INVESTING (8)

My mom has never bought a single share of stock in her life. And when I asked her why, her answer was basically a highlight reel of the scariest headlines she’d ever seen: people losing everything, people going bankrupt, people who “played the stock market” and ended up worse than broke.

The line that stuck with me most: she genuinely believed you could lose more money than you put in. Like, invest $1,000 and somehow end up owing $3,000.

And here’s the thing — she’s not dumb, and she’s not alone. That fear is incredibly common. It’s just aimed at the wrong target. So let me do what I always try to do here: no hype, just math.

First, the big one: you (almost certainly) can’t lose more than you invest

When you buy a normal share of a stock — or a fund like an S&P 500 ETF — with your own cash, the absolute worst case is that it goes to zero. You lose 100% of what you put in. That’s genuinely bad! But it’s not “you now owe the broker money.” The floor is your investment. Full stop.

What my mom was describing — losing more than you invested — is a real thing, but it’s a different, more dangerous game:

• Margin — borrowing money from your broker to buy more stock than you can afford. Now you can owe.
• Options and futures written the risky way — selling naked calls, that kind of thing.
• Leverage in general — anything where you’re playing with borrowed money.

That’s the world where the horror stories come from. And here’s the honest part: I do trade options (cash-secured puts, mostly) and I’ve held leveraged positions, so I’m not going to pretend that corner of the market doesn’t exist. But that’s the deep end of the pool. Buying VOO with your own money is the shallow end, and the shallow end does not have an “owe money” trap door.

Nobody explained that distinction to my mom. The news definitely didn’t.

The news only shows you the car crashes

Think about how financial media works. “Retiree calmly bought an index fund and it slowly went up over 20 years” is not a headline. It’s not a story. Nobody clicks it.

“Trader loses life savings on meme stock” — that’s a story. So is the bankruptcy, the crypto blowup, the guy who bet everything on options and lost. The extreme cases get 100% of the airtime, which quietly teaches people that the extreme case is investing.

It’s survivorship bias in reverse. You’re only shown the disasters, so you conclude the whole thing is a disaster. Meanwhile the boring, math-y version that actually builds most people’s retirement never makes the screen.

The risk nobody puts on the news: doing nothing

Here’s the part that flips the whole fear on its head.

Everyone treats cash in the bank as the “safe” choice. And in the short term, sure — the number in your account doesn’t drop. But there’s a silent leak: inflation.

As of the last reading, inflation (CPI) was running about 3.5% over the past year. That means the same groceries, gas, and rent cost ~3.5% more than they did a year ago. Your dollar buys less. Every year. Guaranteed.

So the real question isn’t “is investing risky?” It’s “is my money keeping up with inflation, or quietly bleeding buying power?” And for a lot of people, the honest answer is: it’s bleeding.

”But the bank is safe, right?” — yes and no

I want to be fair here, because “the bank” isn’t one thing.

If your money is sitting in a big brick-and-mortar bank’s savings account, you’re probably earning something like 0.01% APY. That is not a typo. On the big national banks, $1,000 parked for a year earns you about a dime. Against 3.5% inflation, that’s a straight-up loss of buying power — you’re paying the bank for the privilege of watching your money shrink.

But — and I’d be a hypocrite not to say this — there’s a better version of “the bank”: a high-yield savings account (HYSA). Right now the best ones pay around 4% APY. That actually beats the current 3.5% inflation. So if you’re sitting on an emergency fund or cash you’ll need soon, moving it from a 0.01% account to a ~4% HYSA is one of the easiest wins in personal finance, and I’d tell anyone to do that first.

So why invest at all, if a HYSA beats inflation today? Two reasons:

1. HYSA rates are temporary. They float with the Fed. A few years ago they were near zero, and they’ll come back down. Inflation doesn’t ask permission.
2. Beating inflation by a hair isn’t building wealth. It’s treading water. Growing your money — actually multiplying it — is a different job, and that’s the job stocks have historically done.

So what does “investing” actually look like for a normal person?

Not options. Not day-trading. Not the stuff on the news. For most people it’s shockingly boring:

Buy a low-cost fund that owns a slice of the 500 biggest U.S. companies — something like VOO — and just… hold it. When you own VOO, you’re not betting on one company surviving. You own a piece of all of them at once. For that fund to go to zero, all 500 of America’s largest companies would have to be worth nothing simultaneously — at which point, honestly, we’d all have much bigger problems than our brokerage balance.

How’s it done? VOO is up about +8.95% so far in 2026 (through late July, dividends reinvested). That’s comfortably ahead of the 3.5% inflation rate — so this year, holding it protected your buying power and grew it.

Zoom out and the long-run number people usually cite for the S&P 500 is roughly 10% per year on average (nominal). That “average” is doing a lot of work, though, which brings me to the caveats — because there’s always a catch.

The honest downsides (there’s always a catch)

I’m not here to sell you a fantasy. Investing in stocks is genuinely risky, and anyone who tells you otherwise is selling something:

• It does not go up in a straight line. VOO was down about 18% in 2022. If you’d put money in at the start of that year, you’d have watched a chunk of it vanish on paper for months. Even right now, VOO is sitting a couple percent below its high from earlier this summer. Green years and red years are both part of the deal.
• “Average 10%” is not “10% every year.” Some years are +25%, some are −18%. The average only shows up if you stay in through the ugly ones — which is exactly when panic makes people sell.
• Past performance doesn’t guarantee anything. Everything above is history. History rhymes; it doesn’t promise.
• You can absolutely lose money, especially over short windows. The one thing that has historically bailed people out is time — long holding periods have smoothed out most of the rough patches. Money you need next year should not be in stocks.

The point isn’t “stocks are safe.” It’s that there’s a risk on both sides — the visible risk of investing, and the invisible risk of letting cash rot. Well-informed people don’t avoid risk; they pick which risk they’re taking on purpose.

How I’d actually start (small and boring on purpose)

If I were walking my mom into this, it wouldn’t be “put your savings in the market tomorrow.” It’d be:

1. Emergency fund first, in a ~4% HYSA. Not invested. Untouchable.
2. Then a small, automatic, boring amount into a broad index fund every month — an amount that wouldn’t ruin your week if it dropped 20%.
3. Don’t watch it daily. Daily watching is how you turn a 30-year plan into a 30-day panic.

Related reading on Hebojago: (https://hebojago.com/post/stay-calm-market-crash/).

Let’s make $millions$ (the unsexy way)

Okay, the fun part. Here’s why I get genuinely excited about this instead of scared:

Put $500 a month into a broad index fund and let it compound at that long-run ~10% average, and after 30 years you’d have somewhere around $1 million. (Illustrative — it assumes a steady historical average that real markets will never actually deliver in a straight line. Reality will be lumpier. But the ballpark is real.)

That’s not a lottery ticket. It’s not a hot stock tip. It’s boring money, added consistently, left alone, doing the one thing cash in a near-zero account can never do: outrunning inflation and multiplying.

My mom spent decades believing investing was the risky choice. The quiet truth is that not investing — letting inflation nibble her savings year after year — was its own kind of risk the whole time. Nobody put that on the news.

So consider this your invitation. Learn the difference between the shallow end and the deep end. Start small. Stay boring. Let’s go make some $millions$ — slowly, on purpose, with the math on our side.

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Not financial advice — I’m a software developer who invests and trades on the side, not a licensed advisor, and this is my experience and my math, not a recommendation for your situation. Returns, inflation, and savings rates cited here (VOO +8.95% YTD, CPI 3.5%, ~4% HYSA, ~0.01% big-bank savings) were accurate as of late July 2026 and change constantly — verify current numbers before you act on them. All future/compounding figures are illustrative; past performance doesn’t guarantee future results, and you can lose money investing.

Hebojago is my journey to financial freedom, recorded live — real experiments, real numbers, wins and mistakes. Follow along here.

In 2015 I built a desktop PC from parts. Not a pre-built — I bought every component separately, spread them across the dining table, and assembled the thing myself. Motherboard, PSU, RAM, case fans, cable management I was weirdly proud of.

There was exactly one part I wasn’t willing to compromise on: the graphics card. It had to be Nvidia.

I’d used their cards. I knew the drivers. I knew what the frame rates felt like. The idea of building a machine around somebody else’s GPU just felt wrong to me. That wasn’t a financial decision — it was a taste decision, the same way some people won’t buy a non-Toyota.

Around that same time I was starting to poke at the stock market. I was a software developer with a brokerage account and more curiosity than knowledge. And at some point it occurred to me that the company making the one part I refused to substitute was, itself, publicly traded.

NVDA. So I bought some.

I want to be honest about what my research process was: I liked the product. That was it. No DCF model, no channel checks, no reading the 10-K. Back then, if you weren’t a PC gamer, you had probably never heard of Nvidia. This was years before “AI” meant anything to a normal person.

Then came the crypto mining boom, which made GPUs briefly impossible to buy. Then — the one that actually mattered — AI infrastructure. And now Nvidia is the most valuable company in the world.

The numbers, because no hype, just math

All of these are split-adjusted, which matters a lot here. Nvidia split 4-for-1 in 2021 and 10-for-1 in 2024, so one share from 2015 is 40 shares today.

• Dec 31, 2015 close: $0.80 split-adjusted (the raw price that day was $32.96)
• July 2026: around $205
• That’s roughly 250x from the end of 2015

Put a number on it: $1,000 invested at the end of 2015 would be somewhere around $250,000 today. That figure is illustrative — it ignores taxes, fees, and the fact that almost nobody actually buys at year-end close and never touches it again. But the order of magnitude is real.

I did not have $1,000 in NVDA in 2015. I bought a couple hundred dollars’ worth, because I wasn’t making much money back then and a couple hundred dollars was what I could spare.

A few years later I got married, and my wife and I wanted to buy a home. So I did the thing every investing article tells you never to do: I sold my entire stock portfolio. All of it, Nvidia included.

I don’t regret it even a little. Without the Nvidia gain, we couldn’t have covered the down payment on our first house. That’s what the position actually turned into — not a screenshot of a 250x, but a roof.

Right after the house closed, I started over from zero. Every time I had extra cash, I put it back into Nvidia. My portfolio still isn’t big, but NVDA is now more than 50% of it.

The principle, stated plainly

Here’s the rule I took away from it, and I still use it:

If you use a product, you genuinely can’t live without it, and the company that makes it is publicly traded — buy the stock and hold it for a long time. In the short term the price will do whatever it wants. In the long term, if the product is good and enough other people also can’t live without it, the company eventually pays you back.

This isn’t original to me. Peter Lynch built a career on some version of it — “invest in what you know” — and it’s folk wisdom on every investing forum on the internet. But most people quote the slogan and skip the part where Lynch said the product is where your research starts, not where it ends.

Why it works at all

The reason this isn’t just feel-good nonsense: as a customer, you see demand before it shows up in an earnings report.

Wall Street analysts read filings. You were standing in Micro Center watching the Nvidia shelf get cleared out while the AMD cards sat there. That’s real information, and you get it months before it becomes a revenue line.

You also, crucially, understand why people pay up. I didn’t need a research note to explain Nvidia’s moat to me — I was living it. CUDA, drivers that worked, an ecosystem everything was built around. I couldn’t have told you that would matter for AI training clusters. But I knew the lock-in was real, because I was locked in.

That’s the honest version of the edge: you’re not smarter than the market about the numbers. You’re earlier than the market about the demand.

Where this principle breaks — read this part twice

If I published the story above and stopped there, I’d be doing the thing I started this blog specifically to not do. So here are the four ways “buy what you love” goes wrong, and every one of them has bodies on the floor.

1. Survivorship bias, and it’s massive. I’m telling you the Nvidia story because it worked. I’m not telling you about every product I loved whose stock went nowhere. Think about the products people were obsessed with over the last decade: GoPro, Peloton, Beyond Meat, Under Armour, Fitbit. Beloved products. Devoted users. Shareholders got destroyed. Nobody writes the blog post about those, which is exactly why the strategy sounds better than it is.

2. A great product isn’t a great business. Loving something tells you it’s good. It tells you nothing about margins, competition, capital intensity, or whether the company can stop a competitor from doing the same thing cheaper next year. Plenty of wonderful products are made by companies that can’t make money on them.

3. A great business isn’t a good price. This is the one that gets people hurt today. Whatever you love in 2026, everyone else has probably already noticed. Buying a fantastic company at a ridiculous valuation is a great way to be right about the business and still lose money for five years.

4. The product you loved might not be the product that pays. This is the uncomfortable one for my own story. I bought Nvidia because of GeForce graphics cards. GeForce is not what made Nvidia a $4-trillion-plus company — data center and AI did. My thesis was correct about the company and mostly wrong about the reason. I got paid for a business line I wasn’t even thinking about.

I’d rather tell you that than let it sound like I saw the AI boom coming from a dining-room table in 2015. I didn’t. Nobody did.

The part nobody puts in the story: holding

The 250x number is meaningless without this section, because it quietly assumes you sat still. Almost nobody sits still.

Here’s what “just hold it” actually meant, using the same split-adjusted prices:

• Late 2018: NVDA went from $7.23 in October to $3.17 in December. That’s −56% in about two months, when the crypto mining bust wiped out GPU demand. It took roughly 16 months to make a new high.
• 2020 COVID crash: $8.54 down to $5.33. −38%, in a few weeks.
• Nov 2021 to Oct 2022: $33.38 down to $11.23. −66%, over most of a year, while every headline explained in detail why semiconductors were finished.

Sixty-six percent. If you had $30,000 in it, you watched $20,000 evaporate over eleven months, and the smart-sounding people on TV were telling you it was going lower. That’s the actual cost of the 250x. The math is easy. The stomach is the hard part.

So did I sit through all of that? Not the way the story usually gets told. I have to be straight with you: I am not the guy who bought in 2015 and held for eleven years. I sold every share to buy a house, and I’d make that trade again.

When I came back into the market, it was volatile and semiconductors were getting hit hard. Which, honestly, is what made it easy for me. I knew what Nvidia was doing — I’d been watching the product for years by then — so a falling price didn’t read as danger to me. It read as a discount. I kept buying the dips.

That worked out. I want to be careful about how I say that, though, because “I bought the dip in a stock I believed in” is the exact sentence people say right before they describe a disaster. It worked because Nvidia recovered. It worked because I was buying with spare cash I didn’t need. Change either of those and it’s a very different post.

I’ll also point at my own recent behavior here: I wrote a whole piece about panicking during the 2026 semiconductor selloff — same industry, same lesson, and I still felt it in my chest. Knowing the principle and executing the principle are different skills.

How I actually use the rule now

I still believe in it. I just don’t treat it as a buy signal anymore. It’s an idea generator, and then four questions have to pass:

1. Can I actually not live without it? Not “I like it.” Would I be annoyed if it disappeared tomorrow? Do I re-buy it without shopping around?
2. Is the thing I love actually where the money comes from? Check the revenue breakdown in the 10-K. If you love the app but 90% of revenue is something else, you don’t have the thesis you think you have.
3. Is it public and is it pure? Lots of great products are owned by conglomerates where the product you love is a rounding error.
4. Am I paying a sane price, and can I size it so a −60% year doesn’t change my life? If a two-thirds drawdown would force me to sell, the position is too big — no matter how right I am.

If it passes all four, I buy and I set a horizon measured in years, not quarters. If it only passes the first one, it goes on a watchlist, and I’ve saved myself a lot of money that way.

And since I just gave you rule number four, I should admit I’m breaking it. NVDA is over 50% of my portfolio. That is not a position size I would recommend to anyone, and it didn’t happen because I decided it should — it happened because I kept adding to a winner and never trimmed. If Nvidia has another 2022, I lose a third of everything I have in the market. I know that. I’m telling you so you don’t read “50% in one stock” as the lesson of this article, because it isn’t. It’s the part of my own portfolio I’m least comfortable defending.

My take

The thing I’d want someone to take from this: the reason the rule works isn’t that loving a product is a valuation model. It’s that loving a product gives you a reason to act when the price is telling you to run.

When I came back into the market and semis were getting hammered, the only thing I had that a chart-watcher didn’t was a machine under my desk with an Nvidia card in it that still did exactly what I wanted it to do. That’s not analysis. But it was enough to make me a buyer instead of a spectator, and being a buyer during the ugly stretches is where the entire return came from.

And the best thing that position ever did wasn’t the 250x anybody screenshots. It was becoming a down payment.

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Numbers in this post verified July 22, 2026 and subject to change — Nvidia’s share price, market cap, and standing move constantly, so check current data before acting on anything here. I hold NVDA and other semiconductor exposure, so read this with your skeptic hat on. I’m a software developer who invests on the side, not a financial advisor, and none of this is financial advice. Past returns of one stock tell you nothing about your future returns, and the 250x figure above is illustrative — it excludes taxes and fees and assumes a hold almost nobody achieves.

Not financial advice — just the framework I actually use, in the order I use it. Everyone’s tax bracket, income, family situation, and account access is different, so treat this as a starting point, not a script. Contribution limits and rates below are current as of publish, but always verify them before you act.

where should I actually put my money first? 401k, Roth IRA, taxable brokerage, HSA, 529 — there are a lot of buckets, and most people are just guessing at the order. So here’s mine, ranked from “do this before anything else” down to “nice to have once the foundation is solid.”

I’m deliberately leaving real estate and alternative investments off this list — those deserve their own conversation, not a spot in a general-purpose ordering like this.

1. A starter emergency fund

Before you optimize anything, protect yourself. If you have issues with the house, you lose your job, or a medical bill shows up out of nowhere and you have zero cash saved, you’re reaching for a credit card at 20–25% interest. That’s the very first hole to plug.

This doesn’t need to be 6-8 months of expenses yet. Even a small buffer — a few hundred to a thousand dollars — keeps a bad week from turning into bad debt. Build this first, no exceptions.

2. Capture your full employer match

If your employer offers a 401(k), or similar plan with a match, contribute at least enough to get all of it. A 100% match on your first 5% is an immediate 100% return — no investment reliably beats that.

You don’t need to max out the account here. Just hit whatever contribution percentage unlocks the full match. Free money first, everything else second.

3. Pay off high-interest debt

If you’re carrying a credit card balance at 20–25% interest while hoping to make money from your investments, about 8–10%, that’s the bad investment. Paying down high-interest debt is effectively a guaranteed double-digit “return” — hard to beat with anything in the market.

To be clear, this is about credit cards and high-rate personal loans.

4. Build a fully funded emergency fund

Once the high-interest debt is gone, go back and finish the emergency fund — the standard range is 3–6 months of necessary living expenses, though some people prefer up to 12 for extra cushion to be safe.

A fully funded reserve means you’re far less likely to sell investments during a downturn, less likely to panic, and less likely to reach for high-interest debt again. In personal finance, having options is its own kind of wealth.

5. Max out an HSA, if you’re eligible

If you have access to a Health Savings Account through a high-deductible health plan, I think it deserves serious consideration ahead of most other accounts. It’s the only account with a genuine triple tax advantage: contributions are deductible, growth is tax-free, and qualified medical withdrawals are tax-free.

You don’t need to be sick or expecting big medical bills for this to make sense — healthcare costs eventually show up for almost everyone, and this account lets you get ahead of them tax-free in every direction. Not everyone qualifies (you need an HDHP), but if you do, it’s worth prioritizing.

6. Max out a Roth IRA

Between traditional and Roth, I’d prioritize the Roth. You don’t get an upfront deduction, but qualified withdrawals — both principal and growth — are completely tax-free in retirement. The earlier you start, the more decades of tax-free compounding you get.

A lesser-known perk: with a Roth IRA, you can withdraw your direct contributions (not the earnings) at any time, tax-free and penalty-free, since you already paid tax on that money going in. If you earn too much to contribute directly, a backdoor Roth IRA is still an option.

For 2026, the combined traditional/Roth IRA contribution limit is $7,500 (up from $7,000 in 2025) — always double-check the current-year limit and income phase-out ranges before contributing, since both change annually.

7. Go back and max out your employer plan

After the Roth IRA, return to your 401(k)/403(b)/TSP and push contributions higher. I rank IRAs ahead of this step because they typically offer a wider range of investment choices and lower costs, but employer plans vary a lot — some are genuinely excellent. For 2026, the employee deferral limit is $24,500.

Our mortgage calculator and car payment calculator can help you free up room in your budget to push contributions higher here if cash flow is tight.

8. Taxable brokerage account

No contribution limits, no early-withdrawal penalties, and far more investment choices than any retirement account — the tradeoff is you lose the tax advantages. My advice here: aim for long-term capital gains. Depending on your income, the federal long-term capital gains rate can be 0%, which makes a taxable account a genuinely strong tool once your tax-advantaged accounts are taken care of.

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The honest takeaway

None of these steps are exciting on their own. Getting the match, avoiding high-interest debt, using the tax-advantaged accounts you have access to, and investing consistently — that’s it. That’s the whole game. Building wealth isn’t about finding one incredible investment; it’s about not messing up the boring decisions, over and over, for a long time.

This is a personal framework, not personalized financial advice. Tax brackets, employer benefits, family circumstances, and account eligibility all vary — verify current contribution limits, income phase-outs, and plan rules before making decisions, and consider talking to a licensed financial or tax advisor for your specific situation.

Something strange happened on July 15, 2026. In a single session, the two halves of the AI trade split in opposite directions.

Memory chipmakers cratered — SK Hynix’s freshly listed Nasdaq shares, Micron, SanDisk and Western Digital all fell hard, part of a memory-sector rout that had been building since early July. Yet on the very same day, the companies that use those chips — Apple, Alphabet, Amazon — climbed.

Here’s the twist. That same morning, ASML — the Dutch company that makes the lithography machines every advanced chip is printed on — raised its full-year guidance for the second time this year and said its order book is essentially sold out through 2027. Demand has never looked stronger. So why did only the chipmakers fall?

The short answer: this wasn’t AI switching off. It was money changing seats.

Good news that reads as bad news

ASML lifted its 2026 revenue guidance from €36–40 billion to €43–45 billion and told investors it plans to expand EUV capacity about 30% in 2027, with another 30% under study for 2028. Orders for 2027 are already substantially locked in, with 2028 filling up too.

Buried one line down was the detail that spooked memory investors: ASML expects memory-related revenue to grow roughly 75% this year, as Samsung, SK Hynix and Micron pull forward factory expansions to chase today’s sky-high memory prices.

That sentence is the problem, because memory is a cyclical business. High prices → everyone builds fabs → those fabs switch on about two years later → supply floods in → prices collapse. The better memory makers do today, the more oversupply they’re baking in for 2027–2028. Selling well becomes the source of the fear.

We’ve seen this movie. In 2018, record DRAM prices drove record profits and a fab-building spree. When that capacity came online in 2019, DRAM prices collapsed and memory profits were gutted. What ended that boom wasn’t a recession — it was the factories the boom itself had built.

Three pressures stacking up at once

Three separate signals landed almost together.

Supply is already telegraphed. China’s leading DRAM maker, CXMT, is moving toward one of the largest chip IPOs ever — proceeds that would fund still more memory capacity. And in a Reuters exclusive, AI-cloud company CoreWeave was reported to be exploring put options and other derivatives to hedge against a drop in memory-chip prices. Nothing has been executed, and the hedge would target memory-chip stocks as a proxy. But when a major buyer starts pricing downside protection, that’s a message to the market.

The chips have nowhere to plug in. On July 14, New York became the first U.S. state to impose a statewide moratorium on new hyperscale data centers (50 MW and above) for up to a year. Power is the harder wall: grid operators are struggling to reserve enough future capacity, and billions of dollars of data-center projects have already been delayed by local opposition. This isn’t hyperscalers refusing to buy — it’s that they can’t build fast enough to house what they’d buy.

Everyone already owns the trade. Bank of America’s July fund-manager survey found a record 82% of managers calling “long semiconductors” the most crowded trade — the third month running. An AI bubble is now their #1 tail risk (45%, up from 28% a month earlier), and average cash fell to 3.6%, tripping BofA’s contrarian “sell” signal. When everyone is already all-in, good news can’t lift a stock — and the first seller wins.

Where the money actually went

So it rotated — inside the same AI theme — from the companies that make chips to the ones that run them.

The logic is clean. Falling memory prices shrink chipmakers’ revenue, but they cut costs for the hyperscalers — Amazon, Microsoft, Google, Meta — who buy the chips and rent out computing power. And cloud revenue arrives steadily every month, unlike the cyclical memory earnings the market has suddenly learned to fear.

The narrative even got a marquee endorsement. On CNBC that day, Warren Buffett confirmed that Berkshire’s ~$31 billion Alphabet stake was his own idea (“I initiated it”). Worth the nuance, though: Buffett also said Alphabet isn’t among his very favorite holdings and flagged the staggering AI capital-spending bill as a genuine concern. Apple rose too, helped by news it’s moving to bring AI features to China through a partnership tied to Alibaba’s model.

Don’t over-read it

The easy conclusions here are mostly wrong.

“Memory is finished.” ASML’s order book runs through 2027 with 2028 filling in, and there are no cancellations. Demand is intact; this looks like crowded positioning unwinding, not a bubble bursting. Both show up as red in your account — but they’re very different events.

“Cheaper memory = automatic win for hyperscalers.” Lower costs don’t help if you can’t get a data center approved. The power-and-permitting squeeze hits both sides of the trade.

“Buffett bought, so I’ll follow.” He built the position over several quarters, not on the pop — and he hedged his own enthusiasm. A good company and a good entry price are two different questions.

What to watch

Two things worth tracking from here:

1. Memory contract prices — the quarterly prices companies actually negotiate, not the daily spot number. When those roll over, the buildout has tipped into oversupply for real.
2. A second state moratorium. New York was the first; a second would signal the data-center bottleneck is spreading nationally rather than staying a one-state story.

The July 15 selloff wasn’t AI turning off. It was the center of gravity shifting from the chip makers, who now carry the oversupply time-bomb, to the chip runners, who actually get cheaper if that bomb goes off. Investing isn’t a game of guessing who earns the most — it’s a game of seeing, a little earlier than everyone else, which direction the money is walking.

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This article is for informational and educational purposes only and is not financial advice. All investing carries risk of loss. Do your own research or consult a licensed financial advisor before making investment decisions.

There’s a parasite in the salad, and Wall Street is trying to figure out what to do about it.

As of mid-July 2026, the CDC has confirmed 1,645 domestic cases of cyclosporiasis across more than 34 states, with over 5,100 additional probable cases still being sorted out — some tallies put the combined figure near 7,000. That is a staggering jump from just 249 cases nationally by this same point last year. Michigan alone accounts for more than half the confirmed cases, and investigators have flagged lettuce and salad greens as a likely culprit, though no single source has been confirmed.

Cyclosporiasis is nasty but rarely dangerous — think prolonged, “explosive” watery diarrhea, fatigue, and weight loss, treatable with a course of antibiotics. There have been 141 hospitalizations and no deaths. So this isn’t a public-health catastrophe. But it is a market event, and the way investors are reacting to it is a perfect case study in one of the most useful skills you can develop: telling a real catalyst from a headline.

Let me walk through what an outbreak like this actually does to stocks, who’s exposed, and — because this is Hebojago — how I’d actually think about playing it.

The one time this really mattered: the Chipotle template

If you want to know what a produce-borne outbreak can do to a stock, you don’t have to theorize. Chipotle already ran the experiment for us, and the results were brutal.

In late 2015, the CDC linked an E. coli outbreak directly to Chipotle restaurants across multiple states. The stock, which had traded around $757 in October 2015, cratered to roughly $475 by February 2016 — a decline of about 37% that erased something like $8 billion in market value. This wasn’t a one-day scare that bounced back. Same-store sales fell about 14.6% in the fourth quarter of 2015, the company posted its first sales decline since going public, and it took years to fully rebuild the brand and the multiple.

That’s the template. And it tells you exactly what the market punishes: not the existence of an outbreak, but the naming of a specific brand as the source. The moment the CDC ties cases to your restaurants, three things happen at once — customers stay home (real revenue hit), analysts slash guidance (real estimate cuts), and the “healthy, fresh food” brand premium evaporates (multiple compression). All three fed the Chipotle collapse.

Why the 2026 outbreak is different (so far)

Here’s the part most hot-take articles are getting wrong, and it’s the whole ballgame: no restaurant chain has been named in the 2026 outbreak.

Investigators are pointing at lettuce and leafy greens as a category. That’s very different from pointing at a company. Contaminated produce enters the food supply through distributors and ends up everywhere — grocery stores, cafeterias, and yes, restaurants — but without a named brand at the center, there’s no single stock for the market to punish the way it punished Chipotle.

So the honest framing isn’t “these stocks are going to crash.” It’s: “Here is the template for what happens IF a chain gets named — and here is who is most exposed if that shoe drops.” That’s a watchlist, not a prediction. Anyone selling you a confident forecast right now is guessing.

The watchlist: who’s actually exposed

Exposure here is a function of one thing — how central raw, uncooked produce (especially leafy greens) is to the business. The more a brand’s core product is a bowl of raw greens, the more a lettuce-linked outbreak threatens both its sales and its brand story.

Sweetgreen (SG) — highest structural exposure. This is the name to watch most closely, and it’s the most interesting one on the board. Sweetgreen’s entire identity is raw leafy greens. If the confirmed source turns out to be lettuce, no chain is more thematically and operationally in the blast radius. Its “clean, healthy, fresh” positioning is exactly the kind of brand premium that an outbreak vaporizes — the same premium that made Chipotle’s fall so steep.

Chipotle (CMG) — the veteran with scar tissue. Chipotle uses enormous volumes of produce, including lettuce, so it’s exposed. But it’s also the one chain that has already been through this, spent an estimated $25 million overhauling food safety, and rebuilt investor trust. That cuts both ways: it has the playbook and the systems, but the market also has a memory, and CMG could get hit hard on sentiment alone if it’s ever named again.

Yum! Brands (YUM) — diluted by design. This is a correction worth making, because a lot of people talk about “Taco Bell stock” — there’s no such thing. Taco Bell is owned by Yum! Brands, alongside KFC and Pizza Hut. So even though Taco Bell serves lettuce, any single-brand outbreak exposure is heavily diluted across a three-chain, globally diversified parent. YUM is far more insulated than a pure-play like SG or CMG.

The pattern: pure-plays get punished, diversified parents absorb the blow. That’s a durable lesson well beyond this one outbreak.

The headline catalyst: why the “diagnostics pop” is mostly a mirage

Now the other half of what investors are chatting about: if produce companies are the losers, aren’t the testing companies the winners? Buy the diagnostics names — Qiagen, bioMérieux, and so on?

This is where you need to separate a real catalyst from a headline catalyst, and it’s the most valuable takeaway in this whole piece.

Qiagen (QGEN) did put out a press release this week highlighting that its QIAstat-Dx Gastrointestinal Panel 2 includes Cyclospora as one of its 16 targets, with results in about an hour. Real product, real relevance, genuinely useful in an outbreak. So the narrative connection is airtight — and that’s exactly what makes it a trap.

Look at the actual numbers. The entire global cyclospora diagnostic testing market is estimated at roughly $44 million per year. Qiagen is a company with around $2 billion in annual revenue. Even if this outbreak doubled or tripled cyclospora-specific testing demand overnight, the revenue impact would be a rounding error against Qiagen’s P&L — invisible in an earnings report. A press release timed to an outbreak is a marketing move, not a revenue event.

So what is the diagnostics reaction? It’s sentiment. Traders may bid QGEN or a peer up on headline flow and association, but there’s no fundamental earnings catalyst underneath. That kind of move is fast, thin, and prone to fading once the news cycle moves on — the textbook profile of a headline catalyst.

How to tell them apart, as a rule you can reuse:

A real catalyst changes a company’s future cash flows in a way that will show up in an earnings report — Chipotle losing 15% of same-store sales is real. A headline catalyst changes a company’s association with a news story without meaningfully changing its cash flows — Qiagen being “a cyclospora testing company” for a week is a headline. Real catalysts are worth positioning around. Headline catalysts are mostly worth watching other people get burned by.

How I’d actually think about playing it

None of this is a recommendation — it’s how I frame my own thinking, and I trade options for a living, so I look at these events through a specific lens.

The asymmetry is the thesis. Outbreaks destroy far more value than they create. The downside on a named restaurant stock is large and concrete (Chipotle: -37%). The “upside” on diagnostics is mostly narrative and fades. If you’re hunting for an outbreak trade, respect that the real, sizeable move is on the loser side, not the winner side.

Watch implied volatility, not just price. When an outbreak headline hits a name like SG or CMG, implied volatility on its options tends to spike as fear gets priced in. For someone who sells cash-secured puts, that IV spike is where it gets interesting — but only on a stock you’d genuinely be happy to own through a recovery. The Chipotle lesson is that the fundamentals-strong, brand-strong names eventually came back; CMG went on to fully recover and then some. Selling a put into an inflated-fear moment on a quality name you want to own is a very different act from gambling on a diagnostics pop.

Don’t chase the mirage. If your instinct was “buy QGEN on the outbreak,” this article’s whole job was to talk you out of it. The narrative is real; the materiality isn’t.

Wait for the name. The single biggest swing factor is whether the CDC ends up linking cases to a specific chain. Until then, this is a watchlist. If a name drops, that’s when the Chipotle playbook actually activates — and you’ll already know what to look for.

The market doesn’t reward being early to a headline. It rewards understanding which headlines change cash flows and which just change the conversation. A parasite in the lettuce is a genuinely useful reminder of the difference.

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Disclosure: I actively trade options (primarily cash-secured puts) on names including NVDA and TSLA, and may hold or initiate positions in securities mentioned. This article is for informational and educational purposes only and is not investment advice. Sources: CDC cyclosporiasis surveillance (July 2026); Qiagen company press release (July 2026); CNN Money, Forbes, and CNBC reporting on Chipotle’s 2015–2016 E. coli crisis; Future Market Report / Reports and Data cyclospora diagnostic market estimates.

Microsoft made a quiet announcement last month that should have gotten a lot more attention than it did: the company told Axios it is exploring a fine-tuned, Azure-hosted version of DeepSeek V4 — yes, the Chinese open-source model — as a lower-cost engine for Copilot Cowork, its enterprise AI agent. At the same time, Microsoft is moving Copilot Cowork to usage-based pricing, because the current generation of agentic AI tools burns through so much compute that flat-rate plans stopped making financial sense.

My first reaction was the same one a lot of investors had: this is Tesla vs. BYD all over again.

A scrappy Chinese competitor shows up with a product that’s dramatically cheaper. The incumbent’s shareholders panic. And then — in the version of the story most American investors remember — the market realizes the cheap alternative isn’t actually as good, everyone goes back to the premium product, and the incumbent wins.

I was halfway through outlining that exact article when I did what I always tell you to do before putting money (or your byline) behind a thesis: I checked the numbers.

The numbers told a different story. And honestly, the real BYD lesson is far more useful for thinking about the AI market than the comfortable one.

The story we tell ourselves about Tesla and BYD

Here’s the popular narrative, and I’ll admit I believed a version of it myself:

Around 2023–2024, BYD announced cheaper EVs and briefly outsold Tesla. Tesla’s stock tanked because shareholders feared the competition. But BYD’s build quality “wasn’t even close,” buyers figured that out, and the market’s attention swung back to Tesla. Premium American engineering beat cheap Chinese scale. The end.

It’s a satisfying story. It flatters the incumbent, it flatters American manufacturing, and it gives investors a tidy template: when a cheap Chinese competitor shows up, buy the dip on the quality leader.

There’s just one problem.

What actually happened

BYD won. Not on vibes — on volume, and by a landslide.

In 2025, BYD sold roughly 2.26 million battery-electric vehicles worldwide, growing about 28% year over year. Tesla delivered about 1.64 million, a decline of roughly 9–10% from 2024 — its second consecutive annual sales drop. That made 2025 the first full calendar year in well over a decade that any automaker outsold Tesla in pure EVs, and BYD didn’t squeak past — it won by more than 600,000 cars.

And it wasn’t just a China story. BYD has been expanding aggressively into Europe and Latin America, often with local production. In Europe, BYD now offers more models than Tesla does. The “quality gap” that Elon Musk once literally laughed about in an interview? It closed. Reviewers stopped treating BYD as a punchline years ago.

So why does the “Tesla won” narrative persist, especially among American investors? Two reasons, and both of them matter enormously for the AI analogy:

1. The tariff wall. BYD sells essentially zero passenger vehicles in the United States. Tesla remains the US EV leader not because American consumers compared the two and chose Tesla — they never got the choice. Trade policy built a wall, and inside that wall, Tesla still looks dominant.

2. The stock changed its story. TSLA shares did crater in early 2024 when BYD first outsold Tesla in a quarter, and the stock did recover. But look at why it recovered. It wasn’t because Tesla clawed back EV market share — deliveries kept falling. The stock recovered because the narrative shifted from “car company” to “AI company”: robotaxis, full self-driving, Optimus. As someone who sells cash-secured puts on TSLA, I watch this stock closely, and I can tell you it has traded on the autonomy story, not delivery numbers, for a long time now.

In other words: the incumbent’s stock survived, but not by winning the fight everyone was watching. It survived by changing the subject — while the cheap challenger quietly took the global volume crown.

That is the real BYD lesson. And it should make US AI investors a lot less comfortable than the fairy-tale version.

Now apply it honestly to DeepSeek

The parallel everyone wants to draw: DeepSeek is cheaper per token, but it’s “not even close” to OpenAI’s or Anthropic’s frontier models, so users will eventually come back to US-made AI, just like car buyers “came back” to Tesla.

But we just established that car buyers didn’t come back to Tesla. Globally, they left. So if you apply the analogy honestly, DeepSeek isn’t the fad in this story — DeepSeek is BYD. The cheap challenger whose quality gap keeps narrowing while the incumbents’ costs stay high.

And here’s where the analogy gets genuinely scary for the “US AI wins by default” crowd: there is no tariff wall for software.

BYD is locked out of the US market by trade policy. A physical car has to clear customs. An open-weights AI model doesn’t. DeepSeek publishes its model weights openly, which means Microsoft can download them, fine-tune them, and run them entirely on Azure servers in the United States — no data flowing to China, no licensing payment to a Chinese company, no business relationship at all. That’s exactly what Microsoft says it would do: an optional, self-hosted, fine-tuned DeepSeek V4 living inside Azure’s security and compliance boundary.

The one wall that does exist is political. Washington has floated banning DeepSeek outright, several governments have already banned it from official networks, and Microsoft naming a Chinese model as a candidate for its flagship enterprise product drew immediate criticism. Politics may yet do for US AI labs what tariffs did for Tesla’s home market. But that’s a policy moat, not a product moat — and policy moats can be redrawn with one election or one executive order.

Where the US labs actually win (and it’s not patriotism)

So is the bear case complete? Should we assume DeepSeek does to OpenAI and Anthropic what BYD did to Tesla?

Not quite — and this is where the analogy finally breaks in a useful direction.

Notice what Microsoft is actually doing. It isn’t replacing its frontier models with DeepSeek. Copilot Cowork today runs on Anthropic and OpenAI models, and Microsoft is evaluating DeepSeek (or another open-source model) specifically as the lower-cost tier under usage-based pricing. The premium, high-stakes agentic work stays on the frontier models. The cheap, high-volume routine work goes to whatever is cheapest.

That’s not a story about one side winning. That’s a story about the market bifurcating:

• Commodity inference — summarization, routine drafting, simple agent steps — races to the bottom on price. Open-source models, including Chinese ones, dominate here because you can’t beat “nearly free and self-hostable.”
• Frontier capability — complex agentic work, code that has to be right, anything touching regulated or sensitive data — stays with the US labs, defended by genuine capability gaps, enterprise trust, compliance requirements, and yes, government pressure.

The auto industry has looked like this forever: Toyota and BYD own volume; Porsche and Ferrari own margin. Nobody thinks Ferrari “lost” to Toyota. The mistake is expecting one winner in a market that’s structurally splitting into two.

What this means for your portfolio

I’m not a financial advisor, and none of this is a recommendation — it’s how I’m framing my own thinking:

Don’t buy the comfortable narrative. “Cheap Chinese AI is junk and everyone will come back to US models” is the same story investors told about BYD, and it aged terribly. Price your theses on data, not flattery.

Watch the bifurcation, not the horse race. The interesting question isn’t “DeepSeek vs. OpenAI.” It’s how much of total AI workload ends up in the commodity tier versus the frontier tier. Frontier labs keeping 20% of tokens but 80% of revenue is a very different world from the reverse — and infrastructure names like Microsoft and Nvidia get paid in both scenarios, which is partly why MSFT can shop for cheaper models without hurting its own story.

Respect the policy wildcard. Tesla’s US “win” was manufactured by tariffs. If Washington bans or restricts Chinese open-source models, US labs get a similar artificial home-field advantage — bullish for them, but fragile, because it can reverse.

Separate the company from the stock. Tesla lost the global EV war and TSLA still recovered, because the stock found a new story. Narratives can carry a stock long after the original thesis dies. That cuts both ways, and it’s exactly why I sell puts on volatility-rich names like TSLA instead of pretending I can predict which narrative wins.

The BYD lesson isn’t “quality always wins.” It’s that cheap-and-good-enough wins the volume war, walls decide who gets protected, and stocks survive by changing the story. Every one of those forces is already visible in the AI market. The investors who’ll get hurt are the ones still telling themselves the fairy-tale version.

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Disclosure: I actively trade options (primarily cash-secured puts) on TSLA and NVDA, and may hold positions in securities mentioned. This article is for informational purposes only and is not investment advice. Sources: Axios reporting on Microsoft’s Copilot Cowork pricing and model evaluation (June 2026); Statista and industry delivery trackers for 2025 BYD/Tesla sales figures.

My own read on the market, not financial advice. I hold positions in this space, so read accordingly and do your own work.

The semiconductor sector has been on an absolute tear because of AI. But there’s turbulence ahead, and I want to walk through why — and what I think a Samsung or SK Hynix holder should actually do about it.

The numbers first

Let’s start with the facts, because they’re strange.

• Samsung Electronics: down more than 20% from its high, falling for three straight weeks.
• SK Hynix: also more than 20% off its peak.
• Micron: in a similar situation.
• The Philadelphia Semiconductor Index: down roughly 14% from its record last month.

By any normal definition, that’s a bear market in chips.

Now here’s the part that makes people scratch their heads. Look at Samsung’s actual business: record earnings. On paper, the profits are at an all-time high. Same story across memory. So why is the stock falling?

Because the market wasn’t buying the profits. It was buying the expectations. And the expectations had gotten so high that even record results couldn’t satisfy them. Samsung and SK Hynix each fell around 7% on the day they reported record quarterly earnings — investor expectations had run far past what analysts were forecasting, so “record” wasn’t good enough.

That’s your first lesson right there: a great company and a great stock are not the same thing. Price is what you pay for the future, not the past.

Why Morgan Stanley said to sell

Morgan Stanley — the bank Korean investors nicknamed the “chip grim reaper” after its 2021 “Memory, Winter is Coming” report — told clients to reduce semiconductor exposure and rotate into Big Tech hyperscalers instead.

Their reasoning is subtle, and it’s worth understanding properly because most people get it wrong.

It’s not that chip profits are falling. They aren’t. It’s about something called earnings estimate revisions. Analysts constantly forecast a company’s future profits, and through this AI boom, they’ve been raising those forecasts again and again. That upward revision is the fuel that has been driving chip stocks higher.

Morgan Stanley’s point: the estimates are still going up — but they’re going up more slowly than before. The rate of acceleration is fading. In their words, the narrow, chip-led rally is ending, and market leadership is starting to broaden out to other sectors.

Think of it like a car. The car is still moving forward. But you can feel it stop accelerating. That change is what the market front-runs.

Note the important nuance almost everyone skips: Morgan Stanley called for a near-term correction, while maintaining a positive long-term view on the AI value chain. This is not “the AI story is over.” It’s “chips got ahead of themselves, short term.”

So where does the money go? Hyperscalers.

The hyperscalers — Amazon, Microsoft, Meta, Alphabet — are the companies running the giant data centers and selling AI services on top of them.

And here’s the relationship that matters: hyperscalers and chipmakers are two ends of the same chain. Big Tech companies are the biggest customers Samsung and SK Hynix have. Memory chip sales depend on hyperscaler spending.

But look what happened to the two ends of that chain. Chip stocks ran up enormously, while the hyperscalers actually lagged — one basket of hyperscalers was roughly flat to down slightly over a period when the chip index climbed more than 120%. The customer barely moved while the supplier tripled.

That gap doesn’t stay open forever. When it closes, the money moves from the supplier to the buyer. That’s sector rotation.

There’s also a structural reason hyperscalers are the steadier business, and this is the part I care about most as an income-focused investor:

Chipmakers sell you a thing. Hyperscalers rent you a service. Memory is a commodity — sell the chip, book the revenue, and now go win the next order in a cycle that’s notoriously boom-and-bust. Cloud and AI services are subscription-based: money flows in every single month, whether or not anyone is placing a new chip order that quarter.

Recurring revenue is simply more stable than commodity revenue. That’s not an opinion, it’s a business model.

The real question: should you sell everything?

If you hold Samsung or SK Hynix, this is what you actually want to know. My honest answer: no — but trim.

I don’t think this is a moment to dump the position and run. The AI demand story isn’t broken, the companies are printing record profits, and plenty of smart people (Korean asset managers among them) still think memory has room to run into next year.

But I do think it’s a moment to scale back — to reduce the percentage of your portfolio sitting in semiconductors. If chips quietly grew to be half your portfolio because they went up so much, that’s not a conviction bet anymore. That’s concentration risk that happened to you. Rebalancing back toward a size you’d deliberately choose is just good hygiene, and it’s what I’d do here.

Then should you buy hyperscalers right now?

Careful. My answer is not yet.

The hyperscalers are spending staggering amounts of capex to build out AI infrastructure. What we still don’t have is clear proof those investments generate returns that justify the spending. That’s the open question hanging over the entire trade, and it’s exactly why these stocks lagged in the first place.

So here’s my plan: wait for the earnings. When these companies report and we can actually see that the massive capex is converting into real profit — that’s when I’d want to put money to work. Buying before the proof means paying for a story. Buying after means paying for a fact. I’d rather pay for the fact and give up a few points of upside.

There’s also a warning sign the market is already chewing on: Meta disclosed it’s exploring selling surplus AI computing capacity to outside parties. Morgan Stanley read that as a signal Big Tech’s AI spending growth is beginning to moderate. If you have too much compute, you weren’t a desperate buyer of memory chips. That cuts both ways for this whole trade.

Bottom line

• Record profits with a falling stock isn’t a contradiction — it means expectations outran reality.
• The bear case is about the rate of change, not a collapse. Estimates are still rising, just slower.
• If you’re heavy in chips: trim to a size you’d choose on purpose. Don’t panic-sell a business that’s printing money.
• If you’re eyeing hyperscalers: wait for the capex to show up as profit in the earnings, then decide.

Nobody rings a bell at the top, and Morgan Stanley has been early — and wrong — before. But when the fuel that drove a trade starts running low, the responsible move isn’t to jump out the window. It’s to check how much of your portfolio is riding on one story.

Sources: Bloomberg, Yahoo Finance, Korea JoongAng Daily, Seoul Economic Daily (July 2026). Positions and numbers move fast — verify before acting. This is my personal read, not a recommendation.

A cash-secured put is a commitment: you sell a put option and set aside enough cash to buy 100 shares at the strike price. If the stock stays above the strike, you keep the premium. If it falls below, you buy shares you wanted anyway — at an effective price of strike minus premium.

The strategy works best on companies you’d genuinely hold for years, at strikes you’d genuinely pay. The premium is compensation for taking on that obligation, not free money — the risk is the stock falling far below your strike.

A concrete example: selling a Tesla put

Say Tesla (TSLA) is trading at $250 and you’d be happy to own it at $240. You sell one $240 put expiring in 35 days and collect a premium of $6.00 per share — $600 total (one contract = 100 shares). Your broker sets aside $24,000 of your cash ($240 × 100) as collateral. That’s the “cash-secured” part: if you’re forced to buy, the money is already there.

From this moment there are only two endings.

Scenario 1 — the win: TSLA stays above $240

Expiration day arrives and TSLA closes at $265. Nobody exercises the right to sell you shares at $240 when the market pays $265, so the put expires worthless. Your $24,000 is released, and the $600 premium is yours, free and clear.

The math: $600 ÷ $24,000 = 2.5% in five weeks, roughly 26% annualized if you could repeat it monthly (you can’t always — premiums vary with volatility). Note what didn’t need to happen: TSLA didn’t need to go up. It could have dropped from $250 to $241 and you’d still keep every dollar. That’s the quiet appeal — you get paid even when the stock drifts sideways or slightly down.

Many sellers don’t even wait for expiration: if the put’s value decays to $3.00 after two weeks, you can buy it back, lock in $300 (half the max profit in a third of the time), and redeploy the cash.

Scenario 2 — the loss: TSLA drops hard

Same trade, different world: bad delivery numbers land, and by expiration TSLA is at $200. The put is exercised — you’re assigned and must buy 100 shares at $240, spending your $24,000 while the market price is $200.

Your true cost basis is $234 per share ($240 strike minus the $6 premium). Against a $200 market price, you’re sitting on an unrealized loss of $3,400. The premium cushioned the fall — a shareholder who bought at $250 is down $5,000 — but a cushion is not a parachute.

This is why the golden rule is only sell puts on stocks you want to own at strikes you’d genuinely pay. If you meant it when you said you’d happily buy TSLA at $240, assignment isn’t a disaster — it’s your entry order getting filled, with a $600 rebate. You now hold the shares and can sell covered calls against them while you wait for recovery (that combination is called “the wheel”). If you didn’t mean it, you’re now stuck holding $20,000 of a stock you never wanted — and that’s the mistake that turns this strategy sour.

The worst case is worth stating plainly: the stock can keep falling after assignment, and in theory go to zero. Your maximum loss is the strike minus the premium, times 100 — here, $23,400. Remote for a company like Tesla, but position sizing exists because remote is not never.

How to pick the trade

Screen for liquid options (tight bid-ask spreads), elevated implied volatility rank, and no earnings date before expiration — earnings are exactly the kind of binary event that produces Scenario 2. Position size so assignment never forces you to sell something else.