SpaceX’s Earnings Took Off Like A Rocket SpaceX blasted past expectations in every division last quarter. ▶ The company’s rockets division saw revenue grow 6% last quarter from a year earlier. ▶ Revenue from SpaceX’s satellite internet service, Starlink, jumped 69%, fueled by a near-doubling in subscribers. ▶ SpaceX’s AI division – now dubbed "Super Intelligence", home to its new data center rental business and the Grok chatbot – saw revenue surge almost tenfold. 🔺 That growth helped the company swing from a $1.1 billion loss in the same period a year ago to a $4.4 billion profit last quarter, trouncing analyst estimates. Investors cheered, initially sending SpaceX’s shares higher. Takeaways 1️⃣ The bigger picture: It pays to have access to cash. SpaceX has muscled its way into the neocloud business, building and renting out data center capacity to AI customers. This year, it struck deals with Anthropic, Google, and open-source startup Reflection AI worth a combined $28 billion in annual revenue. No surprise that its AI division overtook Starlink as SpaceX’s biggest moneymaker last quarter. But building data centers takes cash, and not everyone can borrow cheaply – just ask OG neocloud CoreWeave. Yields on its unsecured bonds have surged past 15%, signaling that investors worry about being paid back. Comparable SpaceX bonds yield just 7%. That borrowing advantage, combined with its $90 billion cash war chest, gives SpaceX considerable firepower to expand while rivals struggle to bankroll their ambitions. 2️⃣ For markets: Hold on to your hat... Over the next few days, lockup restrictions covering roughly 35% of SpaceX’s shares are set to expire. That means early investors and company insiders will be free to sell – and with many sitting on life-changing paper gains, they might be tempted to cash in at least part of their winnings. ⚠️ That potential wave of selling, combined with growing investor jitters around AI, could weigh on SpaceX’s shares in the short term. $SPCX #SpaceX #AI

The IT sector accounts for half of global earnings growth this year. And if you thought that was impressive, just wait until 2027. According to Citigroup, tech's contribution to global earnings growth is expected to jump from 48% this year to a whopping 68% next year. That's despite overall earnings growth slowing from 35% to 16%. That kind of concentration is pretty unusual. Historically, the top-performing sector has accounted for around 40% of global earnings growth on average. Next year's forecast would be the second-highest concentration in three decades, beaten only by the energy sector's dominance during the 2022 energy crisis. The US looks particularly reliant on tech, with the sector expected to account for a staggering 78% of the country's earnings growth next year. But a market relying so heavily on a single sector and investment theme to keep it afloat is standing on shaky ground. Investors, beware... #Earnings #Stocks #AI

🔎 The Focus This Week: China’s Growth China’s economy grew by 4.5% last quarter, compared with 5% in the first and 4.3% in the second. That means growth over the past two quarters has been hovering around the lower end of the government’s 4.5% to 5% annual target. That explains why Beijing rolled out a flurry of stimulus measures in recent weeks, hoping to give the economy enough of a boost to hit the lower end of its full-year target. Those measures might do the trick in the short term. But they won't solve China's bigger problem: its consumers aren't spending nearly enough – leaving the economy increasingly reliant on exports to keep growing. Just look at the numbers. Over the past six months, retail sales have grown by an average of just 0.6% year over year, compared with more than 18% for exports. Now, while that export boom is helping keep China's economy afloat, it's creating headaches for the rest of the world. See, Chinese manufacturers aren't just churning out cheap toys and electronics anymore. They're increasingly making their mark in higher-value industries, from EVs and solar panels to robotics and advanced machinery. And thanks to their enormous scale, they can often produce those goods at prices that foreign rivals struggle to match. What's more, the Chinese government continues to give domestic manufacturers a helping hand through subsidies, cheap financing, and other incentives. That means China's export dominance isn't likely to fade anytime soon. And while that's good news for its own factories, it's less welcome elsewhere: cheaper Chinese goods are squeezing foreign manufacturers, putting jobs at risk, and stoking trade tensions. There’s a catch, though: China's export success could end up becoming its Achilles' heel. The US and Europe are already pushing back with tariffs and other trade barriers, and more countries could follow suit. If that happens, Chinese exporters could find themselves shut out of key markets, threatening the very engine that's keeping the economy running. That's why China's bigger challenge isn't simply hitting this year's growth target. It's finding a way to get its own consumers spending again, rather than relying on exports and repeated rounds of stimulus to do the heavy lifting. Until that happens, the country's economic troubles – and the trade tensions they're fueling – aren't going away. Read the full Finimize Weekly Brief – a recap of last week’s highlights and a preview of the key things to watch in the week ahead – here: finimize.substack.com/p/chin… #China @finimize

CoreWeave's Woes Could Be A Sign Of What's To Come CoreWeave has become the poster child for the debt-fueled AI spending boom – and perhaps the canary in the coal mine for the wider AI trade. The company pioneered the so-called “neocloud” business model. The playbook is simple: borrow heavily, issue shares, use the proceeds to build data centers, and rent them out to AI giants like OpenAI, Anthropic, and Microsoft. But with borrowing costs shooting higher, cracks are starting to show. CoreWeave has more than $50 billion in debt on its balance sheet, compared with a market value of less than $40 billion. Sure, it's sitting on $5.5 billion in cash. But it's also burning through money at a staggering pace. Free cash flow has averaged negative $5 billion over the past two quarters, and analysts expect a further $30 billion in cash outflows over the next four. That's nearly six times the cash CoreWeave has in the bank. In other words, the company will need to find a whole lot more money – whether by taking on more debt, selling shares, or issuing convertible bonds. And it's no stranger to tapping investors for cash: it's already raised capital ten times this year, averaging roughly once a month. Trouble is, with its shares and bonds both sliding, raising fresh capital is getting pricier by the day. Take CoreWeave's bonds maturing in 2032. When they were issued in June, they offered a yield of 9.6%. Today, that yield has climbed above 15%. That's firmly in distressed-debt territory. In fact, credit-default swaps – essentially insurance against a borrower going bust – suggest investors see a greater than 50% chance of CoreWeave defaulting within five years. But there's a more immediate headache. All else equal, CoreWeave would now have to pay roughly five percentage points more to borrow than it did just a few months ago. That's a roughly 50% jump in borrowing costs. And that's particularly painful when interest expenses are already swallowing a QUARTER of the company's revenue. Of course, CoreWeave could always raise money by issuing more shares instead. But with its stock price under pressure, it'd need to sell more of them to raise the same amount of cash. That means more dilution for existing shareholders. As if that weren't enough, competition is heating up too. Deep-pocketed players like SpaceX and Meta are muscling into the neocloud market, armed with stronger balance sheets and access to cheaper capital. Put it all together, and it's not hard to see why investors are getting nervous. And if CoreWeave's debt-fueled AI ambitions start to unravel, the big question is whether the rest of the AI trade could get caught in the fallout. Nvidia, which owns 10% of CoreWeave, might swoop in with a bailout. But whether CoreWeave defaults or gets rescued, neither outcome would exactly inspire confidence in the AI boom… #AI #CoreWeave Image credit: @HedgieMarkets

AI Could Make Us All Richer. Here Are Seven Ways To Spread The Wealth. AI could make the world a whole lot richer. But it could also put millions of people out of work while funneling even more wealth into the pockets of just a few tech giants. So policymakers and tech bosses are cooking up ways to spread the gains and soften the blow. Here are seven proposals, neatly rounded up by Bloomberg's Saijel Kishan – along with my take on each. 1️⃣ AI Dividends Governments could tax AI companies and distribute the proceeds directly to citizens, recognizing that AI models were trained on data created by ordinary people. However, many AI firms remain unprofitable, making profit-based taxation difficult. A 1% levy on revenue could offer an alternative. Another proposal involves sovereign wealth funds investing in AI companies, although converting investment gains into regular payments presents challenges. 2️⃣ Universal Basic Income UBI would provide everyone with regular government payments, helping reduce poverty and supporting displaced workers. However, the enormous cost, concerns about work incentives, and America's substantial national debt make widespread adoption unlikely. But taxing AI-generated wealth could help fund such payments. 3️⃣ Universal High Income Elon Musk envisions AI creating such extraordinary productivity gains that governments could guarantee everyone a comfortable income beyond basic necessities. However, the proposal lacks a clear funding mechanism and depends on an uncertain economic transformation. 4️⃣ Universal Basic Compute Sam Altman proposes giving everyone access to AI computing power that they could use, sell, or transfer. This would allow individuals to benefit directly from AI productivity without necessarily requiring government spending. However, fluctuating computing costs, volatile credit prices, and distribution challenges could complicate implementation. 5️⃣ Worker Retraining Retraining programs aim to help displaced workers transition into new industries, including healthcare and manufacturing. Yet retraining is expensive, career transitions are difficult, and supposedly secure jobs could eventually face automation themselves. Providing accessible AI education may offer a more adaptable solution. 6️⃣ Wage Insurance Wage insurance would temporarily compensate workers who accept lower-paying jobs after AI displacement. While easing financial transitions, it could prove expensive and difficult to administer. Establishing whether AI directly caused a salary reduction would also be challenging. Supporting completely unemployed workers may deserve greater priority. 7️⃣ Worker-Focused Tax Reforms Governments could tax AI usage to reduce incentives for replacing employees. Bridgewater Associates has proposed taxing businesses’ AI token consumption, potentially raising $600 billion by 2030. Such measures could encourage human employment while generating revenue for worker assistance.