Syz the moment

Only **Amazon** is expected to generate a positive return on its massive AI capex through 2030 — even under the most generous assumptions (zero costs). Microsoft: -9.2% Alphabet: -15.7% Meta: -28.8% Oracle: -35.6% The AI arms race is getting expensive. Source: FT BraVoCycles Newsletter

Inflation has averaged >4% per year over the past 6 years. Powell's explanation? It was nearly all due to rolling “supply shocks" over which the Fed has no control. The truth: this inflation was made in Washington as it always is - from too much government borrowing/spending and too much government creation of money. Source: Charlie Bilello

Source: UBS, TME

Michael Burry reported that the upcoming public listings for SpaceX, OpenAI, and Anthropic are going to pull more capital out of the market than the entire dot-com wave of 2000. Adjusted for inflation, just these three companies will raise more money than the hundreds of tech firms that flooded the market at the peak of the 2000 bubble. The historical data from 2000 shows exactly why this is dangerous for stocks. That year, the market saw 446 IPOs raise a record $108.15 billion. The Nasdaq peaked on March 10, 2000, at the exact moment this massive supply of new shares hit the market, right before crashing 80%. The crash happened because of a simple liquidity drain. When giant companies go public, big institutional funds need cash to buy the new shares. To get that cash, they have to sell their existing stock positions. This creates immediate selling pressure on the most expensive tech stocks. Today, the setup is identical but much more concentrated. Instead of hundreds of small startups spreading out the drain, just three mega companies are absorbing the market's capital. This directly impacts current market leaders. Microsoft has 49% of its $627 billion cloud backlog tied to OpenAI, and Oracle has 54% of its pipeline dependent on it. The same big funds that need to buy the new IPOs are the ones currently holding these tech giants. In the first quarter of 2000, the average IPO nearly doubled on its first trading day because cash was easily available. By the fourth quarter, capital markets dried up. Gross IPO proceeds collapsed 63% in a single quarter, and average first-day gains dropped to just 14% as companies rushed into layoffs and bankruptcies. When an unprecedented amount of money is pulled out of existing stocks to fund a single massive IPO wave, the broader market historically runs out of the liquidity needed to sustain its peak. Source: Bull Theory

SOFR – FF is the spread between two key US short-term rates: 1/ SOFR (Secured Overnight Financing Rate): the rate at which financial institutions borrow cash overnight, collateralized by US Treasuries (i.e. in the repo market). 2/ FF (Federal Funds rate, usually the effective fed funds rate, EFFR): the rate at which banks lend reserves to each other unsecured overnight. So the spread is secured rate minus unsecured rate. Under textbook conditions, secured borrowing is cheaper than unsecured borrowing — you're posting Treasuries as collateral, so the lender takes less risk and accepts a lower rate. That makes SOFR – FF slightly negative (typically a few basis points below zero) in calm markets. This is the "normal" state. SOFR materially below FF — usually means abundant reserves and ample cash chasing limited collateral. Cash holders accept low secured rates because they have nowhere else to put it. This is typically a sign of: - The Fed's RRP (reverse repo facility) being heavily used - QE having left the system flush - or scarcity of high-quality collateral (Treasury bills, in particular). Source: zerohedge

$640 billion has been wiped out from Nvidia's market cap over the same period. Huawei's new chip architecture is now directly challenging the hardware scarcity narrative that supported Nvidia's $5 trillion valuation. Source: Bull Theory

$SNOW +27% IN AFTER-HOURS Q1 Adj EPS: $0.39 vs $0.32 est Q1 REV: $1.391B vs $1.324B est Source: Trend Spider

You don't pour billions into massive forward-deployed joint ventures if you think the next model release is going to take care of it. In the cloud supercycle, semis led and software followed (and you didn't need Qualcomm or ARM to tell you the value was migrating up the stack). In AI, the infra layer itself is telling us the application layer is a separate, massive opportunity they can't fully capture. Source: a16z @a16z