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Fed

Last week I wrote that the underweight money would probably get stopped into the market, and that the easiest mistake was to confuse “stretched” with “sell”. And then Friday happened, and my weekend inbounds have all been similar questions…

Was Friday the top? Is this the start of something bigger? Was NFP the thing that finally mattered? And so forth.

I think the more important point to take away from Friday is that the AI trade did not die, it just changed category.

NFP caused Friday, I'm fairly sure of that. I sat there watching my PnL get worse by the minute, asking why, after that print, I hadn't bought 0DTE downside. I am still waiting on the answer. AVGO had already made the week feel heavy, and the GOOGL raise added a question nobody fancied dealing with on a Friday. So no, it wasn't a random red candle. The market was standing on one leg and got handed a rates shock, a soft print from a key AI name, and a wall of cost of AI headlines, all at once.

And yet even with all of that, it didn’t look like true panic. I think it was just a stress test where people managed risk via short-dated puts (QQQ+SPY had the highest put volume day in history). To put it bluntly, people haven’t dumped the whole AI trade from one Friday; they just hedged up and then cleared up any positions they didn’t fancy anymore.

To put this in simple terms - if people sell the thesis/narrative - you have a top. If people hedge the thesis/narrative, you just have a positioning problem.

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I think the thing that separates options traders from people who dabble in options and lose money is that options aren’t leveraged stocks. They’re completely different instruments that price direction, volatility, time, and path simultaneously. Most retail traders only think about one of those four. The market charges you for all four, every single time, whether you realise it or not. That gap between what you think you’re buying and what you’re actually buying is where most of the losses live.

Before we begin, the three most important (and probably generic) things I’d tell someone just starting out with options:

1. Your first job is not to make money. It’s to understand what you’re trading.

2. Cheap options are usually cheap for a reason.

3. Being right about direction is necessary, but nowhere near sufficient.

Most blow up because they ignore all three. They skip the understanding, buy the cheapest contracts on the chain, and they confuse a directional opinion with an edge. The irony is that options, used correctly, are the most precise and powerful tool in markets. Used incorrectly, and they’re just the fastest way to lose money with conviction.

Let’s call this post the foundation. No full-on Greeks lesson today (that’s Part 2), nor volatility surface mechanics or dealer positioning. There will also be no vanna or charm chatter throughout the whole series, nor will I write the post in emojis. This is just me explaining the core of what an option actually is, how they’re priced, what you’re really paying for when you buy a premium, the different styles and types you’ll encounter, and the structural mistakes most beginners make that are entirely avoidable once you understand the instrument properly.

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Same deal as the FX and Equities editions of this series, no textbook fluff. Just how it actually works.

And as always, proceed with coffee.

What An Option Actually Is

Let’s forget every convoluted definition you’ve ever read and strip it back.

An option is a contract where one party pays for a right and the other takes on an obligation in exchange for being paid. A right on one side, an obligation on the other, with a premium changing hands upfront. That’s literally it.

The buyer gets the right, and the seller takes the obligation. The buyer decides whether to act. The seller has no such choice. If the buyer wants to use their right, the seller must honour the contract.

This is genuinely different from buying a stock. Own shares and you’re fully in, unconditionally, riding every tick whether you want to or not. Stock drops 30% while you’re away? That’s your loss, and there’s nothing optional about it. With an option, the buyer has genuine optionality. If exercising the right isn’t profitable, you simply don’t exercise it. You lose the premium and nothing else. Your worst case is fixed before the trade exists.

The closest comparison in everyday life is insurance. You pay a monthly premium, and your insurer takes on the obligation to pay out if something goes wrong. Nothing goes wrong, they keep your premium. Something does, they pay. One side has a right to claim, the other has the obligation to honour it. A put option is, mechanically, insurance against a market decline. The terminology is different. The contract structure is identical.

This is worth knowing as many probably won’t know, but options weren’t originally invented for speculators. They were invented for hedgers. Farmers locking in crop prices before harvest, aiirlines capping fuel costs, fund managers protecting equity books without being forced to sell. The original buyers of options were paying for certainty, exchanging a known, capped cost upfront for protection against an unknown outcome. Traders eventually worked out you could use the same instruments to express views with far more precision than just owning the underlying, and here we are today.

Since I am going from the very basics up in this series, some of you will most likely know most of this post, but some won’t.

Calls and Puts

Everything you’ll ever encounter is built from some combination of these two.

Somehow, the definitions of a call and a put are the two definitions I know like a textbook.

A call gives the buyer the right to purchase an asset at a fixed price before a specific date. You buy calls when you think something is going up. Stock clears your fixed price, you buy cheaper than the market and pocket the difference. Doesn’t happen, and you walk away and lose the premium.

A put gives the buyer the right to sell an asset at a fixed price before a specific date. You buy puts when you think something is going down. Stock falls below your fixed price, you sell above the current market level for a profit. Doesn’t fall that far; you lose the premium.

Calls for the bulls, puts for the bears. Simple starting point.

Rights vs Obligations

Worth spelling out clearly, because the asymmetry between buyer and seller is the most important structural fact in all of options trading.

Buy an option: you have the right to act, no obligation to do anything, maximum loss is the premium paid, and your upside depends on how far the underlying moves in your favour. So the worst case is locked in before you enter.

Sell an option: you have the obligation to perform if the buyer exercises. Maximum gain is the premium you collected. If the underlying moves hard against you, the losses can be large. With a naked short call, in theory, the losses can be unlimited.

This asymmetry is the whole reason options exist as a product. The buyer pays a fixed, known amount for an open-ended right. For a binary event where you have a view but the outcome could go either way, that structure is often far cleaner than holding stock through the uncertainty. A position where your worst case is already defined is a very different psychological experience from one that can just keep going against you.

The Other Side of the Trade

For every buyer there’s a seller. This sounds obvious but most retail traders never really think about it.

When you buy a call, someone is selling it to you. That seller collected the premium and is now obligated to deliver shares at the strike price if you decide to exercise. They’re betting the stock won’t reach the strike, or at least won’t go far enough above it to outweigh the premium they collected. In most cases, that seller is a market maker or dealer, running a hedged book and making money on the spread and the mechanics of delta hedging, not on direction. Sometimes it’s an institution selling covered calls against a long stock position to generate income.

Selling options is a legitimate business. Not a dirty secret. Plenty of institutions and retail investors generate consistent returns selling premium, and it makes complete logical sense: insurance companies make money too. The seller is taking on an obligation in exchange for income, managing the risk of that obligation actively, and repeating the process. It works until volatility explodes and the losses overwhelm the collected premium.

Understanding both sides of the transaction changes how you think about pricing. When you pay $3.00 for a call, someone thought hard about whether $3.00 was enough compensation for the obligation they’re taking on. The price reflects a sophisticated assessment of probability, volatility, time, and risk. When you think the option is cheap, you’re implicitly saying you disagree with that assessment. Sometimes you’re right. However, more often you’re not. Being aware of who is on the other side and why they’re comfortable selling at that price is basic market awareness.

The Basics…

The strike price is the fixed price written into the said contract. For a call it’s the price at which you have the right to buy. For a put, the price at which you have the right to sell. Hold a $150 strike call, and you have the right to purchase the underlying at $150 regardless of where it’s actually trading. The strike is set when the contract is written, and it doesn’t change.

Expiry is the date the option stops being a live instrument. After that, the optionality is gone. If it finishes out of the money, it expires worthless. If it finishes in the money, it is exercised or settled according to the contract rules. Either way, the clock has stopped.

Premium is what you pay, quoted per share. One standard equity option contract covers 100 shares of the underlying, not one share. When you see a call quoted at $3.00, you’re paying $300 per contract. Ten contracts will be $3,000. The per-share price you see quoted and the actual money leaving your account are separated by a factor of 100. Sounds obvious, but I imagine it catches newbies constantly.

Open interest is the total number of outstanding contracts that haven’t been closed or exercised. High open interest at a specific strike means a lot of participants have positions there. This matters for understanding where large hedging flows might exist around expiry, and it’s one of the things professional traders watch when they’re trying to understand where the market might be pinned, which I’ll get into properly in Part 2.

Volume is the number of contracts traded in a session. High volume relative to open interest can signal new positioning being built, or existing positions being closed. Unusual options volume before a major move is something you’ll hear talked about constantly. Please treat it as a signal that deserves investigation, not a guarantee of anything.

Option Styles and Types

Not all options are the same contract. You need to know what you’re dealing with before you trade anything…

American Style vs European Style

Nothing to do with geography. This is about when you can exercise.

An American-style option can be exercised at any point up to and including the expiry date. Single stock options in the US are American style. A European-style option can only be exercised at expiry. Not before. You can still sell the option in the market any time before expiry, but you can’t force early exercise. Despite being an American index, SPX options, which are the most heavily traded index options in the world, are European style. Most OTC options are European style too.

The difference matters most in specific scenarios involving dividends and deep-in-the-money positions. If you’re short an American-style call on a stock paying a large dividend, there’s a real risk the holder exercises early to capture that dividend. If you’re carrying short options into an ex-dividend date without thinking about early exercise, you can find yourself with an unexpected stock position and an unexpected loss.

Cash-Settled vs Physically Delivered

When an in-the-money option expires, something has to happen. Either you receive the actual underlying asset, or you receive a cash payment based on the difference between the settlement value and the strike.

Individual equity options are typically physically delivered. If your Apple $200 call expires in the money, you receive 100 shares of Apple per contract at $200. If you’re short that call and it gets assigned, you have to deliver 100 shares. This obviously has real implications if you haven’t planned for it. Being short options that expire in the money and finding an unexpected stock position in your account the next morning is a very avoidable lesson. Although if you’re just getting started with options, I would not suggest you start selling options straight away.

Index options like SPX are cash-settled. No shares change hands. You receive a cash payment equal to the difference between the strike and the settlement value of the index. Cleaner, no delivery mechanics, no early exercise risk since they’re European style. This is a significant reason why serious options traders gravitate toward index products for anything other than single-stock views.

Exchange-Traded Options

Listed on regulated exchanges, primarily the CBOE for equity and index options. Standardised contract terms, live bid-ask spreads, transparent pricing, accessible through any standard brokerage account. The exchange acts as a counterparty through its clearing house, eliminating counterparty risk.

Weeklies, Monthlies, and LEAPS

The expiry you choose changes the character of the trade completely.

Weeklies expire every Friday. Extremely high theta decay. Very sensitive to near-term catalysts. If you’re positioning around a specific event, an earnings release, a Fed meeting, a CPI print, weeklies give you maximum leverage to that event with a premium that’s relatively cheap in absolute terms. If you’re holding a directional view with no specific catalyst in the next five days, weeklies are working against you almost immediately. Time decay in the final days of a weekly is brutal. You need to be right about direction, timing, and magnitude simultaneously. Three things at once.

Monthlies expire on the third Friday of each month. The liquid backbone of the options market for most names. Tighter spreads, more volume, better fills. Enough time for a thesis to develop without paying for excessive extrinsic value. The rational starting point for most strategies.

LEAPS (Long-term Equity Anticipation Securities) are options with expiries of one year or more. The theta decay relative to the premium paid is much lower than that of shorter-dated options. Delta behaves more like owning the underlying directly. LEAPS are normally how institutional money takes long-term directional positions using options rather than stock. Less capital deployed upfront, defined downside, full participation in a large move over a multi-year timeframe. Deep in the money LEAPS on names with genuine long-term conviction can be a more capital-efficient expression than buying stock outright. Most retail traders never even look at LEAPS because they’re focused on the weekly chain.

0DTE

Zero days to expiry. Options expiring today… What a beautiful invention.

SPX 0DTE now accounts for a remarkable share of daily CBOE volume and has fundamentally changed intraday index trading. The appeal is straightforward: massive gamma, cheap premium in absolute terms, violent moves if you get the direction right within the session.

The math is equally straightforward. To profit on a long 0DTE position, you need to be right about direction, timing within the session, and magnitude, simultaneously. Theta is decaying in real time and most 0DTEs expire worthless. There are many people who trade 0DTE profitably and systematically, running strategies that take advantage of the vol, gamma dynamics and intraday flows. But if you’re still building your understanding of how options behave, treat 0DTE as an advanced instrument that rewards experience.

Intrinsic Value vs Extrinsic Value

Every premium you pay is made up of two distinct components. I’d say that if you confuse them, you’ll spend years being confused by how your positions behave.

Intrinsic value is the real, immediately realisable profit if you exercised the option right now at the current market price. A call with a $100 strike on a stock trading at $115 has $15 of intrinsic value. Exercise it immediately, buy at $100 in a market at $115, that’s $15 per share. A $100 strike put with the stock at $85 has $15 of intrinsic in reverse.

Intrinsic value can’t go negative. The floor is zero. If your $100 call has the stock at $95, the intrinsic value is zero.

Extrinsic value (also called time value) is everything in the premium above that intrinsic figure. It’s what traders pay for possibility: the remaining time until expiry, the uncertainty about where the underlying ends up, and the implied volatility expectations baked into the option’s price. A $100 call with $15 of intrinsic trading at $18? That extra $3 is extrinsic.

So here is the critical mechanical fact about extrinsic value: it decays every single day, without exception. At expiry, it goes to zero. The option is worth only its intrinsic value at that point. No intrinsic value means worthless. A stock can go nowhere for two weeks, and the option holder still loses money just from time passing which isn’t unusual. That’s the product doing exactly what it was designed to do. The decay of extrinsic value is called theta, which I’ll cover in depth in Part 2. For now, just understand: time is not neutral for option buyers. It runs against them every day.

ITM, ATM, OTM

Three states. You’ll use these every time you look at a chain.

In the money (ITM) means the option has intrinsic value right now. A call is ITM when the stock is above the strike. A put is ITM when the stock is below the strike.

At the money (ATM) means the strike is close to where the underlying is trading. No intrinsic value, but the highest uncertainty of any strike on the chain. Nobody knows whether it expires in the money or not. ATM options carry more extrinsic value than any other strike and they’re the most sensitive to everything: moves in the underlying, changes in implied volatility, time passing. Watch ATM options closely, and you’ll learn more about how options actually behave than by reading any number of explanations.

Out of the money (OTM) means no intrinsic value yet. The underlying hasn’t reached the strike. OTM options are cheaper in absolute premium terms, which makes them look appealing, and I’ll get into why that’s often a trap.

Moneyness isn’t fixed as it shifts with every tick. An ATM call becomes ITM if the stock rises, and an OTM put becomes ATM as the stock falls toward the strike. The option’s behaviour, its sensitivity to moves, its time decay, all of it changes as moneyness changes.

How Options Are Actually Priced

This is the section most retail traders never encounter or get to read a simple explanation of. Yet it’s the one that changes how you think about every trade you’ll ever place.

An option’s price is a probability distribution made tradeable.

When you buy a call you’re not just buying the right to purchase stock at a fixed price. You’re paying for the probability-weighted expected value of that right at expiry. The market is effectively asking: given everything we know about this stock’s likely behaviour, what is the expected value of owning this right?

The theoretical pricing framework works roughly like this. Take all the possible prices the stock could reach at expiry. Assign a probability to each outcome. Multiply each outcome by its probability and add them all up. The result is the expected value of the option. The premium you pay is roughly the present value of that expected value, adjusted for interest rates and carrying costs.

So the premium is not arbitrary. It reflects a sophisticated probability calculation. So remember that every time you buy an option, you’re implicitly saying that you think the market is wrong about these probabilities.

There are six key inputs into any standard option pricing model. The current stock price, the strike price, the time to expiry, the risk-free rate, any dividends expected before expiry. And of course, volatility.

Five of those six inputs are either fixed or directly observable in the market. Volatility is the exception. It has to be estimated. And since nobody knows exactly how volatile the stock will be over the life of the option, different traders will have different estimates. The volatility assumption is where all the real disagreement lives, and it’s where professional options traders actually make their money. Not on direction bets but on being right about volatility when the market is wrong.

The volatility figure plugged into a pricing model gives you a theoretical value for the option. The actual market price is determined by supply and demand. When the market price is above the theoretical value based on your volatility estimate, the option is overpriced relative to what you think is fair. Professional traders are constantly running this comparison, asking not just “what does this option cost?” but “relative to what I think vol is going to do/be, is this option cheap or expensive?”

Most retail traders will never ask that second question. They look at the dollar cost of the premium and decide whether it feels cheap or expensive based on their gut feeling about the stock. Whereas a professional is making a far more precise assessment: is implied volatility too rich or too cheap relative to my expectation of how much this stock is actually going to move?

Implied Volatility (Implied Vol)

Implied volatility deserves its own section because it’s probably the most important concept in options trading that surprisingly so many consistently ignore or don’t know enough about.

When people talk about implied vol, they’re talking about the volatility level that, when fed into a pricing model, produces the observed market price for an option. It’s the market’s consensus estimate of how much the underlying will move between now and expiry, expressed as an annualised percentage.

If SPX options are pricing implied volatility at 20%, the market is effectively saying it expects the index to move roughly 20% annualised over that period. A 20% annualised vol on a 30-day option implies a daily move of about 1.25% and a monthly move of roughly 5.8%. These are rough guides, not guarantees, but they give you a sense of what’s baked into the premium.

Implied volatility is not constant across all strikes or all expiry dates. Different strikes at the same expiry trade at different implied volatilities. For most equity indices, OTM puts trade at higher implied volatility than ATM options, which trade at higher implied volatility than OTM calls. This shape is called skew, and it reflects a structural reality: markets normally price downside risk more expensively than upside potential because large down moves tend to happen faster and more violently than large up moves. I’ll go more into depth on this in Part 2.

What you do need to understand right now is that when you buy an option, you’re simultaneously buying direction and buying volatility. The premium you pay reflects both. And if implied volatility is elevated because a catalyst is approaching, like earnings or a Fed meeting, you’re paying an expensive premium that reflects uncertainty the market has already priced in. When that event resolves itself and the uncertainty disappears, implied vol will come off, and that collapse can overwhelm any directional gain you made.

This is what is known as a vol crush. It happens after most scheduled events.. Earnings, Fed meetings, Jobs data, CPI prints. Implied vol spikes into the event, then collapses after it. Buying options into these events means you’re paying peak uncertainty and then watching that premium evaporate even as the stock/index moves your way. I’ll go deeper into event vol and how to think about it in Part 2.

IV rank and IV percentile are the two most commonly used tools for contextualising implied vol. IV rank tells you where current implied vol sits relative to its range over the past year. An IV rank of 80 means implied vol is currently higher than 80% of its readings over the past twelve months. An IV rank of 10 means it’s near the bottom of its historical range. IV percentile is similar but measures what percentage of days in the past year saw implied vol below the current level. Both are imperfect, but give you a quick sense of whether you’re buying or selling premium at an historically elevated or compressed level.

Put-Call Parity: Why a Call Is a Put

Here’s something that so many never learn, and one of the things people don’t fully understand, ever, I don’t think.

Calls and puts on the same underlying, at the same strike, with the same expiry, are mathematically bound together. The relationship is called put-call parity and the punchline is this: a call option combined with enough cash to cover the strike price at expiry is exactly equivalent to a put option combined with owning the stock.

In practical terms, this means you can build a synthetic long call using a long put and long stock. You can build a synthetic long put using a long call and short stock. Every basic options position has a synthetic equivalent, and the two must be priced consistently with each other. If they diverge, there’s an arbitrage, and the market will close it almost instantly.

Why does this matter to me, you ask…

First, it means option prices are not independently set. When the call at a given strike moves, the corresponding put must move in step to maintain parity. Both reflect the same implied vol for that strike. They’re not two separate market views. They’re two expressions of the same probability distribution.

Second, it means you can always find the most efficient way to express your view. If you want to be long a call but the call seems expensive, check whether you could synthetically replicate it more cheaply via a put plus stock.

Third, it will give you an intuition for why dealers run their books the way they do. A dealer who is short calls and a dealer who is short puts at the same strike are, after hedging, managing essentially the same underlying risk expressed in different forms. The flow that results from their hedging affects the underlying stock or index in predictable ways…. This is the foundation of what we’ll cover around dealer gamma in Part 2 and maybe Part 4.

“Cheap” Options Are Usually Expensive Lessons

This one has cost me, and it costs almost everyone.

As I said earlier, OTM options are cheap in absolute dollar terms. It’s easy to see the appeal. But when you buy an OTM option, you’re buying a bet the market has already priced to lose most of the time. This is a fact. The price of that option reflects the market’s probability estimate of it expiring in the money. A call with a delta of 0.20 (and I will explain delta properly in Part 2, honestly, Part 2 of Zero to Stock Hero was better than Part 1… this is becoming a theme) A call with a delta of 0.20 is often used as rough shorthand for something like a 20% probability of finishing in the money. It is not mathematically perfect and it is not a real-world forecast, but it gets the beginner’s point across: the market is not treating that outcome as the base case. Four times out of five, by the market’s own probability assessment, it expires worthless.

The market prices options on what they’re worth in probability-weighted terms. You’re not finding a bargain when you buy a cheap OTM option. You are buying something the market has already priced to fail more often than it succeeds.

For that bet to work in your favour consistently, one of two things needs to be true. Either the market’s probability estimate is wrong (the stock is actually more likely to make that move than the price implies), or your payoff when you win is large enough to compensate for losing four times as often. Both can be true. Very rarely are retail traders buying OTM calls thinking about either of them. They’re looking at the $0.50 premium and imagining it becoming $5.

Then you have to add time to it. The OTM option doesn’t just need a big move, it needs that move to happen before expiry. A weekly OTM call bought on Monday that hasn’t moved by Wednesday has already bled a meaningful chunk of its remaining value just from a few days passing, regardless of what the underlying did. Right about direction, wrong about timing. Still expires worthless…

Cheap in premium is not cheap in probability. Separate those two things and you’ve already eliminated one of the most common and avoidable ways to lose money with this instrument.

The Four Things You’re Actually Trading

Buy a stock and you’re trading one thing, which is direction. Up or down. That’s the only variable. Everything else is noise you ride through.

Buy an option and you’re trading four things simultaneously, whether you realise it or not. Most retail traders are only thinking about one of them. But the market prices all four, every single trade, every day.

Direction. The obvious one. Bullish or bearish on the underlying. Necessary but not sufficient. And critically, you need to be right about direction AND speed. A trader who is right that a stock goes from $100 to $120 eventually makes money regardless of whether it takes two months or two years. An options trader who buys a call expiring in three months and the stock reaches $120 in month four loses money. Right on direction, wrong on timing. The option already expired. Womp womp…

Volatility. Baked into every premium. Buy when implied vol is elevated and you’re paying an expensive premium that reflects expectations of large moves. Buy when implied vol is low and you’re getting in cheaply. You can be completely right about the direction something moves and still lose money because you bought expensive vol that subsequently collapsed. You can also make money even when the underlying barely moves, if you bought options when implied vol was cheap and it subsequently expanded. Vol is a tradeable asset in its own right, completely independent of direction.

Time (theta). Not neutral. It runs against the buyer every day, in one direction only. Longer-dated options give your thesis more room to play out. Shorter-dated options demand precision on timing as well as direction. Every day you hold an option and the underlying doesn’t move in your favour, you’re paying theta. It’s the cost of owning the right. Some days, that cost feels negligible. In the final week before expiry, it can feel enormous.

Path. This one surprises people. Hold a stock through three weeks of choppy sideways action before it finally breaks out on day 22? You’re fine, the stock is at your target. Hold a short-dated call through those same three weeks? Theta has eaten most of your extrinsic value. You got there, but not fast enough, and the option that was worth $3.00 when you bought it might be worth $0.80 by the time the stock finally moves. Direction was correct. Path and timing cost you most of the profit.

Every options trade is a simultaneous bet on all four. The market prices all four, and all four show up in your P&L. Trading options as if they’re just leveraged stock is the single most common and most expensive mistake in options trading.

Payoff Diagrams

You’ll see these in every piece of options education, so here’s what they actually show and, importantly, what they don’t.

A payoff diagram plots the PnL of an options position at expiry against different prices of the underlying. Underlying price along the bottom axis, P&L on the vertical axis. The line tells you what the position is worth when time finally runs out.

Long call: flat line on the left at the level of the premium paid, your maximum loss. Stays flat until the underlying reaches the strike. Above the strike it slopes upward. Breakeven is strike plus premium paid.

Long put: mirror image. Flat line on the right at premium paid. Below the strike the line slopes upward in profit terms. Breakeven is strike minus premium.

Short call: flat line at the top representing the premium collected, your maximum gain. Below the strike you keep everything. Above it, losses rise without a ceiling.

Short put: flat line at the top representing the premium. Above the strike you keep everything. Below it, losses build as the underlying falls.

What payoff diagrams don’t show you is everything that happens before expiry. They’re a snapshot of one moment in time: the last moment. In practice, the option’s value changes every day as the underlying moves, as time bleeds out, as implied vol shifts. The diagram shows you the destination. But says nothing about the journey. And the journey is where you actually live as a position holder. You might be sitting on a large profit at expiry and have experienced a 60% drawdown in the position getting there. The diagram won’t tell you that. Useful for understanding the basic shape of a trade’s risk and reward. Not a complete picture of a live position’s behaviour.

A good site to understand how options behave is optionstrat.com. You can see the payoff profiles in action. Visualise how it will behave across different prices, dates and vol scenarios. Genuinely a useful free tool, especially when you start combining legs.

Why Most Beginners Blow Up Buying OTM Calls

I’ve heard this happen so many times it almost feels scripted at this point.

Someone is bullish on a stock. They look at the chain and see the ATM call at $4.00 ($400 per contract), and say an OTM call two strikes higher at $1.00 ($100 per contract). They buy the OTM call. Smaller outlay, bigger percentage gain if they’re right, feels like better risk-reward on paper.

Little did they think… the OTM call has a lower delta. Thus is less responsive to moves in the underlying. The stock has to travel past the strike before the option generates meaningful intrinsic value. While the ATM call participates in every move from day one and the OTM call just waits for a move large enough to matter. Also, OTM options are more exposed to time decay as a percentage of their value. That $1.00 call is almost entirely extrinsic. All of it is decaying every day. One sideways week and it can lose 50% of its remaining value. The ATM call decays too, but proportionally less of a larger premium.

Oh, and of course, this is the one that really gets people: the $1.00 price makes them buy more contracts. Four OTM contracts at $100 each instead of one ATM at $400. Same total spend, feels like more exposure and more potential upside. What they’ve actually done is multiply their time decay and volatility risk by four. When it goes wrong, it goes wrong four times as hard.

The result: stock moves up 3%, which directionally feels like a win, but the OTM strike hasn’t been reached, theta has eaten most of the remaining extrinsic, and the position is worth less than what was paid despite a correct directional call.

This is the most common options story in retail trading - quiet, grinding erosion of capital in positions that felt smart but were structurally stacked against the buyer from the start.

Exercise and Assignment: What Actually Happens

I assume that most retail traders never think about exercise and assignment until it happens to them unexpectedly. Then I’d guess it’s memorable.

Exercising means using the right you purchased. If you hold an ITM call at expiry, you can exercise it, pay the strike price, and receive 100 shares of the underlying per contract. If you hold an ITM put you can exercise it, deliver 100 shares, and receive the strike price per share.

Assignment is what happens to the seller when the buyer exercises. If you sold a call and the buyer exercises, you get assigned: you must deliver 100 shares at the strike price, regardless of where the stock is trading (if you don’t own the stock - you are now short). If you sold a put and the buyer exercises, you must purchase 100 shares at the strike price, regardless of where the stock is trading. If you don’t own the stock already, you do now.

In practice, most option buyers never exercise their options. They sell them in the market before expiry. The reason is straightforward: when you exercise an ITM option you receive only the intrinsic value. When you sell it in the market you receive the intrinsic value plus whatever extrinsic value remains. Exercising destroys the extrinsic value, whereas selling captures it. So, unless you specifically want to own the shares or there’s a specific reason to exercise early, you’re almost always better off selling the option.

The exception to this is with American-style options in specific circumstances.

Early exercise sometimes makes sense for deep ITM calls when a large dividend is about to be paid. If you hold a deep ITM call and the company is about to pay a dividend large enough that the value of the dividend exceeds the remaining extrinsic value in the option, it can make sense to exercise early to capture the dividend. This is called dividend arbitrage, and it’s why call holders sometimes exercise the night before an ex-dividend date.

Early exercise for deep ITM puts can also make sense when the option is so deep in the money that the remaining extrinsic value is minimal and the interest you could earn on the proceeds of exercising (receiving cash from the strike price) exceeds that remaining extrinsic. Rare in practice but it happens.

The assignment risk for short options is the more important thing to understand for most. If you’ve sold calls or puts that expire in the money, you may be assigned. This can happen at any point for American-style options, not just at expiry. Going into an ex-dividend date with short ITM calls is a particular risk because holders may exercise specifically to capture the dividend.

The Friday Lotto Exception

Now, before someone points out the obvious: yes, I enjoy the occasional Friday lotto.

A tiny 0DTE or weekly option punt risking 5-10bps of NAV is one of life’s simple pleasures. Markets are meant to be taken seriously, but not every trade has to be written up like a pension fund allocation memo.

There is nothing inherently wrong with buying a lottery ticket, as long as you know it is a lottery ticket. A 5bps Friday punt is entertainment with defined downside. In fancier terms, it is a small, pre-budgeted convexity bet. If it expires worthless, who cares?

But when someone takes that same idea and sizes it like a real position, they are outsourcing their dopamine system to the option chain.

What I am trying to say here is that there’s a difference between “I am risking 5bps for a bit of fun” and “I am risking meaningful capital on a short-dated OTM option because I saw a chart on Twitter and think this could squeeze.”

So yes, options can be lottery tickets. But lottery tickets belong in the lottery-ticket bucket. Sized like they are going to zero, because a lot of the time, they are.

When Options Are Actually Useful

Options get a bad reputation because most people encounter them through the speculative side first. Which is not what they were built for.

Defined risk on binary events. Earnings, a regulatory decision, central bank meeting. You have a view but the outcome could go either way, and the stock could gap significantly. Buying an option defines your maximum loss before you enter. You can’t lose more than the premium. For events with real gap risk in either direction, the structure is often far cleaner than holding stock through the uncertainty and hoping.

It’s leverage with a floor. A $200 call on a $100 stock controls $10,000 of notional exposure. Unlike leveraged futures or CFDs, the loss can’t exceed the premium paid. The leverage exists within defined limits. Used properly, it’s a meaningful structural advantage over other leveraged instruments.

Hedging without selling. This is why the instrument was invented as mentioned earlier in the post, and where serious money uses it most rationally. Long a large equity book and worried about a correction? Puts cap your downside without forcing you to liquidate positions you want to hold long-term. The premium is the cost of that protection. Whether it’s worth paying depends on how expensive the protection is relative to the risk you’re trying to manage. More on this in the following volumes…

Income generation through selling. Covered calls against long stock positions. Cash-secured puts on names you’d genuinely want to own at the strike. Structured premium harvesting programmes. In the right volatility environment, with proper sizing and active management, it’s a legitimate income source. However, I would say it’s a full-time job with real tail risk that needs to be managed seriously.

Convexity. Options have non-linear payoffs. A large move in the underlying produces a disproportionately larger gain than a small move would suggest, because gamma accelerates the position in your favour as it moves your way. When you’re long options and the market makes a genuinely large, fast move in your direction, you make significantly more than a linear instrument would give you. For tail risk positions, for macro views where you expect the magnitude of a move to be larger than what the market is pricing, the convexity of long options is genuinely powerful.

Expressing a volatility view. This is something that simply doesn’t exist in stock or futures markets. You can have a view that a stock is going to move a lot without knowing which direction, or that it’s going to move less than the market expects, and express that view directly through options without any directional exposure at all. The ability to trade vol as an asset class independently of direction is one of the things that makes options markets unique.

So if you’ve never traded options… here are a few things worth having internalised before you do.

Know what probability you’re paying for. Every premium is a probability estimate. Cheap OTM options are cheap for a reason. Before buying anything, ask yourself honestly: do I think the market is wrong about that probability? If yes, why specifically? If no, there’s your answer…

Check implied vol before you enter. Is IV elevated versus its own recent history? If yes, you’re buying expensive vol that’s about to be crushed. Is IV near multi-month lows? You might be buying options relatively cheaply. This literally takes you less than a minute, and it changes the analysis completely.

Treat time as a real cost. Every day you hold an option without a favourable move in the underlying, you’re losing money on the extrinsic decay. You can’t buy a call and wait indefinitely for your thesis to eventually play out. There’s no eventually, there’s expiry.

Should be obvious, but I’ll say it anyway… size relative to total capital, not per-contract premium. Twenty OTM calls, because each one costs $100 is not necessarily a small position (this all depends on the size of your book, of course).

Have a plan before entering. Where does the underlying need to go, by when, for this to work? What are you doing if it doesn’t? What are you doing if it gets there faster than expected and implied vol collapses? Options without an active management plan tend to decay quietly into losses. Unless you trade them like me, which is prem paid = max loss in most cases… but we will get to this later in the series, where I will try to share how I trade options and give some examples.

What Comes Next…

Greeks, Implied versus realised vol. IV rank and percentile. Skew and term structure. Event vol and the crush. Expected moves. Why buying calls before earnings is often much harder than it looks. Dealer gamma and how large option positions can create predictable behaviour in the underlying.

Once you understand the Greeks and the vol surface, options stop being confusing and start being a product you can actually read.

Part 3 I plan to delve into spreads, risk reversals, calendars, position sizing, when to buy premium and when to sell, how to manage winners, and so on…

If this was useful, the like button is right there. Restacks help other people find this instead of whatever they’re currently being told on YouTube.

See you in Part 2.

Fed

One thing I had to learn through actual losses: being right about direction is one of the four things you need to get right in options. Most people understand this intellectually when they read it. But almost nobody internalises it before it costs them money. I hope this post shortens that particular curve for some of you.

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If you're new here, the Zero to Hero series covers FX and Equities too.

Lord Fed's Gazette

From Zero to Stock Hero

In markets, you're not rewarded for knowing what's next - you're rewarded for surviving what's next…

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a year ago · 319 likes · 15 comments · Lord Fed

Lord Fed's Gazette

From Zero to FX Hero

In the time it takes to read this sentence, over $300 million in currencies will change hands worldwide. Welcome to the world of FX trading, where global currencies never sleep. With over $7 trillion changing hands daily, it's the largest and most liquid market out there. Whether you're just starting to trade currencies or you're keeping tabs on FX for …

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a year ago · 302 likes · 25 comments · Lord Fed

Let me show you the scoreboard first, because it buys me the right to say the uncomfortable thing that comes after it.

The SNOW 180 Jun calls I shared with subscribers before earnings at 6.9 (and allocated 70bps of NAV) last traded at 100.7, I am still carrying a quarter of the original size.

The Phase 3 basket (20% weight) has gone from +12.6% when I last wrote to +35% since I shared the basket in late March, doing exactly what I said it would.

From the last time I wrote, my top weights have done the following…

ORCL (10% weight) 186 to 248. CRDO (5% weight) 156 to 223. I also bought some 170 weekly calls in the dip at 3.5, which settled at 48.33… I took the delivery and sold the delivered stock shortly afterwards. Last night, it reported earnings and knee-jerked 15% down, as I type this, it’s barely down one. Bottleneck is doing what bottlenecks do.

MSFT (7% weight) 416 to 460, with the short 380p I am carrying against it quietly melting into irrelevance.

CRWV was put on ten days ago at 5% weight at 107, now trades at 125.

TEAM put on last quarter at 5% weight was 85 the last time I wrote, now 116.

NOW also put on last quarter at 5% weight was 99 the last time I wrote, now trades at 135.

The 70/90 Jun IGV risk reversal I put on for a credit is now 17 dollars ITM on the call strike.

The list genuinely goes on. Some may say I am victory lapping, maybe I am, but it’s been an incredible quarter, and now we enter the final month of it. I can’t sit here and act like you get many markets like this; you don’t. But when you do, the correct response is not false modesty, but to ask why it happened, whether it can continue, and what the market is about to bid next.

Dispersion has once again proved itself to be the most profitable condition of the spring. The software melt-up every desk has spent the past week trying to explain (IGV up double digits in a few sessions) is the same Phase 3 idea I wrote back in late March. Thus far, the software bid has been nothing but a cover bid. The AI-replacement bear case got way too loud. And so many of these names were too cheap versus their own cash generation.

Now, before you assume this post is going to be me finally climbing into the bear suit, it’s the opposite. The honest and repeatedly back-tested conclusion is that being stretched has not been a tradeable sell at all in this market, and the most likely surprise from here is a further melt-up driving a huge stop-in. So yes, I continue to look up and to the right.

So in this post, I'll share some fresh high-conviction trade ideas and where I think this market is heading next.

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I’ve been doing this long enough to know exactly when my own calls start making me nervous, and it’s actually not when they’re wrong. It’s when they’re right, and the people who told me I was an idiot for making them six weeks ago are now repeating the thesis back to me with slightly different wording, like it was the original thought. I guess that’s where we are right now.

This rally has been so clean that the same machinery now makes the reverse direction equally efficient, and almost nobody is paying for the right to be on the other side of it. Long gamma in the dealer book has been the most recent structural bid. Index vol has been pushed to levels that, in any other context, you'd be calling a gift if you expect a puke. Overwriters keep selling calls into a tape that's grinding higher, getting forced to cover and roll. Levered ETF AUM is enormous and rebalances daily in the direction of the move. And the underweight discretionary cohort has spent six weeks losing the argument with price and is now buying, late and undoubtedly a bit bitter about it. Every one of these flows is reflexive. The problem with reflexive bids is they're also reflexive offers… same door, just the opposite direction.

My Phase 3 basket is very much alive and will become even more so if semis come off. Phase 3 is effectively a short momentum trade right now, so when momentum comes off, the names rally. I don’t monitor 13Fs all that much, but there are some noticeable buys in the software space, specifically in a lot of Phase 3 names - so you could argue the names are in an accumulation phase. In case you missed the Phase 3 post, I have linked it below.

What’s changed in the past week is that something about the feel of last week has made me sit down and write a different kind of post this week. Just thoughts on my mind, a quieter post that if you only read the title, you’d assume I’ve lost my nerve (which I haven’t).

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I have been trying to work out what actually changed last week, because the obvious answer is not good enough. Yes, the market went up again and tech led again. Yes, semis and memory went vertical. And yes, the underweight crowd has run out of clean ways to describe the move without sounding like they have completely missed it.

The thing that’s standing out here is that the buying has started to look less like conviction and more like admission. Conviction will buy because it wants to, whereas admission buys because it has to. Conviction normally has a plan, whereas admission normally just has a sentence it repeats to itself while paying a worse price than it could have a few weeks prior.

I don’t think we are in a clean beautiful bull market where everyone has done their homework and had the realisation that the AI capex cycle deserves a higher multiple. It would be nice, but it would also be bullshit.

What I think is actually happening is much simpler than that. The market has gone just far enough for long enough in exactly the wrong names for a lot of people, that the ones who hated the move now have to buy the thing they spent six weeks calling stupid. This is not the most hated rally; it is the most humiliating. At some point, “I want a better entry” becomes a confession, and I’d argue we are somewhere around that point, which is exactly when the trade gets harder, not easier.

The first phase of this rally was basically survival. Don’t puke the book. Don’t short the recovery because you read three posts about breadth and don’t pretend every geopolitical headline is a secular regime change. Oh and don’t sell the companies still printing earnings. And you were fine. It’s not quite enough now.

Not a lot to update on my book, Phase 3 had a great week last week as did some of the derivatives I hold. I cut the long call leg of the 6500/7000 risk reversal. FSLY got hit post-earnings, not overly concerned with the position being at 2% weight, but a small annoyance since I thought it was about to break out and up. Last week was a good week. This week is the harder question.

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But I have spent the last few days going through the positioning, flow and sentiment data and I do not love what I am looking at. Not in the lazy “the market went up so it has to come down” way that I have been arguing against for some time as that argument is still wrong, and the people running it are still going to get hurt. The conditions that drove the rally are quietly changing, and the next dollar of risk in this book is no longer a long. It is a hedge.

The CTA bid is mostly done. GS has CTAs long around $44B of US equities and over $100B globally, that was your giant bid recently, and it has done a lot of work. Systematics bought almost $80B of US equities over the past month, the second-largest one-month re-levering on a ten year lookback. That tailwind is largely behind us, and the short-term and medium-term SPX pivots now sit around 6,930 and 6,820, which means a real break of either turns a friendly positioning backdrop into mechanical supply uncomfortably fast.

The Nasdaq just had its best month since 2002, and semis their best since 2000. None of that is a sell signal on its own, but stacked together it is the kind of backdrop where the market loses its margin for error.

Retail has moved along with it. Participation in SOXL is sitting at the 99th %ile on a five year lookback, QQQ just had its biggest monthly inflow ever, semiconductor ETF AUM has crossed $100bn, and the dip-buying behaviour from a month ago has quietly been replaced by chase mania.

So you stack it up. CTA bid, sentiment stretched, retail trading in vast volumes, and everyone is suddenly more interested in upside than they were 800 handles ago, which is not the same market I was writing about a month ago.

I have been the most bullish voice in your inbox. I had my hedges on, I didn't puke half the book out in panic, and I was right. But the conditions are no longer what they were, and I think a lot of people are about to learn the hardest lesson in markets, which is that being right on direction is not the same as making money.

For context, here are some marks from the book that have been doing the talking.… The 6500/7000 risk reversal I put on for 18 credit is at 312. The September 5,900 put I wrote for 188 trades at 52. TEAM is up 24% in a week at a 5% weight (still offside though). FSLY is up 11% as a fresh long that I paid 26.5 for last week. Phase 3 was up around 2% on the week with DDOG +8.5%, VEEV +6.5% and WDAY +6% leading the basket.

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Let’s do the unseemly thing first…

Last time I wrote, the S&P was in the 6600s, consensus was that the bounce had already gone too far, and I said the path of max pain was 7,200. Spot as I write this is 7165, 7,000 in Q2 was my call. We are past it, and we are past it on the exact set-up I described.

The trades have done the talking while I have been inactive on the writing front (although I do plan to release the Zero to Options Hero post soon)

• SPX 6500/7000 risk reversal for 6/18 put on at -18 now marked at 265

• SPX 5900P for September sold for just shy of 200, now trade at 65

• Phase 2 basket continues to do its job

• Phase 3 still a smidge off where I would like it

• CRDO (purple cable go brrr) at 6% nearly approaching 200 (I shared this in the mid 40s last year) now a 3% weight after taking some gains off at Friday’s close after reaching the $200 price target.

• The list is, frankly, too long to keep going - there’s some pain in the software names I hold, but overall, the book is outperforming, and that’s what matters.

I leaned the right way when CTAs were “max short” and the doomers were lining up for their oof moment. And I also leaned the right way through the lazy “the bounce has been too much too fast” consensus that we saw in the first half of April.

But the trade has changed. The market did what I wanted. Now I'm doing something different. And I think most people are about to give back what they just made even if index keeps trading higher.

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The easy thing to do here is say the market is crowded, index is high and that we should all sell everything since the market has done what I wanted to do. This is not what I think and crowded is totally the wrong word.

Index has caught up to the set-up but everything underneath hasn’t become one giant consensus long which matters as this is where people get lazy. They look at spot, see 7100s and decide the market must be euphoric, and then miss the fact that there is still a tonne of stress and disagreement under the surface.

It may not be the same setup as a month ago, but it is also not some beautiful everyone is all in top. It’s way more awkward than that…

Prime data continues to show the strangest combinations you can get. Index at the highs, AI leadership broadening, earnings coming through better than expected and yet US L/S books have just seen the largest notional de-grossing in seven months. Gross down hard, net down too and single stocks the centre of the unwind. Tech saw one of its largest weekly de-grossing episodes in years, while consumer discretionary was sold by HFs for the seventh straight week.

The above is not what euphoric participation looks like… it is when the market is doing one thing and the average PM is still fighting a war inside their book. It is hard to be bearish seeing this positioning.

The CTA/systematic bid that helped drive a lot of this has done real work. Rough estimate from banks is that the systematic community has bought ~200B of global equities MTD, taking positioning from a 2 to 6. They were short, trend flipped, vol calmed down enough and they simply HAD to buy. From here the baseline flow picture looks more neutral though they will add exposure if rVol continues on a downward trajectory and we continue trending higher.

This does mean that you can’t rely on the same argument here though. At the lows, the argument was very simple. People were too hedged, too bearish, too underweight… the same when the market bounced but then others started to get convinced that the bounce had gone too far. This was all enough for the market to rip. Didn’t even need every stock to perform well nor every headline to smell like roses - just needed price to stop falling and positioning to be wrong. So now the systematic positioning argument is slightly less clean.

The market can absolutely go higher from here, a lot higher… But the next leg needs more than everyone is the wrong side of the boat/offside. The sloppy bear case has been embarrassed and the same people who thought 6900 was impossible are now trying to work out whether 7300 in Q2 is conservative.

I think the thing I care most about here is not whether the S&P can print a higher number as of course it can. The thing I care about is whether the next dollar of risk belongs in the same place as the last one, which I don’t think it does. The market seems to be moving from beta recovery to leadership discrimination. The rally started off as a positioning squeeze, and leadership is not really Mag7 anymore. Mag7 breaking out does matter, sure, but the more important thing is what is happening underneath the index. The AI trade is no longer owning the obvious mega-caps and sleep as we have seen for a while now. The market is continuing to reprice the entire stack behind AI - semis, optical, data centres, inference beneficiaries and so on.

The boring stuff is becoming less boring because the bottleneck keeps moving and that is the bit that most people still don’t get. AI was once a GPU story, then a data-centre story, then a power story and now it is a full-stack infra story… (soon I hope a software story). Markets are paying for everything required to make the models useful, scalable, cheap/fast/available enough which is why Phase 2 worked so well as it covered all angles. Like CRDO, a bottleneck with a ticker. I guess the annoying thing about AI as a theme in general is that once everyone learns the lesson of bottlenecks getting paid, the obvious bottlenecks get expensive very quickly, and if you’re late, you become the momo guy you didn’t want to be.

I think you need to respect price, CRDO on Friday was a pure example… While I can see the name eventually trading at a 300 handle, my cut was not me losing conviction but respecting price and my target.

I still like the AI infra complex as I think the direction of travel is clear. I would argue that the market is underestimating how large the physical economy around AI can become, but saying this, I am much more interested now in what has not been fully repriced higher than in chasing the bits that have already become everyone’s favourite chart.

I think the next layer is probably power flexibility. For the last year, the market has been obsessed with whether there is enough power for AI which was totally the right question. Data centres need power and grids are constrained and time to power has become one of the biggest bottlenecks in the buildout. The next problem isn’t just total capacity but the shape of demand as training is heavy. Inference is real time, user facing and much spikier. As AI gets embedded into actual workflows and agents, the power requirement becomes less smooth and more volatile which changes things. The question goes from who can produce more electricity and becomes who can deliver flexibility into a system that was never built for this kind of load. Which is why energy storage is starting to matter a lot. Storage will smooth the spikes and reduce peak load pressures + defer infra spend. Electricity as inventory is a very big idea if compute demand is moving towards real-time.

Read a good document at the weekend on it from Morgan Stanley, who have Power for AI as a $1.5T theme rotating from capacity into flexibility. They estimate that data centre linked ESS (energy storage system) deployment could reach ~321GWh by 2030, which is roughly the size of the entire global utility scale ESS market. Sodium-ion could reset costs lower over time which would make storage economic across more use cases. Don’t really want to turn this into a newsletter about batteries but this is one of the spots where the AI trade is evolving. By all means, this does not mean whatsoever to buy every energy storage name with both hands as a lot of them are junk and will dilute you into a coma. But the theme is real, and this is exactly the kind of thing I want in my book when the market starts moving toward finding third-order beneficiaries. Which is why I am also not giving up on Phase 3/software. The trade has been painful, and there’s no point dressing it up. Software vs semis has been horrific and the unwind is going to be nothing short of incredible when people realise that software isn’t going to die. The AI kills software thing is just lazy and the market is rewarding picks and shovels still because the capex is visible. Customer lock-ins are not going to diappear just because some anonymous account on Twitter discovered agents… Owning the highest beta bad software just because it's down is equally lazy. So there are lots of names out there to find and lots of problems to solve. Just need to add more exposure to software where AI becomes a feature, a distribution advantage or a workflow expansion tool.

The other squeeze mechanic that I think people are still underestimating is the short-call/overwrite universe. There is a lot of money in products that have effectively been selling upside because everyone wanted equity income with less bond pain. That works until the market starts ripping through the strikes. Then they are not just passive sellers of vol anymore. They have to cover, roll, adjust, and in some cases buy back upside into a market already making highs. It is another reason why spot up can become vol up, and why waiting patiently for a nice little pullback can become an expensive hobby. The market does not need everyone to be bullish when enough people are structurally short the right tail.

This brings me to the macro left tail. I think we can all agree that the market has done a great job at looking through Iran, Hormuz, oil pricing and rates repricing. The market is probably right to see through the noise and turn its focus onto earnings and capex. But there is a difference between looking through something and pretending it doesn’t exist which is why I still want to own a bit more downside. The Strait situation is not clear at all and crude supply disruption hasn’t shown up in finished product shortages yet. The market has turned from war macro to earnings micro in a matter of weeks and while that can last, it could also reverse extremely quickly if oil, freight and input costs start hitting the wrong parts of the economy.

The safest thing to do is avoid parts of the market that are exposed to higher oil, stickier inflation and a squeezed real income consumer (despite me thinking inflation doesn’t stick). Cheap is not a catalyst, lagging is not a thesis nor is pain automatically an opportunity.

So where does this leave index I ask myself? Higher.

Not in a straight line and without stupid air pockets, not without a few days where everyone decides the world is ending again because of a 2am headline. But higher. The earnings backdrop is good enough so far, the AI capex impulse is powerful enough, leadership is broadening in the right places, buybacks are supportive, positioning is far from euphoric, and the people who missed the move still have to explain why they are underweight a market making highs. That last bit matters more than people admit. Markets don't need everyone to be bullish to go up. They just need enough people to be wrong. There are still plenty of wrong people. The difference now is that the easy wrong has been punished. The next part will be more selective and more violent within. Some winners will run much further than people expect. Some good stories will stop working because the market has already paid them.

So I will stay constructive and not be lazy like I was in other bull runs. You trim into rips and buy dips. Stay long the right tail and keep looking for the next bottleneck as the path of max pain remains higher if earnings keep doing what they’re doing. Hedge where convexity is cheap and trim where price has done enough. That’s the task now. Here at 7150, the edge is working out what people still don’t own properly, and I think there is enough to broaden this market out and keep it moving a lot higher.

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Process

A bunch of you asked variations of the same thing: how do I know when we’re overbought vs. oversold, how did I hold through the recent dip, how did I stay long into the Iran headlines, and does max pain actually work. I’m going to treat these as one question, because they are effectively one question.

The honest answer is that reading the tape isn’t one signal, it’s a stack, and the art is knowing which layer of the stack matters in which regime. CTAs for the most part of last year were totally irrelevant, but this year became relevant again.

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Two weeks ago I called this a buyers’ strike, and I still think that was the right description at the time. The market had stopped behaving like a place where people were looking for opportunity and started behaving like a place where nobody wanted to be first. Hedges got put on, macro took over, every bounce felt rented, and every headline felt like a reason to take off risk rather than put it on.

While the debate has been about whether the market has bounced too much, I have been leaning the right way. Last week’s SPX 6600/6650 call spread, put on the week before, risking 20bps of NAV, closed at max gain. I traded the 6800 calls on 9 April risking 5bps, paid 13 and sold at 39. Friday’s 6850 calls for 5bps died worthless. The direction has been right while this market has been working very hard to confuse people. That doesn't mean it's fixed. Nor does it mean people are back to believing the way they did before the Iran headlines hijacked the tape. What it means is that something important has shifted: the market is trading better than people feel.

We are well off the lows. The weekend talks didn't deliver some grand resolution, and futures are a touch softer again as I write this. This market has just lived through a geopolitical scare, a relatively violent squeeze, and a proper confidence wobble, and it was never going to glide back to all-time highs in a straight line.

What interests me here is not that the market bounced. It’s how it bounced, and more importantly, what still does not seem to be fully believed underneath the surface.

That is where this starts to get dangerous. Anyway. Let's get into it. This is the post where I put my cards on the table. You might think I've lost the plot. Or you might think I'm early. Either way, I think the pain trade is about to become very obvious to a lot of people who are currently sitting on the wrong side of it.

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Capitulation is broad and is when people stop pretending different tickers equal different risks. Correlation jumps, gross gets clipped properly and the market stops caring what you own because all anyone wants is less of it. I don’t think this has really looked like that. It has looked more like a market where people have brought net down, added hedges, trimmed exposure, and still refused to fully let go of the longs they think they will want back the moment the headlines calm down. This is what has made this market feel so awkward.

There has been a solid amount of pain, but the structure underneath it has been very different from a true washout. A lot of systematic selling had already happened. People’s books are a lot cleaner than they were entering the month of March but sadly cleaner does not mean healed.

Once a market gets this hedged, you don’t necessarily need great news to get a sharp move the other way. You just need less bad news - be that lower oil, slightly calmer rates, a pause/slowdown in headlines. Even a simple absence of fresh sellers can be enough when people are leaning on shorts, gamma is unstable, and nobody really trusts the downside as much as they did a week ago.

Macro remains very much in control for now, with oil and rates setting the tone. Growth expectations still have not taken the kind of hit that usually comes with more durable lows. But I’d argue you’re seeing some change in growth pricing when you look at the front-end of the curve… see SFRH7 the trade I recently put on and shared with subscribers which is up 20bps from where we entered.

I think where we are the easiest way to look at this market is one that has reduced risk without fully giving up, which is exactly why the next move can be bigger, faster and much harder to trust.

CTAs are finally relevant. I know I haven’t spoken about them for a while, and there was a reason for that - for most of the past year, they were just passengers (as they should have been), adding to a trend that was already working. Now they do matter, and I think this is where it gets interesting and is one of the most underappreciated dynamics right now.

Over the past month, this small cohort has sold roughly $184B of global equities and is now short in a meaningful fashion according to GS flow estimates. In US equities specifically, they are estimated to be short ~$28B S&P. When you go from long, to getting stopped out, to running negative momentum signals across multiple lookback periods, the character of the selling does change.

I think the supply that has been driving this move a lot is approaching exhaustion. GS modelled flows forecast that only a few billion dollars of selling over the next week under a flat tape, against the tens of billions per week we have seen through March. That deceleration is substantial and changes the market dynamic even before you think about the upside case.

On an up tape - CTAs flip from sellers to buyers with $142B of demand sitting in the wings if price cooperates. I would like to be clear on this though. I am not particularly enthused about this asymmetry because the critical word is if. You actually need an up tape to trigger it. The 142B does not show up because positioning is extreme. It shows up because price moves first, and the momentum signals respond to that. Conditional flows are conditional.

It is also worth remembering that this asymmetry is nothing special despite the expected number being in the top %iles. We had the exact reverse of this setup during the 2025 rally. CTAs were huge buyers on the way up, adding fuel to a move that was already working and would have been enormous sellers on any meaningful down tape at that time. That is simply how trend following works. Large buying on up tapes and large selling on down tapes - pretty standard for the community.

Something circulating right now that I want to address directly, because it is leading people to draw the wrong conclusions from the positioning data. You will have seen it on X… “CTAs now max short”. The implication being that CTAs have hit some kind of capacity ceiling and that they literally cannot sell anymore, thus a violent reversal is imminent. I pushed back on it later night and I want to explain it properly

The percentile ranking that banks publish alongside CTA positioning data is a lookback, not a capacity signal. When GS or Morgan Stanley flag that CTA equity exposure is at the 99th percentile on a five year lookback, all that means is that current positioning is as extreme as the model has observed over that window. It does not mean that CTAs are out of ammunition. It does not mean that they are physically unable to add to the position. The models are not pegged to industry AUM, but momentum signals. If the momentum signals push further negative, the models respond. The positioning can go further from the historical distribution suggest, because history is not a constraint on future behaviour. Another point worth understanding is that the percentile ranking is not scaled to the actual size of the CTA industry. A reading of “max short” today may translate into a very different notional dollar exposure than the last time the same %ile was observed. A 99th %ile short in 2026 may represent more notional than a 99th %ile in 2021. The %ile simply tells you about signal intensity relative to history and tells you very little about flow capacity that sits behind it.

What the extreme percentile does tell you, however, and this is worth taking seriously, is something about the asymmetry of moves from here. At positioning extremes there is simply less room to add in the same direction and can signal that the trend is becoming exhausted. A “max short” reading does not mean the short cannot get bigger, but it does mean the marginal signal required to add further is harder to generrate than it would be from a more neutral starting point. It is not the same as the market being about to rip, but is a real structural consideration when thinking about how future price action might interact with CTA flows.

The honest framing is that the extreme positioning is relevant context for thinking about the conditional flow picture and what could happen. It is not by itself a catalyst.

I have said all of this before. Not a new position for me. In Sept 2025, when CTAs were on the other end of this, the same language was doing the rounds. “CTAs are max long” - same implication just opposite direction.

Percentile rankings are lookback observations, not capacity limits. Models are pegged to signals. At extremes, the asymmetry shifts but capacity does not disappear. The incremental buying power is limited when you are already heavily long, but that is a statement about the risk/reward of the position, not about whether CTAs can add. Ya di ya da. What made this moment worth paying attention to was not that CTAs were “max long” and therefore due to reverse. It was that the positioning asymmetry at that level meant the potential energy from this cohort on the downside was disproportionately large relative to the remaining upside fuel. If markets rolled over from that point, the unwind would have been huge (similar to what we have seen recently).

So. Similar to now… The energy will only convert into actual market force if price gives the signals something to respond to. The machine does not move because the %ile on Goldmans models lookback is extreme. It moves because price moves first. That is the part that keeps getting lost in these “max short” tweets floating around. Positioning is a loaded spring, not a self-releasing mechanism.

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That is not a rhetorical question. It is one of the most important questions in markets right now, and the answer is worth a lot of money to the people who get it right.

The prevailing narrative says AI kills software. That foundation models replace enterprise platforms, vibe-coding startups displace incumbents and the world’s largest companies rebuild their operational infrastructure from scratch and legacy software vendors slowly get left behind. I have spent the last few weeks going deep on this theme and I have come away thinking the market may have it backwards.

I think that narrative is wrong because what I am seeing is not AI replacing software. It is AI being absorbed by it.

And if that is right, the winners of the next phase are not who the market currently thinks they are.

The full thesis, the basket architecture, and all fifteen names are below.

Let’s be honest about the backdrop first.

Software has been ripped apart this year. IGV is down more than 20% year to date, and the median software stock is more than 40% below its 52-week high. Sector valuations have compressed to roughly 40% below their 5yr average on forward sales, while free cash flow multiples are more than 75% off the peak. The broader tape is not exactly offering comfort either. As I write this, the S&P is sitting on key support with the moving averages starting to roll over. There is a very real chance this gets worse before it gets better.

I am launching Phase 3 into that weakness deliberately.

This is not a trade for the next three weeks. It is a multi-year position being built at a point of maximum dislocation between sentiment and reality. If the market deteriorates further, the basket will feel pain in the short term. That is the cost of the entry point and I want to be upfront about it.

The question that really matters is whether the thesis is right.

The Thesis

The software selloff has bundled together two completely different stories, and that confusion is the opportunity.

On one side you have weak, sponsor-backed private software businesses from the zero-rate era. High leverage. Weak vintages. Over-earning point solutions. Businesses underwritten in 2021 on aggressive assumptions, thin moats, and cheap capital that no longer exists. Some of those companies deserved to be re-priced. Some of them face real disruption risk. The fifteen names in this basket are not those companies.

These are incumbent platforms that run the operational backbone of global enterprise. They sit inside payroll, finance, planning, compliance, customer workflows, security, logistics, and supply chain. They are well embedded into the machinery of how large companies actually function. And rather than being threatened by AI, I think they are the primary mechanism through which AI gets deployed at scale.

The market is treating all software as one story. It isn’t. The mistake starts with how people think about software in the first place. The bearish case may sound neat in theory. AI writes code, code becomes cheaper, thus startups build faster. Legacy vendors lose their edge but enterprise software is not just code. In many cases, code is the easy part. The hard part is everything around it.

It is architecture. Workflow logic, regulatory scar tissue, auditability, the integration with dozens of other systems. Customer retraining. Reliability under stress. Years of edge cases discovered the hard way. Years of decisions made by people who actually had to keep these platforms running inside live businesses. And that is where the moat lives.

The market keeps talking about foundation models as if they can simply be dropped into the core of enterprise systems and take over. I do not buy that. A payroll system cannot be mostly right. An enterprise resource planning system cannot hallucinate its way through compliance. A financial workflow cannot produce two different answers to the same question depending on how the model feels that day.

The closer you get to real enterprise workflow, the less tolerance there is for probabilistic nonsense. That is why I think the “AI replaces software” narrative breaks down the moment you move from demos to mission-critical systems. These platforms need to be repeatable, auditable, reliable, and deterministic.

The second mistake is assuming that faster code generation somehow collapses incumbent moats. It doesn’t. The market is acting like vibe-coding equals instant competition. It does not. Writing code faster is useful, but only if you know exactly what needs to be built, how it needs to behave under stress, how it fits into the broader workflow, and how it interacts with the dozens of other systems surrounding it.

A startup can generate code quickly, but that does not mean it can recreate decades of architecture, customer trust, workflow depth, compliance readiness, implementation history, and switching-cost gravity.

In enterprise software, the moat is not just what the product does. It is what the customer risks by leaving. And that is where the replacement narrative really falls apart.

The CFO of a global manufacturer is not ripping out an ERP because a startup has a cleaner interface and a better AI demo. They are thinking about data migration, regulatory exposure, integration with forty other systems, retraining thousands of employees, operational downtime, board accountability, and the non-trivial possibility that the entire project becomes an expensive disaster.

Those risks are real. They have always been real. AI does not make them disappear. If anything, it makes the incumbents stronger because the incumbents already own the workflow. That, to me, is the most important part of the thesis and the bit the market is missing.

The incumbents are not sitting still waiting to be disrupted. They are the ones with the installed base, the distribution, the domain expertise, the customer relationships, the workflow context, and in many cases the best data. If AI is going to be embedded into enterprise workflow, why would the value accrue to outsiders rather than the companies that already own that workflow?

That is why I think the winners of this phase are not the people trying to replace enterprise software from the outside. They are the incumbents absorbing AI from the inside.

That is how I think about what is happening now. AI gets pulled into the software stack as an intelligence layer. Not as a substitute for the platform, but as an enhancement to it. The platform still provides the reliability, controls, audit trail, and scalability. The AI layer improves productivity, speeds up decisions, automates repetitive workflows, and expands what the software can actually do.

Together, that creates something much more powerful than either on its own.

And crucially, the platform captures the value because the platform owns the customer relationship, the workflow, and the place where decisions actually get executed.

That is why I think this is not some niche side theme. This is the main way AI diffuses across the real economy.

Every top company runs on enterprise software. That software is now getting smarter. The companies that own those platforms are, in my view, the primary beneficiaries of everything the market has spent the last few years financing further down the stack.

The Valuation Case

Even if you ignore the thesis completely and just look at the numbers, the setup is attractive.

Software as a sector is trading at roughly 5x forward sales versus a 5-year average closer to 8x. That is around a 40% discount to recent history. On a growth-adjusted basis the discount is still material. P/E multiples are well below their medium-term average and free cash flow multiples have been crushed relative to prior peaks.

In other words, this is not a sector trading as if the market sees a coming acceleration in value. It is still trading as if disruption is imminent.

That is the disconnect. Because I do not think the underlying businesses have deteriorated in the way price is implying. In many cases, their strategic position has improved. Their AI products are more credible than they were a year ago. Their role in the stack is more important, not less. Their moats look deeper once you separate real workflow ownership from AI narrative tourism.

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Not close to some beautiful low where everything lines up perfectly.

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Not because nothing has been happening, but because this has been one of those stretches where the market has become noisier than the signal. Every few hours another headline hits, oil and rates jump, credit gets dragged into the conversation, software gets used as a pinata again, and yet the market still refuses to give anyone the clean break they’re desperate for.

This kind of environment can easily fool people. If you only look at the S&P, it feels like we are just chopping around in a frustrating range. If you look underneath the surface, there has been plenty going on. Hedge funds have been cutting, ETF shorts have surged, asset managers have largely frozen while systematic exposure has been coming down again. ETF shorts just posted one of the biggest weekly increases on record, yet single stocks were still modestly net bought. I don’t think I would deem the flow and positioning situation panic - more of a hedge first and ask the harder questions later kind of thing.

So the right framing here is not "everything is broken." It is that we are in an ongoing positioning clean-up, and until the war path becomes clearer, the Fed speaks, and the market gets more confidence around the next macro leg, equities probably continue to trade with higher vol and a lower tolerance for bad headlines.

The part I think most people are still getting wrong is what the real fear should be.

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I’ve been sitting on this post for three weeks.

That’s not normal for me. I think fast, I write fast, I publish and move on. But this one has been open in a tab since mid-February, half-finished, getting longer and then shorter and then deleted back to almost nothing.

Some of you have been in my DMs. Asking if I’ve flipped. Asking if the Year Ahead is getting quietly shelved. Asking if the name I’ve been most convicted about for the better part of six months has finally broken.

What I will say is this. The last three weeks have felt different from every other drawdown I've navigated since starting this letter. Not in the magnitude. In the quality of the doubt. There's a version of being wrong that feels like noise. And there's a version that makes you sit very still and ask whether you misread something fundamental.

I've been sitting very still…

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February sure was a long year.

The market has not been polite recently… It has been a slow bleed of positioning, a constant churn on internals and a market that keeps pricing fear in the places most people don’t stare at all day.

The most important shift of the last couple of weeks is not whether software is dead, or whether the AI displacement narrative has peaked. It’s that fear is no longer contained in one sector. Software might have been the theatre recently, but it isn’t the only battlefield now.

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Nothing has happened for two months.

If you only watch index, it feels like a holding pattern. The range has been unusually tight and you could argue that we’re drifting. You could argue we’re digesting. Some will argue the market is tired.

But underneath the surface, this has been anything but calm.

Growth has been hit. Beta has been hit. Software has been hit. Factor spreads have blown out and dispersion has been elevated. Single-stock realised vol has felt closer to a correction than a sideways tape.

And STILL the index hasn’t broken.

When the index compresses while internals churn, you’re not in equilibrium. You’re in storage mode. Energy builds quietly in regimes like this. And when it releases, it rarely does so gently.

The narrative doing the damage right now is AI displacement.

Job destruction, recursive automation, permanent impairment of white-collar demand. The sort of framing that sounds inevitable when you string enough hypotheticals together… But in my opinion, there’s a difference between technological capability and economic diffusion. There’s a difference between what a model can theoretically do and what companies actually deploy at scale. Adoption curves don’t go vertical because a Substack went viral. When a Fed board member feels compelled to publicly address a newsletter post, you're not watching a fundamental repricing. You're watching narrative saturation.

Markets don’t wait for nuance. They price fear fast. Software sold off hard. Anything remotely vulnerable to AI was de-rated instantly. Hedge funds cut more exposure and long-only weighed in to their defensive lean. Put hedging surged, skew steepened, and call demand evaporated. The market moved like something was structurally broken. Nothing was.

Some have described the current environment as a 'price-informing narrative' market, where price action sets the tone rather than the other way around (I agree). The tactical cure for negative sentiment in a one-way positioned market could simply be higher prices. That observation matters because it means the reversal doesn't need a fundamental catalyst. It needs the price to move.

It was simply positioning unwinding in response to narrative escalation. The gap between narrative intensity and macro reality has widened more than ever and that gap is important.

Right-tail events do not emerge from optimism. They emerge from situations where positioning has moved further than fundamentals.

What Positioning Actually Looks Like

Prime data shows software exposure has been cut dramatically from prior peaks. AI-disrupted cohorts are sitting near the bottom of historical exposure percentiles. This to me looks like peak fear.

Meanwhile, semiconductors and specific AI infrastructure names remain heavily owned. Consistently net bought YTD… Exposure there is not light.

The spread between semis and software positioning is stretched across every region. The rotation has been forceful, painful for many too.

But something subtle has shifted recently. De-grossing in North America has stopped. Gross exposure has been added globally over the past several sessions. Some things I monitor that had deteriorated are resetting toward neutral. For example, the tactical positioning monitor from JPM Prime just hit neutral, sitting at the 48th percentile since 2015. Software, after several standard deviation weeks of selling, is showing some early signs of stabilisation.

This doesn’t mean leadership has flipped. To me, it means the selling impulse has exhausted itself. And, markets rarely pivot when positioning is still building in one direction. They pivot when the marginal seller is tired.

We are much closer to that condition now than we were a month ago.

Add to this… 80% of 2026 corporate buyback programs have yet to be executed. The market’s largest sponsor is not going away. Repurchase authorisations are tracking at a near-record pace, and the mega-cap names that dominate these programs are still directing significant cash back into their own stock. It is a relentless structural bid sitting underneath the market every single day. (I know I have touched base on this recently, but I think its important for those who might have not seen the last post).

The Semi Cycle Is Mature in Time

I think we can all agree that the semiconductor run has been extraordinary. On duration metrics, the cycle looks statistically mature. But duration alone does not end cycles. What ends cycles is demand concentration and valuation extremes unsupported by diffusion. If AI demand broadens beyond training infrastructure, into inference, enterprise deployment, workflow integration, robotics, edge computing - the next leg is not multiple expansion in chips.

It is application-layer monetisation. That’s software.

Right now, the market has split tech into two clean buckets: physical AI infrastructure and digital AI disruption. One owned and the other has been totally discarded.

If infrastructure earnings hold and software shows incremental resilience rather than collapse, the forced rebalancing between those buckets could be sharp. And sharp rotations in stretched positioning environments create convex moves.

The partnership announcements coming out recently are worth paying attention to. Intuit and Anthropic. Docusign integrating into Anthropic's Cowork platform. Klaviyo and Google. A bit different to what the market sentiment is suggesting..

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I’m back after a week in Cannes, with a tan that won’t last and a phone screen full of alerts that made me question why I ever left. You take one week off and the Supreme Court tries to rewrite the tariff playbook (spoiler: it doesn’t matter), software loses another trillion in market cap, and gold decides it wants to be a five-handle commodity again. Magnifique.

I left the book as it was and only traded ES while I was away. Bought ES1 at 6797, six points off the lows, running 25% notional as a percentage of NAV with a stop at 6697 and a target of 7000. Sold into Friday's close at 6924.5 for a clean 127.5 handles. Not bad for a holiday trade…

Rebought yesterday at 6855 on the same sizing. Stop is 100 points below at 6755, target remains 7000. The thesis is simple: the range is holding, the lows are being defended, and I'd rather be tactically long into NVDA than sitting on my hands. If the stop gets hit, I'll reassess.

Anyway… let's get into it. There is a lot to unpack.

Software… We've Seen This Film Before. Or Have We?

I spent the first half of February writing about why software was not dead, why net exposure had collapsed to record lows, and why the biggest risk was being short into a squeeze. Two weeks later, we got a taste of that squeeze on the back of the Friday snapback... only for the sector to get absolutely obliterated again on Monday.

IBM down 13%, its worst day in 25 years. CRWD down 10% after Anthropic announced their Claude cybersecurity features. MSFT down another 3%. ServiceNow, Salesforce, Intuit, all getting dragged through the mud.

Here’s the thing, though, and I want to be very clear about this… the narrative has now expanded well beyond software. Trucking, logistics, commercial real estate, financial services, and even payments companies like DoorDash and Uber are getting caught in the crossfire. This is no longer a so-called SaaS repricing story. This is the market trying to price in the existential threat of AI to the entire services economy. And when the fear gets that broad and indiscriminate, history tells us we’re approaching the point of maximum pessimism rather than the beginning of a structural move lower.

The S&P North American Software index just posted its worst monthly decline since October 2008. The peak of the GFC. And the bifurcation in how funds are positioned tells the story better than any headline can.

The latest GS Prime data paints one of the more extreme positioning pictures I’ve seen in recent years, and it supports the thesis I laid out in Volume 168 almost perfectly.

TMT made up 70% of the total net selling for hedge funds last week. But within that number, the divergence is insane… funds are aggressively selling software and internet names while simultaneously buying semiconductors and memory. The result is hedge funds are now running their largest ever net long position in semis and their largest ever net short in software, at least since 2016 when the data begins. Record long semis. Record short software. If that isn't the definition of a crowded consensus trade, I don't know what is.

LOs finished the week $4B better for sale, bringing the February MTD total to negative $10B. That is the largest monthly sell skew for asset managers since March 2025 and one of the most significant selling episodes in four years. The other large sell months were these - August 2022 (Hiking Crusade bear market/re-rating $18B), March 2024 (profit taking? can’t even remember - $14B), and March 2025 (Tariff Tantrum - $22B). In other words, the asset management community is behaving as though we’re in a proper risk event, not a flat tape.

And here's the part that really caught my attention: globally, equities saw the largest net selling since liberation day... It seems people are taking down risk in what feels like preparation for index to finally reflect what single stocks have been saying for weeks. Which puts me at two thoughts. The first being that the whole move higher the whole time has been driven by people not having enough risk on, chasing, and buying what they don't own = more up. And the second being that maybe, just maybe, we are due a proper correction. More than 10%. The kind that actually resets things.

So where does that leave me on software?

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I’ve said it before on here, and I’ll keep saying it: size is more important than entry. What I mean by that is that I’d rather be average on entry with perfect sizing than have the perfect entry with reckless sizing. One keeps you in the game while the other eventually takes you out of it.

Most online market content focuses on what to buy, when to buy it, and where to put your stop. Almost nobody talks about how much. And yet sizing is the single variable that determines whether a good idea makes you money or puts you in a hole you spend the next quarter or more climbing out of. It’s also the one decision that is entirely psychological. It has nothing to do with the chart. It has everything to do with you.

This post isn’t a sizing formula you can plug numbers into, although I am sure some of you can make it into that. It’s about the mental side of sizing: how conviction translates into risk, why most traders size backwards, what it actually feels like to be heavy into something that’s going against you, and how I think about it after over a decade managing real capital.

How to Know When the Size Is Wrong

I’m going to give you four rules that have taken me years to learn. They’re not complicated. But they’ll save you from yourself if you’re honest about them.

1. If you can’t hold your stop, the size is wrong.

2. If you’re checking it every two minutes, the size is wrong.

3. If the position is dictating your mood, the size is wrong.

4. If you need it to work today, the size is wrong.

That’s it. You don’t need a spreadsheet or a risk model to tell you whether you’re sized correctly. Your own behaviour is the signal.

I’ve watched experienced guys turn into completely different traders because they got a bit too big in something they were just totally emotionally attached to. The thesis was fine. The entry was fine. But the size turned a rational person into a nervous wreck who couldn’t follow their own process.

The Real Definition of Too Big

Too big isn’t a percentage. It’s not 5% of your book or 10%. Those numbers are fine as guardrails, but they miss the point entirely. Too big is when the position starts changing your behaviour. If a position is large enough that you’re negotiating with your own rules, it’s already mis-sized.

You know it’s too big when you start moving stops because you can’t stomach the loss at that level. This is not risk management, it’s self-preservation dressed up as flexibility. You should also know that you’re too big if you start adding to a loser not because you planned to, but because you need to bring the average down so the P&L looks less painful... If this is you, it’s not conviction - it’s ego refusing to accept reality.

You know you’re too big when a trade becomes a must win. When it stops being one of many positions in a portfolio and starts being THE position. The one that’s going to make the month, quarter or year. Because must-win trades don’t get managed, they get prayed over.

And the worst part is, none of this has anything to do with whether the trade idea is good. The idea can literally be perfect. But once you’re managing P&L instead of risk, the quality of the idea is irrelevant. You’ve shifted from “what is the market doing?” to “what is my P&L doing?” and those are two completely different questions. The first one makes you money over time. The second one willl destroy you.

I’ve had trades where the thesis was perfect, the timing was close enough, but the size was too heavy for me to sit through the noise. So I cut at the worst possible moment, watched it work without me, and learned the lesson the hard way. The idea wasn’t wrong, the size was. Entry price does matter, but entry size matters more. If the size is right, you can survive being early. And, if the size is wrong, being right won’t save you.

I’ve also watched guys lay out a beautiful plan to be scale-down buyers. “I’ll buy at $80, add at $70, last-add $66.” But they’re the type who’ll be throwing up at $70. If that’s you, you shouldn’t be buying at $80 at all, or if you do, it should be a third of the size. You have to trade within your emotional capacity. If you don’t know where that line is, the market will find it for you. And the tuition is expensive. Trust me on that one.

Position-Induced Stupidity

People love to talk about “psychology” like it’s a separate topic from trading. Something you address in isolation, maybe by reading a book or doing some breathing exercises. It isn’t separate. Most of the psychological problems traders face are self-inflicted via size. The moment you go heavy, you hand the steering wheel to your blood pressure.

Here’s what I mean. You put on a trade, the thesis is clean and the setup is there. But you went bigger than usual because you really like this one. For the first few hours, it’s fine. The position ticks around, doing nothing. Then it moves against you by a per cent. Suddenly, your phone is in your hand and you’re continuously refreshing the chart. You’re reading every headline that comes across the wires, searching for a reason to explain the move. And now, you’re scanning Twitter for someone, anyone, who agrees with you. The thesis didn’t change at all. But your nervous system did. And that’s the point nobody makes clearly enough: size creates the emotions that later get blamed on the market. When you’re appropriately sized, a 1% move against you is noise - you barely notice it. When you’re oversized, that same 1% move feels like information. It feels like the market is talking to you, which it isn’t. You’re just uncomfortable, and your brain is scrambling for any kind of narrative to explain the discomfort.

This is where people make the most expensive mistake: they confuse discomfort with signal. They think the anxiety they’re feeling is the market telling them they’re wrong. It’s not. It’s the size telling them they’re too big. There’s a huge difference between “this trade isn’t working” and “I can’t handle this trade at this size.” The first one might require action. The second one required less size from the start.

I’ve made this mistake myself more times than I’d like to admit, sometimes I still do. And every single time, the lesson was the same. The idea was fine and the size wasn’t. Fix the size and fix the psychology. It’s that simple and that difficult.

The Two Kinds of Conviction

You size for the destination and forget about the path. The market doesn’t owe you a smooth ride. As even the best ideas have ugly paths. Size has to be built for the path and not the destination.

This is something that took me an incredibly long time to understand properly. There are two kinds of conviction, and they require completely different sizing approaches.

The first is research conviction. This is your fundamental view on where something is going. You’ve done the leg work. The macro supports it. The positioning is clean. The rates differentials make sense and you believe in the direction. This kind of conviction can be very high, and it should be, because it’s based on analysis and experience.

The second is time-path conviction. This is your confidence in how the trade gets there. Will it be a straight line? Will it chop around for three weeks before working? Or, will it go against you by 10% first, shake out every weak hand, and then rip in your direction? Time-path conviction is almost always lower than research conviction, because the path is inherently uncertain even when the destination isn’t.

The biggest sizing mistake I see, and one I’ve made plenty of times myself, is sizing a slow thesis like a fast trade. You have a view that you think will play out over three to six months. But you size it as if it needs to work this week. Then, when it does nothing for two weeks, or worse, moves against you, you start to freak out. Not because the thesis is wrong but because the size cannot survive the path.

You can be completely right on direction and completely wrong on timing, and at the wrong size, being right on direction is completely worthless. The market can stay irrational longer than you can stay solvent at 3x your normal size.

If you have high research conviction but low time-path conviction, size accordingly. Go smaller than your gut tells you to. You can always add if the trade starts confirming. You can’t un-size after the market has already taken your money and your confidence.

You’re Not as Diversified as You Think

You think you’re sizing positions. You’re actually sizing factors. In calm regimes you get away with it. And during times of stress, everything becomes one trade.

This is something that only becomes obvious after you’ve lived through it. You look at your book and think you’re diversified. You’ve got ten positions across different names. But when you dig into what’s actually driving each position, five of them are essentially the same bet. Maybe they’re all long-duration. Maybe they’re all short vol. Maybe they’re all levered to the same macro outcome. In calm markets, those correlations sit at 0.3 or 0.4 and you feel clever. In a stress event, they all snap to 0.9-1, and suddenly your “diversified” portfolio is one giant position.

I think about this in terms of heat. How much total risk am I running, not at the individual position level, but at the factor level? I’m not just asking myself “how big is my position in X?” I’m asking “if the thing that X depends on has a hiccup, how much of my book gets hit?”

This is where gross exposure and vol regime intersect to create hidden leverage. In a low vol environment, you can run higher gross because the daily swings are much more manageable. But the moment vol expands, that same gross exposure suddenly feels three times bigger. Your positions haven’t changed, but the risk has. If you don’t adjust your book when the regime shifts, you’re running leverage you didn’t sign up for.

Correlation is hidden size. Two positions that look separate on paper but move together in stress are really one position you put on twice. If I’m long three “different” names but they’re all just long duration, then a rates shock isn’t three small problems. It’s one big one. I size them like one trade.

I’ve learned to build a mental correlation matrix before I put on anything fresh. If the new trade needs the same thing to happen as two positions I’m already running, I’m not adding a third position. I’m tripling an existing one. I don’t care that they’re different tickers. They’ll behave identically when it matters most.

Correlation spikes when you need diversification most. If you’re not thinking about this when you put on positions, you’ll learn about it the hard way during a drawdown.

The Three Sizing Buckets

Here’s the mistake I see over and over: people press first and probe last, and I’d say that is backwards. You probe to earn the right to get bigger. You don’t get bigger to force the market to pay you.

I think about sizing in three buckets. It’s not a formula. It’s a framework that keeps me honest about where I am in a trade’s lifecycle.

Bucket A: Test. This is a small, information-gathering position. You have a thesis, but you’re not certain on timing. You want skin in the game so you’re paying attention, but not so much that a move against you matters. These trades exist so that when the trade starts confirming, you’re already in and you can add with conviction rather than chasing from zero. Lots of the time these trades won’t become anything, but the information they give you is worth far more than the small P&L hit.

Bucket B: Core. The thesis has been validated and price action is confirming. You now have both research conviction and some degree of time-path conviction. This is where you move to your normal working size. Not your maximum, but a size where you can sit through noise without it affecting your behaviour. Core is comfortable and lets you be patient. If you can’t be patient at your core size, it’s not actually your core size. It’s too big.

Bucket C: Press. This is reserved for the rare moments when the stars align. Critically, you’re already being paid as the trade is working. You’re pressing from a position of strength, not from a position of hope. Pressing from strength means your average cost is already good, your stop is effectively at breakeven or better, and the market is telling you that your view is right. This is where you can go to your max size.

The discipline is in respecting the sequence. Test, then core, then press. Never press without having earned it. The traders who blow up are almost always the ones who jumped straight to press because they were so sure they were right.

Position size is important not only in avoiding trading too large, but also in trading larger when warranted. When everything lines up, when the thesis is compelling, the potential relative to risk is large, and your confidence is high, you should be positioning bigger than normal. You can transform a mediocre strategy into a winning one purely by varying position size: smaller or not at all for low-conviction setups, larger for high-conviction setups. The sizing is the edge... not your entry.

But there’s a distinction that matters enormously here, and it’s the one thing that I’d want you to take away from this section. There’s a difference between sizing up because your P&L is up, and sizing up because the trade is confirming. The first is ego and the second is process. I only press when my risk is shrinking. If you’re pressing because you’ve had a good run and you feel invincible, that’s not conviction. That’s hubris with a tailwind!

Scaling Rules That Protect You From Yourself

Adding to losers feels like bravery. Yet most of the time it’s just ego. The market is offering you a deal: pay up for being wrong and the professional always declines.

Scaling is where most traders fall apart, because it’s the moment where emotion is most likely to override process. You’re already in a trade. It’s either working or it isn’t. And the decision to add or trim is rarely made rationally unless you have rules written down in advance.

Here are the rules I follow mentally…

Add only when the trade is confirming. If the market is moving in your direction, the thesis is playing out, and you’re getting paid, that’s when you can add. You’re pressing winners from strength. That’s how I scale into positions.

Never average down unless it was pre-planned. There’s a difference between a planned scale-in at predetermined levels with a clear invalidation point and panic-averaging because your P&L looks ugly. If you didn’t write or mark down the level you’d add before you entered the trade, you’re not following a plan. You’re making it up to justify a loss.

No adding during emotional states. If you’ve just had a losing trade, if you’re angry, if you’re chasing, do not add to anything. The market will be there tomorrow.

Now, I want to be honest about something. “Press winners, trim losers” is how I trade. But it’s not gospel. Some of the best traders I’ve known or studied do the opposite, and they do it successfully. They systematically reduce into strength, take money off the table when the trade is in their favour, and look to rebuild the position on pullbacks. Some are so good at trading around positions that they make money even when the net move goes against them. Others have a simple rule: always take some off when it’s working. Always. They say it saves them because when the inevitable reversal comes, they’re already smaller.

Why does this matter for you? Because if you read my buckets framework and interpret it as “always add to winners, never take profits,” you’ll be wrong. The buckets are about when it’s appropriate to get bigger. They’re not a commandment to always get bigger. Some trades are better served by taking profits into strength and looking to re-enter on a pullback. Especially in choppy markets where trends don’t run clean, trimming into strength and buying back cheaper can generate returns that pressing straight through never would.

Stops Are Not Risk Management if the Size Is Wrong

If you’re not certain you can hit the stop; the stop doesn’t exist. It’s just a story you tell yourself so you can enter.

This is one of the most important things I can say in this entire post. Everyone talks about stops. But here’s the problem: a stop is only real if you can actually execute it at that size without hesitation. If you’re running a position where the stop represents a loss so large that you know, deep down, you won’t take it, then you don’t have a stop. You have a suggestion and that won’t protect your capital.

I’ve seen this play out so many times. A trader puts on a cable trade and says “my stop is 1.3320” and they genuinely believe that when they set the trade up. But when price gets to 1.3330, they’re already moving it. “Let me give it a bit more room.” Why? Because at that size, the loss at 1.3320 is too painful to accept. So the stop moves to 1.3280. Then 1.3250. Then eventually they’re so far offside that the stop has become meaningless, and they’re just holding and hoping.

The correct framework is simple. First, decide at what price you would believe your trade is wrong. That becomes your stop. Then work out how much you’re willing to lose on the idea. Then divide that acceptable loss by the per-unit loss to the stop point. That gives you your position size. Most traders do it backwards. They start with size, then find their pain threshold, and that determines where the stop goes. The result is stops that are set based on emotion rather than on where the trade is actually invalidated.

The solution: size so your stop is executable. Work backwards from the loss you can genuinely absorb without it affecting your behaviour, your sleep, or your process. Then calculate the position size that makes your stop level consistent with that loss. If the answer means you have to be smaller than you want, be smaller. The alternative is a stop you won’t honour, and that’s the fastest way to a drawdown spiral.

Sizing in Different Regimes

The market has seasons. Your size has to have seasons too. If your sizing is static, your drawdowns won’t be.

This is something that separates lots of professionals from everyone else. The same trader, with the same idea, in a different regime, should have a completely different size on. Sizing is not a fixed input. It’s a variable that needs to adapt to the environment you’re operating in.

In a low vol regime, you can afford to size up. The daily moves are smaller, your stops are tighter in percentage terms, and the probability of a gap through your stop is lower. This is when most traders feel comfortable, and rightly so. But the trap is that low vol regimes breed complacency. You get used to running more size because it “works,” and then when vol expands, you’re caught oversized in a new regime that punishes you for it.

In a high vol regime, size needs to come down. The daily ranges are wider. Moves are faster and more violent. Liquidity is thinner, meaning your stop might not fill where you want it. Everything that was comfortable at low vol becomes dangerous. If you don’t reduce size when vol expands, you’re effectively running leverage you didn’t choose. When vol explodes, I cut gross aggressively. Survival should always take priority.

In trending markets, you can lean in more because the trade has a tailwind. In choppy, range-bound markets, size should come down because you’re just going to get whipsawed. The win rate in chop is lower, so each trade needs to cost less.

Around events, whether it’s CPI, earnings, central bank decisions, or geopolitical risk, gaps dominate. Your stop might be at a sensible level, but if the market gaps through it on a print or a headline, you’re going to take a much larger loss than you planned. Sizing into events needs to reflect this. If you can’t afford the gap risk at your current size, you need to be smaller. It’s that simple.

The discipline is recognising which regime you’re in right now, not which regime you were in last week. Most traders size for the regime they just experienced. They run low vol sizes into a vol expansion and high vol sizes after the storm has passed. By the time they’ve adjusted, they’re already behind.

The Sleep Test

I don’t care how perfect the setup is. If the position is hijacking your life, it’s not a trade you should be in.

This is the simplest and most honest heuristic I know for sizing. And it has nothing to do with maths.

If you can’t sleep, the size is wrong. If you’re waking up at 3am to check futures, the size is wrong. If you’re lying in bed rehearsing excuses for why the trade isn’t working, the size is wrong. If your partner asks you “what’s wrong?” and you reply “nothing” but you’re thinking about your book, the size is wrong.

Your body knows before your brain does. Anxiety, disrupted sleep, irritability, distraction. These aren’t signs that the trade is bad. They’re signs that the size is simply too big for you. Not too big in some abstract risk management sense. Too big for your nervous system.

I’ve learned to trust this signal above almost everything else. When I’m sized right, I can go about my day. I check my positions when I need to, not because I’m compelled to. The trade is running in the background, not dominating the foreground. That’s how it should feel and you can get on with whatever tasks/research you need to do.

If a trade is costing you sleep, trim it until it isn’t. The lost P&L from sizing down is nothing compared to the compounding damage of trading the next day, exhausted, emotional, and compromised.

The Drawdown Trap: Why Size Gets Worse When You’re Losing

Drawdowns don’t end from hero trades. They end from boring discipline. If you’re in a hole, the answer is rarely “more risk.”

I covered drawdown psychology in a previous post, but I want to address it specifically through the lens of sizing because this is where the two topics collide in the most destructive way.

When you’re in a drawdown, the temptation to fix it with size is almost irresistible. You’re down 10%. You think: “If I just size up on this next idea and it works, I’m back to down 5%. Two of those and I’m flat.” The maths checks out, and the logic is sound on paper. But the psychology is utterly lethal.

Because here’s what actually happens. You size up in a drawdown. The trade goes against you. Now you’re not down 10%, you’re down 14%. Then the emotional pressure doubles. You size up again because now you need an even bigger win to dig out. The trade chops around, you can’t think clearly, and you cut it for a loss. Now you’re down 18%. At this point, desperation takes over. You take a trade you’d never normally take, at a size you’d never normally use, because “I just need one good trade to get my mojo back.” That one trade either saves you (very rarely) or puts you in a hole so deep that you spend the next quarter or two recovering. Usually, the latter.

This is the death spiral. Bigger size leads to worse decisions, which lead to bigger drawdowns which lead to even bigger size. Every step feels logical in the moment. Every step makes the problem worse. And the lottery-ticket mindset, the idea that one big winner will solve everything, is one of the most dangerous things in trading.

The traders I respect most handle drawdowns the same way. Any time drawdowns approach a certain threshold in a given month, they flatten everything and start fresh at half their normal size or less. They don’t increase size again until they’re making money. This might sound extreme to many of you. That is because most people can’t do it, many of you would have seen me do it last April and boy was it the best decision that I made. But the principle is universal: when you’re losing, the answer is less risk, not more. You trade smaller until you prove to yourself that you’re back in sync with the market. Only then do you scale back up.

Now, I want to flag a tension here, because I think about this a lot. If drawdowns in a given strategy tend to mean-revert, then the period right after a bad stretch is often when the best opportunities appear. And that’s exactly when you’ve made yourself smallest. I’ve lived it. You cut size after a rough patch, then the next three trades are perfect, and you’re running at half size for all of them. But the cut is still correct even when it costs you. Because the alternative, maintaining full size through a drawdown, is what turns 10% drawdowns into 20% drawdowns. You’ll occasionally leave money on the table by being small at the wrong moment. But you’ll never blow up. And in this game, not blowing up is the prerequisite for everything else.

If you’re in a drawdown right now, read this carefully: the move is less risk, not more. Cut your size in half. Take fewer trades and focus entirely on process. The P&L will follow the process, not the other way around.

The Only Maths Point That Matters

I said at the start that this post isn’t about formulas. So one maths point, then back to psychology.

The Kelly Criterion is probably the most famous sizing formula in finance. It tells you the optimal bet size to maximise long-run compounding. In a casino, where odds are precisely known, it works perfectly. In markets, the odds are never precisely known. And that’s where the formula gets interesting, because the lesson it teaches is the opposite of what most people expect.

The penalty for overestimating your edge is twice as severe as the penalty for underestimating it by the same amount. Bet double Kelly and you eliminate 100% of your gain. Bet more than double, and your expected return goes negative, regardless of how strong your edge is on any individual trade.

The people who understand this formula most deeply don’t bet full Kelly. They bet half. When the edge is genuinely uncertain, some go as low as one-tenth. The most rigorous mathematical framework for position sizing ever created says the same thing your nervous system says: be smaller than you think.

A One-Page Sizing Playbook

If you take nothing else from this post: write your sizing rules when you’re calm. Then follow them when you’re not.

Here’s the framework I use. It’s not perfect. But it keeps me honest, and it might keep you honest too.

The Three Buckets

Test: Small size. Information gathering. You’re paying for clarity, not returns. Small enough to survive anything.

Core: Your normal working size. Thesis confirmed, structure in place. Normal working risk. You can sit through noise at this level without it affecting your behaviour.

Press: Maximum conviction size. Only when all the stars align. You’re already being paid. Risk is shrinking, and the trade is paying.

Portfolio Heat Rules

Know your factor exposure, not just your position exposure. If three positions depend on the same outcome, treat them as one for sizing purposes.

Adjust gross exposure for the vol regime. What’s comfortable in low vol is reckless in high vol.

Correlation Cap

No more than three positions driven by the same factor at any one time. If you find yourself with four or five names that all need the same thing to happen, you don’t have five positions. You have one, and it’s five times bigger than you think.

”No Add” Rules

• Don’t add to losers unless it was pre-planned at specific levels with clear invalidation.

• Don’t add to anything when you’re in a drawdown. Drawdowns get fixed with less risk, not more.

• Don’t add into events where gap risk makes your stop theoretical.

• Don’t add when you’re emotional. If you’re angry, desperate, or in chasing losses walk away.

Pre-Trade Sizing Checklist

• Can I hold my stop at this size without moving it? If no, size down.

• Can I go about my day without obsessing over this position? If no, size down.

• If this trade hits my stop, does it materially affect my month? If yes, size down.

• Am I pressing from strength or pressing from hope? If hope, don’t press.

• Is this size appropriate for the current vol regime?

If you made it this far, do one thing before your next trade. Write down your sizing rules. Not during a drawdown. Nor after a bad day. Now, while you're calm and thinking clearly. Then follow them when you're not. That's the edge, and eventually it becomes automatic.

Size isn’t everything. But it’s the thing that makes everything else work.

If this post hits 300 restacks by Saturday, 21st February, 5pm ET, I'll gift 10 free annual subscriptions to readers picked at random from the restacks list.

Happy trading,

Fed

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