Fed’s QE Strategy: Could AI Mania Lead to a Repeat of the 1999 Bubble?

Bitget-RWA2025/11/06 21:14

By:Bitget-RWA

- Billionaire Ray Dalio warns Fed's shift to QE risks inflating an AI-driven bubble akin to 1999's dot-com crash. - He criticizes reinvesting MBS proceeds into Treasury bills as monetizing debt while cutting rates amid large fiscal deficits. - Analysts highlight risks of reduced T-bill supply, lower yields, and repo market strains from Fed's $15B/month Treasury demand. - AI sector valuations and corporate earnings will test Dalio's concerns as November inflation data and PMI reports approach.

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Billionaire investor Ray Dalio has sounded a serious alarm regarding the Federal Reserve’s latest policy direction, cautioning that its shift away from quantitative tightening (QT) toward a version of quantitative easing (QE) could fuel a speculative bubble similar to the late 1990s dot-com surge, as reported by a

Morningstar report

. In a post on LinkedIn, Dalio pointed to the Fed’s strategy of channeling funds from maturing mortgage-backed securities (MBS) into Treasury bills, warning that this move might blur the line between genuine technological innovation and rampant financial speculation. “Should the Fed’s balance sheet begin to grow rapidly while rates are being lowered and fiscal deficits remain high, we would interpret this as a textbook case of monetary and fiscal policy working together to monetize government debt,” he stated.

The central bank’s recent decision to end its QT initiative and keep its balance sheet steady has sparked concerns about potential market instability, according to a

Reuters report

. Experts have observed that the Fed’s stepped-up purchases of T-bills—projected at $15 billion each month—may shrink the available supply for private investors, possibly pushing yields down and intensifying liquidity issues in the repo market, the report notes. While the Fed’s intention is to ease short-term funding pressures, critics such as Dalio warn that these actions could foster a climate of excessive optimism, especially in sectors like artificial intelligence, where valuations are already seen by many as overheated, a point raised in a

Business Insider piece

Fed’s QE Strategy: Could AI Mania Lead to a Repeat of the 1999 Bubble? image 0

Dalio’s warnings reflect broader worries in the market about the formation of asset bubbles. The artificial intelligence industry, for example, is increasingly likened to the tech mania of 1999, with prominent figures such as Alibaba’s Joe Tsai and C3.ai’s Tom Siebel voicing concerns about excessive valuations. At the same time, the Fed’s supportive policies are unfolding against a backdrop of significant fiscal deficits and strong growth in private credit, all of which could heighten inflation risks if not addressed. “This appears to be a bold and risky wager on economic expansion—particularly in AI—funded by extremely loose fiscal, monetary, and regulatory measures,” Dalio warned.

The next few weeks will put these perspectives to the test. Investors are monitoring November’s inflation numbers and manufacturing PMI data for hints about the Fed’s future policy decisions, as indicated by the

Investing.com calendar

. Upcoming earnings reports from companies like Coca-Cola and Cisco Systems could also shed light on the state of the economy. For now, Dalio’s caution highlights a rising sense of unease that the Fed’s efforts to balance economic growth with inflation control could ultimately lead to asset prices detaching from underlying fundamentals, reminiscent of the turbulence seen in previous financial bubbles.

Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.

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1. Technology stocks fell sharply as investor interest shifted toward energy and selected defensive assets. From October 10 to 16, the Nasdaq 100 declined 5.49% and the S&P 500 fell 1.95%, while the Dow gained 0.67% and WTI crude rose 10.41%. BTC, ETH, and SOL declined 1.27%, 2.65%, and 4.44%, respectively. This week's technology earnings will be an important test of whether revenue growth, margins, and cash flow can justify current valuations. Better-than-expected results could help stabilize markets in the near term. 2. Crypto continues to see pockets of strong activity, but a broad-based altcoin season has yet to materialize. CoinMarketCap's (CMC) Altcoin Season Index stood at 54 as of the October 18 UTC daily observation, below the altcoin-season threshold of 75, while BTC dominance rose to 60.08%. Our proxy leverage ratio fluctuated between 4.00 and 4.07 during the week, showing no sustained increase and suggesting limited appetite for additional leverage. Meanwhile, as major exchanges expand access to traditional financial assets, the recent sell-off in AI-related equities could attract short-term speculative capital away from crypto. Such capital rotation could make it more difficult for a new altcoin season to take hold. 3. Papertrade's loss-to-mine model has generated significant interest across the crypto community. The protocol combines high-leverage derivatives trading with zero slippage and a mechanism that rewards trading losses with PAPER tokens. Across the eight complete UTC days from October 10 to 17, cumulative reported revenue reached approximately $56.08 million, including $51.90 million distributed to token holders. With growing participation from key opinion leaders (KOLs), Papertrade has reportedly ranked among the top three platforms by profitability in the broader market recently. Assets to watch: BTC, ETH, SOL, ARB, OP, SKHYNIX, SKHY, META, TSLA, LRCX, and SPCX. Key research priorities this week: Cash flow performance in technology earnings; the relative discount and holding costs of the two SK Hynix contracts; and U.S. initial jobless claims and PMI data. Weekly market data cover the period through October 16, while research information was verified through October 18. Observation periods are specified separately for each chart.

Bitget•2026/10/19 06:51