Episode summary
Half the S&P Is One AI Trade. This Isn’t 1999. What If the Bubble Is in the Safe Stocks?
Excess Returns
· · 48 min · Hosts: Jack Forehand, Matt Zeigler · Guests: Jay Hatfield, Kai Wu, Ted Mortonson, Daniel Crosby
Summary
The discussion argues that the market’s gains can be explained by two separate forces: valuation multiples and earnings. Jay Hatfield says his S&P 500 target was right even though his rate and multiple assumptions were wrong, because earnings estimates moved up enough to offset the hit from higher rates. He also argues that if war and higher rates ease, the market could have room for a strong year as multiples and earnings both expand.
Kai Wu’s segment shifts the focus from headlines to hidden exposure inside the S&P 500. He argues that the index is far more concentrated in the AI buildout than most investors realize, with roughly half of the benchmark tied directly to AI infrastructure when you combine the major platform companies, semiconductors, and related hardware. He presents that as a warning that many “diversified” investors are effectively making one crowded trade.
The episode also pushes back on a simple 1999 comparison. Ted Mortonson says today’s AI cycle is more powerful than the dot-com era because it is already affecting every industry and forcing companies to adapt. Daniel Crosby closes the loop on behavior, showing how a fund can deliver strong returns on paper while the average investor still loses money by buying and selling at the wrong times.
Key takeaways
- Jay Hatfield argues that earnings growth can offset multiple compression, which is why the S&P can rise even when rates and headlines look hostile.
- Kai Wu says about 50% of the S&P 500 is effectively tied to the AI trade once you aggregate big tech, semis, and related infrastructure exposure.
- Ted Mortonson argues the current AI cycle is more powerful than 2000 because it is already changing margins, operations, and national competitiveness across industries.
- Daniel Crosby says a fund can earn about 18.5% annually while its average investor loses money if investors cannot stay with the strategy.
- The hosts argue the key investment question is not just whether a stock call is right, but whether the return can be captured through investor behavior.
Notable quotes
“So the numbers were 23 time 27 earnings which is 23 times 350 that's roughly 8,000”
“we've kind of stored to the extent it does end, which is unclear, but if it does, at some point it seems like it would have to, then we've stored up returns in the stock market”
“when you do all the math it turns out that about 49% let's call it 50% of the S&P is directly tied to this trade, right”
“This is totally different from 2000. In 2000 we were valuing companies off of eyeballs”
“there was one focused equity fund that did 18 a.5% a year over this 10-year clip”
How the episode opens
Welcome to the Exis Returns weekly rap. I'm Jack Forehand and I'm joined by a man after the YouTube's algorithms uh reaction to our last podcast. Will not be using anything beginning with can and ending ending with ism uh in this in this podcast. So any words? Those are all off the table now, man.
Off the table. I will say nothing to the likes. Thank you for the warning YouTube algorithm. I see you. And uh Amazon Prime did have the movie I was referencing for the record. — Amazon has it. It's there. It's glorious. It's not too late. Said word, the musical.
As you know, the the YouTube be a little bit dicey. I'm actually gonna bring in my first pop culture reference ever. Um, and as you can imagine, it's going to be the most obvious pop culture reference of all time because radio head radio heads in the basement.
No, it's actually going to be uh so like the YouTube algorithm is very similar to I was just watching Seinfeld the other day. He did a thing where he had to pick his favorite five episodes of all time. Like it was an interview that was on Twitter.
Um, and as you can imagine, one of the ones he picked is a soup Nazi. uh which you I would say most people would pick as one of the best. But uh the YouTube algorithm is very similar to the soup not see anyways.
It's like if you don't do exactly what it wants, it's like no views for you basically. It's like this this word this negative word that could be associated with this is in there and no views for you. Like this is not a negative macro strategist who like thinks the market's going down.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- ai exposure in indices
- earnings growth vs valuation multiples
- dot-com vs ai buildout
- fund returns vs investor behavior
- factor exposure and diversification
Companies and tickers mentioned
- ARK Invest
Watch the episode
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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Excess Returns, this episode and its artwork belong to Excess Returns. Octagon is not affiliated with the show; this page is an independent summary.
