🚨BEST Stock Investing Opportunity of 2026 - AI Boom or Bust?!

Summary

The presenter argues that markets may be rotating away from high-growth technology and that volatility could create opportunities to buy quality companies and ETFs at lower prices. He cautions, however, that the AI boom carries financing risks: some AI infrastructure companies rely heavily on debt, and their ability to repay or refinance it may become a problem if cash flows and data-center profits fail to meet expectations.

He does not predict an inevitable AI crash or recommend broadly selling AI investments. His approach is to stay diversified, understand portfolio concentration, and scrutinize companies’ cash generation, borrowing costs, and data-center economics.

Market and macro context

• The presenter says SCHD rose nearly 35% over a year, Berkshire Hathaway gained 14.5% year over year, while VOO was up 11.3% year to date and QQQ was up 10.5% year to date. He uses the comparison to illustrate that market leadership can change.
• Recent pressure has been concentrated in technology and other high-growth stocks. He describes the decline as possibly a healthy correction, while noting uncertainty around AI spending, oil prices, inflation, and future profitability.
• The Fed kept rates unchanged at its recent meeting. The presenter says a December rate hike remained possible and was largely priced into markets.
• He expected elevated portfolio volatility around the November 3 midterm elections, with the November 6 employment report and November 10 CPI release also on the calendar. He advises against making long-term decisions based on short-term market swings.

AI financing and debt risks

• Citing Moody’s, the presenter says the five largest U.S. technology companies plus CoreWeave could spend nearly $1 trillion on capital expenditures in 2027, including data centers, chips, cooling systems, and power infrastructure.
• Citing a Federal Reserve Bank of Kansas City study, he says AI-related firms’ share of investment-grade corporate bond issuance rose from about 2% in 2023 to 10% by Q2 2026. Such issuance reached approximately $330 billion in the first half of 2026.
• Citing Reuters and LSEG data, he says CoreWeave had roughly $50 billion in debt in October, and some of its bonds had yields around 15%. He emphasizes that this does not mean all CoreWeave debt yields 15% or that the company is certain to default; it indicates bond investors are demanding more compensation for risk.
• Moody’s warned on October 27 that private-credit loans maturing in 2027–2029 could create refinancing difficulties for weaker borrowers.
• The presenter offers these illustrative examples:
  • A $1 billion loan at 8% costs about $80 million annually in interest.
  • Refinancing $500 million of debt from 5% to 10% raises annual interest from $25 million to $50 million.
  • A $100 million loan with 10% payment-in-kind (PIK) interest could grow to $121 million in two years, as interest is added to the balance rather than paid in cash.
• He warns that stress could spread beyond AI firms to lenders, banks, real estate companies, and suppliers in electricity, industrial equipment, construction, and engineering. He says this does not automatically imply a financial crisis or a repeat of the dot-com bubble.

Valuation illustration

The presenter explains how a stock can fall even while earnings rise:

• At $10 earnings per share and 35× earnings, a stock would be worth $350.
• If earnings rise 10% to $11, but the valuation falls to 25×, the implied price becomes $275—about a 21% decline despite earnings growth.

His point is that investors may pay less for expected future growth if they become less confident in its profitability.

Investing framework and recommendations

For the next 12–24 months, the presenter says to monitor:

• Free cash flow: Can companies generate enough cash to support their investment plans?
• Borrowing costs and refinancing access: Higher rates or difficulty refinancing are particular concerns for smaller, debt-dependent firms.
• Data-center profitability: Are there enough paying customers to justify construction and operating costs?

For long-term investors, he recommends:

• Maintaining a diversified core and assessing actual exposure to technology.
• Being especially cautious with smaller companies that promise large profits while carrying substantial debt.
• Reviewing holdings for overlap: VOO, QQQM, VGT, and AI-focused ETFs may appear diversified but can share major holdings.
• Using market volatility to research holdings, identify portfolio gaps, and consider whether changes would improve balance and resilience.
• Avoiding the assumption that transformative technology makes every company in the sector a good investment. He compares the AI investment cycle with the 19th-century railroad boom, when the technology transformed the economy but some overborrowed companies failed.

Assets and sectors mentioned

• ETFs: SCHD, VOO, QQQ, QQQM, VGT, and AI-focused ETFs (not individually named)
• Companies: Berkshire Hathaway, Nvidia, Microsoft, Google, Amazon, CoreWeave
• Other instruments: Investment-grade corporate bonds, private-credit loans
• Sectors and themes: Technology, AI infrastructure, data centers, semiconductors, electricity and power grids, industrial equipment, construction, engineering, oil

Disclosures and sources

The presenter says that all investing involves risk, advises viewers to do their own research, and states: “This is not financial advice, and I am not a financial advisor.”

Presenter: Nolan Goveya, who says students call him Professor G (also referred to in the subtitles as Professor Ji/Gee).

Sources cited in the video: Moody’s; Federal Reserve Bank of Kansas City; Reuters; LSEG data.