Seven — 003 · The 20-Second Version

Full breakdowns below. Not financial advice. See the disclaimer.

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Last Week's Biggest Financial Events (June 29 – July 5)

1. The jobs report came in soft, but the "good news" part is a bit of a mirage

The June employment report was the biggest thing that happened all week. Payrolls rose by just 57,000, well short of the roughly 115,000 economists were expecting, the softest month in four months. On paper, unemployment ticked down to 4.2% from 4.3%, which sounds like a win.

Here's the part I want you to really sit with, though: that drop happened because fewer people were actively looking for work, not because more people found jobs. The labor force participation rate fell to its lowest level since March 2021, and household employment actually dropped by over half a million. So the headline rate improved for a reason that isn't actually good news.

Wage growth stayed calm. Average hourly earnings rose 0.3% for the month and 3.5% over the year, right in line with what was expected.

Why this matters: This is a good example of why I never take a headline number at face value. A "better" unemployment rate driven by people leaving the workforce is a different story than one driven by hiring strength, even though the number itself looks identical. The question I keep coming back to is: does this move the odds of the Fed holding, cutting, or hiking? Here, it leaned toward "the Fed has room to stay patient," not the "hikes are coming" story that's been building the last few weeks.

2. The rate debate didn't get resolved, it just shifted a little

We've spent the last couple issues talking about markets pricing in the possibility of a hike, not just debating how fast cuts might come. This report didn't kill that story, but it did soften it. It wasn't weak enough to guarantee the Fed backs off entirely, but it gave the "labor market is cooling" camp a bit more ammunition. I'm treating this as inconclusive rather than a resolution. We need to see the Fed's own words this week to get more clarity.

3. Money moved around based on what investors expect next, not just what already happened

Treasury yields reacted to the employment data, growth stocks stayed sensitive to rate expectations, and AI/tech names kept trading more on future earnings assumptions than on anything happening in the economy right now. The chain I keep coming back to:

Economic data → Fed expectations → Bond yields → Stock valuations

Softer labor data pushed short-term yields down as traders priced out some hike risk, which is generally supportive for growth and long-duration stocks, at least in theory.

4. But here's the part that surprised me: the "good news" reaction wasn't even across the board

This is the piece I think is worth slowing down on. Even though the overall market took the report well (the Dow closed at a fresh record high, and both the S&P 500 and Nasdaq finished the week up), that strength wasn't shared everywhere. Chip stocks had a rough few days. Names like Micron, Applied Materials, and Marvell all fell mid to high single digits as investors took profits after a huge run for semiconductors this year, while money rotated into steadier, more traditional names that helped carry the Dow higher.

I found this to be a really clean example of something I want this newsletter to keep teaching: an index going up doesn't mean everything under the hood is going up with it. The market cheered the "Fed might not need to hike" story with one hand while quietly taking chips off the table (pun intended) in the sector that's been running hottest with the other. If you only glanced at the Dow record, you'd have missed that the AI/semiconductor trade had a genuinely tough week.

What to Watch This Week (July 6–10)

Three things I'm personally tracking this week:

If I had to bet on what moves markets most this week, it's the FOMC minutes and how yields react to them. A more dovish tone could extend last week's yield decline and keep supporting growth valuations. A more hawkish one, especially given how divided the committee reportedly was after the June meeting, could reverse that pretty quickly.

This week's stock is a two-parter. There's too much here to rush, so this issue covers the business and the moat. Next issue covers valuation and whether the price makes sense.

If you read The Market section above, you saw that chip stocks had a rough week while the broader market hit records. Alphabet is an interesting company to study right now precisely because it sits on both sides of that trade. It spends tens of billions on AI infrastructure like the companies that sold off, but it makes its money the old fashioned way, and I want to start there.

What Alphabet actually sells

Most people say Google sells ads. I think it's more precise to say Google monetizes intent. The chain looks like this:

People search → Google learns intent → Businesses want that attention → Businesses buy ads → Google earns revenue

Google sits in the middle of two groups who need each other: people looking for answers and businesses looking for customers. That intermediary position is the profit engine, and it explains why advertising has been so profitable for so long. Quick note on names since I'll use both: Google is the operating company, Alphabet is the parent that owns it, and the stock trades as GOOG/GOOGL.

The four engines

A personal note on engine #3

I recently bought the Fitbit Air, Google's new $99 screenless health tracker, and I think it's a small but telling example of how Alphabet operates. It competes directly with Whoop and the Oura Ring, and it does the core things those devices do (sleep, recovery, heart rate, workout tracking) without requiring a subscription just to function. A Whoop is basically a bracelet without its roughly $200 a year membership. Oura charges about $70 a year. The Air's base features work out of the box.

The clever part is the business model behind it. The Gemini-powered AI health coach is the upsell, part of a Google Health Premium subscription after an included trial. So the $99 device is really a funnel: accessible hardware pulls users into the ecosystem, some percentage convert to recurring subscription revenue, and the health data improves Google's AI models along the way. Hardware revenue, subscription revenue, and better AI, all from one cheap wearable. As an owner, it's a genuinely good product. As a shareholder-in-training, it's a case study in how everything Alphabet builds feeds something else.

That's the first principle worth internalizing: Google doesn't really sell products. It sells attention, information, computing power, and AI, and almost every product exists to strengthen those. Android is the classic example. More Android phones means more searches, more data, more ad opportunities, higher profits. The products reinforce each other.

The moat

My question when studying any dominant company is simple: why can't someone just build another one? For Google, here's how I score the six classic moat types:

Having several of these at once is rare. The two I find most powerful:

The data network effect. Google's network effect is different from a social network's. Every search teaches Google what people want, which results satisfy them, and which searches are related. Billions of daily searches compound into an understanding that a new competitor starting with a few thousand queries simply cannot match. Google doesn't win because it has more data in raw volume. It wins because it has high quality, real-world behavioral data about what people actually want.

The ecosystem. Android leads to Chrome leads to Search leads to Maps, Gmail, YouTube, and now Gemini, with Google Cloud running underneath much of it. Every product increases the value of the others, and leaving one service means giving up the convenience of the whole system. When your brand becomes a verb ("just Google it"), your customer acquisition cost is effectively zero

The pillar scorecard

Running Alphabet through the 8 pillars:

Six of eight pass, and the two that fail are both valuation pillars. That pattern tells you something specific: the business is excellent, and the market knows it. Nobody is confused about Alphabet's quality. The debate is entirely about the price.

Two honest footnotes on the scorecard. First, the 5-year average P/E of 44.78 looks scarier than the current picture; the trailing P/E sits around 27, so some of that average is inflated by earlier years. Second, the Price to FCF of 64.23 deserves the same framing I gave Micron's extreme ratios last issue: Alphabet is in the middle of a massive AI capex cycle, spending enormous sums on data centers and chips, and every dollar of capex directly suppresses free cash flow. When the denominator is artificially compressed, the ratio inflates. That doesn't make the pillar meaningless, but it does mean the red flag is partly an artifact of heavy investment rather than pure overvaluation. Whether that investment pays off is the real question, and it's exactly what Part 2's valuation work has to wrestle with.

One more thing worth flagging on pillar 3: the share count decline is real over five years, but the current picture has genuinely changed. Alphabet paused buybacks in early 2026, took on roughly $100 billion in debt, and then in June announced an $84.75 billion equity raise to fund AI infrastructure, which means the share count will rise, not fall, in the near term. A company that spent years shrinking its share count is now issuing stock and borrowing money at the same time, all to fund the AI buildout. Notably, Berkshire Hathaway took $10 billion of that raise. Whether this capital pivot creates or destroys value per share is exactly the kind of question Part 2's valuation work exists to answer.

The risk that matters most

Every moat has cracks, and Alphabet's biggest one is existential in a way that's worth naming plainly: what if search becomes less economically valuable?

Think about Google's position. If Google builds the best AI, it may cannibalize its own search advertising, because an AI that answers your question directly gives you fewer links to click and fewer ads to see. If Google doesn't build the best AI, someone else will, and users drift to them instead. This is the innovator's dilemma, a concept from Clayton Christensen: incumbents must choose between protecting the existing business and disrupting it before someone else does. Google is navigating that exact tradeoff right now, in public, with its core profit engine on the line.

That's why I'd argue AI is simultaneously Alphabet's greatest opportunity and its greatest risk. It's a horizontal technology, meaning one innovation that improves Search, Cloud, Ads, YouTube, Workspace, and Android all at once. But it's also the first technology in twenty years that could plausibly change how people find information, which is the entire foundation of the cash machine.

Next week in Part 2: what Alphabet is actually worth, including the fair value work, the balance sheet adjustment, and whether those two red pillars are a warning or just noise.

Reminder: Stock of the Week is a two-parter this issue, so this is a watchlist setup, not a trade setup. The valuation work lands next week, and I'm not going to suggest positioning before I've finished answering "what is it worth?" That would violate my own process.

The big picture: an uptrend digesting a shock

GOOG has been in a strong uptrend over the last 12 months, with a low of $172.77 and a high of $408.61. Last earnings (April 29) the stock gapped up on a blowout quarter and eventually printed that all-time high. Since then it has pulled back to a low around $330.

Here's the context behind that selloff that I think matters: on June 1, Alphabet announced an $84.75 billion equity raise to fund its AI infrastructure buildout, one of the largest equity raises in market history. When a company issues new shares, existing shareholders own a smaller slice of the pie, and the market reprices for that dilution. The notable detail inside the announcement: Berkshire Hathaway agreed to invest $10 billion of it in a private placement. When the most famously price-disciplined investor on Earth writes a $10 billion check, that tells you something about how at least one buyer views the valuation. So the pullback isn't mysterious weakness. It's the market digesting a massive, deliberate capital decision.

The technical picture

The story these tell together: the trend damage from the June selloff is real but contained. Price held well above the 200 EMA, which means the 12-month uptrend structure never actually broke. The 20 and 50 EMAs sitting nearly on top of each other is a coiling pattern; the indecision usually resolves with force. MACD turning up from below zero while RSI sits neutral suggests the sellers have exhausted more than the buyers have committed. Nobody has conviction yet, which makes sense given what's on the calendar.

The catalyst map

This is where it gets interesting, and it connects directly to The Market section above:

What the options market is telling us

IV Rank is 63.4 and IV percentile is 92.06, meaning implied volatility is higher than it's been in 92% of readings over the past year. Translation for newer readers: the options market is pricing in a big move, and options are expensive right now. That earnings-plus-Fed cluster at the end of the month is almost certainly why.

This has a direct practical implication we'll pick up in the Options Desk: when IV is this elevated, buying options means paying a premium for a move that has to be even bigger than the market already expects, just to break even. Elevated IV environments tend to favor strategies that sell premium rather than buy it. More on that below.

The confluence check

My framework says conviction comes from multiple methods agreeing. Where we stand: the fundamentals from Part 1 are strong (six of eight pillars pass, and the failures are both valuation pillars). The technicals are neutral and coiled, leaning slightly toward early recovery. The valuation verdict is unfinished until Part 2. So the honest summary is: quality business, repaired-but-unconfirmed chart, unanswered price question, and two major catalysts in three weeks. That's a watchlist, not a trade. The levels I'm watching: a reclaim of the 20/50 EMA zone around $359 with follow-through would confirm the momentum shift; a loss of the 100 EMA near $345 would say the digestion isn't over.

Reminder: nothing in this section is a position or a recommendation. These are trades I analyzed on paper to show how a trader might think through the current setup. Do your own work before risking a dollar.

The situation the options market is handing us

From The Setup: GOOG's IV Rank is 63.4 and its IV percentile is 92.06, with earnings July 28 and the Fed decision July 29. The options market has already priced the fireworks. That single fact drives every structural decision this month.

Teaching moment #1: IV crush, or why "I was right and still lost money" happens

Implied volatility is the price of uncertainty, and GOOG options currently carry more uncertainty premium than they have in 92% of readings over the past year. The trap for newer traders: the moment earnings drop, that uncertainty resolves and the premium evaporates almost instantly. This is IV crush. A trader can buy a call, watch the stock gap up 4% on good earnings, and still lose money because the volatility premium collapsed faster than the stock moved. At the 92nd percentile, you're not just betting on direction. You're betting the move will be bigger than the already-large move the market has priced in.

Teaching moment #2: the expiry calendar is the whole game

Last issue we covered how an August expiry doesn't avoid a July 30 earnings event. This month the calendar splits cleanly in two: expirations on or before July 17 avoid the earnings and Fed cluster entirely, while expirations July 31 and later contain both binary events, back to back, whether you planned for them or not. There's no neutral choice. The trade analyzed below deliberately lives on the safe side of that line.

The trade I analyzed: put credit spread

The thesis is humble on purpose: GOOG stays above the $340 area, right around the level buyers defended in June, for twelve more days. Not "GOOG goes up." Just "GOOG doesn't break down." Because event fear has inflated all of July's premium, the seller collects unusually rich credit for that modest claim, and the position expires eleven days before the earnings risk it's being paid to fear. If it works, that's a 28.9% return on risk in 12 days.

Why this structure fits the confluence framework: it agrees with the technicals from The Setup (defended floor at $330-340, long term trend intact above the 200 EMA), it requires no opinion on the unfinished valuation work from Part 1, and it sidesteps the event cluster entirely. Every piece of the analysis points the same direction.

The trade I analyzed and passed on: iron condor

I also worked up an iron condor at the same expiry, and walking through why it didn't make the cut is probably the most useful part of this section.

On paper it looks tempting. Nearly double the credit, and a 67.8% return on risk versus the spread's 28.9%. So why pass?

Three reasons, in order of importance:

To be clear, the condor isn't a bad trade. It's a different opinion about the same chart, one that says "nothing decisive happens for two weeks." It just isn't the opinion my own analysis supports right now. Knowing why you're rejecting a trade is worth as much as knowing why you're taking one.

The framework tie-in

Notice what the featured structure doesn't require: knowing whether GOOG is cheap. Part 2's valuation verdict is still pending, and this trade is deliberately agnostic to it. If Part 2 concludes the price is attractive, longer-dated directional structures get interesting after July 29, when IV crush makes premium cheap again. The same calls will likely cost meaningfully less on July 30 than they do today. Patience has a literal payday here.

This section exists so that nothing in this issue reads as easy money. Every idea above has failure modes, and naming them out loud is the discipline.

Risk #1: The short strike sits inside the defended zone, not below it

This is the most important weakness in the featured trade, so I want to be honest about it. The June selloff bottomed around $330. The short put is at $340, with breakeven at $339.44. That means the trade doesn't just lose if the floor breaks. It loses on a simple retest of the floor. GOOG could revisit $332, bounce perfectly, and finish the year higher, and this spread would still take its full $388 max loss if held to expiry through that dip.

The counterargument for the strike placement: the richer credit at $340 versus, say, $325 is exactly what elevated IV is paying for, and a 76% POP already accounts for this. But readers should understand the tradeoff that was made: this trade is short the zone, not short the breakdown. A more conservative version of the same idea would sell the $327.50/$325 spread for less credit and survive a retest. Where you place the strike is where you place your opinion.

Risk #2: The catalyst inside the window

The trade dodges earnings and the Fed decision, but the FOMC minutes on Wednesday, July 8 land squarely inside the 12-day window. A hawkish read pushes yields up and growth stocks down, and GOOG is a growth stock no matter how strong the balance sheet is. This is the single most likely trigger for a fast move toward the short strike. There's no structure that avoids all events. This one just chooses its events consciously, and Wednesday is the one it chose to accept.

Risk #3: Vega, or losing on paper while being right on price

A detail that surprises newer premium sellers: this position is short volatility as well as short the put. If IV rises further between now and July 17 (and at IV Rank 63, it has room to run higher into the event cluster), the spread can show a mark-to-market loss even while GOOG sits comfortably above $340. That paper loss is real if you're forced to close early, and psychological even if you aren't. The defense is already built into the plan: defined risk, small size, and an exit rule that doesn't depend on feelings.

Risk #4: Sizing, and why the max loss number is the first number

Total risk on the 2-lot is $388. Whether that's responsible sizing depends entirely on account size, which is why I frame it as a percentage rule rather than a dollar figure: many premium sellers cap any single defined-risk trade at 1% to 5% of the account. At 5%, a $388 max loss implies roughly an $8,000 account minimum. If the max loss on any trade would genuinely hurt, the trade is too big, full stop. The credit received should never be the number that decides the size. The max loss is.

Risk #5: Exit discipline is the whole edge

The plan says close at 30% to 50% of max profit ($34 to $56 on the 2-lot). The risk here isn't in the market, it's in the mirror. High-POP trades tempt you to hold for the last dollar, and holding a nearly-worthless short spread into expiry week trades a few dollars of remaining profit for days of gamma risk, where one bad session can flip a winner into max loss. The other side of the same coin: if the trade goes against you early, defined risk means defined. The structure was chosen so that the correct response to being wrong is nothing. No rolling into earnings to "fix" it, which converts a contained loss into event-cluster exposure, exactly what this whole issue argued against.

Risk #6: The two-part structure has its own risk

Worth naming since it's unusual: Part 2's valuation work isn't done, and it's possible the fair value analysis comes back saying GOOG is meaningfully overvalued. The featured trade was built to be agnostic to that outcome, but readers should hold the whole GOOG story loosely until the price question is answered next issue. Six green pillars describe a great business. They don't yet describe a great investment. That's what Part 2 is for.

The theme across all six: none of these risks are exotic. They're the ordinary ways this ordinary trade fails, which is exactly why they're worth writing down before the outcome is known rather than after.

The three ways a company can fund growth, and what it means when one uses all three at once

Every company that wants to grow faster than its profits allow has exactly three sources of money:

There is no fourth option. Every capital decision a company makes is some blend of these three, and the blend it chooses tells you what management believes.

Here's why this clicked for me this week: Alphabet just used all three in about six months. It's spending its enormous operating cash flow on data centers. It issued roughly $100 billion in debt for acquisitions and infrastructure. And in June it announced an $84.75 billion equity raise, one of the largest in history. A company that spent years buying back stock (shrinking the pie so each slice got bigger) flipped to issuing stock (growing the pie so each slice got smaller), all to fund AI compute.

What each choice signals is the interesting part. Funding with cash says "business as usual." Funding with debt says "we're confident future cash flows cover this." Funding with equity says something sharper: management would rather give up ownership than miss the opportunity, which means they believe the opportunity is worth more than the dilution costs. Either they're right, and the AI buildout earns returns that dwarf the dilution, or they're wrong, and shareholders paid for it twice, once in dilution and once in disappointing returns.

The practical takeaway for reading any stock: when you see shares outstanding change, always ask why. A falling share count usually means buybacks. A rising share count means dilution, and dilution is neither good nor bad by itself. It's a bet management placed with your ownership. Your job as an investor is deciding whether you'd have placed the same bet.

Alphabet's June equity raise, announced June 1 and upsized a day later, one of the largest in market history. It includes a $10 billion private placement from Berkshire Hathaway and a $40 billion at-the-market program to sell shares over time.

This one number explains most of this issue. It's why GOOG pulled back from its $408.61 all-time high (the market repricing for dilution). It's why pillar 3's falling share count needs an asterisk (the count is about to rise). It's the clearest possible signal of how seriously Alphabet takes the AI opportunity (management chose dilution over missing it). And it's the question Part 2 has to answer: is the buildout this money funds worth more than the ownership it cost?

Remember the number. Next week we find out what it bought.

Disclaimer: Everything in this newsletter is for educational purposes only. I'm sharing my learning process, not giving financial advice. Nothing here is a recommendation to buy or sell any security. Options involve substantial risk and are not suitable for everyone. Do your own research and consult a licensed financial advisor before making investment decisions.

Why "Seven"

Seven has always meant completeness. In the oldest stories, the world was finished in seven days — and the seventh was the day to step back and take in the whole of it. That's the promise of this letter: seven sections, one complete and careful look at a company, every single week. No shortcuts, no half-finished thinking — the whole picture, with precision, laid out plainly enough that anyone can follow it.

This week, completeness meant admitting that one issue wasn't enough. A great business deserves a whole second week before we put a price on it.

See you next Sunday.

— 7even Seven — 003