US Treasury Yields Near 5%: Why the AI Narrative Hasn't Broken Yet
Money is getting more expensive in the US, yet AI is still inflating while every other industry deflates. The contradiction resolves either by AI genuinely breaking through and pushing rates down, or by AI being falsified — but no one dares slow down first.
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The argument · tap a timestamp to hear it
Q3 markets: the exhaustion comes from having no direction
In the third quarter the S&P rose 2.1%, the Nasdaq was roughly flat, Japan and Korea fell 8-point-something and 18.5 respectively, the CSI 300 dropped 9.4, ChiNext fell 23 points, and the Hang Seng gained 8 points while Hang Seng Tech remained very weak. Commodities were the bright spot: WTI and Brent both rose 40 points over the quarter, and gold gained 8.5. But the host says his own feeling is ‘a strong sense of exhaustion’ — unlike the first half, when hearing a narrative and watching the market move still made you wonder what opportunity there was, whether to buy or sell, how to allocate. Now it's ‘tired, forget it.’ Ricky's summary: the first half was making money with your heart in your throat; this quarter was adjusting until you were completely drained.
— David WengThree forces pushing US Treasury yields up
A Clock Tower research note attributes the rise in long-end US yields to three forces. First, energy prices are climbing as the Middle East stalemate drags on and becomes permanent. Second, US nominal growth is resilient: Q2 real GDP grew about 1.5 and core PCE inflation was 3.4, which adds up to 5% nominal growth — compare the late 1990s, when the combined level of US Treasury yields was around 5%. Third, corporate bond issuance is expanding rapidly and AI infrastructure buildout continues, all against the backdrop of an already-high US fiscal deficit. The respective remedies are Middle East de-escalation, tighter macro policy, and a substantial slowdown in the AI investment cycle — but the latter two contradict each other.
— David WengBond yields are credit pricing, not a buy-sell mismatch
Ricky explains it by going up a dimension: a bond yield is fundamentally the cost of funds generated on the basis of credit. After the Soviet failure in the late 1980s and early 1990s, the US entered a long period of low rates, because it was the most powerful country in the world and its borrowing cost should be the lowest on earth. Since 2018 the US has entered the middle-to-late phase of its national fortune cycle, facing more and more doubt, its credit downgraded, and so its borrowing cost must rise. The two-dimensional world sees fewer buyers of Treasuries and more redeemers; the three-dimensional world sees declining national power driving up borrowing costs. The US decision at the three-dimensional level is to keep pushing on AI, mobilising the whole country for AI buildout while also pushing manufacturing reshoring — which sets private capital and state capital competing for money, and everyone's borrowing cost rises.
— RickyWill AI infrastructure repeat the ROA trap of the great infrastructure buildout
Ricky compares US AI infrastructure to China's great infrastructure buildout starting in 2008: an economic entity dominated by CAPEX will inevitably see ROA decline — more and more assets, no breakthrough in production technology, so the return per unit of asset falls. When ROA drops below the borrowing cost, an asset crisis follows. The current worry is precisely that AI infrastructure will end up with ROA unable to cover the borrowing cost, while the borrowing cost is rising and the improvement in ROA is not yet obvious. David Weng adds: what's different this time is that the deficit wasn't this high before — past cycles didn't casually involve trillions the way they do now, and the current magnitude has already exceeded the range of human comprehension.
— RickyThe prisoner's dilemma behind the calls to slow AI down
This week Dario wrote "We must pace the frontier," Musk reposted it saying he agreed, and Sam Altman also said in an interview that things should slow down, even saying OpenAI isn't in a hurry to IPO this year. A Reuters piece on September 9 was titled "Researchers want AI to slow down, but labs can't afford to." Ricky sees three layers. First, right and wrong in the two-dimensional world cannot be overturned in the three-dimensional world — Asimov's Three Laws saw it a hundred years ago, and you can't stop the disaster before it happens. Second, a unified alliance of three or more players is unachievable; the prisoner's dilemma ends with everyone choosing the worst outcome, and it takes an external force — the government — but the government only abandons its own problems once great-power competition produces enough damage and disaster. Third, the funding side cannot tolerate such a long verification period: if within a year large models haven't proven they have a sufficient application and commercial environment, a lot of money will see runs and even broken funding chains, at a magnitude that would certainly be many times that of the 2008 subprime crisis.
— RickyLarge-model revenue of 150 billion against 200 billion of investment
Ricky runs the numbers: total large-model revenue is 150 billion, investment is 200 billion. Split between frontier and open-source models: frontier models bring in about 120 billion USD in revenue on 100 billion of investment; open-source models take 100 billion of investment for 30 billion of revenue. Frontier model revenue alone is only so much, and open-source models are still a long way from actually generating revenue to cover investment — not even profit covering investment. So the pressure is heavy on whether these companies will still post big profit gains next year. More critical is the second layer: even if corporate earnings still rise by low double digits next year, will the capital market accept it? Because the second derivative is actually heading down, and valuations are set on the second derivative, not on earnings growth. If you can't count on white-collar replacement, the math doesn't work — and then it's definitely expensive.
— RickyMidterms: the probability Trump loses the House is very high
From BCA's research: over more than a century of US history, every midterm where the incumbent performs badly on livelihood issues and inflation has seen the party lose the House and Senate with near-certainty. The path laid out on the show early this year was that by June the US-Iran issue would be resolved, energy costs brought under control, and Trump would add some fiscal policy support, giving him a shot at holding the Senate. But neither of those has materialised, so the polls show a very high probability Trump loses the House, with many swing states and minorities — Hispanics among them — who were once Trump supporters starting to switch to the Democrats. The probability Trump holds the Senate should be high. If he only holds one chamber of Congress, he becomes a lame duck.
— RickyA-share rally in Q4, but don't get too far left of it
Ricky thinks A-shares can still look forward to a rally in Q4, but it shouldn't be played too far to the left; watch capital flows as the main signal, and if there's a short-term amplification in volume, it's worth participating. After that participation, switch to full defence and wait for the next, larger-magnitude breakthrough — for example, something clear on white-collar replacement, or clearer investment next year in the Huawei supply chain and the DeepSeek supply chain. If this rebound comes, it will certainly be led by tech, because many sectors have been tried without effect and only tech can drive the market up. Most fund managers did nothing in Q3, busy writing self-criticism; in Q4 they'll have to do something no matter what. David Weng is more conservative: still put cash first, second dividend low-volatility, third a narrower slice of tech such as the STAR 50, with a position of maybe two or three points.
— RickyIn their own words · checked verbatim
Although on the one hand the market really has been up and down, I don't know about Ricky, but I myself have a strong sense of exhaustion — it's just, unlike the first half, when you heard some narrative and saw the market move, you'd still think, so what opportunity do I have, do I buy or sell, how do I allocate — now it just feels like, tired, forget it, that's how it is, that kind of feeling.
虽然一方面市场确实跌宕起子，但是我不知道Ricky怎么样，我自己是有一种很强的疲惫感，就是，就不像上半年，你在听到一些叙事，然后看到一些市场的涨跌的时候，你还会想，那我有个什么机会，我到底是买还是卖，我要怎么去配纸，就现在就感觉累了算了，就这样了，就这种感觉。
David Weng5:03
A bond yield is just the borrowing cost of a bond. All bonds, whether secured or unsecured, are fundamentally a cost of funds generated on the basis of credit. For example, if David Weng's credit is better than mine, then his cost of borrowing must be lower than mine — that's the core.
债券利率就是债券的借贷成本，所有的债券，无论是你有抵押还是无抵押的，它本身其实是一个基于信用产生的资金成本，就是比如说大卫翁的信用比我好，那他借钱的成本一定比我低，这是核心。
Ricky22:17
Figures
| S&P 500 Q3 gain | 2.1% | 2:00 |
| CSI 300 Q3 decline | 9.4% | 2:00 |
| ChiNext Q3 decline | 23 points | 3:00 |
| WTI and Brent Q3 gain | 40 points | 3:00 |
| US 10-year Treasury yield | near 5%, at 4.8 the week of recording | 3:00 |
| Japan 10-year Treasury yield | 3% | 4:02 |
| China 10-year Treasury yield | 1.7 points | 4:02 |
| US Q2 real GDP growth | about 1.5 | 18:14 |
| US Q2 core PCE inflation | 3.4 | 18:14 |
Glossary
- CAPEX
- Spending by a company to acquire, maintain or upgrade physical assets.
- ROA
- Net profit divided by total assets; measures how much profit each unit of assets generates.
- carry trade
- Borrowing in a low-interest-rate currency to invest in higher-yielding assets and capture the spread.
- hyperscaler
- A tech giant that owns large-scale data centres and cloud infrastructure.
- second derivative
- Here it means the rate of change of earnings growth; valuations are often set on this rather than on the absolute growth rate.
How to listen
Investors and founders watching global macro and asset allocation, and anyone trying to understand the contradiction between rising US Treasury yields and the AI narrative.
The Q4 asset ranking segment after 1:35:32 — the conclusions are fairly casual and can be skipped.