vol trading is easier than directional trading

I want to clarify a statement from my chat with John from Risk of Ruin.

I said “vol trading is easier than directional trading”.

This is something I’ve felt from experience. I long attributed it to derivatives pricing being, well, derivative of an underlying. Trading an ETF or index future, both derivatives, is “easier” in the sense that there is a fair value with respect to some assumptions like cost of carry but the variation in the assumptions is vanishingly small compared to the error bars on the assumptions one makes when formulating an opinion about a stock price.

For options, most of the inputs except volatility also have error bars that are far smaller than anything you’ll assume about a stock.

Which brings me to volatility.

Volatility is more stable than returns.* This is why quants target risk in their sizing, not returns.

🔗See Know-Nothing Sizing for a fuller discussion. It’s an idea that underpins my approach to investing and risk management.

So if handicapping volatility is easier than handicapping returns, shouldn’t everyone just trade options for that sweet, easy cash?

The fact that it’s easier, also means the competition is fierce. It’s a zero-sum, capacity-constrained game. Predicting vol is easier than predicting returns, but…so what? You care about “how easy is it to make money?” and that is not easier.

The distinction reminds of this Daryl Morey bit on sport analytics:

Our underlying data is more predictive, quite a bit predictive. I talk to a lot of quants on Wall Street, and I tell them our signal to noise ratio using whatever measure you want….And they go like —whoa, you guys are — that’s incredible. And I’m like, yes, but you remember, we have to be best of 30. You guys just have to beat the S&P by 2% and you are geniuses. So each industry has its own challenges.

*For the option enjoyyyyers who are thinking “Bruh, VVIX is way higher than VIX, how can you say vol is less volatile than the vol of returns?”, here’s my rebuttal: What’s your 90% confidence interval on SP500 returns next year vs SP500 1-year realized vol?

An investor doesn’t care about vol of vol as if they are trying to price an option on VIX. If SPY realizes 14% give or take 5 points for a year (this is about the high/low range of 365 day vol using overlapping data for the past 4 years), this is not as destabilizing as the outright returns being say -5% vs +15% which is probably an even narrower relative range than 9% to 19% for a 1-year realized vol.

when quitting is ambitious

Let’s hop right into a recommendation.

This essay is packed with useful decision frames. If you’ve been with me for awhile I think you’ll understand why I’d appreciate it.

In praise of quitting (Cate Hall)

From the opening:

  • the danger is in devoting our days to something that fundamentally doesn’t matter to us, because we’re too afraid to cut our losses.
  • Tournament poker is basically about finding the highest-value uses of a scarce resource, your chips. The fact that losing those chips means getting completely locked out of a shot to win major money means that their opportunity cost is high. This means it can be a big mistake to commit yourself to hands that are somewhat positive-value in expectation, if you have good reason to believe there will be better, higher-value opportunities…Life is, of course, just like this: You get only one shot, and it’s up to you to make the most of it by rejecting okay or even pretty good ways to allocate your time or other resources — to hunt down the opportunities to make really great bets on yourself. Do not make barely positive-value bets with your life!

A description of almost anyone can relate to by middle-age, if not earlier:

The interesting thing about steady jobs is that they’re actually not so steady. They are static in a conceptual sense — in the sense that if you say you’re a “lawyer” when you’re 30, and say you’re a “lawyer” when you’re 50, there is the same label for what you do. And that can feel like steadiness, like a reassuring kind of coherence to your life story.

But the truth is that everything is in constant flux. Beneath the labels, life continues evolving all the time. Your interests change, companies change, and industries change. Given that your “steady job” is constantly evolving, even if you picked the highest-leverage option initially, there is a low chance that it will remain your highest-leverage option over time.

The same goes for places to live, relationships, opinions, and hobbies. Over time, these things can degrade in value or resonance — and yet still retain the emotional pull of their initial promise. And when this happens, people often stay too long.

Cate offers some exercises or what I think of as useful frames:

By default, we tend to think of “choices” as the kinds of things that take us off the path we’re already on. From this stance, it doesn’t feel like we are “choosing” to go to our job every day, or choosing to remain where we live. The scary thing is that this means we can actually be making the biggest mistake of our lives on a daily basis, despite it feeling like nothing is happening at all. If we want to evaluate whether our current set of choices is really best or whether it’s just inertia keeping us where we are, it can be powerful to upend that frame.

Try it. Go around your day, narrating all of your choices to yourself. With everything you do, consciously say, in your head: “I am choosing to do this, because it’s the best course of action according to all the information I have available.” See if it feels true. It might — perhaps this exercise will reinforce your conviction. But you might also find that entire regions of your life suddenly look strange. The declaration that you’re doing the best thing will sound like hollow propaganda, an attempt to convince yourself of something you know just isn’t so.

More:

Another powerful exercise, of a similar kind: Imagine that you were instantly unsubscribed from everything in your life. All of your choices undone — where you live, who you’re with, what you do with your time. All of a sudden, you’re a completely empty canvas. And then, imagine that you have the power to bring back each element just by hitting a “resubscribe” button, like it’s an email newsletter. Being honest with yourself, which elements would you hit “resubscribe” on?

Once you realize you’re choosing something, you regain the ability to un-choose it.

Note that un-choosing doesn’t always mean quitting in the complete, traditional sense. It might just mean an alteration — working hard to establish a new phase in your relationship, or changing roles at your job, or moving to a different neighborhood rather than a different country. This, too, is strategic quitting: declaring that a given battle is over so that you can win the war.

She closes with a bright side.

Leaving can still break your heart even though it’s the right thing to do…But something to remember is that there is always some unknown part of the future that you will be equally fond of.

When people think about quitting, it’s hard because they’re comparing the rich web of attachments they have now to some mostly blank slate, or, worse, the possibility of disaster. However, what’s more realistic to imagine, if you’re leaving something you’re no longer aligned with, is a future with more to love than you have now.


My 2 cents since we’re here.

Quitting the familiar always feels risky. And to be clear, it often is. But it’s also risky to stay and even though we can feel that in our hearts, we don’t seem to warn people about that risk with the same urgency we do about when they plan to change.

The asymmetry is an expensive risk reversal. Paying up for the put, and hittin’ bids on calls. Playing for upside, I don’t mean financially, although that can be included, demands courage. Not heroism. Small courageous steps. Folding a comfortable hand never feels heroic, but it does take courage. It risks looking like a fool.

We are surrounded by grand examples of ambition. Bottomless appetites for wealth and power. But figuring out how to live on your terms, around people you are happy to be around, working on things that light you up, and staying true to your values is an ambitious goal. Pulling that off is hard because unless you got lucky and ended up on YOUR path from the start, at some point you will need to know when to quit.

I don’t know where I heard it, but someone said the reason some finance people stay in finance (unhappily) long past satisfying their financial goals is that they can’t do anything else. Not in a “they lack the ability” but in a learned helplessness kind of way. They cannot stomach the hit to their identity, status, or sense of usefulness, even if all of it is in vain. For appearance. For others. For lack of creativity. Soul last seen on the back of milk carton at age 17.

On a personal note, even having went through a substantial quit, I’m still not here to glorify it. I effectively run a craft consumer-facing small business between the writing, consults and option analytics. Bruh, I’m teetering on the edge of self-doubt and self-belief from day to day.

Making money and creating surplus go together. That I make less than I used to hurts because it feels like a statement about the surplus I create.

[I obviously understand that it’s not that simple. Leverage and ability to capture a share of surplus are giant inputs into what you actually get paid. That there’s no-name closet indexers richer than your favorite drummer is capitalism’s bunion but I’m not suggesting we amputate the foot even if I’d get some perverse joy from clawbacks against people who suck.]

Still, I wrestle with this quite a bit. I don’t really see myself as a businessman. As someone who would spin something up just because they see an opportunity. I’ve always been impressed by those kinds of people because I wish I could be like that. But it’s hard for me to care about something unless I love it. I don’t care about solving a problem just because it exists. There are infinite problems and I have one attention span. To a businessman, profit helps them filter. But more money than I actually need* is not motivating enough to do work I don’t care about. How would I even be excellent at something I didn’t care about?

But this perspective is a constraint of my own making. I don’t get to eschew opportunism and then complain that’s how the world and economy work. As it goes, I’m trying to figure out how to make more money doing these things that intersect my interest and ability. There’s a better product-market fit at the end of this rainbow, but finding it is harder than trading, and there’s no guarantee it will pay as well. But I’m immersed in the process of going there. And for that feeling, quitting was right for me.

*Adulting means you gotta do whatever you gotta do to make what you need OR lower what you need. But I’m talking about the same decisions we all make on the scale that is personally relevant. For some, it’s the choice of doing X for the 100k they need or Y for the extra 50k, and for others it might be the choice of $500k working remote or $1mm being on the road 60% of the time. Cate’s point in this essay is that everything is a choice and when you forget that become an entitled victim. Or to use one of my favorite lines…you’ve exchanged a walk-on part in the war for the lead role in a cage.

Moontower #290

Friends,

Let’s hop right into a recommendation.

This essay is packed with useful decision frames. If you’ve been with me for awhile I think you’ll understand why I’d appreciate it.

In praise of quitting (Cate Hall)

From the opening:

  • the danger is in devoting our days to something that fundamentally doesn’t matter to us, because we’re too afraid to cut our losses.
  • Tournament poker is basically about finding the highest-value uses of a scarce resource, your chips. The fact that losing those chips means getting completely locked out of a shot to win major money means that their opportunity cost is high. This means it can be a big mistake to commit yourself to hands that are somewhat positive-value in expectation, if you have good reason to believe there will be better, higher-value opportunities…Life is, of course, just like this: You get only one shot, and it’s up to you to make the most of it by rejecting okay or even pretty good ways to allocate your time or other resources — to hunt down the opportunities to make really great bets on yourself. Do not make barely positive-value bets with your life!

A description of almost anyone can relate to by middle-age, if not earlier:

The interesting thing about steady jobs is that they’re actually not so steady. They are static in a conceptual sense — in the sense that if you say you’re a “lawyer” when you’re 30, and say you’re a “lawyer” when you’re 50, there is the same label for what you do. And that can feel like steadiness, like a reassuring kind of coherence to your life story.

But the truth is that everything is in constant flux. Beneath the labels, life continues evolving all the time. Your interests change, companies change, and industries change. Given that your “steady job” is constantly evolving, even if you picked the highest-leverage option initially, there is a low chance that it will remain your highest-leverage option over time.

The same goes for places to live, relationships, opinions, and hobbies. Over time, these things can degrade in value or resonance — and yet still retain the emotional pull of their initial promise. And when this happens, people often stay too long.

Cate offers some exercises or what I think of as useful frames:

By default, we tend to think of “choices” as the kinds of things that take us off the path we’re already on. From this stance, it doesn’t feel like we are “choosing” to go to our job every day, or choosing to remain where we live. The scary thing is that this means we can actually be making the biggest mistake of our lives on a daily basis, despite it feeling like nothing is happening at all. If we want to evaluate whether our current set of choices is really best or whether it’s just inertia keeping us where we are, it can be powerful to upend that frame.

Try it. Go around your day, narrating all of your choices to yourself. With everything you do, consciously say, in your head: “I am choosing to do this, because it’s the best course of action according to all the information I have available.” See if it feels true. It might — perhaps this exercise will reinforce your conviction. But you might also find that entire regions of your life suddenly look strange. The declaration that you’re doing the best thing will sound like hollow propaganda, an attempt to convince yourself of something you know just isn’t so.

More:

Another powerful exercise, of a similar kind: Imagine that you were instantly unsubscribed from everything in your life. All of your choices undone — where you live, who you’re with, what you do with your time. All of a sudden, you’re a completely empty canvas. And then, imagine that you have the power to bring back each element just by hitting a “resubscribe” button, like it’s an email newsletter. Being honest with yourself, which elements would you hit “resubscribe” on?

Once you realize you’re choosing something, you regain the ability to un-choose it.

Note that un-choosing doesn’t always mean quitting in the complete, traditional sense. It might just mean an alteration — working hard to establish a new phase in your relationship, or changing roles at your job, or moving to a different neighborhood rather than a different country. This, too, is strategic quitting: declaring that a given battle is over so that you can win the war.

She closes with a bright side.

Leaving can still break your heart even though it’s the right thing to do…But something to remember is that there is always some unknown part of the future that you will be equally fond of.

When people think about quitting, it’s hard because they’re comparing the rich web of attachments they have now to some mostly blank slate, or, worse, the possibility of disaster. However, what’s more realistic to imagine, if you’re leaving something you’re no longer aligned with, is a future with more to love than you have now.


My 2 cents since we’re here.

Quitting the familiar always feels risky. And to be clear, it often is. But it’s also risky to stay and even though we can feel that in our hearts, we don’t seem to warn people about that risk with the same urgency we do about when they plan to change.

The asymmetry is an expensive risk reversal. Paying up for the put, and hittin’ bids on calls. Playing for upside, I don’t mean financially, although that can be included, demands courage. Not heroism. Small courageous steps. Folding a comfortable hand never feels heroic, but it does take courage. It risks looking like a fool.

We are surrounded by grand examples of ambition. Bottomless appetites for wealth and power. But figuring out how to live on your terms, around people you are happy to be around, working on things that light you up, and staying true to your values is an ambitious goal. Pulling that off is hard because unless you got lucky and ended up on YOUR path from the start, at some point you will need to know when to quit.

I don’t know where I heard it, but someone said the reason some finance people stay in finance (unhappily) long past satisfying their financial goals is that they can’t do anything else. Not in a “they lack the ability” but in a learned helplessness kind of way. They cannot stomach the hit to their identity, status, or sense of usefulness, even if all of it is in vain. For appearance. For others. For lack of creativity. Soul last seen on the back of milk carton at age 17.

On a personal note, even having went through a substantial quit, I’m still not here to glorify it. I effectively run a craft consumer-facing small business between the writing, consults and option analytics. Bruh, I’m teetering on the edge of self-doubt and self-belief from day to day.

Making money and creating surplus go together. That I make less than I used to hurts because it feels like a statement about the surplus I create.

[I obviously understand that it’s not that simple. Leverage and ability to capture a share of surplus are giant inputs into what you actually get paid. That there’s no-name closet indexers richer than your favorite drummer is capitalism’s bunion but I’m not suggesting we amputate the foot even if I’d get some perverse joy from clawbacks against people who suck.]

Still, I wrestle with this quite a bit. I don’t really see myself as a businessman. As someone who would spin something up just because they see an opportunity. I’ve always been impressed by those kinds of people because I wish I could be like that. But it’s hard for me to care about something unless I love it. I don’t care about solving a problem just because it exists. There are infinite problems and I have one attention span. To a businessman, profit helps them filter. But more money than I actually need* is not motivating enough to do work I don’t care about. How would I even be excellent at something I didn’t care about?

But this perspective is a constraint of my own making. I don’t get to eschew opportunism and then complain that’s how the world and economy work. As it goes, I’m trying to figure out how to make more money doing these things that intersect my interest and ability. There’s a better product-market fit at the end of this rainbow, but finding it is harder than trading, and there’s no guarantee it will pay as well. But I’m immersed in the process of going there. And for that feeling, quitting was right for me.

*Adulting means you gotta do whatever you gotta do to make what you need OR lower what you need. But I’m talking about the same decisions we all make on the scale that is personally relevant. For some, it’s the choice of doing X for the 100k they need or Y for the extra 50k, and for others it might be the choice of $500k working remote or $1mm being on the road 60% of the time. Cate’s point in this essay is that everything is a choice and when you forget that become an entitled victim. Or to use one of my favorite lines…you’ve exchanged a walk-on part in the war for the lead role in a cage.


Money Angle

I want to clarify a statement from my chat with John from Risk of Ruin.

I said “vol trading is easier than directional trading”.

This is something I’ve felt from experience. I long attributed it to derivatives pricing being, well, derivative of an underlying. Trading an ETF or index future, both derivatives, is “easier” in the sense that there is a fair value with respect to some assumptions like cost of carry but the variation in the assumptions is vanishingly small compared to the error bars on the assumptions one makes when formulating an opinion about a stock price.

For options, most of the inputs except volatility also have error bars that are far smaller than anything you’ll assume about a stock.

Which brings me to volatility.

Volatility is more stable than returns.* This is why quants target risk in their sizing, not returns.

🔗See Know-Nothing Sizing for a fuller discussion. It’s an idea that underpins my approach to investing and risk management.

So if handicapping volatility is easier than handicapping returns, shouldn’t everyone just trade options for that sweet, easy cash?

The fact that it’s easier, also means the competition is fierce. It’s a zero-sum, capacity-constrained game. Predicting vol is easier than predicting returns, but…so what? You care about “how easy is it to make money?” and that is not easier.

The distinction reminds of this Daryl Morey bit on sport analytics:

Our underlying data is more predictive, quite a bit predictive. I talk to a lot of quants on Wall Street, and I tell them our signal to noise ratio using whatever measure you want….And they go like —whoa, you guys are — that’s incredible. And I’m like, yes, but you remember, we have to be best of 30. You guys just have to beat the S&P by 2% and you are geniuses. So each industry has its own challenges.

*For the option enjoyyyyers who are thinking “Bruh, VVIX is way higher than VIX, how can you say vol is less volatile than the vol of returns?”, here’s my rebuttal: What’s your 90% confidence interval on SP500 returns next year vs SP500 1-year realized vol?

An investor doesn’t care about vol of vol as if they are trying to price an option on VIX. If SPY realizes 14% give or take 5 points for a year (this is about the high/low range of 365 day vol using overlapping data for the past 4 years), this is not as destabilizing as the outright returns being say -5% vs +15% which is probably an even narrower relative range than 9% to 19% for a 1-year realized vol.

Money Angle For Masochists

Speaking of VIX…

Here’s an FYI that reinforces a lot of moontower 2025 writing on option synthetic futures.

This is from my IBKR screens from 10/22:

Spot VIX was 18.4

I highlighted the March VIX future. It had a mid-market of 21.725

The ATM strike for options on VIX expiring in March is 22.

The combo or price of the 22 synthetic =

call price – put price = 3.50 – 3.78 = -.28

Synthetic future = Strike + Combo = 22 -.28 = 21.72

No arbitrage available folks (as expected).

The synthetic future on VIX and the actual VIX futures trade in line.

💡The VIX options typically expire on the Wednesday morning preceding monthly option expiry cycles. The future expires on Thursday morning, 1 day later. For them to trade out of line with one another would imply a significant jump in forward vol for 1 day, and working through that math with our forward vol calculator can be educational. Unless there is an extremely impactful event on that Wednesday, I’d expect the actual and synthetic futures to trade in lockstep. A good homework for option firm trainees might be to draw indifference curves for various DTE (ie 5, 10, 30, 60, 90) of forward vols based on the VIX future vs synthetic future. I haven’t done it, but I imagine it will be self-evident that any variations between the 2 would be worth trading against, justifying why they trade in lockstep.

Like I said I haven’t done this, so I’m going off intuition on how forward vol works. If you are a VIX complex arb trader (I know you’re out there) feel free to correct me.

 

Stay groovy

☮️

Moontower Weekly Recap

Posts:

what hides in the option chain

We’ve been talking about option funding stuff recently in the paid Thursday issues. Recently, I had a trader ask for some help making sense of an option expiry in a single name that trades by appointment but where some chunky size goes through.

It’s a name with lots of hair on it with respect to events and distribution.

[The current mark of a big option trade that went through a few weeks ago is still rattling in my head. I’m looking forward to where the roulette wheel is gonna land on this thing!]

I’m obviously not going to give away the name, but I can recycle some of what I explained to the client using a fake stock.

It’s rooted in funding and why understanding it is frankly critical for making sense of names that have wide markets. You’ll see :

  • the first thing that caught my eye when I looked at the option chain
  • put-call parity’s relationship to a vol curve
  • how to avoid making really dumb trades (or if you’re a broker how to look like a hero to your client)

We can do this with screenshots and commentary to make this tour brisk but rich.

We begin with an invented option chain for our fake stock. I chose these values to be in keeping with the quality of the real stock’s markets without giving anything away.

For any junior traders or trainees this is good diagnostic practice — to eyeball an option chain and take notice of what’s interesting.

Relevant background info:

✅European-style expiry (it’s complicated enough without early exercise)
✅No dividends
✅RFR: 4%
✅DTE: 43
✅Stock price: $108.50

What do you notice:

Don’t start all nerd mastermind. Instead observe. These markets are wide!

Well, before you start thinking “The 125/130/135 call fly is negative, yay free money”, you should recognize that the market widths are obscuring this vol surface. I mean, if you think you can trade at mid-market, there’s free money all over this board. All kinds of bells should be going off but just as a surgeon has a checklist, there is definitely a priority thing to look for.

Think a bit before I offer a hint.

 

Ok, here are 2 columns that should help:

IVM = “IV Mid”

Categorically, the call IVs are greater than the put IVs on the same strike.

 

It’s safe to assume the stock is $108.50 as I indicated in the setup.

So what’s the likely culprit?

The rate.

We used RFR = 4% but with that rate put/call parity is not holding.

This is messy since we are using the mid of wide markets, but I didn’t contrive this situation from scratch— it is based on a real snapshot the client showed me on a screenshare, so it’s an opportunity to address real-world complications.

If call IVs is categorically higher than put IVs then the IV is being computed from a rate that is too low.

Instead of imposing a rate, let’s try something else. We will require that put/call parity hold at each strike.

💡Review the method: implying the cost of carry in options

This table is a handy way to start:

I highlighted the 110-strike because it’s closest to the $108.50 spot price.

The right-most column shows the implied yield of each strike. By computing an implied yield the call and put IVs are forced to be the same but I left the stale ones in the table for the sake of this chart:

It demonstrates that a difference in call and put IVs is another way of saying the implied yield or cost of carry on each strike is different.

If you impose put/call parity, forcing the IVs on the strikes to be the same (I didn’t recompute the IVs on each strike here with the implied rates from their strike), then instead of seeing a chart with call and put IVs not lining up you’ll get some implied rate curve across strikes like you see here.

Let’s look at this like a checklist:

✔️If the call and put IVs differ across the strikes when imposing a cost-of-carry parameter (as we did with 4%) then the market is telling you your cost-of-carry parameter is wrong.

✔️Instead, impose a market-based yield by starting with the no-arbitrage assumption of put/call parity to get call and put IVs to line up.

✔️But if this leads to large disparities in implied rates across strikes, well, we still have a puzzle.

Looking at our rate curve…we still have a puzzle.

Experienced traders know why, but just to bring it along gradually, here’s another table that will look very familiar to anyone with an ETF, index, or options arbitrage background:

Computing the implied market by calculating the implied synthetic stock futures bid and offer.

Remember, the synthetic is just the combo price (c-p) plus the strike price. In the prior table we based our synthetic prices on the midmarket values of the options.

Here we want more detail. For each strike, we calculate:

synthetic bid = call bid – put offer

Take the 110-strike as an example to consider what this means…if you hit the screen bid on the calls AND simultaneously lifted the screen offer on the puts, effectively crossing 2 $3 wide markets (before you got fired), you have sold the synthetic future at $107.

We compute the implied yield bid/ask using the implied combo bid and offer with the same logic. [Again, to turn option combo prices into implied yields see this post.]

The puzzle as to why we are getting a ridiculous range of implied yields is not too mysterious — the markets are just too wide. Garbage.

We will do our best with what we have because there’s still plenty to see.

The art of computing the vol surface

The preferred way to set a vol curve is to imply the rate, then impose that on the surface to generate strike vols. Since the implied rate on each strike based on mid-market won’t be perfectly uniform (although likely much better than this stock) you will still get different call and put IVs on the same strike but they are not likely to “cross”. In other words, you won’t be able to lift a call option on a strike for a lower IV than you can sell on the put (or vice versa). The error in IV should be within the market widths.

To give you a flavor of how you impose an implied rate on the strikes across the same expiry we can consider a few methods.

The tightest market

We cobble together the best bid and offer from any of the strikes to imply a yield. I don’t love this method for actually estimating the rate, but it’s the fastest way to spot an arb! Look at all the implied rates…the 75 strike really sticks out like sore thumb. If you hit the call bid and lift the put offer you have synthetically sold the stock at $109.80. If you buy the shares for $108.50, borrowing to finance them until expiry in 43 days, you will have legged a “conversion” trade for a fat profit.

Trader math — I borrow $108.50 for 2 months at 5% (notice conservative assumptions on both days and rate) that’s 1/6 * 5% or 80bps on $108…call it 90 cents. So I buy stock for $108.50, sell it at $109.80 and pay $.90 in interest…$.40 pure profit. Manage to get filled on 50 combos? That’s $2k in 2 seconds. Annualize that.

I’m getting carried away. This kinda thing is never just sitting there because it’s easy to program a bot to “eye” for it and then if it does find it, it’s because you ingested stale data. Still, I hope I conveyed the benefit of the “tightest market” method even if the benefit accrues to speed demons.

Weightings

How else can we find an implied rate to impose across all strikes? We could average the implied yields we find at each strike but give more weight to strikes with tighter markets (in this case, every market is $3 wide so the strikes would get equal weight and given the widths — still garbage).

We can just choose to look at a range of strikes near-the-money. We can weight their implied rates by inverse distance to the stock price. We can exponentially weight tight markets. We can draw hard cutoffs on strikes that exceed specified widths. You can use a solver across strikes but even then you probably filter the strikes according to criteria that come from experience.

[And when it comes to American options, may god have have mercy on our souls. The value of rev/cons can vary widely across strikes as the probability of early exercise differs. You are very much triangulating across several unknowns because the probability of an option being exercised also depends on its vol so you end up falling back on some ordinal relationships that bound early exercise relativity between strikes. In English, it’s easier to say relative things about early exercise adjustments to rev/cons than it is to absolutely value a rev/con. If there’s one area that even experienced traders trip up on its American options. Through the grapevine, from multiple sources, I’ve heard that one of the largest market makers in the biz lost a meaningful proportion of their annual profits because their mispricing of early exercise was exposed during the rate hikes in 2022.]

Anyway, there are enough choices involved that no 2 firms compute vol surfaces starting with implied rates in exactly the same way. There’s no benefit to bogging down on a specific method for this post so I’m just going to impose the 11.65% rate from the 110-strike and re-compute IVs.

With the single rate, the call and put IVs come closer together especially for the near-the-money options. The deep OTM options are going to stay a problem because a $3 wide market on a .15 delta option is just a lot of vol points of noise. [The vega on those options is much smaller than ATM, so $3 represents more vol width.]

Towards a single vol curve

Usually when you look at a surface, it’s just a single vol curve through all the strikes for a given expiry. A common way to do this is to simply use the IV from the OTM option. That option tends to have a tighter bid/ask width since it has less delta risk for the quote streamer.

If you don’t want to dismiss all the information from the ITM option on the strike, you could weight the IV inversely to the market widths or even to the options’ contribution to the straddle price on the strike. Here’s the vol curves using the OTM method and the Inverse Contribution To Straddle method:

Looks like a “W”.

If you have been paying attention to all the stuff I’ve written about vertical spreads and butterflies, you can guess the implied distribution:

bimodal

And yes, the original stock I helped the client with does indeed look bimodal. This is also a distribution you often see on stock earnings.

[My group used to call it the “teepee” and I heard from some transplants that it was another famous market maker who made a lot of money “teaching” the market that this was the right shape for a vol surface in particular situations.]

While this fake stock is the spawn of a real bimodal stock, this is not the most interesting thing about the surface.

By far the most important thing to see is that the implied rates are totally jacked!!! The calls are leaned incredibly high relative to the puts. You have to be able to see this right away (or infer it from the call IVs being high relative to the put IVs if you use a platform that doesn’t impose put/call parity on ATM mid vols).

Calls should never be too high relative to puts because conversions are easy arbitrages especially in non-dividend-paying stocks.

[In conversion trades, you sell call, buy put, buy stock. You must fund the stock purchase so you are exposed to rising interest rates. But that is the only material risk.

Reversals which entail buying call, shorting puts and shorting stock are exposed to declining rates but also any suprise dividends or the stock becoming harder-to-borrow. That’s why you almost never see implied rates trade much higher than SOFR — it’s easy to arbitrage via conversions. But implied rates often trade far lower than SOFR because borrow is uncertain. If you do a reversal trade because you want to exploit the implied rate, your most likely outcome is to find out the rebate you anticipated on your short stock was wishful thinking].

What can you do if you notice the calls are too high relative to the puts?

The eager beaver is going to say “do a conversion arbitrage”. I appreciate the optimism. But those markets are wide. Those mid prices are fake. You can’t get filled anywhere near mid if you try to sell calls or buy puts.

But that’s the clue.

What do you do with the knowledge that the implied rate is too high if you can’t do conversion arbs?

You simply don’t buy calls or sell puts anywhere near mid-market. You are walking into a trap. If you are a broker or advising someone, you explain this to them as well. You’ll save them a bunch of money and they’ll appreciate that you know your stuff.

[This also helps manage expectations. If you are a broker and given an order to sell calls into this market, you should point out that the implied rates are high, meaning the calls are leaned up, and the customer shouldn’t expect to get filled near mid. Similarly, they wouldn’t be able to buy puts near mid either as those are leaned down.]

 

In closing, when you look at an option surface there are so many invisible decisions about how to compute the IVs. When you see call and put IVs that vary greatly, your instinct should be to imply the rate. This post has been in the recent tradition of “options are ALWAYS about vol EXCEPT when they are about funding” but I hope today’s effort has actually shown that we can’t actually compute the vols without understanding funding.

One of the funny things about options is that while variance is an abstract concept to trade (the square of standard deviation??) it’s a straightforward bet — the outcome of the trade is tied to the intent. The payoff reflects the expression. If the realized volatility will be low, sell this.

Meanwhile, listed options, literally called “vanilla”, these American-style shape shifters tradeable from your phone are a pile of path-dependent, hard-to-solve “halting” problems, being discussed by weekend-house-flipper salespeople because there are so many ways to win or lose that are unmoored to your original intent that the randomness of the experience makes them perfectly marketable despite their basics being inscrutable to their average user.

I hope this post made them a little less inscrutable to you.

so you’re interested in trading…

Friends,

This is a follow-up letter I wrote to someone who called me interested in learning to trade. Look, trading is a neat career for many reasons (I discuss that at the end of my chat with John). But if you don’t enjoy the material below, it’s probably not a job you’ll like or excel in. Finding that out alone is worth diving into this. From the outside, it’s easy to get a mistaken impression of what trading is. It’s also easy to conflate it with investing.

None of the below material is technical. If you consider it technical, you’re a little bit behind but not drastically if you enjoy the material because that means you can catch up quickly. If the thought of learning this basic stuff sounds like a chore, really, just leave now. No judgment.

[Just as a matter of calibration. If you read this letter regularly, you can use me as a benchmark. I’m not technical by the standards of trading in 2025. I was more on the technical side of traders about 15-20 years ago. If graduating today, my education is too general to get hired as an assistant trader at a prop firm. You can still differentiate yourself by demonstrating an exceptional proof of work in the form of projects, entrepreneurship, leadership or competitiveness. But the bar is high.

Technology is leverage. 99.9%-tile is 1 in a 1000 while 99.0% is one in a hundred. In winner-take-all games, you want mutants not common valedictorians. At this point, my experience is what makes me valuable. My aptitude is average for this field, and below average, for many of the directions it’s heading in.

Luckily in America, how much signal you are doesn’t decide your prosperity. There are a lot of rich idiots because randomness is blind. The less skill you have, the more you want to play roulette not chess. Crank the vol. If you look at the trading or asset management worlds, can you capably classify which jobs are roulette and which are chess? Look at the winners in certain investment-related jobs and you can start to figure it out. This is called being strategic about what you should do and comes way before “I want to be a trader”.

A recurring theme: calibration is everything. Knowing where you are in a pecking order and choosing your actions in light of that is a life skill. You don’t need to be especially smart to do that, but you do need to be self-aware. That means interpreting feedback without your defensive ego scrambling the message.]

In short, trading is competitive. You need a genuine interest to maintain the required persistence when the going gets tough, which it always does. This is true of every competitive field.

Anyone promising easy returns is either:

  • inexperienced
  • stupid
  • lying

In other words, running a grift or flattering an ego gassed up by luck.

If I haven’t deterred you, enjoy the letter…


[name redacted],

As promised, here’s a short list of resources I think you’ll really enjoy if you’re interested in markets, decision-making, and risk. These cover a mix of foundational ideas, practitioner insights, and a few of my own essays.

Trading starts with a general way of thinking — what service does the market need that it offers a return for? Think of these resources as the mental operating system on which the tactical labor runs.

Remember, while investing is compensation for patience and risk tolerance, trading is compensation for research and labor. Work. And that work must outmaneuver the work of the competition. It follows that this will lead you to look for easy games where the best competitors are less likely to look (in fact understanding their barriers will be part of your prospecting).

If you google “trading systems” or anything related to making money from the comfort of your home, there is a high likelihood it’s the equivalent of house-flipping seminar lead gen. It’s a space rampant with unserious grift and marketing.

There is no shortcut. This material is groundwork and since it’s not project-based, should be done fairly quickly (I give some roadmap below). One of the primary benefits of working through this material is seeing if these ways of thinking resonate.

If it’s a drag, you’ve learned a lot about what you’re not interested in, and this is valuable, time-saving knowledge!


Books

  • The Most Important Thing — Howard Marks’ lessons on second-level thinking shines because it’s so approachable. The Gladwell of professional investment writing.
  • The Laws of Trading — Agustin Lebron connects adverse selection, psychology, and rational decision-making. If Mark’s book is a 101, this is the 3rd-level thinking grad course without being formal or technical.
  • Thinking in Bets — Poker player Annie Duke emphasizes one of the hardest but most fundamental principles in decision-making – restraint from judging outcomes by whether they worked. She teaches you to separate decision quality from result quality, embracing probabilities, updating beliefs, and thinking in expected value rather than absolutes.
  • Superforecasting — Philip Tetlock’s research on probabilistic thinking and what separates great forecasters. It’s a manual for improving accuracy and something even more important — calibration.
  • Fooled by Randomness — Nassim Taleb’s classic on luck, risk, and the illusion of skill.
  • Adaptive Markets — Prof. Andrew Lo on the evolving predator/prey dynamics in markets.
  • Retail Option Trading — Euan Sinclair and Andrew Mack’s practical look at option trading frameworks. Although focused on options, the messages are delivered in the context of general principles you must internalize. So think of it as “how they apply the OS to options”. You want to focus on the application more so than the option details.
  • Books by Andrew Mack — worth exploring if you want to dive deeper into what research looks like
  • Poor Charlie’s Almanac — Slipped this in just because. Even middle-schoolers should read it.

Podcasts

  • Risk of Ruin — thoughtful, narrative-style interviews with traders and gamblers exploring the psychology of edge and risk.
  • Bet The Process — focused on sports betting but full of probabilistic and behavioral lessons applicable anywhere.
  • Flirting with Models — Corey Hoffstein’s excellent conversations on quant finance, risk management, and portfolio design (more advanced, so this is aspirational. A glimpse of down the line.
  • Founders — stories of entrepreneurs told through deep dives into biographies, rich with insights about iteration and resilience. Generally motivating. Lots of timeless, simple ideas.

Blogs

  • Money Stuff — Matt Levine. Best finance writer on Earth. A daily habit of reading this will rewire your brain.
  • Robot Wealth — practical, data-driven experiments in systematic trading and learning.
  • Kid Dynamite’s Blog — not currently active, but the archives are incredible for plainspoken lessons from a former trader.
  • Michael Mauboussin’s Essays — an incredible collection of writing on expectations, capital allocation, and decision-making.
  • Newfound Research Blog — Corey Hoffstein again, blending quant research with clear, thoughtful writing.

Moontower Essays

A few of my own writings that expand on themes like volatility, edge, and how traders think:

This portal will help get your brain trained to more probabilistic patterns:
Moontower Brain Plug-In

This portal introduces you to a foundational, often underappreciated understanding of investing: Moontower Money


If I had to pick where to start, I’d say:

1. Howard Marks book

2. The RobotWealth Blog

3. Laws of Trading book

4. Thinking in Bets book

5. The select Moontower blog posts including the Moontower Money portal (the Brain Plug In is more of an ongoing thing to refer back to for brain food).

That should take about a month of reading in the evenings after work ( ~ a book + 2 blog posts per week).

Then I’d read Mauboussin…there’s so much there, it’s not about reading all of it but go with what sounds interesting. His way of thinking infuses everything he writes and those are the thinking habits you are trying to absorb.

Start here:

Probabilities and Payoffs The Practicalities and Psychology of Expected Value

Then from this link try:

Untangling Skill and Luck: How to Think About Outcomes – Past, Present, and Future

From this link try:

The Paradox of Skill: Why Greater Skill Leads to More Luck

The Importance of Expectations: The Question that Bears Repeating: What’s Priced in?

From this link try:

Min(d)ing the Opportunity: Excess Returns Require the Chance to Apply Skill

IQ versus RQ: Differentiating Smarts from Decision-Making Skills

Bootcamps

If you’d like to do a course I’d recommend:


I’ll close with something I told John Reeder near the tail end of the Risk of Ruin episode.

John prefaces my comments with:

Despite the fact that Kris writes about how to learn the math of options and about behavioral elements of trading — and despite the fact that a lot of this stuff is offered for free — some people are just not going to get it.

My take:

It’s gonna sound maybe harsh, but I tend to think that if you’re gonna figure it out, you just kind of are. You’re gonna find what to read; you’re gonna find the right things. And it’s like, if you’re unable to do that meta work, you’re just not cut out for it.

This is competitive. If you need to have your hand held just to figure out what’s good content and what’s not — you’re already cooked. Honestly, I really do try to be optimistic, but I think the people who are capable end up finding what they should be looking at.

On average, it probably works out that the people who are going to figure it out will end up finding the people who would have been their guides. I don’t think anybody’s born knowing how to do any of this. I’m very SIG-pilled in that way — I think you can learn. I don’t think everybody can learn it. I’m not saying that. You absolutely need some sort of minimum threshold of certain characteristics.

John to the audience:

Kris told me he sees a problem that exists today — a widespread rejection of experts. And he says that really isn’t going to work if the goal is to learn. Even the very top people that firms like SIG hire — brilliant, brilliant people — still have to be coachable.

So if those people have to be coachable, then everyone else trying to learn the same material, probably without even close to the same aptitude, can’t start the whole thing by rejecting the idea that there’s anything to learn.

I close that section with:

What does SIG do as soon as they hire somebody? They humble the shit out of them. Every single person they hire is smarter than almost everybody you’ve ever met. But what do they have to do? They have to cut them down a bunch of notches and say, “See everybody else in this room? They’re all trying to do the same thing you’re trying to do. And by the way, you’re not any smarter than any of them.”

So unless you can be taken down to where you’re ready to learn — to become a sponge, to become coachable — it’s not going to work.

can you read better than a 4th grader?

Friends,

Last Sunday morning’s letter talked about reading. The night before at my cousin’s wedding, he quoted CS Lewis in his speech. Later that Sunday, he was hosting a post-wedding fiesta at his house and the topic turned to book suggestions.

He recommended Lewis’ Screwtape Letters. I have the book but haven’t read it.

[Actually we have 2 copies now because my wife ordered it on my cousin’s rec not knowing I had it, but it works out since I can’t find mine since the move.]

My mother was visiting this week for the festivities so she opened it up and read the first page. She couldn’t understand it. I took a peek. I could read it just fine and in fact I quite like the style but it’s certainly harder than reading popular novels. My mother is a voracious reader, both fiction and self-help, but it’s all Dan Brown level.

I looked up its Lexile Score*.

*According to the Gemini blurb at the top of your Google search that steals views from someone else’s site, a lexile score is a measure of how difficult a text is based on attributes like sentence length and vocabulary

1170.

I looked up Lexile scores for Harry Potter or Dan Brown stuff. It’s all in the 850-920 range.

For context, I highlighted those mid to upper 800s here:

A top decile 3rd grader reads the same as a bottom decile 9th grader. Popular writing is about 4th-grade level. I asked my 7th grader to read a page from Screwtape and he liked it! He started it this past Thursday, after wrapping the Unwanted series he was addicted to. I looked them up. Only about 800 Lexile. Confirming my frustration that while he reads a ton, it all seems below grade level.

But I guess that’s true for almost everyone.

If interested, years ago, I compiled this table of books for kids based on reader recs or personal experience. It includes Lexile scores:

https://notion.moontowermeta.com/book-ideas-for-kids

 

Moontower #289

Friends,

Last Sunday morning’s letter talked about reading. The night before at my cousin’s wedding, he quoted CS Lewis in his speech. Later that Sunday, he was hosting a post-wedding fiesta at his house and the topic turned to book suggestions.

He recommended Lewis’ Screwtape Letters. I have the book but haven’t read it.

[Actually we have 2 copies now because my wife ordered it on my cousin’s rec not knowing I had it, but it works out since I can’t find mine since the move.]

My mother was visiting this week for the festivities so she opened it up and read the first page. She couldn’t understand it. I took a peek. I could read it just fine and in fact I quite like the style but it’s certainly harder than reading popular novels. My mother is a voracious reader, both fiction and self-help, but it’s all Dan Brown level.

I looked up its Lexile Score*.

*According to the Gemini blurb at the top of your Google search that steals views from someone else’s site, a lexile score is a measure of how difficult a text is based on attributes like sentence length and vocabulary

1170.

I looked up Lexile scores for Harry Potter or Dan Brown stuff. It’s all in the 850-920 range.

For context, I highlighted those mid to upper 800s here:

A top decile 3rd grader reads the same as a bottom decile 9th grader. Popular writing is about 4th-grade level. I asked my 7th grader to read a page from Screwtape and he liked it! He started it this past Thursday, after wrapping the Unwanted series he was addicted to. I looked them up. Only about 800 Lexile. Confirming my frustration that while he reads a ton, it all seems below grade level.

But I guess that’s true for almost everyone.

If interested, years ago, I compiled this table of books for kids based on reader recs or personal experience. It includes Lexile scores:

https://notion.moontowermeta.com/book-ideas-for-kids

 


Job Posting

Financial Sourcer/Researcher – Part-Time, Remote (Greythorne Associates)

We’re looking for a skilled researcher who can find talented quant traders, PMs, and strategists—the people who don’t respond to generic recruiter messages.

Greythorne is Stacey Crognale’s recruiting firm. Stacey was the director of HR at SIG when I was hired back in 2000. She started Greythorne in 2007 and specializes in quant finance with an especially strong pipeline in prop trading. This role is not an external mandate, but to work with her directly.

—> Apply here


A chat with John Reeder

John is the man behind the Risk of Ruin podcast. He interviews advantage gamblers and the occasional investor. The format is one of my favorite. It’s more like an audio essay than an interview. He does a lot of writing for them, weaving together his knowledge and lessons from experience and discussions, and then treats the guests answers the way you quote in an essay.

I’ve always been impressed by how well they are put together not to mention how much work they clearly require. As a long-time fan, I was totally honored to be invited on. John’s questions are always thoughtful and unique.

🎙️The episode is available on Spotify

We don’t get into the nitty gritty of options because that’s not the audience here, but for those interested in options, I do explain why vol trading is easier than directional trading (and why this is not the refuge it sounds like).

 


Money Angle

So You Want to Abolish Property Taxes ( Lars Doucet)

I remember being on some freeway, I mean highway, in the DFW area and seeing a billboard for some candidate promising to 86 property taxes. As a CA resident drawn to Georgist economic principles, in no small part due to Lars’ persuasive education, I’m just shaking my head as I whizz past the smarmy ad. Like what’s wrong with you? Your state’s economy is a positive role model — no state income tax, high property taxes, and allows builders to build. And you come up with this?

If your plea of “Don’t California My Texas” amounts to symbolic own-the-libs gestures like banning rainbow crosswalks and cannabis while inviting, hell, speedrunning Prop 13 distortions, then you are about as serious as a pixie stick.

Lars breaks it down so well, just check it out. If nothing else, read the section Answers to Various Objections.

 

Money Angle For Masochists

Option trader and author Euan Sinclair published a labor-of-love project that will become a cult classic for trading nerds.

The Theta Pig Letters

It is a remarkable pastiche of none other than — The Screwtape Letters.

The Screwtape Letters are an escalating correspondence between the devil and his demon protege Wormwood. The devil is teaching his dear nephew how to sabotage the lives of humans.

The Theta Pig Letters are an exchange between a master manipulator and his understudy whose trying to undermine traders attempts to succeed.

It’s not only brilliant, it’s fun to read. The condescending tone towards the incompetent nephew is relentlessly hilarious.

You can download it here:

The Theta Pig Letters
665KB ∙ PDF file

Download

A selection of excerpts:

  • The mistakes described here are not rare. They are routine. They do not announce themselves as errors. They arrive dressed as insight.
  • My dear Backtest: Congratulations on your first assignment. There is nothing quite so exhilarating as the early days of a Patient’s trading career, when vanity and vulnerability sit so invitingly close together. Trading, you must tell him, is uniquely stressful. Unbearably so. More grueling than any other occupation. (Do not, under any circumstances, allow him to reflect that bartenders suffer drunks, that teachers manage thirty howling infants, or that soldiers are expected to remain calm while being shot at.)Encourage him to think of himself as a kind of artist-warrior—misunderstood by ordinary mortals, ennobled by his suffering. His partner’s raised eyebrow becomes an attack on genius. Any well-meaning question is interpreted as doubt. He will learn to ignore those who do not mirror his self-image and surround himself only with those who validate it.And better still, he will eventually seek out “kindred spirits”—online forums, trading chatrooms, or overpriced mentorships—where the mythology is reinforced. He will not look for conflicting views or rigorous critique. He will look for comrades in suffering, not comrades in truth. A good trader seeks out disagreement; your Patient will seek only confirmation. the more he believes that trading is uniquely punishing, the less responsibility he will take for improving his own skills. The idea that competence, not courage, is the antidote to stress must never cross his mind. If he begins to study properly, to practice restraint, to track his errors with cold detachment—well, then you will have lost him. He will, without realizing it, become sturdy.
  • Let him convince himself that the law of large numbers is his ally, not his executioner.
  • Let them drown in a sea of partial differential equations and symbolic regressions.
  • Let them believe that beauty implies truth. Encourage him to chase symmetry where there is only noise, to assume continuity where there are jumps, and to impose causality where there is merely coincidence. Most importantly, let him believe that the clarity of a model matters more than its performance. That the elegance of his thinking is a substitute for testing. Make him allergic to heuristics. To approximations. To ugly truths. Let him scoff at simplicity and worship coherence. If you succeed, he will spend months—perhaps even years—building intellectual castles in the sand. He will conflate sophistication with strength. And when the tide inevitably washes those castles away, he will rebuild them: higher, more intricate, but equally unstable.Let him mistake thought for progress. That has always been our favorite kind of failure. And, Satan knows, you should be familiar with failure.
  • Let him believe that by reading financial statements, scanning headlines, and pondering macroeconomic conditions, he can infer what the market has missed. Encourage him to imagine that he is not reacting to price, but interpreting value. He will feel sophisticated. He will say things like “market overreaction” and “long-term thesis.” He will call himself a contrarian and imagine that patience is a strategy. Do not let him suspect that he is merely doing what everyone else is doing: consuming public information and projecting his own beliefs onto it. He must never consider the possibility that the balance sheet he’s analyzing, the CEO he’s quoting, the trend he’s spotting—are already priced in. Let him imagine that the edge lies in how he reads the data, not in whether that data is actionable.This is especially potent for Patients who fancy themselves worldly. They will cite books, articles, and podcasts. They will draw connections between oil prices and grain futures, between central bank policy and auto sales. Let them draw. Let them weave vast, fragile webs of inference and call it research.Most important of all, convince him that the more connections he sees, the smarter he is. He will not realize that each new variable adds noise, not clarity. You must never let him notice that it is merely confusion with a vocabulary.And let him pride himself on general knowledge. He has read The Economist, after all. He remembers something about China’s shadow banking system. He once mansplained negative interest rates to a bored babysitter. He will come to believe that markets reward this sort of cleverness. That his perspective is not just informed—it is rare.Do not let him test this belief. Do not let him look at the returns of those who trade on earnings reports or macro forecasts. Do not let him study the failure rates of discretionary portfolio managers. Above all, do not let him ask how many successful traders he knows who rely on reading. (Kris: profound…success is being repetitive, in some ways dull. A hammer. Types that fancy themselves intellectual is not the archetype anymore than you expect a professional poker player sitting in a chair 16 hours a day in poorly ventilated, unglamorous room with smelly dreamers to have a James Bond passport and home library.
  • Now we come to one of the most elegant diversions in our entire arsenal: the myth that risk management is the edge….If he were astute, he might see the absurdity of it all: that if risk management alone were the edge, then he could play the lottery with good position sizing and come out ahead. That perfect risk control, taken to its logical conclusion, simply means taking no risk at all. And there’s no edge in abstention.But he won’t see it—not if we play our part. Keep his thoughts on risk superficial. Let him use “asymmetric payoff” as a shield against deeper inquiry. Let him feel clever for “limiting downside while keeping upside open.” Just make sure he never notices that he doesn’t know where the upside is coming from.He will think himself disciplined. He will think himself wise. And best of all, he will think that not losing money is the same as making it.Let him worship at that altar, Backtest. It is a quiet church, and its congregation rarely asks for proof
  • Letter XI: But if he asks, “Why is VVIX diverging from VIX?” or “Why is NASDAQ volatility rising while the Dow’s is falling?”—that’s dangerous. Because relationships are where inefficiencies hide.How does skew behave as realized volatility rises? How long does it normally take for implied volatility to relax after a spike? Do the VIX options and SPX options account for the weekend in the same way? These are the sorts of wrinkles that arise not because the market is dumb, but because it is constrained. Because participants face capital charges, mandates, and rebalancing needs. The inefficiency is often the residue of friction.But if your Patient starts thinking in this way, we’re in trouble. He’ll begin to measure rather than guess. To observe rather than judge. To know the structure well enough to notice when it flexes. And that is edge.Stop this immediately.Distract him with headlines. Give him a guru who trades Tesla based on vibes and political bias. Feed him chart patterns shaped like ducks. Whatever it takes to keep him watching the show instead of reading the script.Snuff the curiosity. Leave him the confidence.
  • My regrettable aide,It seems I’ve overestimated you—again. You need help.You are enthusiastic, certainly. Eager. Occasionally—not often—effective. But in matters of craft, you remain a blunt instrument—loud where subtlety is required, impatient where patience would rot more deeply. And now, as the Patient begins to experiment with backtests, you must understand: this is a specialist domain that demands precision, not noise.Which is why I’m assigning you an expert.You will be working with Overfit. Do not speak unless spoken to. He does not tolerate enthusiasm. Or questions. Or you, if I’m honest— He will teach the Patient that systems must be tweaked, improved, optimized—until they hum with apparent perfection. He will praise him for reducing drawdowns, for raising Sharpe, for improving win rate by 0.03. And just when the Patient believes he has built something invincible… Overfit will let it collapse.Not immediately. That would be merciful. No, he will let it erode slowly, unpredictably, across market regimes that were never covered in-sample. And the Patient will blame volatility, not the process. He will tweak, not question. He will descend into an eternal loop of minor improvements. Like an old general planning for a war he fought many years previously.Overfit works in silence. In metrics. In elegance. He leaves no fingerprints—only code.Learn from him.He may even let you observe one of his routines: the 17-parameter breakout strategy that has a 1.47 Sharpe from 2008–2018, then disintegrates into noise. The Patient won’t discard it. He’ll “tune it for the new regime.” Again. And again. And again.Welcome to the second layer of hell, Backtest. You’ve played with belief. Now you’ll learn how to destroy through data
  • Letter XIII (Overfit’s first letter): Poison the foundation. We ruin the story in two ways: through data, and through method. The Patient must never suspect that his dataset is already betraying him. Some of the most reliable sabotages are achieved before the first line of code is written…
  • The point, Backtest, is not to mislead him directly. It is to cultivate his belief in rigor. To have him confuse exhaustiveness with validity, iteration with insight, and polish with truth.He must never think: “Does this idea make sense?”He must only think: “Can I make this idea work?”In this way, we will bury him in process. And the most beautiful part? When the strategy fails—as it must—he will blame himself. He will believe the system almost worked.That’s the mark of true failure: not that the backtest was flawed, but that it was nearly right.Almost correct. Endlessly refinable. Infinitely seductive.
  • Let Him Worship the Process. That is your final goal. Make him revere the ritual of validation more than the reality of outcomes. Let him define his identity as a “data scientist” rather than as a trader. Let him think that discipline replaces insight.He will become a guardian of statistical purity. A monk of withheld data. And he will lose money correctly. There is no cleaner form of failure than that.
  • Options. It is wonderful that the Patient has been allowed to discover options. Although I suspect you were just lucky in stumbling across this idea, it opens up many promising avenues for our project.You’ve done well to confuse him with the usual smoke: theta decay graphs, multi-leg jargon, and variations on iron condors named after insects. Now comes the ripest fruit: convincing him that an option strategy itself is an edge.Not the underlying market behavior. Not the statistical tendency of volatility to mean-revert, or of skew to overprice puts. No, no. The structure. The shape. The aesthetics of the trade. “My edge is in strike selection,” he said the other day. Selection! We are nearly there.Your task now is to seal the confusion between frequent and favorable. This is easier than it sounds. A wide short strangle, for example, wins often. Most days, nothing happens. The underlying chops around or drifts, the wings decay, and the trade is profitable. It is, in the short term, comfortingly correct. And like all good traps, it flatters his need to be proven right—again and again—until it suddenly doesn’t.What matters, of course, is the average outcome. Not the common one. But he has spent his whole life being rewarded for consistency, for pattern recognition, for turning in neat homework. The idea that a trade can win ninety times out of a hundred and still be a disaster is alien to him. Keep it that way
  • Your next task is to convince him that knowing the Greeks is the same as having an edge. We must not let him realize that the Greeks are merely descriptors—thermometers, not thermostats. They measure exposures, but say nothing of whether those exposures are favorable.
  • Make him identify as “a long vol trader” or “a short vol trader”. Make him pick a side before estimating which side is likely to win.
  • Whisper to him that true mastery lies in perfect delta hedging. That one day, with enough precision, he will out-calculate uncertainty itself
  • Your next task is to help him improve the strategy. Do not misunderstand me: we are not trying to make the strategy more profitable. We are trying to make it more elaborate.This is the art of post-discovery sabotage. The Patient has found something simple that works—some recurring pattern, some repeatable structure—and now feels the itch to “refine” it. Scratch that itch with gusto (it is no coincidence that mosquitos are on our side).Encourage him to add filters. Conditions. Weightings. Perhaps a volatility overlay. A moving average confirmation. A custom indicator. Or two. Or six. Suggest he look at volume, sentiment, cross-asset flows, macro overlays, news feeds. It doesn’t matter what. Just keep adding. Convince him that if he stops refining, he’s being lazy. That the real professionals are out there stress-testing their systems across twenty-seven regimes and fifty-three metrics and nine asset classes. Let him think elegance is amateurism. Most importantly, get him to optimize. Not once. Not simply. But obsessively. Every parameter must have a range. Every range must be backtested. Every backtest must have cross-validation. Let him run grid searches until his processor whines as much as you do. Let him discover the perfect lookback period, the ideal stop-loss, the optimal entry condition for a phenomenon that doesn’t. Over time, the original idea—the edge—will be so buried beneath rules and tweaks that even he won’t remember what made it work in the first place. If the strategy fails, he will have no idea why. He will re-optimize. Re-fit. Re-torture the data. Let the logic drown in complexity. Let the confidence die by a thousand knobs.
  • Automation: I am delighted that you have prompted the Patient to automate. This is the first real initiative you have shown and somewhat assuages my concerns about your ability and potential. Splendid. He will tell himself this is about efficiency. “The logic is sound,” he’ll say. “Why not let the machine handle it?” He will cite objectivity, discipline, and scalability. He will feel proud—professional, even. What he will not notice is that he is about to spend weeks automating a task that takes two minutes a day to do manually. This is the first victory: the gift of misallocated time. Every hour he spends writing code, debugging data feeds, and integrating APIs is an hour not spent thinking about the trade itself. He will be productive but only be producing something pointless.And the best part? Even if he gets it all working, it will still fail. Possibly not immediately, and probably not dramatically. But slowly, subtly, and in ways he won’t trace back to us.There will be bugs, of course. A mislabeled column, an off-by-one error, a missing data point that seeps through the system like a weeping pustule. He’ll fix these issues eventually. But each error will chip away at his trust. Not in the system—he’ll double down on that—but in his ability to implement it. He will begin to suspect he is the bottleneck. That more automation is the answer. Now comes the second level failure. Once automated, the trading process no longer asks anything of him. It runs. Quietly. Invisibly. His only feedback will be a daily P&L, eventually unnoticed, like the death of a woman who lives alone with the cats that will eat her. There will be no touch, no feel, no reason to monitor execution or slippage or spread. No sense of flow, timing, or friction. And because he no longer must think about the trade, he eventually won’t.The edge might remain, technically—but it will be unexamined, unmonitored, and unprotected. Execution costs will creep in. Fills will worsen. The strategy will degrade, not from a fundamental change in the market, but from neglect. And he will not notice.You must understand, Backtest: automation does not always kill by malfunction. It kills by abstraction. By replacing attention with convenience. By allowing the Patient to feel like he is trading when he is, in fact, only observing a spreadsheet. If you allow the patient to automate something out of necessity you will have committed a great error (and will be punished appropriately), but if he automates out of convenience then you have had quite a success. Please don’t ruin such a promising start.

 

Stay groovy

☮️

Moontower Weekly Recap

Posts:

implying the cost of carry in options

This is the follow-up to last week’s the easiest win in options is for stock traders.

In that post, we started with a puzzle that leads to a critical insight:

The collective pursuit of option arbitrage means that we can use put-call parity in reverse — to imply the cost of carry instead of assuming one, THEN trying to impose put-call parity.

In the example of the $100 stock and 4% SOFR rate, we computed the cost of carry or what we formally call the “reversal/conversion” or R/C was $3.92.

synthetic future = C – P = intrinsic Value + R/C

where:

C = call value on the 100-strike

P = put value on the 100-strike

The fair value of the synthetic future in our example is therefore:

→ synthetic future = intrinsic Value + R/C

→synthetic future = (S – K) + R/C

→ synthetic future = (100-100) + 3.92 = $3.92

I expect the call to be trading for $3.92 MORE than the put on the 100-strike if the stock is $100.

If it’s trading for a larger premium than $3.92 then there should be an arb:

  • Sell call, buy put [short the synthetic future]
  • Buy the stock

This is a “conversion trade and since the cost to finance the long shares is the 4% we used to compute fair value, I should have a profit left over.

If the call is trading at a discount to $3.92 vs the put then I should be able to do a “reversal” arbitrage where I:

  • Buy call, sell put [long the synthetic future]
  • Short the stock

The interest I collect on the proceeds of the short sale should exceed the premium I paid for the synthetic.

That’s the theory.

Of course, if you’re fair value differs from market pricing, guess who’s probably wrong.

Instead of using some assumption about the cost-of-carry, we invert:

“What does the cost-of-carry need to be for put-call parity to hold?”

It’s hard to overstate how powerful this inversion is. It has profitable applications to retail option traders, directional stock traders, both long and short, quants modeling option surfaces, and even fundamental investors concerned with dividends.

Conveniently, the lowest-hanging fruit affects the largest groups — directional stock and option traders. We will cover this in detail while keeping explanations shorter for the more professional applications.

We start with a question:

Have you ever noticed that the call IV and put IV for the same strike on an option chain are NOT equal?

This is all going to make sense soon. With some basic mechanics and simple algebra we are going to discover a whole new order book for stocks.

Solving for r: volatility is not the only thing we imply

We are going to take this journey in small steps.

We start with our identities to build our “if-then” muscles:

where:

K = strike
r = risk-free rate
t = fraction of a year

If r increases, R/C increases as the gap between the strike and strike discounted to PV widens.

Let’s re-arrange the synthetic future identity which includes the R/C to be in terms of the call and put respectively:

→ Synthetic future = Intrinsic + R/C

→ C - P = (S-K) + R/C

If r increases, R/C increases, therefore, calls go up in value while puts go down in value.

The heuristic:

When interest rates are higher the opportunity cost of buying shares increases or the cost of leverage increases if you buy on margin. Arbitrage ensures these costs are passed into the value of calls just as they are passed into the basis of futures over cash in any forward market.

Volatility

The inputs to the Black Scholes pricing formula are:

  • stock price
  • strike price
  • DTE (as fraction of a year)
  • RFR
  • volatility

For a given volatility, you can compute the call value, then, without using an option model, use put/call parity identities to compute the put from the call.

Note these call and put values are generated by the same volatility. We used the vol to get the call and then computed the put.

But this workflow isn’t typical. Instead, we are usually looking at option prices from a chain with implied volatility. In other words, the workflow is inverted. Instead of inputs generating option values, we see option values and imply inputs.

Notably, implied volatility.

Implied volatility is computed by fixing the option price and letting the volatility be the unknown.

[The solution is usually computed with a simple search algo like the Newton method which starts with a guess, then iterates until you are “close enough”.]

The RFR will be fixed to compute the implied vol, but when you observe the option prices you may find that the call and put have different implied vols. Another way to interpret this:

Put/call parity is not working.

But here’s the thing — put/call parity must work. If it doesn’t “work” there’s an arbitrage.

  • If the call IV is lower than the put IV, you can do that reversal trade: buy call, sell put, short stock
  • If the call IV is greater than the put IV, you can do the conversion: sell call, buy put, buy stock

What do you think is going to happen?

You will discover that a key assumption in the formula for generating those implied vols is wrong. The strike and DTE are in the contract specs. The stock price and option prices are observable from the marketplace.

The only variable remaining is the interest rate.

You can certainly call your broker to verify the interest rate, but they won’t be able to tell you tomorrow’s rate or any day after that.

What does this mean?

If you impose the rate and the call IV > put IV, then the market’s implied rate is lower than your assumption [and vice versa].

By assuming put/call parity must hold we are saying that the IV on the call and put of the same strike must be equal. But the only release valve for this constraint is we must accept that the market-implied rate can be different from what we think it is.

This is exactly what we should do.

By measuring the market rates by assuming no-arbitrage, we can then decide if a trade is attractive given our own funding rates. If the market implied interest rate is lower than what our broker offers (ie calls look cheap and puts look expensive or said otherwise the synthetic future looks discounted), then instead of buying the stock, we can buy the synthetic.

In fact, this is what professional option desks are doing all the time — they compare their funding costs from their brokers to the market-implied funding costs. If they can “refinance” their position in the options market, they effectively “go around” their broker. The implied funding market in options, including box rate markets, is often tighter than the spread of your broker’s long vs short rates. For a large enough desk it is not uncommon to have a trader whose entire job is to “manage funding” by trading rev/cons across the portfolio to reduce gross notional balances (ie if they are long lots of stock they will look to reverse or swap into futures if the cost of carry is cheaper than what the broker charges to borrow).

Solving for implied rate

Back to something we can easily see in the market — the price of the synthetic future (also known to older traders like myself as a “combo”):

Synthetic future = Intrinsic + R/C

C - P = (S-K) + R/C

I’ll use the examples from the webinar.

On 7/18/25, USO was trading $76.06

I pulled up the closest ATM strike in each month — the 76 line — and computed the synthetic future as the call – put.

I then subtract the intrinsic value of $.06 from each combo. The remainder is the R/C or cost of carry.

Remember:

We just rearrange this to solve for r, which gives us the implied rate.

Notice that the implied rates are below the Fed Funds curve at the time.

If you started with “I’m certain that the Fed Funds curve reflects my funding rate” then the combos would all look too cheap. When you “reversed” to do the arbitrage by buying the synthetic future and shorting the stock you’d discover why your Fed Funds assumption was faulty.

You will find that you are earning less than Fed Funds on your short stock proceeds.

But this gets better.

This is a perfect demonstration of why understanding this concept is immediately profitable. On 7/18, Interactive Brokers was charging 5.93% annualized to borrow USO. But you could short the stock via options to collect the rev/con instead of paying fees!

Consider the October expiry:

You could sell the synthetic futures at $.98 or $.91 more than intrinsic value, effectively collecting 3.3% annualized to be short USO instead of paying 5.93%. This is more than a 9% swing in carry costs (which is about 1/3 of the stock’s annual vol to put it in context).

Even though the funding rate from your broker stinks, you can “inherit” the market-makers rates by trading the options. The market-makers battling for arbitrage is a giant peace dividend to the rest of us who cannot access the same rates and borrow that institutions can. But even if you are a professional, the implied rates are often out of sync with the rates you can access, so there’s ample opportunity to refinance your positions in the synthetics market. The implied rate curve in the term structure is effectively an order book for a stock through time.

💡Refresher on how shorting works
→ If a stock is easy to borrow, you might earn a positive rebate (e.g., SOFR – 25 bps) on collateral of short proceeds
→ If the stock is hard to borrow (high demand, low supply), the rebate can be negative. This means you pay to borrow the stock (sometimes called the borrow cost)

Discussion

It should be a revelation to realize that the physical shares market is only one price for a stock, but the derivatives markets offer many others. The USO example showed how you can short USO at a higher synthetic price than if you borrowed the shares directly. Similarly, if a synthetic future trades far below the stock price, reflecting a high borrow cost, anyone who cares to buy the stock will get a massive discount in the options market.

The “real” market

When BYND went public, the peanut gallery (ie twitter) was all screaming how they wanted to short this fake meat company, but this was a consensus view — the shares were impossible to get your hands on to short. I’m going off memory, but the options market was pricing the synthetics at about ~40% discount to the ordinary shares. So the question for the peanut gallery isn’t “Do you still want to short the shares at the market-clearing price where the stock can be both bought and sold?”

Because that price is 40% lower. And if you were a long-term bull, what are you doing buying the ordinary shares? Just take the 40% discount and buy the synthetic.

[BYND has lost most of its value since it went public 6 years ago, but I wonder if a trader who but synthetic futures and rolled the position at each expiry would have actually won. I really hope so since that would be one of my favorite case-studies on the nature of trading.]

Backtesting

Directional traders who test both long and short strategies should be using the option synthetics market to reflect tradeable prices because those prices “lock in” a funding rate. Otherwise, backtests not only require borrow rate data sets but also need to deal with the fact that borrow rates change daily. A wicked backtesting concern.

Funding all the way down

In etf fair value, I mentioned an old habit from my arb days: computing the premium/discount on an ETF before trading options on it. I’ll leave this for you to ponder:

If an ETF trades 1% above its NAV, where should the synthetics on the ETF trade?

Vol modeling

When computing option surfaces, it’s common practice to imply the rate, THEN use that rate in the implied volatility formula to compute the IVs across the skew. This ensures that each strike has a single IV, and when charting the skew, we use the implied vol from the OTM option — its mid-market willbe more reliable because of narrower bid/ask. Having a single IV per strike also ensures the absolute delta of the call and put sum to 1.

In the examples I gave above, we implied the rate from a single strike that was closest to ATM. But a more robust method would average (or weighted average) the implied rate from more than 1 strike in case the bid/ask on any single strike was shaded too much in one direction. Multiple strikes would minimize the impact of those artifacts.

Dividends

I only addressed dividends in the appendix of the prior post to keep all of this a bit easier. For our current purpose, just recall that dividends decrease the cost of carry or R/C since the call owner misses out on the dividend but still experiences the stock falling by the amount of the dividend. Meanwhile, the put owner forgoes owing the dividend on the counterfactual short shares position and benefits from the stock falling by the amount of the dividend when it “goes ex”.

→The rev/con falls pushing puts up relative to calls

Easy enough.

However, the idea of an implied rate gets more complicated when we solve for r in the presence of dividends. Although it’s not hard to understand conceptually.

Consider a situation where Fed Funds (I’ve been using FF and SOFR interchangeably), is 4%, we expect the stock pays a 1% dividend, but the rev/con is 2.5% instead of something closer to 3% that we would predict from the general shortcut of cost of carry is interest – dividends.

Is this because the options market is saying your short rebate is 50 bps less than Fed Funds OR the stock’s dividend is expected to be 50 bps more than it has been in the past OR some blend of a dividend increase and rebate difference?

Do you see how incorrect assumptions here change the implied rate, which in turn affects all the implied vols?

Not only is there an implied rate, but an implied dividend. Whenever we get multiple unknowns, we need multiple lenses to triangulate. This is the realm of quantitative vol surface modeling, a task that many professional option traders outsource to specialty firms especially if their trading must discern the value of a penny in the premium.


This concludes the 2-part series on options as funding markets. As I said in part 1, this topic represents the largest gap between what people know and what they should know about options. It affects pricing, it’s highly actionable, and by allowing anyone to “refinance” a position at professional rates, it stands as one of the easiest win-wins in trading.

machine-readable

🎙️Media M&A (Business Breakdowns)

In this interview, Matt Reustle talks to Blake Saunders, a media investment banking expert and a partner at Core Advisors:

We cover the shift from generational ownership of media assets to rapid-fire M&A, how legacy media companies are responding to the potential of YouTube and Substack, and the dystopian economics of a future where media is driven by AI and algorithms.

Contents

 

On Sunday, I shared an interview with Doug Rushkoff. Doug said something in it that has kept rattling when he talks about the algo nudging us into binaries:

We desperately want to be machine-readable in this world. And the way to be machine readable is not to be in that liminal in-between space. Where do you fall?

Machine-readable.

This is what Postman recognized as Huxleyian dystopia as opposed to Orwellian. Our freedom wouldn’t be stolen by an authoritarian Big Brother but traded to our tech overlords for convenience and cat vids. (Ok, maybe Postman didn’t anticipate the cats).

Self-reinforcing loops of scale and consolidation have bottomless appetites for capital when the TAM is the entire human-wide industry of sales and persuasion. So long as you possess a waking minute with attention to spend, there is a last-mile problem the tech giants get paid to broker.

To defend your attention is to resist the bid to become machine-readable. Just as the food scientists at McDonald’s engineered the perfect mix of salt/fat/sweet addiction, there are wildly well-funded efforts to keep your eyeballs. You’ll understand why I chose the food analogy by the time you get to the end of this excerpt.

Technology will accelerate the Pareto-filtering of our society. I appreciate this excerpt because its implied message is critical: Sort yourself.

I mean don’t let that all-time sick disco guitar riff distract you from the message:

From the interview (emphasis mine):

Matt
I stopped getting my news from some sources. I mean, social media has overtaken the news feed so quickly that that’s incredibly hard to dig out of, especially if it’s not well-researched. Everything that we’ve talked about has a tie to what’s happening in AI. But would you just wax poetic in terms of the impacts that AI are having on the market? From any angle you want to hit on, what would you say stands out?

Blake
The biggest thing is people still question if it’s going to have an impact and then use weird analogies to say that everything’s going to be fine. Society is very fragile. The reason why we had a shutdown during COVID was not because half of the population had COVID—it was because a couple of percentage points and we had to stop the spread. So when you think about how our economy is built, the amount of people that are actually working in the US is not whatever 300 million plus people; it’s a lot less.

And the amount of people that actually pay taxes is less than that. AI doesn’t really need to impact that many jobs, but if it impacts a couple of them, it will need to radically change how we deliver value to people that aren’t working. This idea that the more free time we get, the more creative we get—it’s not true. We have more free time than we’ve ever had.

And most people are stuck on their phones and they have more anxiety, they have less friends, they have less sex, we’re more overweight than we have ever been, ever. If there’s one fact that someone can point to to say all this extra time and all this extra technology has made our life better, I don’t see it. I made this point last week: the only way to coexist with AI in a normal way is to disconnect, not connect more. The COVID point is we underappreciate how significant the tax rates will need to increase, not just on ordinary income.

I think the safe haven of capital gains—and you start to see regressive tax societies in Europe and other places where they start to come after retirement. And it’s the Elon Musk tax of let’s just figure out a way to tax assets that you haven’t sold yet. It has to come because you’re going to have to rebalance out how people make a living, which is going to be UBI. It’s a weird debate that I get into with people and most of the times the other side of the debate is just it’s going to be so great and stuff like that.

Great in their minds, which they don’t see yet: is everybody on GLP-1s, everybody on social media 24 hours a day? To me that’s not good.

Matt
If the AI is naturally deflationary, where it could do all the road work and it can teach in the schools, pick your various government expenses, then maybe there’s some offsetting impact?

Blake
I recently bought business class tickets to Japan and I was thinking, this is so cheap and I can just buy for a personal expense. I would normally not buy business class tickets on a 15-hour flight. Yes, the world will be completely deflationary and I think most things will be cheap. The problem is most people will be given effectively government money and the people that are creating assets and creating value will make a lot of money and basically be able to do whatever they want. Yes, everything will be cheap, but most people won’t be able to buy it.

Matt
It’s very dystopian. But I hear you in terms of the reality of it.

Blake
I’m not trying to be the 3 a.m. radio show of the aliens are coming—play out these basic trends. So if everyone gets an extra hour because of technology, are they going to put down their phones? I see this every time I take my son to the playground. Everyone else is on their phone, which is crazy to me. Put your phone down.

If people are given an extra hour, AI is going to be more addicting, not less. The world’s not going to end. For people that are operating businesses, it should be okay, but you just need a recognition that is probably why I started my own firm: you have to be a creator of economic value. That’s the only way to sort of exist.

You can’t be an employee and then there has to be a significant recognition—one or two percentage changes in the economic base and how people are employed. If we just take out drivers in the US, semi-truck and Uber drivers, that’s a big hit to the income base. It has happened before when we had to pay back the debt from World War II, where the tax rates were much higher for an extended period of time. It’s less about worrying about it and more about looking at where the trends are going.

If you have the realization you could see the COVID lockdowns coming a couple weeks before, and I think you can see this coming now, where the income base is going to go down, the taxes are going to go up. There’s still a society that you and I want to exist in which is less technology and more creative. I think there’ll be a lot of creativity happening, but for the majority of Americans, and that is today, 60% of Americans are overweight. It’s just a fact.

how overconfidence and confirmation bias create reinforcing loops

Below is an excerpt from the presentation I did at McCombs Business School at UT Austin.

It’s more hands-on to watch it after you take this quiz:

Confidence Test

(Respondents tend to score about 4 out of 10 on it.)

There’s a fun experiment in the video as well.

You’ll see just overconfidence and confirmation bias feed off each other in an escalating, reinforcing loop — and the key to stopping it.