Why Did Tech Rally While the Fed Raised Rates?
The Fed raised rates, and tech stocks still rallied.
Every textbook says the opposite should happen.
The explanation comes down to one thing: the gap between what the market had priced in and what it actually got.
On 16 September, the Fed raised its policy rate by 25 basis points to 3.75–4.00%. The decision was unanimous at 12–0 and marked the first hike since 2023. Projections point to one more increase before year-end. August CPI came in at 3.4% year on year with core inflation at 2.4%, and nonfarm payrolls beat expectations at +162,000. The macro backdrop points to tightening, not easing.
Yet on 17 September risk appetite improved: the 10-year Treasury yield slipped to 4.93%, back below 5%; the VIX dropped 11% to 15.7; oil eased. Investors read the hike as less hawkish than feared and reversed the previous session's sell-off.
The real fuel, however, is AI capital expenditure. The top five cloud providers are set to spend roughly $602bn in 2026, up 36% year on year, with about three-quarters of that going into AI infrastructure. UBS models $4.1tn of hyperscaler investment across 2026–2028. A narrative backed by cash flow can survive a high-rate environment.
DeFi veterans will recognise the logic: narrative sets direction, liquidity sets speed.
But are these four stocks really one "AI basket"? No — and that distinction changes your risk. Article 3 explains why.
This content is not investment advice. Always perform your own research before making financial decisions.
#Gate广场中秋团圆局 #美股AI概念股全线反弹 #GateMemeCarnival #WhereToParkStablecoinsWhileWaiting #GateSquareMidAutumnReunion

It's Called the AI Rally, But the Fuel Is Liquidity
The market calls it an AI rally.
But would this picture have formed if the 10-year Treasury yield had not slipped below 5% and the VIX had not dropped 11%?
And does on-chain liquidity tell the same story?
Three variables carried risk appetite on 17 September: a 4.93% 10-year yield, a VIX at 15.7 and softer oil. Together they lower the cost of carrying risk. More often than not, prices are moved by conditions rather than headlines.
Crypto lives this dynamic faster. Stablecoin supply, transfer volumes in cash-like assets such as USDC, collateral quality inside DeFi protocols and the depth of liquidity pools rank among the most transparent measures of risk appetite. That is Web3's edge: this data sits on-chain rather than behind closed doors. An analyst watching on-chain liquidity can answer "where is the leverage coming from?" far faster than in traditional markets.
The first signs of deteriorating risk appetite show up here early too: tightening collateral ratios, sudden jumps in lending rates, stablecoin flows changing direction. In traditional markets such signals arrive late, after the close; on-chain they are readable in real time — an asymmetry that makes Web3 tooling a genuinely useful complementary risk panel.
GateSquare is where that bridge gets built: while the AI narrative drives the Nasdaq, the same theme finds expression in crypto through new Launchpad structures, tokenomics design and DeFi products. One caveat still applies: correlation is not causation, and the two markets do not always react to the same headline in the same direction.
So what is this optimism missing? Three concrete risks — and the series finale — in Article 5.
This content is not investment advice. Always perform your own research before making financial decisions.
$BTC $GT $ETH
#Gate广场中秋团圆局 #美股AI概念股全线反弹 #GateMemeCarnival #WhereToParkStablecoinsWhileWaiting #GateSquareMidAutumnReunion