*FED MEDIAN PROJECTION MAINTAINS 25 BPS OF RATE CUTS IN 2026

*FED SAYS SCHMID, GOOLSBEE DISSENT IN FAVOR OF NO RATE CHANGE

FOMC STATEMENT

POWELL: RATES ARE WITHIN RANGE OF PLAUSIBLE NEUTRAL ESTIMATES

POWELL: RECENT RATE CUTS SHOULD HELP STABILIZE LABOR MARKET

FOMC Review: INFINITYHEDGE

* Hawkish Cut as Expected — but it wasn’t all that hawkish
* Projections shows policymakers see one more cut in 2026 – unchanged from Sept....suggests officials see little reason to accelerate the pace of easing. The Fed voted 9-3, the first time in six years that three officials cast dissents (Only Two Dissents for no cut)

* Fed said it will buy $40b of treasury bills in next 30 days, will begin purchases on december 12th (bills to 3 year notes) with further purchases beyond that period, in order to ensure that reserves within the US financial system remain at an ample level...this is not QE, with the Fed not aiming to lower long-term rates, or reduce duration in the market through this policy action. Instead, these purchases are being made simply to ensure that the financial system continues to function smoothly, and that no plumbing issues crop up: M. Brown

* Fed painstakingly calibrated postmeeting statement signaled a higher bar to additional cuts by echoing a similar pivot after cutting rates one year ago.

* Next Cut Priced For June, 2026

POWELL'S PRESSER:
* Surprisingly Dovish leaning with some hawkish undertones.

* Powell’s opening remarks were more dovish than the Oct. meeting, and the most dovish since 2021: BI's natural-language processing model

* Powell: 75bps Policy Rate Reduction Since September Puts It In Neutral Territory; Well Positioned To Wait To See How Economy Evolves

* Powell: Policy Decisions Right Now Are A Close Call; I Could Make The Case For Either Side; Gradual Labor Market Cooling Justified Rate Cut Today

* Powell said there will be a “great deal of data” between now and the January meeting. The data, he adds, will factor into their thinking.

* Powell said A very large number of participants agree that risks are to the upside for unemployment and to the upside for inflation, so what do you do?....You’ve got one tool, you can’t do two things at once. It’s a very challenging situation.

* Powell said It’s early days for AI, and it’s not showing up in the jobs data yet.

* Powell: I Think AI Makes People Who Use It More Productive.

* Powell said payroll gains are probably negative...payroll increases likely being overstated by 60k, So sees a negative 20k for monthly payrolls since April.....It doesn't feel like a hot economy.....

* Powell said This is a labor market with significant downside risks, and it’s really tariffs that are causing “most of” the overshoot on inflation.

* Powell said T-bill purchases may stay elevated for a few months

* Nomura: The improved outlook for the US economy indicated by the FOMC also makes it easier for the BOJ to decide on interest rate hikes and allows the market to better anticipate Japan’s monetary policy, which is also positive for the market.

BE: On the dovish side, Fed sharply revised up the growth trajectory while lowering the inflation outlook, and kept the dot plot unchanged. FOMC also announced the commencement of reserve-management purchases. On the hawkish side, there’s a signal in the policy statement that suggests the committee is inclined for an extended hold. Even though the dot plot shows just one 25bp cut in 2026 — markets are pricing two — our view is that the Fed will end up cutting by 100 bps next year. That’s because we anticipate weak payroll growth and currently see scant signs of an inflation resurgence in the first half of 2026.

SILVER SURPASSES MICROSOFT TO BECOME THE 5TH LARGEST ASSET BY MARKET CAP: INFINITYHEDGE

OPENAI RELEASED GPT-5.2: INFINITYHEDGE

* The launch comes just days after CEO Sam Altman internally declared a “code red".

* On GDPval⁠, an eval measuring well-specified knowledge work tasks across 44 occupations, GPT‑5.2 Thinking sets a new SOTA score. Specifically, GPT‑5.2 Thinking beats or ties top industry professionals on 70.9% of comparisons on GDPval knowledge work tasks, according to expert human judges. These tasks include making presentations, spreadsheets, and other artifacts. GPT‑5.2 Thinking produced outputs for GDPval tasks at >11x the speed and <1% the cost of expert professionals, suggesting that when paired with human oversight, GPT‑5.2 can help with professional work. Speed and cost estimates are based on historical metrics; speed in ChatGPT may vary.

- GPT‑5.2 is priced at $1.75/1M input tokens; $14/1M output tokens
- 400k context window
- 128k max output tokens

Link: https://openai.com/index/introducing-gpt-5-2

Wall Street Banks Revises 2026 Debt issuance Forecasts: INFINITYHEDGE

* Fed’s plan to buy $40 billion of Treasury bills a month triggered revisions in Wall Street banks’ 2026 debt issuance forecasts.

Barclays:
* Fed will be a major buyer of T-bills in the months ahead, buying about $55b/month for Dec., keeping this elevated pace through 1Q before dialing it back in April to an estimated $25b/month — up from prior call of $15b/month. This means the Fed could buy close to $525b in T-bills in 2026, up from prior projection of $345b, so net issuance to private investors will fall to just $220b from previous forecast of $400b — further alleviating bill supply pressures.

TD Securities:
* Expect the Fed to buy $425 billion in bills during FY2026 between RMPs and MBS reinvestments into bills, which is most of the net supply.

Bank of America:
* anticipates the Fed may have to keep an increased pace of purchases for longer to add enough reserves and stabilize money market rates. Expect the Fed will need to add back $150 billion to achieve ideal outcome.
* Fed will shift to UST coupons out to three years if they perceive bill investors are “being adversely affected” to limit their displacement.

Wells Fargo:
* $40 billion is on higher-end of expectations, but the Fed has suggested purchases will be sized to accommodate fluctuations in demand for Fed liabilities.

JPMorgan:
* Expect the Fed will keep purchases at $40 billion through mid-April before stepping down to a pace of $20 billion/month. Combined with the roughly $15 billion/month of MBS paydown reinvestments, the Fed will buy about $490 billion of T-bills in secondary market in 2026 versus prior forecast of $280 billion; now forecast just $274 billion of net T-bill issuance.
* Announcement of potential coupon purchases is preemptive, underscoring the Fed is attentive to disrupting the market.

TERRA LUNA FOUNDER DO KWON SENTENCED TO 15 YEARS IN PRISON: INFINITYHEDGE VIA INNERCITYPRESS

China Prepares as Much as $70 Billion in Chip Sector Incentives

At the maximum end, the proposal translates into the largest-ever state-backed semiconductor incentives program conceived, at a time nations from Europe to the Middle East are seeking to ensure local production and supply of a component considered critical to AI and national security.

SOME ORACLE DATA CENTERS FOR OPENAI DELAYED TO 2028 FROM 2027: BBG

ORACLE DELAYS ARE LARGELY DUE TO LABOUR AND MATERIAL SHORTAGES

ORACLE: THERE HAVE BEEN NO DELAYS TO ANY SITES REQUIRED TO MEET OUR CONTRACTUAL COMMITMENTS, ALL MILESTONES REMAIN ON TRACK

IS IT A BUBBLE? - Howard Marks (We recommend you should read/listen to The Full Memo here: link

Anyway We are sharing the Important 7 Parts (Long Summary): weekend read

PART 1: UNDERSTANDING BUBBLES:
* One of the most interesting aspects of bubbles is their regularity, not in terms of timing, but rather the progression they follow. Something new & seemingly revolutionary appears & worms its way into people's minds. It captures their imagination, & the excitement is overwhelming. The early participants enjoy huge gains. Those who merely look on feel incredible envy and regret and – motivated by the fear of continuing to miss out – pile in. They do this without knowledge of what the future will bring or concern about whether the price they're paying can possibly be expected to produce a reasonable return with a tolerable amount of risk. The end result for investors is inevitably painful in the short to medium term, although it's possible to end up ahead after enough years have passed.

* One might think the losses experienced when past bubbles popped would discourage the next one from forming. But that hasn't happened yet, and I'm sure it never will.

* The key realization seems to be that if people remained patient, prudent, analytical, & value-insistent, novel technologies would take many years and perhaps decades to be built out. Instead, the hysteria of the bubble causes the process to be compressed into a very short period – with some of the money going into life-changing investment in the winners but a lot of it being incinerated.

* The key thing to note here is that the new thing understandably inspires great enthusiasm, but bubbles are what happens when the enthusiasm reaches irrational proportions. Who can identify the boundary of rationality? Who can say when an optimistic market has become a bubble? It's just a matter of judgment.

* Marks reflects on his own history of calling bubbles, specifically the dot-com bubble of 2000 and the sub-prime crisis of 2007. He admits that in neither case did he possess "any expertise regarding the things that turned out to be the subjects of the bubbles". He was not a computer scientist in 1999 nor a mortgage banker in 2006. Instead, his edge came from observing "behavior taking place around me". This reinforces the memo's central thesis: one need not be an AI expert to identify an AI bubble; one merely needs to be an expert in human behavior.

PART 2: CRITICAL QUESTIONS: (Part 2 to 4)

* Who will be the winners, and what will they be worth?
If a new tech is assumed to be a world changer, it's invariably assumed that the leading companies possessing that tech will be of great value. But how accurate will that assumption prove to be? As Buffett pointed out in 1999, "[The automobile was] the most important invention, probably, of the first half of the 20th century… If you had seen at the time of the first cars how this country would develop in connection with autos, you would have said, 'This is the place I must be.' But of the 2,000 companies, as of a few years ago, only 3 car companies survived. So autos had an enormous impact on America but the opposite direction on investors."

In AI, there are some very strong leaders at present, including some of the world's strongest and richest companies. But new tech is notoriously disruptive. Will today's leaders prevail or give way to upstarts? How much will the arms race cost, and who will win?

* Will AI produce profits, & for whom?
Will AI be a monopoly or duopoly, in which one or two leading companies are able to charge dearly for the capabilities? Or will it be a highly competitive free-for-all in which a number of firms compete on price for users' spending on AI services, making it a commodity? Or, perhaps most likely, will it be a mix of leading companies and specialized players, some of whom compete on price and others through proprietary advantages. It's said that the services currently responding to AI queries, such as GPT, Gemini, lose money on every query they answer (of course, it's not unusual for participants in a new industry to offer "loss leaders" for a while). Will the leading tech firms – used to success in winner-take-all markets – be content to experience losses in their AI businesses for years in order to gain share? Hundreds of billions of dollars are being committed to the race for AI leadership. Who will win, and what will be the result?

Altman: we'll build this sort of AGI and then ask it to figure out a way to generate an investment return from it." ("It's a bet on A.G.I. or bust")

* What will be AI's impact on the companies that use it?
Clearly, AI will be a great tool for enhancing users' productivity by, among other things, replacing workers with computer-sourced labor & intelligence. But will this ability to cut costs add to the profit margins of the companies that employ it? Or will it simply enable price wars among those companies in the pursuit of customers? In that case, the savings might be passed on to the customers rather than garnered by the companies. In other words, is it possible AI will increase the efficiency of businesses without increasing their profitability?

PART 3: Circular Deals & Asset Life

* Should we worry about so-called "circular deals"?
In the telecom boom of the late 1990s, in which optical fiber became overbuilt, fiber-owning companies engaged in transactions with each other that permitted them to report profits. If two companies own fiber, they just have an asset on their books. But if each buys capacity from the other, they can both report profits...so they did. In other cases, manufacturers loaned network operators money to buy equipment from them, before the operators had customers to justify the buildout. All this resulted in profits that were illusory.

* OpenAI is set to receive billions from tech companies but also sends billions back to the same companies to pay for computing power and other services....OpenAI has made investment commitments to industry counterparties totaling $1.4t, even though it has yet to turn a profit.

* Goldman Sachs has estimated that Nvidia will make 15% of its sales next year from what critics also call circular deals.

* What will be the useful life of AI assets?
How many years of earnings growth should be counted on in assigning p/e ratios for AI-related stocks? Will chips and other aspects of AI infra last long enough to repay the debt undertaken to buy them? Will AGI be achieved? Will that be the end of progress, or might there be further revolutions, and what firms will win them? Will firms reach a position where technology is stable and they can extract economic value from it? Or will new technologies continually threaten to supplant older ones as the route to success? Dynamic change creates the opportunity for incredible new technologies, but that same dynamism can threaten the leading companies' reign.

PART 4:

* FINANCIAL REALITY:
"The AI data centre boom was never going to be financed with cash alone... JPMorgan analysts have done some sums on the back of a napkin, or possibly a tablecloth, and estimated the bill for the infrastructure build-out would come to $5tn (not including a tip).". ...(&) we have good reason to expect close to $0.5t in spending next year. Meanwhile, the biggest spenders (MSFT, Google, Amazon, Meta & Oracle) had only about $350b in the bank, collectively, as of the end of the Q3.

* (JPM estimate that to drive a 10% return on their modeled AI investments through 2030 would require —$650bln of annual revenue into perpetuity, which is an astonishingly large number. But for context, that equates to $34.72/mo from every current iPhone user, or $180/mo from every Netflix subscriber: infinityhedge)

(OpenAI needs to raise at least $207bn by 2030 so it can continue to lose money, HSBC estimates. Based on a total cumulative deal value of up to $1.8tn, OpenAI is heading for a data centre rental bill of about $620bn a year — though only a third of the contracted power is expected to be online by the end of this decade. HSBC’s model assumes that OpenAI’s rental costs will be a cumulative $792bn between the current year and 2030, rising to $1.4tn by 2033. HSBC’s estimates are very optimistic because Google is excluded entirely & we have china also)

* Oracle, Meta, google have issued 30y bonds to finance AI. In the case of the latter two, the yields on the bonds exceed those on Treasurys of like maturity by 100 basis points or less. Is it prudent to accept 30 years of technological uncertainty to make a fixed-income investment that yields little more than riskless debt? And will the investments funded with debt – in chips and data centers – maintain their level of productivity long enough for these 30-year obligations to be repaid?

(Oracle sold $18bn in bonds in Sept. alone; Meta sold $30bn in recent weeks and raised another $27bn in private debt last month; Alphabet sold $25bn in bonds. CoreWeave, small by comparison, has issued $7.5bn in debt this year.......Oracle is the only one with negative free cash flow. Its debt-to-equity ratio has surged to 500%: infinityhedge). Oracle’s cash burn increased in the quarter and its free cash flow reached a negative $10 billion. Overall, the company has about $106 billion in debt.

(Oracle Bonds are now trading more like junk bonds, as some data centers delay reports add to fears about profits from its AI investments. Paper losses for investors that bought the $18 billion of high-grade notes that Oracle sold in Sept. now totals about $1.35 billion. Cost of protecting Oracle’s debt against default jumps to highest since 2009)

* The use of off-balance sheet financing via SPVs, which were among the biggest contributors to Enron's precariousness and eventual collapse. SPV is a way to make it look like a company isn't doing the things the SPV is doing and doesn't have the debt the SPV does. Hyperscalers are setting up SPVs to hold data center assets and debt, keeping leverage off their main balance sheets. Marks warns that this creates "systemic risk" where the true leverage of the system is hidden from investors and regulators.

* For AI infra, the warning signs are flashing: vendor financing proliferates, coverage ratios thin, and hyperscalers leverage balance sheets to maintain capex velocity even as revenue momentum lags. We see both sides – genuine infrastructure expansion alongside financing gymnastics that recall the 2000 telecom bust. The boom may yet prove productive, but only if revenue catches up before credit tightens. When does healthy strain become systemic risk? That's the question we must answer before the market does.

PART 5:

OTHER POTENTIALLY WORRISOME FACTORS:
* A speculative asset (AI)...we don't know how much of it we're really going to need in two to five years.
* Lender personnel with incentives to make loans but no exposure to long-term consequences.
* The chance that future generations of AI chips will be more powerful, obsoleting existing ones or reducing their value as backing for debt.
* The possibility that the supply of AI capacity catches up with or surpasses the demand.
* Powerful competitors who vie for market share by cutting rental rates and running losses.

DOT-COM COMPARISON:

Bear Case (Similarities):
* A "change-the-world" narrative driving val.
* Suspect, circular revenue deals.
* The proliferation of SPVs and off-balance-sheet debt.
* $1 billion seed rounds

Bull Case (Differences):
* Product Reality: Unlike the "vaporware" of 1999, AI products exist at scale and have hundreds of millions of users.
* The absence of an IPO craze with prices doubling in a day.
* Well-established main players with revenues, profits, and cash flow
* Reasonable p/e ratios: Microsoft: 69x (2000) vs 32x (2025), Cisco: 101x (2000) vs. Nvidia's 30x (2025) (This valuation discrepancy is the strongest argument against a bubble)

PART 6:

HISTORICAL ANALOGUES:
* AI's closest historical analogue here may be not electric lighting but radio.

* When RCA started broadcasting in 1919, it was immediately clear that it had a powerful info tech on its hands. But less clear was how that would translate into business. "Would radio be a loss-leading marketing for department stores? A public service for broadcasting Sunday sermons? An ad-supported medium for entertainment?".. "All were possible. All were subjects of technological narratives." As a result, radio turned into one of the biggest bubbles in history – peaking in 1929, before losing 97% of its value in the crash. This wasn't an incidental sector; RCA was, along with Ford Motor, the most high-traded stock on the market. It was "the Nvidia of its day."

* In 1927, Lindbergh flew the first solo nonstop transatlantic flight from NY to Paris...It was the biggest tech demo of the day (ChatGPT-level-launch). "Expert investors appreciated correctly the importance of airplanes & air travel,".."the narrative of inevitability largely drowned out their caution. Technological uncertainty was framed as opportunity, not risk. The market overestimated how quickly the industry would achieve technological viability and profitability."....As a result, the bubble burst in 1929 – from its peak in May, aviation stocks dropped 96% by May 1932.

* Both helped inflate a bubble so big that when it burst, in 1929, it left us with the Great Depression.

* "The railroads were a bubble, they transformed America. Electricity was a bubble, & it transformed America. Broadband build-out of the late-1990s was a bubble that transformed America. I am not rooting for a bubble, and quite the contrary, I hope that the US economy doesn't experience another recession for many years. But given the amount of debt now flowing into AI data center construction, I think it's unlikely that AI will be the first transformative technology that isn't overbuilt and doesn't incur a brief painful correction".

IS AI FOLLOWING THE PATTERN?
"AI Could Be the Railroad of the 21st Century. Brace Yourself"

Sama:

"When bubbles happen, smart people get overexcited about a kernel of truth"

"While the parallels to past bubbles are inescapable, believers in the technology will argue that "this time it's different."...."But on the third hand, it must be borne in mind that behavior based on the belief that it's different is what causes it to not be different!"

PART 7:

BOTTOM LINE:
no one should go all-in; no one should stay all-out; A moderate position seems like the best approach. These days, people promoting real estate funds say, "Office buildings are so yesterday, but we're investing in the future through data centers," whereupon everyone nods in agreement. But data centers can be in shortage or in oversupply, and rental rates can surprise to the upside or the downside. As a result, they can be profitable… or not…

THE PRODUCTIVITY PARADOX:
* "If a lot of jobs are lost to AI, how will people be able to afford the additional goods AI enables to be produced?".
* if we eliminate large numbers of junior lawyers, analysts, doctors, where will we get the experienced veterans capable of solving serious problems requiring judgment and pattern recognition honed over decades?
* Finally, I'm concerned that a small number of highly educated multi-billionaires living on the coasts will be viewed as having created technology that puts millions out of work. This promises even more social and political division than we have now, making the world ripe for populist demagoguery.
* More Americans are turning 65 in 2025 than in any preceding year, and that approximately 16M baby boomers will retire between now and 2035. Could AI merely make up for that? There's an optimistic take for you.

Technological Recession for Consumers Powered by AI: INFINITYHEDGE

* RAM Shortage: The core issue driving this crisis is that memory manufacturers Samsung, SK Hynix, and Micron have strategically reallocated production capacity from consumer segments to HBM for AI data canters. AI data centers will consume massive quantities of HBM, LPDDR5X, and GDDR7 memory.

* Micron and Samsung Both are also pulling out of the consumer SSD market at the same time. Samsung is reportedly halting SATA SSD production in 2026, which would put pressure on the pricing of both SATA and M.2 NVMe SSD drives; Samsung's withdrawal has significantly more serious consumer implications than Micron's decision to exit the Crucial consumer brand.

* Samsung reportedly Also abruptly raised the DDR5 contract prices by 100%.

Impact:
* Samsung: expected to increase price of smartphones or downgrades on specs
* Dell: Price increases of 15-20% from mid-Dec. 2025.
* Lenovo: Price increases from Jan 1, 2026.
* HP: warned Price increases starting in May 2026.
* Memory downgrades: Entry-level Laptops may drop to 8GB, mid-range to 12GB, & high end may drop to 16GB RAM. Entry-level phones may drop to 4GB, mid-range to 6-8GB, & high end to 12GB.
* Storage downgrades: 64GB of storage instead of 128GB, 512GB SSD configuration reduced to 256GB, and 1TB models are being cut back to 512GB.
* GPU: AMD considering increasing prices in response to climbing prices of GDDR6 memory. Nvidia reportedly no longer supplying VRAM to its GPU board.
* Nintendo Switch, PlayStation and Xbox Series: might hike prices soon, global console adoption might stagnate.
* Other Electronics: smart TVs, routers, medical devices will be paying higher prices or facing supply delays.

Recovery Projections:
- 2026: Demand exceeds supply across all memory types, driving sustained price increases.
- 2027: Peak pricing and inventory depletion arrive
- 2028: New Megafabs in Korea, US, and Taiwan begin easing pressure.

Multiple experts warn that memory constraints could persist well beyond 2026:
- SK Hynix's Internal Analysis Suggests Tight Memory Supply Lasting Through 2028.
- TeamGroup Manager predicts deeply constrained memory through 2026, with serious relief only in 2027-2028.
- Counterpoint Research: Projects DRAM prices could double by late 2026 compared to early 2025.

YOU WILL OWN NOTHING AND BE HAPPY

JPMORGAN LAUNCHES FIRST TOKENIZED MONEY MARKET FUND ON ETHEREUM: INFINITYHEDGE VIA WSJ

* JPMORGAN TO SEED FUND WITH $100 MILLION INTERNAL CAPITAL

* JPMORGAN SEES 'MASSIVE' INTEREST IN TOKENIZATION FROM CLIENTS

Details:
* JPMorgan will seed the fund with $100 million of its own capital, and then open it to outside investors on Tuesday.

* Called My OnChain Net Yield Fund, or "MONY," the private fund is supported by JPMorgan's tokenization platform, Kinexys Digital Assets, and will be open to qualified investors, or individuals with at least $5 million in investments and institutions with a minimum of $25 million.

* Investors can subscribe to the MONY fund through the bank's Morgan Money portal, a money-market investing platform. In exchange, they will receive digital tokens in their crypto wallets.

The Week Ahead: infinityhedge

Mon:
* Cboe Futures to offer trading in Continuous Futures for BTC and ETH
* Saylor expected announce another BTC purchase

Tue: U.S. combined Oct & Nov Nonfarm Payrolls (Powell cited a weakening labor market as the main reason for cutting rates). Economists project a 50,000 increase in payrolls and a 4.5% unemployment rate, consistent with a sluggish, but not rapidly deteriorating, labor market. Fall in payrolls could help extend the rally and pull forward the first full rate-cut pricing from June to April.

Wed:
* Coinbase to launch prediction markets and tokenized stocks
* Fed’s Williams speaks

Fri:
* BOJ expected to hike rates (first hike since Jan) (Investors will keep a close eye on Ueda’s post-meeting press conference for clues on how many more rate hikes could lie ahead)
* Putin to hold a televised event
* Deadline for the U.S. Department of Justice to release Jeffrey Epstein-related files

TBA/Whole Week: Ukraine-US talks to continue as Ukraine willing to drop NATO ambitions

ICYMI:
* Vanguard Equity Quant Says Bitcoin Still a ‘Digital Labubu’ Toy, For Now.
* Tether Blocks Investor Sales While Pitching $20 Billion Funding
* Five cryptocurrency firms (Circle, Ripple, BitGo, Fidelity and Paxos) received preliminary approval to perform certain banking functions (they can hold assets in custody) from a US regulator on Friday.
* Wall Street Hedged Big Crypto Bet in $500M Ripple Deal. Two of the funds that put in money assessed that at least 90% of the company’s net asset value derived from a token XRP. The funds investing in Ripple were given the option to sell their shares back to Ripple after 3 or 4 years at a guaranteed annualized return of 10%.
* SpaceX Sets $800B Valuation, Confirms 2026 IPO Plans that would be aimed at funding an “insane flight rate” for its developmental Starship rocket, AI data centers in space and a base on the moon.

https://infinityhedge.substack.com/p/the-7-days-fe1