Except for Nvidia, the Magnificent Seven has an earnings problem

Except for Nvidia, the Magnificent Seven has an earnings problem

In aggregate, the “Magnificent 7” companies have reported higher (year-over-year) earnings growth than the other 493 companies in the S&P 500 over the past several quarters. Is this trend expected to continue in the first quarter of 2026?
The answer is yes. with one huge caveat. For the first quarter of 2026, the estimated (year-over-year) earnings growth rate for the “Magnificent 7” companies is 22.8%. The blended (combining actual and estimated results) earnings growth rate for the remaining 493 companies in the S&P 500 for the first quarter is 10.1%. However… Nvidia (NVDA) is expected to be the top contributor to (year-over-year) earnings growth for the “Magnificent 7” companies (and the entire S&P 500) for first quarter of 2026. If Nvidia were excluded, the estimated earnings growth for the “Magnificent 7” companies for first quarter of 2026 would fall to 6.4% from 22.8%.

Except for Nvidia, the Magnificent Seven has an earnings problem

I think it’s time to give Nvidia a rest–selling my position tomorrow

When the CEO extends the company’s $500 billion revenue projection for 2026 by adding another $500 billion for 2027–we’re talking $1 trillion in revenue here, folks–and the stock barely budges, I think we’re looking at a stock in need of a valuation reset. That’s exactly what happened to shares of Nvidia (NVDA) yesterday and today, March 16 and 17.And it’s why I’m selling Nvida out of my 50 Stocks Portfolio tomorrow, March 18. I expect I’ll be back into Nvidia shares when the valuation is less stretched–either because of a pull back in the shares or because projected revenues have turned into booked earnings (or some of each.) I’ve done this rotation in and out of Nvidia once before, selling in late 2023 and then rebuying in December 2023 for a 290% gain as of the close on March 17, 2026. Nvidia shares predawn 1.75% for 2026 as of the close on March 16.

Is AI spending insane? Depends on what an AI monopoly is worth–and if there will be one

Is AI spending insane? Depends on what an AI monopoly is worth–and if there will be one

Journey back with me to the heady days of 1999 when another technology boom pushed stocks to record highs on the promise of revolutionizing everything. Why is this exercise important?Because it’s a real life example of the work on the role of monopolies in our economy by economists like Joan Robinson and Paul Sweezy. Their work begins with the extreme excess returns that companies with effective monopoly power generate–and points to the important role that monopolies play in the business cycle of boom and bust. And because monopoly economics are critical to deciding if the current generation of AI stocks are really going to be worth what investors now say they are.

Coming soon, DeepSeek V4: the next  big test for AI stocks, tech sector, and the entire market

Coming soon, DeepSeek V4: the next big test for AI stocks, tech sector, and the entire market

China’s AI disruptor DeepSeek is preparing to introduce a new model. Reuters had initially reported that DeepSeek would launch its next‑generation model “V4,” focused on coding, in mid‑February 2026. Rumors now peg the expected release window as “Q1–Q2 2026.” The mid‑February window has passed but context‑window changes and internal benchmark leaks signal that V4 is close. And it will be a BIG DEAL for AI competitors AND ai chipmakers such as Nvidia (NVDA). A big enough deal that the V4 release will move the entire tech sector and quite probably the stock market as a whole.

Will OpenAI go broke?

Will OpenAI go broke?

Will OpenAI go broke this year? 2027% Never?–with the company navigating its way to a company-saving initial public offering in 2026 or 2027?

The company’s current attempt to raise an additional $50 billion in venture capital from Middle Eastern investors will certainly help answer the question.

And the answer isn’t of interest only to those private investors who have put $57.9–$64 billion into the company across 11 funding rounds. OpenAI owes so much money to the companies supplying its chips and building its data centers–an estimated $1.4 trillion in contingent liabilities– that an OpenAI failure would dent–or worse–the entire technology sector.

Saturday Night Quarterback says, for the week ahead expect…

Saturday Night Quarterback says, for the week ahead expect…

I expect more volatility as forth quarter earnings season picks up speed. Next week, despite the short week created by Monday’s Martin Luther King holiday, 157 companies are scheduled to report earnings with highlights that include Netflix (NFLX) on Tuesday; and General Electric (GE),Procter & Gamble (PG), and Intel (INTC) on Thursday.

Except for Nvidia, the Magnificent Seven has an earnings problem

Nvidia speeds things up in AI

I’d argue that the bIg news out of the 2026 Consumer Electronics Show in Las Vegas so far isn’t about new chips, or flashy hardware across TVs, PCs, phones, and robots.

It’s all about speed: Nvidia (NVDA) pushed up the launch schedule for its new Vera Rubin AI computing platform by several months from late 2026 to the middle of 2026. Vera Rubin promises about 10x higher throughput and 10x lower token cost than the prior Grace Blackwell platform. The chip now looks be available to customers in the second half of 2026. Cloud partners like AWS, Google Cloud, Microsoft, and CoreWeave planning Rubin-based instances starting in that second half 2026 window.

Will OpenAI go broke?

Another short seller, Jim Chanos, is flagging the risks in AI debt

I take everything from both extreme speculative bulls and extreme negative bears with a grain–or more–of salt. Members of each camp talk their own positions and certainly aren’t above cherry-picking facts to buttress their own views.
But I do take shorts like Jim Chanos very seriously. In his long career on the short side of the market Chanos has proven himself to be a well-informed analyst of company weaknesses and corner-cutting. So I think it’s very important to listen when he has joined his voice to those pointing to serious accounting problems at AI companies and the possibility that those accounting problems could lead some of the huge amount of debt that AI companies have issued this year to blow up. Chanos and other short sellers like Michael Burry have focused on the use of asset backed debt to pay for the huge build out in AI data centers. The problem, these shorts say, is that many of these new AI companies–particularly in the part of AI called “neoclouds–have used assets in the form of Nvidia (NVDA) chips to secure large loans to buy more AI chips to scale up their operations. But, and this is the crux of the shortsellers’ case, they are using unrealistically long schedules to depreciate the value of these assets–5 or 6 years when the life of these technology assets is more like 2 to 3 years.