New AI Era Thinking and Circular Financing Deals

By the Curmudgeon with Victor Sperandeo

In a highly volatile week full of wild stock market swings, the S&P 500 and DJIA each declined -1.9%, while the NASDAQ Composite was down -2.7% and the Russell 2000 was off -0.8% for the week, despite rising +2.8% on Friday.

What’s so unusual is that the decline started immediately after the DJIA reached its all-time closing high of 48,255 on Wednesday, November 12^th. The DJIA is -4.2% since then, closing at 46,242 on Friday (+1.07% on the day).

Bitcoin continued its decline (-7.9%) and is down -31.67% from its October 6^th high on a massive “risk-off” move.

The Conference Board's November 2025 forecast projects U.S. real GDP growth will be +1.8% year-over-year in 2025. The projection for growth from Q4 2025 to Q4 2026 is +1.5%. The Atlanta Fed GDP Now estimate for 4Q-2025 is +4.2%.

The University of Michigan’s Consumer Sentiment report for November showed further weakness in consumer attitudes as the Overall Index declined from 53.6 to 51.0. Consumer Future Expectations ticked up slightly from 50.3 to 51.0 while the Current Conditions Index dropped from 58.6 to 51.1. This report continues to confirm that consumers, and the economy, are highly vulnerable.

The BLS Jobs report for September was released this week, over a month after its scheduled release date of October 3rd. It showed an increase of 119,000 jobs added with a downward revision of 33,000 for the prior two months. Most importantly, the unemployment rate increased to 4.4% – the highest level in 4 years and the third consecutive increase.

That’s probably enough ammo for the Fed to cut the Fed Funds rate by 25bps (to 350bps to 375bps target) at its next FOMC meeting on December 10^th. According to the CME Fed Watch Tool, there’s a 71% probability of that currently, up from only 44% one week ago on November 24^th.

New AI Era Thinking?

What me worry about the economy or job market? Not a chance!

In this new AI era, consumers and workers are not what drives the economy anymore. Instead, it’s spending on all things AI, mostly with borrowed money or circular financing deals.

BofA Research noted that Meta and Oracle issued $75 billion in bonds and loans in September and October 2025 alone to fund AI data center build outs, an amount more than double the annual average over the past decade. They warned that "The AI boom is hitting a money wall" as capital expenditures consume a large portion of free cash flow. Separately, a recent Bank of America Global Fund Manager Survey found that 53% of participating fund managers felt that AI stocks had reached bubble proportions. This marked a slight decrease from a record 54% in the prior month's survey, but the concern has grown over time, with the "AI bubble" cited as the top "tail risk" by 45% of respondents in the November 2025 poll.

JP Morgan Chase estimates up to $7 trillion of AI spending will be with borrowed money. “The question is not ‘which market will finance the AI-boom?’ Rather, the question is ‘how will financings be structured to access every capital market?’ according to strategists at the bank led by Tarek Hamid.

As an example of AI debt financing, Meta did a $27 billion bond offering. It wasn’t on their balance sheet. They paid 100 basis points over what it would cost to put it on their balance sheet. Special purpose vehicles happen at the tail end of the cycle, not the early part of the cycle, notes Rajiv Jain of GQG Partners (see End Quote below).

AI Data Center Spending Boom and Circular Financing Arrangements:

This week’ s Barron’s says that investors might start looking to buy again, especially if AI’s big spenders keep spending. Indeed, huge spending to build AI data centers has kept the economy chugging along despite all-time low consumer confidence and huge economic uncertainty due to President Trump’s unpredictable tariff and trade policies.

“The spending boom is not likely to be over until one of the big cloud companies says, ‘Enough is enough,’ and we’re not seeing that yet,” says Tavis McCourt, equity strategist at Raymond James. “There will come a day where that happens. It feels early,” he added.

In addition to cloud/hyperscaler AI spending, AI start-ups (especially OpenAI) and newer IT infrastructure companies (like Oracle) play a prominent role. It’s often a “scratch my back and I’ll scratch yours” type of deal.

Let’s look at the “circular financing” arrangement between Nvidia and OpenAI where capital flows from Nvidia to OpenAI and then back to Nvidia. That ensures Nvidia a massive, long-term customer and providing OpenAI with the necessary capital and guaranteed access to critical, high-demand hardware. Here’s the scoop:

l Nvidia has agreed to invest up to $100 billion in OpenAI over time. This investment will be in cash, likely for non-voting equity shares, and will be made in stages as specific data center deployment milestones are met.

l OpenAI has committed to building and deploying at least 10 gigawatts of AI data center capacity using Nvidia's silicon and equipment, which will involve purchasing millions of Nvidia expensive GPU chips.

Here’s the Circular Flow of this deal:

l Nvidia provides a cash investment to OpenAI.

l OpenAI uses that capital (and potentially raises additional debt using the commitment as collateral) to build new data centers.

l OpenAI then uses the funds to purchase Nvidia GPUs and other data center infrastructure.

l The revenue from these massive sales flows back to Nvidia, helping to justify its soaring stock price and funding further investments.

What’s wrong with such an arrangement you ask? Anyone remember the dotcom/fiber optic boom and bust? Critics have drawn parallels to the "vendor financing" practices of the dot-com era, arguing these interconnected deals could create a "mirage of growth" and potentially an AI bubble, as the actual organic demand for the products is difficult to assess when companies are essentially funding their own sales.

However, supporters note that, unlike the dot-com bubble, these deals involve the creation of tangible physical assets (data centers and chips) and reflect genuine, booming demand for AI computing capacity although it’s not at all certain how they’ll be paid for.

There’s a similar cozy relationship with the $1B Nvidia invested in Nokia with the Finnish company now planning to ditch Marvell’s silicon and replace it by buying the more expensive, power hungry Nvidia GPUs for its wireless network equipment. Nokia has only now become a strong supporter of Nvidia’s AI RAN (Radio Access Network), which has many telco skeptics.

OpenAI as the Poster Child of AI Mega Deals:

OpenAI has been making mega AI data center and cloud computing deals without the cash flow to pay for them.

Microsoft has invested over $13B in the ChatGPT maker while providing Microsoft’s Azure cloud resources to the company -- OpenAI is committed to spending $250 billion on Microsoft’s cloud services.

OpenAI is also committed to spending over $300B on Oracle’s cloud starting in 2027, $22 billion with CoreWeave and $38 billion with Amazon (AWS), which is a big investor in rival Anthropic (as is Microsoft as of this week).

-->Where will OpenAI get the money to pay for those deals when it’s burning cash and is not expected to be profitable until 2030?

BCA Research is Wary of the AI Capex Boom:

They expect the AI boom to end within the next 6 to 12 months and remain on watch for a “Metaverse Moment” [1.] to mark its terminal stage. BCA writes:

“Although AI is now vying for the (Capex Boom) crown, no boom was as spectacular as the internet boom of the late 1990s. Like most booms, the internet one was based on real innovation – innovation that raised productivity and changed the way people lived and worked. However, as often occurs during booms, investment spending got ahead of itself, setting the stage for a bust.”

AI capex is increasingly being funded by debt (see chart below). In October, Meta announced a $27 billion data center financing deal to be housed in an off-balance-sheet SPV. Oracle tapped the bond market for $18 billion after recently securing a $38 billion loan. The company now holds nearly $96 billion in debt. Several power generation companies have also announced significant debt-financed expansion plans.

The biggest concerns swirl around companies such as CoreWeave and other “neoclouds” that rent AI compute to the hyperscalers. They have taken on a considerable amount of debt to finance their expansion. CoreWeave’s CDS rate currently stands at 532 bps, up from 359 bps in early October.

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AI-generated content may be incorrect.

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Note 1. A “Metaverse Moment,” as defined by BCA Research, is an occasion where an AI public company announces a major AI project only to see its stock price fall. So far, the opposite is the case, most notably Oracle’s stock rose ~40% on September 10^thwhen it announced its $300B deal with OpenAI.

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Victor- AI Energy Consumption is a Critical Issue:

The Curmudgeon (my co-author for the last 14 years) possesses deep expertise in artificial intelligence (AI), whereas my own understanding is primarily at a macro level. Consequently, I defer to his judgment on the technical aspects of AI.

From an economic standpoint, however, it is important to note that the energy demands associated with large-scale AI deployment exceed the current capacity of the U.S. power grid. Meeting this demand will likely put upward pressure on residential electricity prices. Entering an election year (2026 mid-terms), this issue is almost certain to trigger political debate and regulatory hesitation, potentially slowing the timeline for AI to become consistently profitable.

End Quote:

“A significant part of the growth in data centers is not coming from hyperscalers, but from other players. Private credit is a big part of it. You’re seeing cracks appear. Look at Oracle’s CDS (Credit Default Swaps). If the credit market seizes up—look at the First Brands and Tricolor bankruptcies—a lot of GPUs are being packaged as asset-backed securities. They need to get funding from the markets. Bond issuance is very heavy from the tech side. The whole narrative of these being cash-rich companies will be shown to be a myth. Based on our numbers, data center by data center, with the help of S&P, around 60% of the data centers aren’t through hyperscalers.”

Rajiv Jain, Chair and Chief Investment Officer of GQG Partners, in a Morningstar interview: “Why the AI Bubble Is Poised to Burst.”

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Wishing you good health, peace of mind, success and good luck. Till next time……

The Curmudgeon
ajwdct@gmail.com

Follow the Curmudgeon on Twitter @ajwdct247

Curmudgeon is a retired investment professional. He has been involved in financial markets since 1968 (yes, he cut his teeth on the 1968-1974 bear market), became an SEC Registered Investment Advisor in 1995, and received the Chartered Financial Analyst designation from AIMR (now CFA Institute) in 1996. He managed hedged equity and alternative (non-correlated) investment accounts for clients from 1992-2005.

Victor Sperandeo is a historian, economist and financial innovator who has re-invented himself and the companies he's owned (since 1971) to profit in the ever-changing and arcane world of markets, economies, and government policies. Victor started his Wall Street career in 1966 and began trading for a living in 1968. As President and CEO of Alpha Financial Technologies LLC, Sperandeo oversees the firm's research and development platform, which is used to create innovative solutions for different futures markets, risk parameters and other factors.

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