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VCP pattern

SpaceX AI Satellites are HUGE. They have a wingspan of 70 meters (229 ft) when deployed. To put that in perspective, a Boeing 747-8 has a wingspan of 68.4 meters (224.5 ft).

3 days ago, Elon Musk sat in front of JP Morgan’s 3,500 wealthiest investors and explained why the AI economy is moving to space: 1. Starship is the first rocket in history designed to be fully reusable. Every other mode of transport... planes, cars, ships... you take reusability for granted. Rockets have always been thrown away after one use. That ends with Starship. Once you achieve full reusability, the only cost is fuel. Starship runs on liquid oxygen and methane. Both are cheaper than jet fuel. 2. Sending cargo to orbit will soon cost less than international air freight. This is not a distant projection. It is the direct mathematical outcome of reusable rockets plus cheap propellant. The economics of space change entirely. 3. Starlink V3 is 10 to 20 times more capable than what's currently in orbit. The satellite is so large it can only launch on Starship. It cannot fit on any other rocket on Earth. 100 times more bandwidth. Half the latency. It may become the highest bandwidth, lowest latency communication system that exists. 4. AI and robots will consume bandwidth at a scale humans cannot picture. Peak human bandwidth is a few hundred bits per second. A computer runs at a trillion. The appetite of AI for data infrastructure will be unlike anything built for human use. Starlink V3 is being built for that world... not this one. 5. Data centers are moving to space. Not as an experiment. As the primary way to scale AI compute going forward. It is increasingly hard to build power plants on the ground. Nobody wants one near their home. Space removes that constraint entirely. 6. From the moon, you can scale to 1,000 terawatts of compute per year. From Earth... maybe 1. The moon has no atmosphere and one-sixth Earth's gravity. You can manufacture solar panels from moon materials and launch data centers with a railgun. No rockets needed. The math on this is not close. 7. Current human civilization uses less than one trillionth of the sun's energy output. You could scale to a million times Earth's entire economy and still be using less than one millionth of what the sun produces. The ceiling on what's possible is so far above us it barely registers as a ceiling. 8. There is not a single high-volume computer memory fab in America right now. Zero. The chips needed to build the AI future do not exist in sufficient quantity anywhere in the Western world. That is why SpaceX is building one. Not to compete. Because there is no other option. 9. SpaceX has been cash flow positive since around 2014. The IPO is not a distress move. Past funding rounds were not even fundraising... they were liquidity events for employees. The company bought back its own stock. The IPO is happening now because the next phase requires capital private markets cannot absorb. 10. The senior team has barely changed in over a decade. The CFO has been there 15 years. Musk joined as the seventh employee in 2002. He says people who believe in the mission don't leave. And above technical skill, he now looks for one thing... whether someone is genuinely a good person.

The 30m pivot might single handedly be the best reversal strategy I've ever seen in the markets Combine this with a high probability level like a key moving averages or gap support & you have an incredibly high probability low risk approach to buying pullbacks.. got long $RKLB today off the 50 EMA + 30m pivot bought some $MSCHP off the 50 EMA + 15m pivot & added some $TE off the 8 week EMA + 30m pivot If you are looking to buy relative strength on weakness this is about as good as it gets.

There is one concept I don't think I've ever seen properly explained in books or on FinX: The low of a Power Earnings Gap (PEG) often acts as a major support level. Why? Because a PEG isn't just a technical event. It's a fundamental re-rating. Institutions realize the company is worth much more than they previously thought. They rush to build positions, creating a large imbalance between buyers and sellers. The result? That earnings gap becomes an area where institutions often defend their positions. When price revisits the low of the PEG candle on lighter volume, it can offer one of the best low-risk, high-reward entries: Your risk is clearly defined below the PEG low. The reward can be substantial if the stock resumes leadership. You're buying where big money previously stepped in. Of course, it doesn't work every time. But in true market leaders, the PEG low often tells you where institutional conviction lives. $SNOW $AKAM are good examples of that concept playing out right now. Past example $JBHT $KEYS

While a chart like this may support 'buy and hold,' the more important point to raise is your age and where you are in terms of retirement, as well as risk-adjusted returns. The chart hides the many 30-50% drawdowns the S&P500 incurred over that 36-year span. 2000-2010 was a decade of no returns. Someone without cash flow must think about risk completely differently from someone else just starting their career in their 20s.

Your moving average isn't lying to you. You're reading it backwards. The same line tells two completely different stories, and which one you see depends on one thing most traders never check. Here's how the pros read the chart you're already looking at 👇

SpaceX could become larger than the public space market combined $SPCX SpaceX’s planned IPO valuation is reportedly targeting around $1.75T, based on an estimated IPO price of $135 per share. To put that into perspective, most public pure-play space companies — including $RKLB Rocket Lab, $PL Planet, $BKSY BlackSky, $ASTS AST SpaceMobile, and $RDW Redwire — trade at market caps in the low-single-digit billions or below. Even larger satellite and communication names such as $IRDM Iridium, $VSAT Viasat, and $GSAT Globalstar generally sit from the mid-single-digit billions to low tens of billions. The comparison becomes even more striking against aerospace and defense primes. $LMT Lockheed Martin, $RTX RTX, $NOC Northrop Grumman, $AIR Airbus, $BA Boeing, and $GE GE Aerospace trade around the $100B–$200B range. At $1.75T, SpaceX would be several times larger than any major aerospace-defense company and above the approximate $1.6T combined market cap of major public space-related names.

WATCH: Elon Musk's full technical update on how SpaceX plans to build AI data centers in space. Posted by SpaceX ahead of the IPO. About 31 minutes, with Ian Dahl from the Starlink team. Notes on this upload: ~ Audio boosted ~ Subtitle added ~ Timestamps added for easy navigation Timestamps ~ 0:00 Intro ~ 0:42 The Kardashev scale ~ 2:19 How big the sun is ~ 3:25 Energy we use vs the sun ~ 4:38 Why we go to space ~ 6:49 Solar power in orbit ~ 8:06 Three limits to scaling ~ 8:46 Starship and reusability ~ 11:41 Starship by the numbers ~ 12:39 Mass to orbit ~ 13:42 Data center in space ~ 15:13 Simpler than Starlink ~ 16:05 AI satellite design ~ 18:30 A rack of compute in orbit ~ 20:26 Million satellite constellation ~ 21:39 The Bastrop factory ~ 23:22 The chips ~ 24:16 The TeraFab ~ 25:46 Gigawatts to a terawatt ~ 27:04 The Moon mass driver The plan behind every orbital compute headline this month, straight from @elonmusk

A pressure cooker never looks dangerous. It just sits there. Quiet. Boring. Until the whistle. This chart did the exact same thing for weeks, and most traders scrolled right past it. Here’s what the whistle looked like 👇 #datapatterns

Thanks to @801010athlete for his post this weekend about $QCOM Weekly from 1999. Want to highlight it as well because it has been sitting in my head! Look closely at that upper wick weekly candle in the early part of that move. The stock was extended by many metrics. One thing you don't see is many many trims and sells along this rally. A lot of ADDS though as it pulls back and forms new short term bases. Does that weekly with that upper wick early out of the base remind you of any charts right now? Do your actions and thoughts even allow you for a potential move of this magnitude over 1 year? I can't help but think this reminds me of $ARM $DELL $MRVL and many others also. This exact structure and path is found in many big winners in the stock market. It is an incredible example of what "America's Greatest Opportunities" can provide. Again though, do any of your actions, thoughts, and strategy even allow for a move like this to be captured? Or would that one weekly candle and short term extension early out of the base prevent you from capitalizing? Food for thought!

Elon Musk literally broke down his 5-step process for applying first-principles thinking to build anything:

$SPCX unveiled AI1 which is its first AI compute satellite featuring a 150kW payload and deployable liquid cooling. Elon Musk says AI1 repurposes proven Starlink V3 power, cooling and laser-link technology into an orbiting AI compute platform.

$IREN ✅ Any nice person who follows me: are you good at math? So tell me approximately 400 MW gets $IREN 4.4 Billion ARR. 🤯 So an additional 5400 MW will increase ARR to ____? 🤔 -Add $NVDA, $DELL & $MSFT Deals to it. -Add $MIRANTIS AI Cloud Software acquisition. This is likely the most undervalued stock if you do your research thoroughly.

Watch @ElonMusk provide a technical update on SpaceX’s capability to manufacture, launch, and operate AI satellites at scale → spacexipo.com

Mark Cuban reveals how he protected himself from losing the 1.4 billion dollars he made selling Broadcast .com to Yahoo "We sold the company to Yahoo for stock. I had seen stocks go up and stocks go down. I told everybody, there's a good chance the whole thing could crash. Don't be greedy" "Pigs get fat, hogs get slaughtered. Don't get slaughtered" "I put together what they call a collar. I sold some of the upside to the Yahoo stock and protected myself by buying puts on the downside" "Three months later the internet stock market cratered. It was called one of the top 10 Wall Street trades of all time" "All I had to do was protect it and not get greedy and I'd be set for the rest of my life"

If all you ever did was: 1. Find trending stocks 2. Buy them at daily 21EMA 3. Ride them until it breaks you'd not have to worry about what others think of a stock. Study: $SIVE $INTC $MRVL $MU $NOK $SNDK All trends start at 21EMA. All of them.

The first phase of Tesla's planned fab is bigger than the entire CHIPS Act budget. The AI5 chip that just taped out won't be sold to anyone outside Tesla. This is the part of vertical integration that NVIDIA can't price into its forward guidance. *** Thank you @DavidCarbutt_ for the edit.

In February, we released our first full $NBIS model to X with and set a staggering $1,250 end of 2029 price target ($644 present value @ 18% discount rate) for our premium members. We have decided to open our full model for free this week. (link in first comment) Although all of our reports are free for readers, our price targets, portfolio allocations, present value calculations, and buy/hold/trim/sell zones are generally gated. Before we release our new $NBIS model next week, we have decided to open up our most popular model to date for everyone on the X community who has supported our work on $NBIS and many other names in AI infra. We appreciated you and hope you gain something on the way we think, what we got right, and more importantly what we got wrong. It's not easy to set a target so high with confidence when Nebius was trading under 100 a share at the time, but it's much easier when you put in the work, do the research, and actually base price targets on real numbers. The original report was published when most public analysis still treated Nebius as a GPU rental business. Our report instead modeled the company around power availability, connected MW, ARR per MW, utilization, customer funding, enterprise mix, and dilution. Several parts of that framework were correct. We correctly identified Nebius as a vertically integrated AI infrastructure platform rather than a simple reseller of GPU capacity. We correctly identified power and energization as the primary operating constraints. We correctly modeled revenue as a function of connected and monetized MW rather than applying a simple revenue growth rate. We correctly treated hyperscaler contracts as both revenue sources and financing instruments. We correctly identified customer prepayments, deferred revenue, operating cash flow, secured financing, and asset-backed financing as central components of the capital stack. We correctly identified Aether and the broader software layer as important to utilization, orchestration, customer integration, and long-term margin quality. We correctly expected enterprise, AI-native, and inference workloads to become more important over time. We correctly argued that equity outcomes would differ significantly across AI infrastructure companies depending on power control, capital structure, dilution, depreciation, and software integration. We were materially above most public and Wall Street valuation estimates. Our original public model included: Bear case: $752 Base case: $1246 Bull case: $1760 Those estimates were based on long-term infrastructure throughput and earnings power rather than near-term revenue alone. Several assumptions now appear too conservative. ARR per MW may be ramping faster than we expected. The original model assumed ARR per MW would increase gradually as rack density improved, utilization rose, and enterprise and inference mix expanded. Our modeled midpoint assumptions were: 2026: $9M per MW 2027: $11M per MW 2028: $13M per MW 2029: $15M per MW The current revenue and ARR trajectory suggests the starting point and slope may both need to move higher. Contracted power has expanded faster than expected. The original report assumed more than 3GW of contracted power by the end of 2026. The disclosed pipeline has since expanded beyond that level, increasing the potential long-term capacity base. Contracted power is not the same as energized capacity, but it increases the top of the future deployment funnel. The energization schedule may have been too conservative. The old model assumed approximately: 2026: 900 connected MW 2027: 1,500 connected MW 2028: 2,000 connected MW 2029: 2,650 connected MW That schedule already appeared aggressive at publication. New site announcements, construction progress, and disclosed capacity targets suggest the ramp may occur faster or reach a larger endpoint than our original base case. Customer funding appears stronger than expected. The original model assumed that prepayments and contract-related cash flow would fund a meaningful portion of the buildout. The increase in deferred revenue and operating cash flow suggests that customer commitments may be contributing more funding, and contributing it earlier, than our original assumptions. We will distinguish carefully between deferred revenue, cash prepayments, working capital movements, and operating cash flow in the update. Enterprise and AI-native mix may be ahead of our original assumptions. The old model assumed the following revenue mix: 2026: 85% hyperscaler, 15% cloud and enterprise 2027: 80% hyperscaler, 20% cloud and enterprise 2028: 72% hyperscaler, 28% cloud and enterprise 2029: 65% hyperscaler, 35% cloud and enterprise Current customer activity and product development suggest enterprise, inference, healthcare, life sciences, and AI-native workloads may be scaling faster than this path assumed. The capital structure has become more complex. The old model used scenario-based equity issuance assumptions. The updated model must now include: Basic share count Prefunded warrants Convertible notes Potential conversion dilution Interest expense Cash raised Customer funding Secured financing Asset-backed financing The old share-count framework is no longer detailed enough. CapEx will need to move higher. The original model used approximately $18B as the midpoint of 2026 CapEx. A larger contracted power base and faster site development may require higher spending. Higher CapEx can increase long-term value if the capacity is efficiently funded and monetized. It can also increase execution and financing risk. The update will evaluate both sides. The original report correctly identified the structure of the opportunity and was materially ahead of the market on valuation. The new report will update the assumptions where Nebius has moved faster than expected and add greater precision where the original model relied on incomplete information.