – where one event fuels the next – often lead to that kind of bewilderment.

Find a feedback loop and you will find people who underestimate how crazy prices can get. (full post)
A Thought Exercise For Outsourcing Liquidity Risk

A portfolio manager shorting a stock will size a position not just based on price target and conviction but based on the risk relative to bankroll and relative to the liquidity. There are conventional ways to do this. Volume, days-to-cover, variance, 90s nostalgia factor (kidding on that one…worrying about that going forward is like closing the barn door after the horse escaped). While these inputs inform a sizing decision, the bottleneck in the risk management process is not in the sizing. It’s in the remedy when your sizing turns out to be wrong. Eventually it will be. Your plan needs to tolerate that eventuality.

Most plans are to cut risk by buying back some percentage of your shorts. This is like trading with a stop. You are constructing an option since you cover as the stock goes against you and you add as the stock goes in your favor (remember if you short a stock and it falls, to maintain exposure as a percentage of AUM you need to short even more).

The problem with this plan is it is soft optionality. It’s not the same as buying a hard option like a deep ITM put, or buying an OTM call to hedge your short position. Hard options protect you from gap risk. You know, that thing that happens when a stock is halted. Or when the US goes to sleep. Or when a gamma squeeze creates a massive imbalance.

To improve risk management, managers should at least entertain the question: “if I wanted to buy X amount of deep ITM puts instead of shorting shares how much would it cost?”

The answer to that question comes from market-makers who sit in the middle of the marketplace. They hoover up market intel to synthesize a price so you can know exactly how much it costs to express your view with a hard option. Sure, that price embeds a consultation fee in the form of a vig, but at least they are on the hook for mispricing. Not you.

A market maker’s job is to price the spread between soft optionality and hard optionality by gauging the liquidity required to dynamically hedge. Market makers are also in highly competitive, low margin businesses. If you pass on their price for the hard optionality you must ask yourself…”is my assessment of the liquidity/gap risk that much better than theirs OR are their margins excessive?”

At the very least, you can consider this reasoning a sanity check before you size up a big short.

Brokerages are in the Credit Business

The conspiracy theories around Robinhood suspending trading in GME can be cut to shreds with both Occam’s and Hanlon’s razors. RH and any broker for that matter are clearly desperate once they resort to cutting off their customers. The customers are the lifeblood.

Sure Citadel pays RH for order flow, but that relationship is downstream of RH having customers in the first place. Just because RH’s checks come from Citadel, not from the Yolo’ing redditors directly, doesn’t mean Citadel comes before the customers. After all if Citadel didn’t pay RH another market maker would slide right in to that spot. To think the customers come second to Citadel is to confuse accounting for economics. It’s breathtaking to imagine this kind of naivety.

What created a situation so dire that RH had to anger its mob? A good ole’ fashioned credit crunch.

I’ll let Byrne Hobart explain not just the dynamic but why RH had to “explain it poorly”:
A simple model of a stock brokerage is that it’s an almost fully-reserved bank. The brokerage has clients, the clients have positions, and in one sense each position is an asset on the broker’s balance sheet, while the customer’s ownership of that position is a liability. So your broker is a sort of bank, that takes deposits in dollars, but also in shares of IBM, treasury bonds, far-out-of-the-money call options on AMC. Normally, this bank tanks very little risk, but there are a few things that can go wrong: trades take time to settle, which creates a brief liability mismatch. Brokers put up collateral to ensure that, in the event that they go out of business before the trade completes, their customers won’t lose their assets. When trade volume rises, and the volatility of the assets rises, this creates a larger demand for collateral.

This is, day-to-day, a problem brokers are able to manage. Their capitalization needs don’t change that much. But when users are all piling into the same volatile trades, the need for capital rises suddenly. As a result, Robinhood stopped processing trades in GameStop, except trades to unwind existing positions. (As did several other brokerages: Interactive Brokers, WeBull, and Public, for example.)

This story certainly sounds sinister; it matches the appearance of strings getting pulled in order to bail out hedge funds. But the brokers’ actions also look like the actions of any financial intermediary faced with a sudden increase in uncertain obligations. (And there were not stories about brokers like Vanguard and Fidelity, which have fewer day-traders, blocking GameStop trades.) When volatility is high, brokers often act in their own interest. This has happened before: one major short-selling firm was basically shut down mid-crisis because their prime broker raised margin requirements. (The prime broker in question denies much of this.) While it’s rare in the US, brokers can go under because of client losses. FXCM, for example, had many clients who were borrowing the Swiss franc to fund other currency bets. It was a stable currency with low rates, until the Swiss gave up on keeping it stable and allowed it to float; it instantly rose 45%, wiping out many clients many times over and forcing FXCM to get rescued by a larger financial institution, and to rescue many of those clients in turn.

Which doesn’t excuse Robinhood, WeBull and the rest. They communicated inaccurately, but not poorly, because an accurate description of the problem was “We’re more of a bank than we realized, and we’re in danger of insolvency.” And that would lead to a run on the bank—and definite insolvency. WeBull’s CEO did clarify this later on, and with enough time to digest it, and new funding from their venture backers, the bank-run risk is minimal.

The brokerage experienced a familiar technology problem — a rapid increase in capital requirements for scaling infrastructure when user growth explodes compounded by a frumpy problem as old as time — the need to raise more collateral.

The combination of these forces should be more than enough to satisfy the explanation with the least and most likely assumptions. If this theory is still not as compelling as blaming Citadel let me ask a question — if you were Ken and owned a machine that printed cash would you rather turn the machine off for a few days or would you try to forge the bills you aren’t able to make jeopardizing the entire future of the printing press?

Please. You don’t make foie gras out of the golden goose.

The Big Guy Vs Little Guy Debate

If conspiracy theories weren’t enough, then we get the ambulance chasers.

AOC, Chamath, and the Barstool meatball.

Right on cue and impossibly aligned proving that the arc of moral outrage bends towards grift.

Unable to resist the warm embrace of Twitter hearts and re-tweets, this band showed up to promote the populist WSB underdog David vs hedge fund elite Goliath narrative. Ranjan Roy dispels that framing handily. Not to take anything away from Roy, but anyone with a clue how trading works knows that framing is nonsense.


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 recently.

My full thoughts on this are out of scope here, but I couldn’t help but chime in on this @skelecap & @SuperMugatu thread.

Sticking It To The 1%

The most populist development in the story is not daytraders getting rich. Sure, a few will, but when you turn GME into one of the top 10% of stocks by market cap you are also guaranteeing a large cohort of bagholders. Since, ya know, math.

The real damage will be to savers in a story that will rhyme with this:

Random Thoughts on Leitner’s Upside Digitals, Time Horizon, and WSB

Some thoughts on Jim Leitner’s interview on MacroHive:

  • My favorite idea from the pod: the discussion of replacing equity allocation with digital calls. He talks about buying say 5 year 100% OTM digital for 7 cents on a dollar. You should listen for his full reasoning but it rhymes with Warren Buffet’s thoughts on option pricing which is ultimately the difference between no-arb risk neutral derivs pricing and odds implied if you believe in an equity risk premium. (Alpha Architect blog)

    Let me add to that.

    Indulge this lazy theory as to why Leitner’s idea might be correct for a technical reason he can probably feel more than explain. Suppose we quintiled the broad market by valuation. Whatever metric, the US is in the highest partition. I would not be surprised if stock replacing your equity exposure with options would have been historically a good trade conditioned on extreme valuation. Not because you win more, but because you lose less when the markets roll over. And of course that means you can rebalance with a better hand after a drawdown. Total CAGR improves.

    I’ll go a step further. Why might the market might price the vol too cheap on those OTM calls? Perhaps a very expensive market exhibits autocorrelation on longer time frames (ie monthly vs weekly returns). In other words, momentum prevails. The momentum can lead to cheap implied to realized vol ratios in the same way that a stock that rallies 1% per day for 20 straight days will have been a bargain buy at 16% implied vol.

    So when Jim gets 13 to 1 on that digital, perhaps the true odds conditioned on an expensive market are 8 to 1 or 10 to 1. Again, this is a lazy musing, I would love to see if there’s any work out there on this.

    This whole exercise is the upside version of Spitznagel’s point about conditioning convex trades based on valuation. The piece very much flies in the face of anti-timing arguments and it’s quite robust to how expensive the convexity actually is. See Universa’s Those Wonderful Tenbaggers (Link)

  • Jim’s discussion of BTC was ok but prompted a discussion with Yinh about our BTC holdings (which you can presume is small since I still fly coach):

    1. Your time horizon should dictate the dashboard of metrics that informs your decision.

    2. Disagreements about the “right” price are always a disagreement about time horizon. That’s what makes a market.

    One of the points he made was about PayPal making it easy to buy BTC was bullish. This kind of argument is simultaneously insightful and deranged because it is reflexively Ponzi but also right. The “horizon” field is left blank and for the investor to fill in.

  • Jim’s book recs:

    1. The Checklist Manifesto

    Doctors make lots of decisions under uncertainty and Gawande’s book has many transferrable lessons to investment processes.

    2. Superforecasting

    Predictions should have time horizons and a confidence interval. Score yourself and over time you will improve.

  • Other recs:

    1. Keep a journal of trades and the reasoning behind them. Your future self will thank you.

    2. Open a play account where the money isn’t make or break. His is $100k. This account absorbs the trades which come from “feeling the need to do something”. For your real accounts, most of the time you should sit on your hands.


  • WSB gets emotional on Mad Money (5 min vid)

    Last week I wrote Is Social Harmony The Last Collateral?It was a post that regrettably resonated with many of you. Not to be dark (narrator: it’s dark), but this re-purposed Joker clip expresses the same message as my post but even better. Where I put “dentist”, it put “millennial”. The framing is more desperate and nihilistic than my post, but I reluctantly admit, it is probably more in touch. It shares my sense that the GFC was an even more watershed moment than it seemed at the time.

  • Made my first financial meme. Look how grown-up I am. (link)