Your Centsational Market Update 16th July 2026

Hi love,

This week a lot of people are asking the same thing: the market seems stuck… is something wrong?

I'm not going to assume you already know a single term. We'll build each idea one link at a time, because once you can see how one thing causes the next, you stop reacting to headlines and start reading the market like someone who actually understands it. That's the whole goal.

First, the big picture: the market is moving sideways.

For about the last month and a half, the largest indexes haven't really gone anywhere. Quick step back: an index is just a basket that tracks a group of companies at once, so instead of following hundreds of separate prices, we can watch one number. The Nasdaq is the index packed with the big technology companies. Lately its price keeps bouncing inside the same range — up a little, down a little — with no clear direction. There's a name for this: a sideways market. Not a crash, not a boom. A pause. And here's the why behind the pause, because this is the first connection I want you to really feel: markets don't move on what's happening today. They move on what's changing. When nothing new is pushing prices, buyers and sellers roughly cancel each other out, and the price just drifts. To break out of that, the market needs a fresh reason to move. That fresh reason has a name: a catalyst — an event big enough to tip the balance decisively in one direction. Right now the market seems to be waiting for one of three, and I want to walk you through why each one would matter, because that's exactly the kind of connection that usually gets skipped:

1. An easing of the tensions in the Middle East would matter because conflict there pushes up the price of oil, and expensive oil raises the cost of almost everything, which markets dislike. So calm in the region removes a worry.

2. Another drop in inflation would matter: inflation simply being the general rise in prices over time because when prices rise more slowly, the pressure on interest rates eases, and cheaper borrowing tends to lift markets

3. And company profits climbing higher would matter most of all, because — and this is the single most important link in all of investing — the price of a company ultimately reflects the profits it earns. More profit, more the company is worth.

Until one of those arrives, this quiet phase can simply continue. That's not a warning sign. It's the market catching its breath.

Now the interesting part: the ones left behind are catching up.

Here's what gets missed when everyone stares at the same few giant tech names. While the big companies soared over the past couple of years, other corners of the market got left behind. Now some are closing the gap what's called a catch-up. And why does that happen? Because when the popular names get expensive, investors start hunting for value elsewhere, and money rotates toward the parts that were ignored. Watching that rotation is one of the most useful habits you can build. Two examples. First, small-cap companies "cap" is short for market capitalization, which is just a company's total value, so small-caps are simply the smaller businesses, as opposed to the giants. They're tracked by an index called the Russell 2000, and they're starting to recover relative to the big names. (I'm measuring them against the S&P "equal-weighted" index that's the same 500 large US companies, but counted evenly so a handful of giants don't dominate the reading. It gives a truer picture of the average company.) Small-caps still have a long road ahead, but because big and small companies tend to shine at different times, holding both can give a portfolio better balance when one zigs, the other often zags.

Second, Chinese technology. This sector sat out the rally for a long time and is now moving sharply. What makes it worth noticing is its valuations. A valuation asks: how expensive is this company compared to the profits it earns? If two companies both earn the same profit but one costs twice as much to buy, that one is more expensively valued and you're paying more for the same earnings. Chinese tech valuations look genuinely low right now, which means investors are paying relatively little for those profits. And why does cheap matter? Because, over the long run, the less you pay for a stream of profits, the more room there is to gain. That's often where the more interesting long-term stories begin.

Indonesia.

Indonesia's economy keeps growing its GDP, the total value of everything a country produces, is rising steadily. Normally you'd expect a growing economy to lift its stock market. Yet Indonesia's market kept falling. So the two came apart and whenever the economy and the market disagree like that, the interesting question is always why??

The reason wasn't weak companies. It was concern about accounting transparency whether investors can fully trust the reported numbers. And here's the link: markets run on trust. If people doubt the figures, they refuse to pay up for those profits even when the profits are real, so prices sink for reasons that have nothing to do with how the businesses are actually performing. There's one more thread. Indonesia produces oil, and oil prices climbed recently because of the Middle East tensions which would normally be a tailwind for an oil-producing country, since its exports earn more. Even with that helping hand, its market kept drifting lower against other emerging markets. That tells you the selling was about trust, not fundamentals. And here's why that distinction is worth so much: when something falls this far because of fear rather than broken performance, you often reach a point where the room left to fall is small compared to the room to recover once trust returns. Seeing that difference — fear versus fundamentals — is a real step from beginner toward advanced.

"But isn't the bull market over?"

This is the worry I hear most, so let's meet it head-on. A bull market is simply an extended stretch of rising prices (its opposite, a falling stretch, is a "bear market"). Some argue this one is finished because company profits are a "bubble" meaning profits have supposedly been inflated beyond anything real and are about to pop. Remember the most important link from earlier: a company's price ultimately follows its profits. So it follows logically that as long as profits keep rising, it's hard for a bull market to truly end. The real question, then, isn't opinion it's whether profits will keep rising.

Start with productivity — how much a company produces for each worker it employs. That's been going up. Now hold that beside wages (what workers are paid) which have not risen at the same pace.

When a business produces more but pays out relatively less of that gain in salaries, the extra doesn't disappear into thin air. It has to go somewhere. It flows straight into the company's profits. A chart from the St. Louis Federal Reserve (a highly trusted US source) shows exactly this: the slice of value going to company profits has kept climbing, while the slice going to wages has kept sliding.

It's good news for company earnings and therefore, in the short term, for markets. It's a harder story socially, over the long term, for workers, whose share is shrinking. Both are true at once.

And "isn't AI just a bubble about to pop?"

Start with the simplest version of the worry: that the enormous investment in semiconductors the tiny chips that power computers, phones, and artificial intelligence has run its course. If chip demand had peaked, a big engine of this market would be sputtering, so it's fair to check.

History gives us a ruler. During the great internet build-out from 1990 to 2000, semiconductor sales grew roughly sevenfold. In this current AI wave, they've grown only about one-and-a-half times so far. Here's the connection to draw: if the last comparable technology boom ran far longer and far higher before it topped out, then today's much smaller rise suggests we're likely nearer the beginning than the end.

But I want to go deeper than that, because "is it a bubble?" is actually the wrong question it's too vague to be useful. There are two sharper questions underneath it, and once you can ask them, you'll read every AI headline differently. This is exactly the kind of thinking that separates a beginner from an advanced investor.

Question 1: follow the dollar. Quick reminder first: revenue just means the money a company takes in from selling its product. Normally, when a company's revenue grows, we assume more customers are genuinely buying a healthy sign. But in the AI world, some of that money isn't coming from new outside customers. It's the same money going round in a circle between a few companies.

Let me make it concrete. Imagine I give you €100. You use my €100 to rent a room from our friend Anna. Anna then uses that same €100 to buy something from me. Look at what just happened: I "earned" €100, you "spent" €100, Anna "earned" €100 but there was only ever one €100, and it started in my pocket and came back to it. If the three of us reported our numbers separately, it would look like €300 of healthy business. It was one note, passed around a table.

Now here's the real version. A chip-maker (think of a company that makes the powerful computer chips AI runs on) invests money into an AI company it hands over cash in exchange for part-ownership. Why would it do that? Two sensible reasons: it's helping to create its own customer (now that AI company can afford to buy chips), and it's betting that if the AI company grows huge, its slice of ownership will be worth a fortune one day. Nothing shady about it so far.

But watch where the money goes. That AI company uses the cash to rent computing power from a cloud provider. The cloud provider then spends it buying chips from the very same chip-maker who put the money in at the start. The dollar has gone in a full circle. And along the way it got counted as "sales" at three different companies. From the outside it looks like three thriving businesses. It's really one dollar wearing three different coats.

The trouble isn't that any of this is illegal… it isn't. The trouble is on the page: when that money comes home as a chip purchase, the chip-maker records it as a "sale," exactly as if a brand-new outside customer had walked in. But that customer only existed because the chip-maker funded it first.

So here's the simple test to carry with you: would this sale still have happened if the seller hadn't first given the buyer the money to spend? If yes, it's real demand. If no, part of that impressive "growth" is really just the company's own money circling back home. (Notice this is the very same "can we trust the numbers?" muscle we used with Indonesia the same skill, a different market.)

Question 2: find the hidden clock. The moment a computer chip is installed, it starts losing value not slowly like a building, but fast like a phone, because a better chip is always on the way. Companies typically spread the cost of those chips over five to six years in their accounts, even though the chips are really only cutting-edge for a bit over a year. Spreading a short-lived cost across a long timeline makes today's profits look bigger than they honestly are, the bill just arrives later. That gap is where risk hides, and almost nobody is watching it.

So is it a bubble? There's reassuring news on the other side of the ledger: for every dollar being spent on AI equipment, roughly $1.19 of real income is now coming in to cover it and that figure has climbed above $1 for the first time, up from below $1 a year ago. In plain terms, the money coming in has just overtaken the money going out. JPMorgan's midyear read is that the largest players are profitable and the cycle still has room to run. The real lesson isn't "AI is a bubble" or "AI is fine." It's that "AI is a bubble" is a mood, not a thesis. The actual skill the one worth building is telling the sturdy companies (real customers, income that covers the spending) apart from the fragile ones (circular revenue, borrowed money, that ticking chip-clock). Same sector, very different risk. Seeing that difference is the whole game.

The bigger picture remains this:

Three things to carry with you. The bull market doesn't look finished, because profits are still rising. There are real opportunities hiding inside this quiet, sideways market, especially among the names left behind, as money rotates toward value. And on AI, the honest answer isn't "bubble" or "no bubble" it's that the income is now covering the spending, so the engine still looks intact, as long as we keep asking the two questions that tell a sturdy company from a fragile one.

My role here isn't to tell you what to do. It's to help you understand why each piece connects to the next so that when the noise gets loud, you stay calm, because you can actually see the machinery behind the headlines. That's the real edge, and it's exactly how a beginner grows into an advanced investor: one connection at a time.

We'll keep watching this together not to react, but to understand.

With love,

Francesca