Chartr Much of it comes down to the index’s new center of gravity: a handful of unusually profitable tech giants. The Magnificent 7 alone account for more than a third of the S&P 500’s total market value, and they’re punching far above their weight, posting 63.2% earnings growth in Q1, which is nearly 4x the rate of the other 493 companies.
Chartr
Bloomberg data through Thursday shows the trend still holding, with both operating and net profit margins at their highest in at least two decades. This means that companies are making more from their core businesses, as well as keeping more for shareholders after costs, interest, and taxes are paid.
4. But….Revenue Per Employee Falling for Small Cap Companies….Margins Flat for S&P 493
Apollo
5. Goldman Sachs Non-Profit Tech Index Down Double S&P Friday
6. AI Demand ..What Inning?
AI demand. “AI demand indicators remain bullish across the board. Overall, token expenditure looks robust, while the memory chip shortage continues to boost memory chip prices. Meanwhile, Nvidia data centre revenue shows no sign of slowing down, while overall AI adoption remains low”.
DAILY CHARTBOOK
7. Tesla Retail Investors 42% of Float…Space X Wants Same Model
Financial Times
8. When speculative small stocks win big, often it’s because investors aren’t thinking straight…Penny Stocks Outperforming
WSJ James Mackintosh Speculation is most obvious in the tiniest companies. Penny stocks, usually defined as those that trade for less than $5 a share, are often opaque and get zero attention from Wall Street analysts. When they go up this quickly, it’s often more about a frenzy among investors than underlying economic fundamentals.
Since March 30, penny stocks have risen 28% on average, well above the 22% of non-penny stocks in the Microcap index—and beat the Mag 7 of Amazon, Alphabet, Apple, Meta, Microsoft, Nvidia and Tesla. Unlike the Mag 7, the tiniest companies were slightly up in the first quarter, too.
Gambling in penny shares adds to a sense of wild speculation more widely in stocks. Just look at the demand for AI-linked stocks: Three loss-making IPOs are about to be among the most-valuable listed companies. Investors are cheering on capital spending so big that it moves the economy without knowing quite how it will make money. And companies have quintupled or more their value simply by announcing they are pivoting their business.
I call them “dark hours” because no one sees them. You don’t have a boss, you don’t have a clock, other people are off doing their thing, and it’s just you and the work. You play, experiment, and learn one dark hour at a time.
What looks like skill is mostly just a lot of work in the dark.
1. Emerging Markets Now Tech Stock ETF—44% Weighting
Google
2. Korean and Taiwanese AI Export Boom
3. Chinese Investors Dumping Hong Kong Stocks—Buying Chinese AI and Chips
4. Bitcoin ETFS Longest Streak in a Row of Net Outflows
On Tuesday, bitcoin ETFs registered their 12th day in a row — and longest streak ever — of net outflows, according to SoSoValue. Net assets across bitcoin ETFs fell to $85 billion from $107.8 billion on May 14.
Bitcoin is down 12% week-to-date after some fear-based unloading on Monday — following Strategy’s minor sale of 32 coins — triggered a cascade of long liquidations that accelerated the downward pressure.
5. COIN Coinbase Stock at Support Going Back to 2024
StockCharts
6. LLY Breaks Out to New Highs
StockCharts
7. Data Center Build Out 70% Of Americans Oppose
Semafor
8. The World Will Need 3x the Amount of Magnets in 10 Years….China 80% of Production
IDTechEx
9. Mega-IPOs Will Be Small Weight in Indexes
How Will Mega-IPOs Change the Face of the US Stock Market?
The effects of SpaceX and other big private companies going public won’t be sweeping or come all at once. Dan LefkovitzThe Alexes estimate initial weights for the mega-IPOs in CRSP market indexes based on their float-adjusted market capitalization. The impact is smallest in the total market index but greater for both the CRSP US Large Cap Index and the CRSP US Mega Cap Index. At a $75 billion float-adjusted market capitalization, SpaceX would receive a 12-basis-point (0.12%) weight in the total market index, falling well outside the top 100 constituents. (As weights adjust and constituents are reshuffled, indexes will experience some turnover, which is quantified in the paper.)
Estimated Impact of Including Mega-IPOs in CRSP US Market Indexes
Source: Alex Poukchanski and Alex Bryan’s analysis based on data from PitchBook, CRSP US Market Indexes, and FinancialPress. Data as of March 31, 2026. Except for SpaceX, valuations are based on PitchBook valuation estimates. Except for SpaceX, offering sizes computed under the assumption of 5% float; SpaceX valuation and offering size based on media reports; estimates of weight and change in top 5 constituents of CRSP US Market Indexes based on March 2026 data.
Morningstar
10. Habits of High Performers
Cognitive Performance Habits (40-52) success.com
Your brain is not built for constant output. It operates in cycles. These habits are about working with your neurology rather than against it.
40. Time-block your deep work in two-hour windows. Research on ultradian rhythms—the brain’s natural 90- to 120-minute focus cycles—suggests that peak cognitive performance happens in distinct windows, followed by dips. Two-hour blocks align with this cycle. Schedule your hardest work in your biological peak hours.
41. Do your most important task before noon. For most people (non-night-owls), prefrontal cortex activity is highest in the first half of the day. Use it on creative, strategic or complex work. Use the afternoon for communication, admin and meetings.
42. Shut off notifications during focus time—completely. Not silenced. Off. A notification doesn’t need to be read to break focus; the awareness that one arrived is enough to fragment attention. Studies consistently support the foundational finding that it takes an average of 23 minutes to return to deep focus after an interruption.
43. Write down your top three priorities before you start each day. Not a full to-do list. Three things. This practice forces prioritization under constraint and sets an intention that survives the reactive pull of the morning.
44. Do a weekly review every Friday afternoon. Block 30 minutes. Review what you completed, what didn’t get done and why, and what your top priorities are for next week. This practice prevents the feeling of being perpetually behind and connects daily work to longer-term goals.
45. Read intentionally for 20 minutes a day. Not scrolling. Not trade newsletters. Books. Long-form reading builds sustained attention, strengthens vocabulary and exposes you to ideas at a depth that short-form content cannot replicate.
46. Avoid multitasking during deep work—completely. Your brain does not actually multitask. It switches between tasks rapidly, and each switch carries a cognitive cost. What feels like efficiency is usually just faster degradation of output quality.
47. Create a “shutdown ritual” to end your workday. Close your tabs, write tomorrow’s top three goals and say a specific phrase that signals the day is done. This ritual—as small as it is—trains your brain to disengage from work mode and makes the transition to personal time more successful.
48. Keep a decision journal. Log important decisions with your reasoning at the time. Review it quarterly. High-performers who track decisions improve their judgment not because they think harder in the moment but because they learn from patterns they would otherwise forget.
49. Batch your email and Slack into two or three windows per day. Constant inbox monitoring is the cognitive equivalent of allowing interruptions every 10 minutes. Set windows—morning, midday, late afternoon—and let the rest wait.
50. Learn something new outside your domain once a week. Cross-domain learning is consistently linked to creative thinking—research shows that knowledge breadth, especially in mid-career, is one of the strongest predictors of creative output. Read something in a field adjacent to yours. Take a course. Attend a talk.
51. Reduce daily decision volume wherever possible. Steve Jobs’ black turtleneck was famously a decision-reduction strategy. You don’t need to go that far. But standardizing low-stakes decisions—meals, clothes, default responses—preserves cognitive resources for decisions that actually matter.
52. Protect your thinking time like it’s revenue-generating. Because it is. Block 30 to 60 minutes of unstructured thinking time on your calendar at least twice a week. No deliverables. No agenda. Just space to process, connect and generate. Most high-performers consider this their most productive time once they build the habit.
2. Annual IPOS 25 Years ….2021 SPAC Frenzy….2026 Running at Average Pace but Big 3 are Difference
Dorsey Wright There have been 152 IPOs already this year, looking at data through the end of May. IPOs are rarely consistent month-to-month, but if we did continue at that pace in the second half of the year, we’d be close to the pace of the 347 IPOs seen in 2025. This puts us in the average to above-average range for historical IPO counts going back through 2000.
Nasdaq Dorsey Wright
3. IPO ETF Breaks to New Highs…50day thru 200Day to Upside
StockCharts
4. 30 Major IPOS-One Year Drawdown
Josh Schafer
5. Tokenization of Stocks Expanding
The Kobeissi Letter
6. Joe Weisenthal List of Reasons for Crypto Winter
Joe Weisenthal
7. IBM Beating XLK Tech ETF
Abnormal Returns
8. Gold Overtakes US Government Bonds as the World’s Top Reserve Asset-FT …Single Biggest Buyer of Gold 2025 Tether
Financial Times
9. Biggest Central Bank Buyers 2025
Perplexity
10. 2 Frustrating Habits of the Most Intelligent People
Why intelligent minds often face misunderstandings from others.-Psychology Today —Mark Travers Ph.D.
Key points
Intelligent people often update beliefs mid-conversation, reflecting cognitive agility.
Higher intelligence tolerates ambiguity and thrives on revising ideas.
Belief updating showcases intelligence, while fence-sitting signals cognitive weakness.
We tend to picture intelligence as exemplary mental organization: crisp opinions, sharp delivery, and confident stances held firmly. The “smart person” in the room isn’t the one who hedges or backtracks. It’s the one who walks in already knowing the answer, delivers it cleanly, and moves on. But that picture, research increasingly suggests, has it backwards.
Highly intelligent people are not always faster, calmer, or more decisive. Sometimes, their minds are busier, slower, and more conflicted. In my work as a psychological researcher, I’ve noticed that people with higher cognitive ability are often misunderstood simply because their mental habits don’t always look the way we expect intelligence to look. Two habits in particular tend to get them misread, and both are far more cognitively sophisticated than they appear.
1. Changing Their Mind Mid-Argument
Few things irritate people more in conversation than someone who contradicts themselves. Someone who states a position with apparent confidence, then stops mid-thought and says, “Actually, I think I was wrong about that.” It reads as wishy-washy, underprepared, or lacking conviction. In a meeting, it can cost someone credibility. In an argument, it looks like surrender.
What it actually reflects, however, is one of the clearest behavioral markers of higher intelligence: belief updating, or the willingness to revise a held position when confronted with new evidence, even when that confrontation happens in real time, in public, at social cost.
A 2024 study published in Cognitive Research: Principles and Implications found consistent evidence that individuals with higher fluid intelligence changed their attitudes more readily in response to correction, while those with lower reasoning ability showed a stronger tendency to persist with misinformation even after receiving a correction message. In other words, the person in the room most willing to say “I was wrong” is often, cognitively speaking, the most capable one there.
This connects to a broader pattern researchers have identified in how intelligent people relate to uncertainty. Research shows that individuals with a lower need for cognitive closure tend to tolerate ambiguity more easily, and separate lines of work suggest that higher cognitive ability is associated with greater openness and cognitive flexibility. Where most people feel pressure to land on a position and hold it, highly intelligent individuals are more comfortable sitting in the revision process, even when that process is visible to others.
The frustrating part for observers is precisely this: the intelligent person doesn’t feel the urgency to perform with certainty before they’re ready. And if the thinking is still happening, they’ll do it out loud.
Consider the colleague who, midway through a strategy meeting, says, “I want to walk back what I said ten minutes ago,” and the room visibly deflates. To everyone else, it signals confusion. To that person’s brain, it signals that something more accurate just became available, and loyalty to the original position would mean ignoring it.
The distinction worth drawing is between belief updating and chronic fence-sitting. Updating is responsive, that is, it moves in reaction to new evidence. Fence-sitting is avoidant, as it moves in reaction to social pressure. One reflects cognitive strength. The other can signal the opposite. But in everyday settings, the two tend to get collapsed into the same frustrated label: unreliable.
2. Giving Too Much Unnecessary Context
Imagine you ask a simple question to someone and receive a five-minute answer that starts three steps before the point. There are caveats, qualifications, historical background, and exceptions to exceptions. The person doesn’t seem to register that you needed a sentence, not a seminar. It can feel patronizing, exhausting, or simply socially tone-deaf.
What you are almost certainly witnessing, however, is a well-documented cognitive phenomenon called the Curse of Knowledge—and it correlates directly with genuine expertise and deeper cognitive ability.
The Curse of Knowledge is a cognitive bias that causes the brain to overestimate how much other people understand. When we master an idea, we lose access to the memory of how it felt not to understand it. This creates a blind spot that makes it difficult to empathize with people who don’t share our background. The deeper the knowledge, the harder it is to locate the entry point for someone who doesn’t share it.
Highly intelligent people have often, entirely unconsciously, built elaborate mental scaffolding around a topic over years of thinking about it. When they try to explain it, they dismantle that scaffolding from the top down, which means they start with all the architecture you don’t yet have, rather than with the ground-floor answer you actually asked for.
When experts develop complex mental models for organizing information, the problem in communication arises because those models aren’t shared—the explanation becomes accurate, thorough and, for the listener, completely impenetrable.
To the person on the receiving end, this registers as a failure of social awareness. But it’s a side effect of too much knowledge, not too little. The highly intelligent person isn’t unable to read the room; they genuinely can’t locate where the room is relative to where their own thinking begins.
Think of the researcher who responds to “what do you work on?” with a ten-minute tour of their entire field. Or the engineer who answers “how does this feature work?” by explaining the underlying architecture from first principles. The intention is almost always generosity: a desire to give you the real answer, the full picture, the thing that actually makes sense of it. The social effect, unfortunately, is often the opposite.
It’s worth noting that the Curse of Knowledge doesn’t excuse poor communication—over time, it’s a skill gap worth closing. But understanding its origin matters. The next time someone overexplains to the point of frustration, the more useful question isn’t “why can’t they read the room?” It’s “how much do they actually know about this?” The answer, often, is more than they can easily compress.
A version of this post also appears on Forbes.com.
3. Retail Investor Optimism on Tech Stocks Near Record Highs
Retail opening options. “Retail optimism in Tech is reaching a near record, with bullish trades making up almost two-thirds of all retail opening options activity in the mega-cap Tech stocks (e.g. buying calls or selling puts to open).”
Even if you’re not applying, this thought experiment gives a glimpse into how the world is about to be rewired.
The top 10 most selective colleges in the US admit about 5% of those who apply. They’re not selling education as much as a label, a rare chance for someone to slot themselves into a category in our economic and cultural hierarchy.
If all the famous schools wanted to do was be elite, they could use a formula–grades plus SAT plus something–and algorithmically draw a line and pick everyone over that line.
But it’s more complicated than that.
First, they want to find some sort of balance, to create a reasonably diverse group of backgrounds that coalesce into a community. They don’t want 100 kids from the same high school…
Second, they have special cases, many of which they don’t want to talk about in public, involving alumni, outgroup dominance considerations, and sports, which in many cases can count for as much as 50% of the incoming body.
Third, they use variable pricing, with many students ultimately paying different tuition. Few can afford to be fully need-blind in selection.
The end result is complicated, onerous and mostly a charade. 50,000 applicants coming into each institution cannot possibly be reviewed coherently or consistently. And uncertainty takes a toll, not just on the students, but the schools and their teams as well.
It’s expensive and time-consuming, and fraught with worry. The typical fancy college applicant applies to nearly ten schools. Some kids get into a few schools, some to none at all. And essays in the age of AI are now officially meaningless.
[I’ve written earlier that they should have two sorts of rejection letters. Half the people should get one saying that they simply didn’t get in. The other half should receive a letter saying that they were good enough to get in, but didn’t get lucky.]
This is what you’d invent if it were 1952.
If we rethink it, it might be more like this:
Each applicant ranks the schools they apply to. That’s a forced ranking, and binding.
The application is online and interactive. It shifts in real time based on the answers applicants give. I’d prefer we get rid of standardized testing, but I’d imagine some sort of asynchronous vetted skills testing can be referred to by the applicant.
Sit down at 10 am on the day of your choosing, and all your applications will be done by 3 pm. Chaperones, video, and real-time snippets make it likely that the real applicant actually is the one engaging with the application.
It’s easy to imagine that this is simply a digital form of the existing application, but it’s not. It works with the student, finding their strengths, asking follow-up questions, presenting them in the best light for their skill set. Get some math questions right and it will ask you some more. Talk about your work at the Fuller Center and it will dive deeper. It’s not adversarial; instead, it’s a scout and a coach.
Even better, it’s not just one session–it’s a series of conversations, over time. And as a coach, the process can advise the student on their forced rankings, helping them reconsider preferences based on their interactions.
The schools have to be very clear to the system about the balances they seek, the trade-offs they’re making and what’s important to them. This won’t be easy at first, because naming it is uncomfortable. In fact, this is the hardest part of the transition.
[Hard indeed: Lawsuits will be an inevitable outcome. Discovery in the SFFA case against Harvard put the previously unrevealed rules into the record—the admission rates by legacy status and athletic skill. Naming the trade-off is what turns it into a lawsuit.]
Then, on selection day, the AI system, which has read every single application, applies game theory and ranking to create the best possible allocation of seats, aid and students. The Gale-Shapley stable-matching algorithm is already used in medical residency placement. It leads to its own game theory implications, of course.
This shift saves money, reduces anxiety, is probably more fair. It’s auditable and improvable and uses far less time as well. It used to be impossible. Now that it’s not just possible but easy, the pressure falls on the constituents who’d prefer to avoid it.
Is it better to believe that you got into a famous college because of a mysterious, perhaps human, definitely flawed, and easily gamed system, or would we prefer a different sort of black box, one that puts data to work in a coordinated and prioritized way?
Systems change is difficult and unpredictable, and I’m not holding my breath. Just imagine, though, how many processes we live with now that will be rebuilt on top of widespread coordination.
What’s been the best hedge against inflation over the past 50 years? (Podcast Discussion)
@Charlie Bilello
2. Rising Gas Prices Historically Non-Event for Stocks
Rising gas prices are painful for households but a non-event for stock market investors.
The Iran conflict has pushed prices at the pump to the highest in four years and consumer sentiment to a record low, yet a ProCap Insights analysis of historical data suggests these bearish metrics have zero impact on S&P 500 returns.
Digging through 537 non-recession months of data since 1976, forward returns for stocks had almost no correlation to gas prices.
The ProCap report found that the top decile of real gas readings produced an average 12-month forward return of 11.2%, statistically indistinguishable from the typical return of 11.4% across all years.
Five of the six gas-spike episodes since 1979 left the S&P 500 flat or higher over the next year.
The one clear exception was 2007-08 — a 23.5% drawdown that credit spreads and the yield curve had already flagged before equities broke.
Gas has climbed 53% since the war began February 28, lifting the AAA national average to $4.56 a gallon.
Meanwhile, the University of Michigan’s consumer sentiment index fell to 44.8 in May, the lowest ever, with nearly 40% of respondents volunteering gas prices as the reason.
Opening Bell Daily
3. Q2 2026 Highest Increase in Earnings Estimates Since 2021
Q2 EPS revisions. “In a typical quarter, analysts usually reduce earnings estimates during the first two months of a quarter … The second quarter marks the largest increase in the bottom-up EPS estimate during the first two months of a quarter since Q3 2021 (+3.8%).”
John Butters – FactSet
4. May Gains Over 5% Historically Bullish for Stocks
History says to take that seriously. When May gains more than 5%, the S&P 500 has never been lower one year later. That stat has held every single time since 1950, with an average return of nearly 20% in the following 12 months.
Ryan Detrick
5. Taiwan Chip Business Using 25% of Electricity on the Island
The chip boom is becoming so dominant that the semiconductor sector now consumes roughly 25% of all electricity on the island.
ZeroHedge
6. Leveraged Single Stock ETFs $65B Inflows
Barchart
7. Space ETFs 5x Increase in AUM Going into Space X IPO
Bloomberg
8. U.S. Military Is Quietly Guiding Ships Through the Strait of Hormuz
U.S. Central Command has helped around 70 commercial ships pass through the strait in the last three weeks, an official said.
Vessels waiting to pass through the Strait of Hormuz. Before the U.S.-Israeli attacks on Iran, well over 100 commercial ships a day passed through the strait.Credit…Reuters
American forces in recent weeks have helped coordinate the passage of dozens of commercial vessels through the Strait of Hormuz, according to U.S. officials, even as travel through the waterway remains risky amid stalled negotiations to end the war with Iran.
U.S. Central Command has guided around 70 commercial ships through the strait, traveling into and out of the Persian Gulf, in the last three weeks, one of the officials said, speaking on condition of anonymity to discuss operational matters. The U.S. officials added that most of the vessels had turned off their transponders to avoid detection when going through the narrow waterway.
The officials declined to say what type of vessels were going through and what route they took, but one official indicated that at least one route was not close to the Iranian coastline. Ships passing near Iran without obtaining Iranian approval face the threat of an almost-certain attack by Iranian drones or missiles, U.S. officials said. Shipping analysts say the U.S.-guided crossings appear to follow routes that are closer to Oman.
Most people give soft feedback because they care more about how the conversation feels than about whether the problem gets solved. This is selfish.
Another thought on this… A lot of people don’t actually want direct feedback; they prefer something softer. When they hear direct feedback, they focus on how it makes them feel and not the substance. If you’re focusing on how feedback makes you feel and not its accuracy, you’re robbing yourself of the opportunity to get better.
Exceptional results happen when people are willing to give direct feedback and to hear it.
Commentator Ezra Klein on reading:
“Part of what is happening when you spend 7 hours reading a book, is you spend 7 hours with your mind on the topics in the book, grappling with them, drawing connections, having thoughts you would not otherwise have had. And so without that process of grappling, without those hours inside that book, it doesn’t get inside you. It doesn’t impress itself upon you. It doesn’t change you. What reading and writing and processing information is supposed to do is change you.”
This is fascinating to think about through the lens of AI. You can get the answer without much effort, but you can’t get the understanding.
