The 10-year Treasury yield fell from 5.28% on 2 October to 4.84% on 5 November, 44 basis points, while the VanEck Semiconductor ETF (SMH) lost 29.0% and Nvidia 22.4%, on US Treasury and Yahoo Finance daily closes. The Wall Street Journal ran a story on 13 November headlined “How the AI Trade Hijacked the Treasury Market for a Month”. We could not read the article, which is paywalled, so this piece rests on the public data alone.
Over those 23 sessions, the daily change in the 10-year yield and the daily SMH return had a correlation of 0.61 by our arithmetic, and 0.58 against Nvidia. In the 22 sessions from 1 September to 2 October, the same correlation was minus 0.51. On all five days in the window when SMH fell 3% or more, the 10-year yield fell.
Business Pill · Capex and Depreciation Explained
An evergreen Business Engineer explainer on capital spending and depreciation. It teaches the general idea and does not discuss Treasury yields.
The key insight: From 2 October to 5 November the 10-year Treasury yield fell 44 basis points to 4.84% while SMH lost 29.0%, and daily moves in the two had a correlation of 0.61 by our arithmetic, against minus 0.51 in September; on all five days SMH fell 3% or more, the 10-year yield fell.
The biggest yield drop of the five came on 22 October: SMH fell 6.0% and the 10-year yield dropped 17 basis points, to 4.96%. On 5 November SMH fell 11.2% and the yield fell 6 basis points, to 4.84%. The other three days were 14 October, 16 October and 30 October, with yield moves of 1 to 4 basis points.
The 30-year yield moved the same way, from 5.63% on 2 October to 5.25% on 5 November, 38 basis points. A positive correlation here means yields fell on the days chip stocks fell: buyers bid for Treasuries, which pushes yields down, as chip shares sold off. In September the correlation was negative.
Method: daily changes in the Treasury 10-year par yield in basis points against daily percentage returns of SMH and Nvidia, on days both markets traded. The figures are our arithmetic from the published closes. A correlation over 23 days does not show that one market caused the other.
US 10-year Treasury yield and the VanEck Semiconductor ETF (SMH), daily closes from 1 September to 12 November 2026, from US Treasury and Yahoo Finance data. Shaded: 2 October to 5 November. The changes are our arithmetic.
The Week Since 5 November
From 5 to 12 November the 10-year yield rose 26 basis points to 5.10%, SMH rose 12.1% and Nvidia fell 8.5%, on the same closes. On 10 November Nvidia fell 5.5% while the 10-year yield rose 10 basis points. The bond market was closed on 11 November.
Bloomberg ran a 12 November story headlined “Long-dated US debt rises as Nvidia woes revive haven demand”. On Treasury’s end-of-day figures, the 10-year closed that day at 5.10%, up from 4.98% on 10 November, and the 30-year at 5.43%, up from 5.35%.
Why AI and Long Bonds Are Tied
AI also reaches the bond market through supply. Alphabet, Amazon, Meta, Microsoft and Oracle took in $253.4 billion from new long-term debt in their latest nine reported months, about 45% of their capex, as we reported from their filings. A PIMCO note cited by CNBC put AI-related borrowers at almost half of year-to-date issuance of non-financial US investment-grade debt with maturities beyond 15 years.
In October, Bank of Japan Deputy Governor Shinichi Uchida said bond issuance by AI-related companies is putting upward pressure on long-term rates, as we reported from his remarks. On the equity side, Goldman’s 8,700 S&P 500 target rests on hyperscaler valuations.
The Structural Read
As we read the closes, for five weeks Treasuries traded like a hedge on the AI chip trade: the sessions when chip stocks fell hardest were sessions when buyers bid for long bonds. That sits next to the supply side we have tracked, $253.4 billion of new long-term debt at Alphabet, Amazon, Meta, Microsoft and Oracle in nine months, about 45% of their capex. Since 5 November the 10-year has risen 26 basis points to 5.10%.
Bank of Japan Deputy Governor Shinichi Uchida, 5 October 2026, as we reported
“a big positive demand shock”
Three Implications
FOR BOND INVESTORS On the closes we used, the 10-year yield fell on each of the five days in the window when SMH fell 3% or more, with the largest drop, 17 basis points, on 22 October.
FOR AI BORROWERS A PIMCO note cited by CNBC put AI-related borrowers at almost half of year-to-date issuance of non-financial US investment-grade debt with maturities beyond 15 years, as we reported.
FOR THE WINDOW In September the same daily correlation was minus 0.51 by our arithmetic, and from 5 to 12 November the 10-year rose 26 basis points while Nvidia fell 8.5%.
The framework argues: “It is a sovereign-scale financing problem dressed in tech-company clothing”.
As we read it, five weeks of Treasury yields moving with chip stocks are one sign of that: the AI trade now shows up in the government bond market. The framework predates these moves and does not discuss them.
Daily SMH return against the daily change in the 10-year Treasury yield, 23 sessions from 2 October to 5 November 2026, from US Treasury and Yahoo Finance closes. The correlation of 0.61 is our arithmetic.
What Is Not Established
We did not read the Wall Street Journal article and do not know its argument, figures or sources beyond the headline. We did not read the Bloomberg story beyond its headline. Correlation is not causation, and we did not control for rate expectations, economic data or other flows. The result depends on the window chosen, and with only 23 sessions the estimate is noisy.
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From 2 October to 5 November, on public closes, the 10-year Treasury yield fell 44 basis points as SMH fell 29.0%, and daily moves in the two lined up with a correlation of 0.61 by our arithmetic, against minus 0.51 in September. Since 5 November the 10-year has risen 26 basis points to 5.10%.
A note on sourcing. Yields are US Treasury daily par yield curve rates and prices are Yahoo Finance daily closes for SMH and Nvidia, both downloaded on 13 November; the correlations and changes are our arithmetic, method stated above. The Wall Street Journal article of 13 November was paywalled and we did not read it; we quote its headline only, as we do Bloomberg’s 12 November story. We did not contact either publication.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
