Transcription
The US economy will grow a bit more than 2% in 2026. So just about half of the US economic growth this year is from AI when 50% of the S&P 500 is tech and tech-related. Owning the index does not provide diversification. It's all one trade. It's all AI. So AI better succeed and succeed big because if it fails or takes a lot longer to become profitable, the US is going into a recession and the market is going straight down.
So let's get started. Hi, this is Steve Eisman and this is another edition of the weekly rap. This is for the week ending Friday, July 10, but recorded Thursday night, July 9. We were off last week, so I have a few things to catch up on. But before we get to the rap, I would like to remind everyone about our exciting move to Substack for all premium content. If you have been on the fence or considering joining us there, I would encourage you to sign up as a free subscriber, while you will receive emails sent directly to you every time we release a new premium episode, which also includes sneak peek previews of both the video and newsletter. Go to the link in the description, and let me flag some things that are on our premium subscription service. We released my personal portfolio on July 1st. And on July 8th, we released a deep dive with Kathleen Kelly and Nancy from Queen Anne's Gate into energy, oil, and gold. Kathleen discusses the pending UAE pipeline, which will open in 2027 and makes the Strait of Hormuz much less important for the oil trade. On July 15th, we will release a biotech deep dive with Boris Peaker from Jones Trading.
On this wrap, we will discuss:
One, Iran war news.
Two, Circle and stable coins.
Three, Nike stock stays flat after a disappointing conference call.
Four, GDP growth and its dependence on AI.
Five, diversification no longer really exists. The stock and bond market are making one trade, AI.
Six, AI arguments and why we need to really understand the thesis in order to measure the risks of the AI trade that dominates most investment instruments.
Seven, lessons learned during the lead-up to the GFC shed light on the structure of the arguments surrounding the AI trade.
And then two mailbags.
So let's get started.
In Iran war news, Iranian attacks on ships in the Strait of Hormuz as well as 85 attacks on US sites in Bahrain and Kuwait led to retaliatory attacks by the US. The region looks increasingly fragile.
On Tuesday, June 30th, there was some very negative news for Circle, the stable coin company that went public last June. Circle creates stable coins, a financial product that is trying to make inroads into the traditional payment systems. Circle is the second largest creator of stable coins. Tether is the largest. Circle was down 17.5% that day because a consortium of companies including Stripe, Visa, Mastercard, Coinbase, and BlackRock unveiled their own stable coin and stable coin ecosystem. The importance of having Visa and Mastercard as part of this consortium cannot be overstated. For a deeper dive, take a look at our episode on January 26, 2026 with Ken Sahauski, the payments analyst at Autonomous Research.
Nike reported their quarter after the close on Tuesday, June 30th. Now, Nike is a perpetual turnaround story, and frankly, I think these results won't move the needle one bit. On the positive side, the company reported adjusted EPS of 20 cents versus 14 cents last year and versus 13 cents expected. So, a nice beat. Revenue was $10.97 billion. Also a beat above expectations. However, despite the revenue beat, Nike revenue was down 1% versus last year. So, the numbers aren't terrible, but they certainly don't tell a turnaround story. The company also sounded very cautious on the call. As management spoke cautiously, the stock proceeded to go down after hours.
Next week, earnings season begins with the banks, as usual, reporting first. Because this week is kind of a holiday week without a great deal of news, I'm taking the time to review some things about AI and its impact on the economy and the markets and where the risks lie.
With respect to the economy, the impact of AI is massive. On July 13, we will post a free interview with Torsten Sløck, chief economist of Apollo. I'm just going to flag one part of that. First of all, we have an AI spending boom because of the data centers and the energy associated with the data centers. We calculate that that contributes at the moment about 1 percentage point to GDP growth. Normally GDP grows at two and now 1% is coming from the AI spending boom alone. According to Torsten, the US economy will grow a bit more than 2% in 2026. AI spending and capex will constitute 100 basis points of that 2%. So half of the 2% increase. 30 basis points is from reshoring, meaning bringing the supply chain back to the United States as well as other infrastructure expenditures. and a roughly 90 basis points is from tax refunds given as part of President Trump's quote "big beautiful bill" unquote. So just about half of the US economic growth this year is from AI and the other half is a result of recent economic policy.
The impact on the markets I believe is even bigger than the statistical impact on the economy. This is such an important point so I will repeat it. The impact of AI on markets is simply bigger than its pure economic impact. Why? InfoTech constitutes 38% of the S&P 500. If you add Google and Amazon and other tech-related names, you get to 50% plus. Now, most investors these days are index investors, and that used to mean some pretty decent diversification. But not today. When 50% of the S&P 500 is tech and tech-related. Owning the index does not provide diversification. Now, someone might say, "Hey, I'm diversified because I have 60% of my money in equities and 40% in bonds." So, okay, maybe my 60% is not as diversified as I once thought, but I own bonds. And there you would be wrong. 15% of all corporate existing debt is AI-related. And 50% of all newly originated corporate debt in 2026 is AI-related. So a 60/40 equity bond strategy in my view does not create real diversification. It's all one trade. It's all AI. So AI better succeed and succeed big because if it fails or takes a lot longer to become profitable, the US is going into a recession and the market is going straight down.
That's why it's important to review the arguments for and against AI. Arguments that have evolved considerably over the last several months. What do I mean by that? To explain, let me take a brief detour. Arguments and ideas don't spring out fully formed. They evolve. They take time to develop as new facts emerge. Believe me when I tell you that I did not have a sudden revelation in 2006 that the subprime mortgage market was going to implode and that implosion would cause a massive financial crisis. Not at all. In the spring of 2006, all I thought, all I knew was that I had heard anecdotally that mortgage lending standards had deteriorated enormously. But it wasn't until the summer of 2006 that I saw that loans securitized in 2006 were becoming delinquent at a rapid pace. That's when I knew something was really wrong. But my team and I kept doing research and did not pull the trigger on shorting subprime paper until October of 2006. And we kept shorting it until July of 2007. I did not really know that Wall Street had any balance sheet exposure to subprime mortgages until a friend told me about an internal subprime mortgage hedge fund at Morgan Stanley. I learned that piece of information in May of 2007. From there, my team and I went on a research mission to see how much exposure Wall Street firms had to subprime paper. It was a bit of a treasure hunt. It took at least a year to figure it out, and even then, we did not uncover everything. The point of this story is that arguments and ideas develop over time.
Now, let's apply this concept to the AI debate. If we were having this discussion last summer, there would barely be a debate. On the bullish side, you had mega companies like Amazon, Google, Meta, and Oracle all racing to buy Nvidia chips and related AI equipment because AI was going to change the world. And who could argue with them? These are not internet startup companies circa 1999. These are among the biggest and most admired tech companies in the world and they were all pulling in the same direction. So, how could they be wrong? There were a few lone negative voices like Gary Marcus, but it was unclear exactly what they were arguing. Gary pointed out that AI keeps hallucinating and AI could never achieve artificial general intelligence. But even if he was right about AGI, that did not necessarily mean that AI was useless. It could be very useful. And that was the status of the arguments through most of last year.
The first crack in the AI bull case showed up late last year. Oracle reported third-quarter numbers in October and showed a massive increase in backlog. The stock went from 230 to 330 in a few days. But then analysts figured out that 50% of that backlog was solely from OpenAI and that made the market nervous and the stock corrected to below where it was when it reported. Today, Oracle is even lower at 140. But that's just Oracle. The next crack in the argument showed up when the tech companies reported fourth-quarter numbers. Nvidia, of course, reported 70% revenue growth. So clearly, the AI capex story was not slowing. What got people to start to freak out was the capex budgets for 2026. Take Google as an example. In 2025, Google spent $90 billion on AI capex. When it reported fourth-quarter numbers, it guided 2026 AI capex to $180 billion. Wow. Meta guided to $135 billion and Amazon guided to $200+ billion. These numbers started to scare people. But what really freaked them out was that in June, Google raised $85 billion in equity capital. Oracle raised capital and there are rumors that Microsoft and Meta will follow. Why is this important? Historically, these are companies that don't ever raise capital. They generate so much cash that they have trouble figuring out what to do with it all. Now, all of a sudden, the hyperscalers have transitioned from no need for capital to massive need. The business has become highly capital-intensive.
Now, capital intensity would not be so bad if the end result was highly profitable businesses, but there seems to be several problems. Lack of moats, users are becoming less than thrilled with token price increases and the bizarre question of whether there is oversupply of capacity like Meta announced or undersupply which is driving data center hysteria. As to moats, one day Anthropic is on top and the next day it's Gemini and the next day it's someone else. Spending trillions on a business that has no moats is a recipe for a price war, not for high levels of returns on massive investments on capex. And it looks like companies are starting to experiment with Chinese AI because it's much cheaper. Maybe a full-blown price war is somewhere down the road.
Now we get to the issue of pricing. The cost of AI is measured in tokens, which is roughly equivalent to a word. Until this year, AI companies were charging subscriptions that did not come close to covering the cost of the tokens. In other words, usage was heavily subsidized in order to get customers hooked. With subsidized pricing, corporations went all-in. Some corporate users of AI actually measured employee performance by quantity of usage. Employees were heavily criticized for not using enough AI. With this fiscal approach and decreasing subsidies of token pricing, annual corporate budgets were blown within a few months. The word is that customers are reversing the "all you can eat" AI buffet for employees and limiting their AI usage.
So that's the status of the arguments as of today. On the bullish side, AI capex continues to grow, but the combination of capital intensity and no moats has made investing in the hyperscalers less compelling, at least for now. Investors have migrated from the hyperscalers to semiconductor and semiconductor equipment companies and AI power-related stories. The hyperscalers will have to prove that all this AI spending will generate high returns and they will be able to build big moats around their AI. This story is far from over, but even semiconductors are beginning to show signs of worry. Samsung reported this week an operating profit was up a massive 1,800%. But the stock went down 7% as investors fear that hyperscalar AI growth will slow, thereby hurting semi-pricing. By the way, semi-pricing continues to go up, but investors are starting to worry.
We have two mailbags this week. The first question is from Battel, who is a premium subscriber on the pod. And the question is, quote, "Great episode. Your explanations are always so clear." You're welcome. How does this portfolio of stocks, my portfolio, fit into your overall investment portfolio? Can you share rough percentages of other asset classes like bonds, commodities, metals, and real estate investments? Do you hedge it all? My investment portfolio is actually quite simple, and I disclosed it as I mentioned earlier on an episode on the premium. The 16 stocks that I own are my entire long portfolio because I have lightened up of late. My other major asset class is cash, which I mostly have in a money market fund. I do own a home, but I don't think of it at all as an investment. When and if I sell it, I'll be happy to just get my money out. I don't think that residential real estate is a great investment any longer. I don't own any bonds or precious metals or gold. I'm a stock jockey. My hedges are in my shorts, some of which I will share one day. I plan to do an episode soon with Lakshmi Gopalan of Unicus Research looking closely at FICO and one other short. Together we will cover the macro and micro analysis. I'm not going to share the percentages of my positions because they do change.
Second question is by Cocaine Compounder, who is also a premium subscriber. "Steve Eisman, would you be against making a post with recommended books like a list of mandatory reading you'd have an intern read?" Well, with respect to interns, I used to require that interns who worked for me take a civics test. Knowing the names of all Supreme Court justices was one of the questions. Who was on the $5 bill? And what was Jonas Salk famous for were all part of my list of questions. My point was to see who was paying attention outside the narrow focus of stocks and bonds and who was curious enough to acquire information that at first glance seemed unconnected to investing. I have been asked before to recommend books and I have hesitated until now because my answer is generally not what I think people expect to hear. First of all, I generally don't read business books. I read the Wall Street Journal and Barron's and I read tons of research every week. After all of that, I just want to read something else. Not everything I read is related to stock picking. However, over time, the content of my reading has informed my investment decisions. Acquiring broad knowledge is how I became an investor. Within the knowledge I have acquired by reading, I have learned to identify ecosystems and repetitive patterns. All of which can be relevant to investing. Breadth of knowledge about patterns within ecosystems is crucial because I firmly believe that all learning is by analogy. This is where my reading comes into play. The more I read about many different ecosystems, the more analogies I have to draw upon when making stock decisions. As part of this process, I like to read a lot of history of all periods and all nations because I learn about historical patterns that I often find relevant and prescient to current events. With respect to history books, I sometimes read straight history, but more frequently I prefer books of historical analysis. Here are a few:
One, *The Nation That Never Was: Reconstructing America's Story* by Kermit Roosevelt. This is maybe the best discussion of the history of our Constitution that I have ever found. It gives a perspective you will not find elsewhere.
Two, *Intellectuals: From Marx and Tolstoy to Sartre and Chomsky* by Paul Johnson. This book is an example of why ideas matter, both good and bad ideas. Powerful ideas can change the world and bad ideas can do great harm.
Three, *The Guns of August* by Barbara Tuchman. It's a classic. The book shows how the world can go to war even when no one wants to go to war. Countries can get trapped by treaties and stupidity.
Four, *The Cultural Revolution* by Frank Dikötter is a story of how an entire country fell into madness because it was led by a madman.
I also love historical fiction. When done well, I find I learn more from such literature than most straight history. The best example of this in my view is the Rome series by Colleen McCullough. The first novel in that series is called *First Man in Rome*.
I also read comic books and graphic novels. This form of literature has been extremely influential in my thinking. Writers of graphic novels are often extremely intellectual and think creatively about dystopian futures. The stories I have read have informed my view of the world and along with history have taught me that anything is possible. World leaders often do not behave rationally and unpredictability is actually somewhat predictable if enough variables are in place. This is what happened during the Great Financial Crisis. Greed replaced all rational thinking and educated, intelligent leaders acted against all rational expectations and self-interest. Disbelief and critical analysis were suspended. My cynicism was criticized and laughed at, at least initially. I didn't care. I had read enough stories in my life to know I was right and they were wrong. And being well-read is my superpower.
Last Monday, July 6th, we posted an interview with Dan Clifton, the politics analyst at Strategas. We discuss what's going on with the midterm elections and the impact of tariff refunds. So check it out.
This coming Monday, July 13, we will post an interview with Torsten Slack, chief economist at Apollo. We discussed the broad impact of AI capex on the entire US economy and how sensitive the US economy is to any changes in AI. We also discussed the K-shaped economy. So tune in.
Be sure to check out our website, realizingplaybook.com. And thank you for joining. And that's the wrap.
This podcast is for informational purposes only and does not constitute investment advice. The hosts and guests may hold positions in stocks discussed. Opinions expressed are their own and not recommendations. Please do your own due diligence and consult a licensed financial advisor before making any investment decisions.