Matt Levine, who probably knows more about finance than anyone on this site, has said the same thing. He’s also talked about all the hate mail he gets. Large market etfs like VTI or VOO are supposed to track the market. It would be weird if they ignored trillion+ market cap companies. If the market decides to dump these companies then they’ll fall out of the index.
Index criteria have also changed many times over the years, and they are changing again to deal with later stage companies coming to the market with already huge valuations.
I completely agree. People have parroted the benefits of passive investing and blindly following the benchmark index for decades, yet the instant some overpriced turds (Anthropic, OpenAI, and SpaceX) are considered being adding to the benchmark, they backtrack and fight tooth and nail against including them.
All three companies are large enough by market cap ($1T+) to qualify for the S&P 500 benchmark, which claims to track the top 500 largest U.S. large-cap equities.
They have a point (not wanting to invest in overpriced equities), but if you don't like the companies that surface through passive investing then don't be a passive investor. It sounds like these people want active investing instead. If that's your position, just buy actively invested funds, not ruin the benchmark for everyone.
S&P is caught in a bind, because if they add these companies to the index, it would aggravate millions of passive investors.
While there's some truth in your point, I think you're being unfair in framing this story as passive investors betraying their own philosophy because they suddenly realize this passivity would cause some "overpriced turds" to be included in their portfolio.
Passive investors did not "backtrack", on the contrary their preference on this matter is that index rules should remain unchanged. Conversely, it seems fully consistent for a passive investor to criticize Nasdaq-100 for actively amending their rules to achieve a specific result.
So I find it rather unfair to conclude that "these people want active investing instead". As far as I know, these people are reacting to "active" decisions (such as Nasdaq-100's) and cheering actual passivity (such as S&P500's decision).
Now, one can argue that there are good and legitimate arguments for the inclusion rules to evolve, but by definition amending the rules is an active decision.
I don't care about being forced to own SpaceX if it's in the index, I do care about it being forced into the index before it's had a chance to settle, so that private investors can dump on me.
But that wasn't going to happen with the S&P 500, the proposal was to reduce inclusion time from 12 months to 6 months, and this did not pass. 6 months is more than enough time for price discovery to occur.
And even if it was added to the index immediately after IPO, index weighting in S&P is float weighted, SpaceX at IPO will have minimal float, and SpaceX would be ~0.125% of the index at IPO. Not much to matter.
That ".125% is not much to matter" argument also cuts the other way, against the Matt Levine argument that the S&P is excluding trillion dollar companies and should adjust the rules for them.
Should S&P really adjust the rules for such a small portion of the index?
Market pricing will be interesting. People have been complaining about TLSA being over priced for years and now it's 2%+ of the S&P. Are people selling VOO and VTI because of the TSLA allocation? Nope, in fact TSLA has made them all a lot of money.
People were falling over themselves to invest in these AI companies and SpaceX not that long ago. 75B worth of SpaceX now has to get sold to IPO investors to hit the desired valuation. People say a lot (especially on the internet), but when the rubber meets the road we'll see what people do with their money.
The other bind the S&P is caught in is if these AI stocks IPO and then moonshot before they get added. The question will then be is the S&P an antiquated index? How do multiple trillion dollar companies in the market not end up in the S&P 500 sooner? No one thinks of that case because everyone is so sure they are all going to zero.
I'm having a difficult time imagining how an admissions event in 2021 materializes in the spring semester of 2026 in a class largely taken by first-year students.
In addition to overreliance on AI, Garcia also pointed out that many students are underprepared mathematically, a concern echoed by campus associate teaching professor Gireeja Ranade.
From the article discussed the other week:
Over three years — from fall 2021 to fall 2023 — the letter said, at least 20% of Berkeley first-semester calculus students who took a diagnostic exam showed deficits. “Basic mathematical fluency is analogous to literacy; without it, success in university-level STEM becomes structurally unattainable for students,” faculty wrote.
It's been steadily getting worse. The current article only looks at F's which conveniently hides if there has been a slope down. Additionally, kids entering HS in 2021/2022 would just now be hitting college.
A sudden materialization is what's depicted by the data.
> It's been steadily getting worse.
I don't believe this is accurate. Failing grades are what the observation entails, and the data clearly depict an abrupt change; not a gradual one.
In the section titled "Failing grades in 3 CS classes skyrocket in spring 2026
", there's a clear jump in failing grades for all cited courses between 2025 and 2026. Failing grades for every course jump by multiples of the previous year.
The jump is very likely due to AI usage and lack of skills in mathematics. It seems like prerequisite classes are not being fulfilled.
"Ranade said students are expected to enter the course having taken classes on linear algebra, vector calculus and mathematical proofs. However, she found out in office hours that many students struggled with linear algebra, and was even more shocked when one student told her the linear algebra class they took at UC Berkeley had an “open-internet, open-AI policy” for homework and exams."
Also, this professor doesn't grade on curves? Could be very specific to this teacher. I don't know. Would be great to have more data but it is a big jump and could be very specific to this professor or perhaps this class.
"Also, this professor doesn't grade on curves? Could be very specific to this teacher. I don't know." Someone has to hold standards up -- they seem to be falling down across the board in education.
Actually, when I read they usually graded on a curve, I lost all interest. I don't respect teachers that grade on curves.
You should be graded by how well you know the material - not how well your peers don't know it. I'm always grateful both my undergrad and grad professors didn't curve on a grade.
In my first company, I had 4 different jobs. It was a common adage: Go into a low performing team that does simple work and you'll get promotions much quicker than in a high performing team doing challenging (but fun) work.
It was right. I had 2 "dream" jobs where I did cool, challenging stuff, but where everyone was more than competent. They turned out to be career killers. The promotions I got were all in the other 2 jobs where I did boring business logic coding, and where my peers were barely competent (one had trouble navigating directories using the command line).
That's what happens when you grade on a curve. Smart people begin to work on boring stuff, and not the real challenges.
For failing grades sure, there must be some sort of minimum competence. For sorting out >= B/3.0 grades, a curb can work since you are getting evaluated against your peers to see he is standing out vs just doing acceptable.
If you wanted to grade purely off a curve, you would be stuck with old test problems that were thoroughly vetted and calibrated, an impossible task for smaller classes where the material changes rapidly.
> For sorting out >= B/3.0 grades, a curb can work since you are getting evaluated against your peers to see he is standing out vs just doing acceptable.
I'm still not getting it. For a standard course, the criteria for what is "good" vs "great" should be pretty clear, and it should be independent of your peers. You have a syllabus, and a set of abilities for each grade level. If you hit those targets, you get the grade. If half the class gets an A, then it means they're pretty smart, or you did a great job in teaching. Of course, there's the chance the class was too easy, but you can always fix that.
No, I don't see why you're stuck with old test problems. For standard engineering classes, there's a huge (almost infinite) set of problems one can create.
For smaller classes, grading on a curve is even sillier, as the variance is always higher when the population size is small. For example, a lot of my small classes consisted of highly motivated students (all "A material"), because they're usually obscure electives where the content is challenging. You then pointlessly penalize students who sign up (just like they do at work). In fact, my professors were usually much more lenient on small classes for this very reason (i.e. lowering the standard needed to get an A).
I once took an Intro to Analysis course. It was moderately challenging. I got the highest score in the class, and my grade was A-. Everyone else got B+, B, or lower. A friend of mine (who didn't take the course) got really upset that I didn't get an A (or A+) given that I was the top scoring student.
But I knew my level of understanding/performance. It wasn't that great. I felt even an A- was too high a grade for me. And the teacher did a pretty good job in teaching. Why should I get a higher grade just because the other students were worse?
> For a standard course, the criteria for what is "good" vs "great" should be pretty clear, and it should be independent of your peers.
Do you think upper division college classes are somehow like high school classes with well developed curriculum and teaching professors who teach the same thing every quarter? Now you expect the professor to not only come up with new test material, but also extensively calibrate it before students take it, maybe for a 15-hour per week class (3 hours of teaching + 12 hours of studying), with maybe 15 students? Well, thank God we have AI for these kinds of things now.
Ok, let's exclude upper devision classes and just focus on lower division courses (since you mentioned an Intro to Analysis course). Here you have a relatively better chance of a well understood enough curriculum and testing material to actually not grade on a curve. BUT these are also usually weed out classes, with the idea that they only have N spots for students to proceed on to the upper division course, so curving serves an actual purpose that is aligned with the intended result.
> Do you think upper division college classes are somehow like high school classes with well developed curriculum and teaching professors who teach the same thing every quarter?
I repeatedly said "standard course", which implies it is a commonly taught course (be it upper or lower division). In my undergrad, Analysis I, II and Abstract Algebra I, II were upper division courses. In the engineering departments, stuff like Electromagnetics I, II were upper division.
Anything that is not an elective (and even some popular electives) were standard courses.
Now I'll grant that in CS, some material like machine learning changes rapidly. But in most engineering, very little in the undergrad material changes. Even my semiconductor courses in undergrad haven't changed much in decades.
So yes - for most of those classes (and that means the vast majority of undergrad engineering) classes, the curriculum is relatively standard.
> Now you expect the professor to not only come up with new test material, but also extensively calibrate it before students take it, maybe for a 15-hour per week class (3 hours of teaching + 12 hours of studying), with maybe 15 students?
First: In my very average undergrad university, professors were always careful not to reuse old homeworks/exams. It wasn't a huge burden. Professors who don't do this (e.g. most professors in top universities) signal very clearly their lack of interest in pedagogy.
Second: You want to do a curve on <= 15 students? Are you aware of basic statistics and the problems you get with small N? Are they using a normal distribution or one that is more appropriate for small N?
And as I already said, for a lot of electives where the material isn't standardized, professors lean towards lenient grading. They offer those classes because they want people to take it, and grading via a curve discourages it.
> since you mentioned an Intro to Analysis course
That was an upper division course. Yes, I know some universities have it as a lower division, but many (most in the US?) treat it as upper division.
> BUT these are also usually weed out classes, with the idea that they only have N spots for students to proceed on to the upper division course, so curving serves an actual purpose that is aligned with the intended result.
It was not a weed out course. Neither my undergrad nor grad math departments had weed out classes. I saw that concept only in the engineering departments. My EE department had only Circuits I, Circuits II and digital logic as "lower division". Circuits II was the weed out course, and you were not allowed to take anything else (e.g. E&M, Electronics, etc) unless you got a B or higher.
SAT/ACT math is incredibly simplistic and at worst maybe contributed by not filtering as many out. Math scores have been declining nation wide for decades now, that’s been a big issue for a while.
One big reason is preparation, people start preparing for tests 2 to 3 years in advance. And the method of testing influences exams used in grades before as well.
So assume 4 years of high school and someone that just came in. They are still preparing for SAT like tests in their first year of high school. Someone in final year of high school is well trained in it. So even though the benefits do not carry, enough portion of incoming students are still reaping benefits of standardized tests. The decay only shows later when batches without any benefits of standardized tests are coming through.
> people start preparing for tests 2 to 3 years in advance
Pardon? Is that a normal thing in the USA? I don't think I've ever started preparing for a test more than a week and a half ahead, a month if you count graduation exams. Not sure they ever determined more than a year in advance (more commonly: a bit less than a semester) what tests we'd be given in the first place
> They are still preparing for SAT like tests in their first year of high school.
Literally nobody does that except high achievers whose parents are pushing them for a high SAT score to get into Stanford or whatnot. Those are not likely to be the kids who are now getting Fs.
That's not what this actual data shows. While there has been an increase math deficiency, the increase in failure rates happened recently and probably only partially related to the math preparation issue.
I think we will make a major mistake if we think math preparation fixes this - especially in CS classes where AI literally calls out to be used for projects. And it certainly doesn't explain me hearing the same problems are happening at MIT -- they just are being a bit wiser about "catching students" (or rather not doing so).
> Most people definitely can't meditate for 30 minutes, so if you can do this, it's very impressive.
Maybe not traditional meditation, but I have no problem taking a 30 minute plus walk with nothing but my thoughts. It’s actually when I do most of my thinking. The other is in the shower/sauna where devices don’t work anyway.
Also given how the S&P weights, it'll have about as much sway as DoorDash.
Annoying they pushed it into the indexes, but like you said, we've also never had a company come out in the 1T range or even the x00B range. These indexes are supposed to represent the market and can't ignore a 1T market cap company for very long.
EDIT
One other thing to add, is that we still do not know what the stock will price at. It's already come down once, and as more information comes out it can continue to come down until it's finally priced the day before the first trading day.
You shouldn't be downvoted because your point is completely valid. Matt Levine made the same point in the last Money Stuff podcast. These indexes are supposed to contain the largest, most significant, and in some cases all companies so people shouldn't be mad at the indexes for pulling in a company that's going to have a 1.5T market cap at IPO. Given the market cap, it would actually be weird to not have it in an index like the S&P500 or QQQ.
Instead blame the bankers and market who are putting buying in at 1.5T valuation.
If people really don't want SpaceX in their S&P 500 tracking ETF, we should see a S&P-ex SpaceX in short order.
> The whole point of original rule was to have market discover price over time before adding a company.
IPOs and indexes were not really built to handle companies that stay private as long as we are now seeing. SpaceX is trading at crazy levels in the private market right now. Even if it prices down to something ~1T, it would be silly for an index that is a total market or the biggest 500 companies to ignore it. With that said, it'll be float weighted and have about as much impact on the s&p 500 as something like DoorDash.
>>If people really don't want SpaceX in their S&P 500 tracking ETF, we should see a S&P-ex SpaceX in short order.
"People" don't know much about finance to put it mildly.
ETFs are created by market demand. Even "factors" ETFs are often based on completely irrational things like dividends, P/E ratios and other meaningless metrics. This happens because people are easily seduced by narratives ("solid dividend paying stocks", "low P/E ratio - good returns") which are plainly wrong but tempting to an average person.
Most people realized they don't know anything about finance and would like to pay someone (their fund manager) to make responsible decisions and expose them to wide market while avoiding blatant manipulations. Unfortunately the incentives are misaligned here. The managers' incentives are somewhere else. They are not paid by long term performance of their fund and they are disproportionally penalized for taking contrarian decisions.
People being force feed those mega IPOs losing money on them is bad for others as well - there will be less wealth for productive investments and more in hands of "players" (or scammers if you want to call it out). There might be a crash. Trust in financial market will plummet and hostile regulation might arise which other market participants will pay for even though they are not to blame.
I will not have exposure to those mega IPOs but I am in privileged position because:
-My understanding of financial markets is much better than that of an average person.
-I have quite a bit of time to follow all of it and react in time
-I pay 0% capital gain tax and use a broker with nearly 0 fees which allows me to rotate for free (almost)
-I know where and how to move my money so I don't lose advantages of wide market exposure
It took me a lot of effort to set it all up like that. An average person falls short on all of the above and is not in position to avoid donating part of their pension fund to Musk and Altman though. It is still bad for me for reasons mentioned above.
What's really clever is that Musk could pull his Nazi salute at the inauguration of the president he bought, and the ensuing 'voting with your dollars' against him doesn't matter because he was able to orchestrate forcing people to pay him by cutting them out of the loop. I mean it's absolutely evil, but it's pretty clever - his team proved they can't run a country (they probably could, but don't want to), but they're incredibly adept at stealing.
I wonder if Musk chose rocketry solely because of the ability to use it to drain money from government?
> Years of experience don’t correlate to output in all careers.
YoE only gives potential, but are not necessarily sufficient in any career. I've interviewed engineers who learned the narrow job they were doing in 6 months, and then only did that for a few years. Do they have 6 months of experience or 3 years? I'd argue closer to 6 months unless they were doing more. I imagine surgeons are similar, where I'd rather see X number of successful surgeries performed than YoE.
This issue with YoE is also why I'm bothered when HR uses YoE too heavily to base salaries around.
Another thing I tell people is if you can't be replaced, you can't be promoted. Many people do a job well and make themselves too critical in a certain position thinking it will make their job more secure. First, the way layoffs typically work, they are likely not more secure. And second, it makes promotions much harder.
I wouldn't say hardly noticeable especially for experienced lifters. After training for a few years those extra reps and slightly more weight have compounding effects over time.
Index criteria have also changed many times over the years, and they are changing again to deal with later stage companies coming to the market with already huge valuations.
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