Alan Fournier

Trump: We're going to bomb your energy facilities if you don't open the Strait of Hormuz in 2 days. Iran: F off. Trump: OK, you have 5 more days. Iran: F off. Trump: Fine, we'll give you 10 days like you asked. Iran: We didn't ask for anything. F off.

Iran entered Day 25 with the following active positions: a formal 5-condition war termination document with zero flexibility, a parliamentary bill formalizing Hormuz sovereignty, $2 million per vessel fees being collected, Kharg Island fortified against seizure, the IRGC publicly calling the diplomatic process deception, and hotels in GCC countries declared military targets. Iran exits Day 25 with all of those positions intact plus a 10-day pause on the strike category it most wanted suspended, a US President publicly crediting Iran with requesting that pause, and zero concessions made on any of its five conditions. The positive-carry framework predicted exactly this outcome. A party earning positive carry on conflict duration has no incentive to concede anything in exchange for a pause. The pause removes cost without removing carry. Iran did not need to offer anything to receive it because Trump's own financial market sensitivity and domestic political constraints produced the pause without Iranian concession. Iran's leverage was structural, not negotiated. Trump's political model appears to be: diplomatic signals suppress energy prices and lift equities, which reduces political pressure, which buys time for the military option to develop. This model worked in earlier contexts where markets were willing to price diplomatic hope over supply arithmetic. It is failing here for a reason that I have been documenting for the last month. The supply shock is not sentiment-driven. It is physical. Hormuz is physically closed. Mines are physically in the water. Ras Laffan is physically under a 5-year force majeure. Iraqi fields are physically disrupted. Brent at $109 against a net 22 mb/d supply shock equivalent to COVID is not a sentiment problem that a diplomatic statement corrects. It is a physical supply problem that only physical Hormuz reopening corrects. Trump is attempting to use the tools that work on sentiment-driven markets against a physically-driven supply shock. The market will price the physical reality regardless of the diplomatic narrative, and it will do so increasingly clearly as the 10-day window progresses without a single additional barrel reaching the market. The irony is precise. Trump's financial market sensitivity, which we have identified as the primary driver of US negative carry in keeping the war going, has been weaponized against him. Iran understood that Trump would prioritize short-term market management over strategic consistency. The pause is the proof. Iran did not need to threaten markets directly. It simply needed to maintain its position long enough for Trump's own market anxiety to produce the concession Iran wanted.

Who did this lmao

“They Looked Iranian”: Security Footage Shows Trump Negotiating With White House Patio Umbrellas for Six Hours theshovel.com.au/2026/03/25/the…

*IRAN DOES NOT ACCEPT CEASEFIRE, PROMISES SWIFT DEATH TO AMERICA The stock market:

Leaked photo of Trump negotiating with Iran

Holy shit. Wow. This is HANDS DOWN the best take I’ve heard. If there is one video you listen to today it’s this one. Every single word of this and it’s a huge “f*ck you” to @antonioguterres for propping up the barbaric terrorist Islamic Regime in Iran. Must be shared everywhere in my opinion. Unfortunately I have no idea who this young British woman is to credit her, if you know who it is feel free to tag below.

🚨 FLASHBACK 11 years ago, then Senator Marco Rubio stood on principle and voted AGAINST the disastrous Obama-Iran Nuclear Deal. He warned it would fund terror, empower the mullahs, and put America at risk. History proved him RIGHT. Watch this. America is blessed with leaders who have foresight like this 🇺🇸 Believe it. For the Republic! Thank you @marcorubio

@TPLeds U can’t wait to hang down there Tim ❤️

🇮🇷 Iranians doing the Trump dance while waving American, Iranian, and Israeli flags. Three flags that were never supposed to be in the same sentence together.

Patriots' Offensive Line Surprised To Learn Super Bowl Was Yesterday buff.ly/8Ysn6xB

@isabelletanlee @kielporter Why not just buy $SATS stock?

Excitement around a potential SpaceX IPO is reaching fever pitch. With a proposed valuation of $1.5 trillion, investors are scrambling for last-minute exposure. In our latest How To, @kielporter and I break down the different ways to get in bloomberg.com/news/articles/…

Another quant unwind day in factor land. This is now 5 days in a row. I think we are getting closer and closer to having a larger episodic volatility event, similar to August 2024 and February 2018, as this de-grossing and alpha unwind ultimately begets a beta faceplant

@lisaabramowicz1 So most of it is not OpenAI, and tell me what is wrong with OpenAI?

OpenAI continues to be a dominant force behind the earnings of hyperscalers. Microsoft disclosed for the first time yesterday that 45% of its $625 billion book of future cloud contracts was from OpenAI. ft.com/content/42f83e…

This is the most important video for AI investors right now Eric Schmidt: “AI’s natural limit is electricity, not chips” The former $GOOGL CEO dropped the truth. Forget the chip shortage, power is bottleneck Find out who controls the power… and monetize every last megawatt

She didn’t understand but did you?

Get to work and invent something, you can’t take it from those that have and expert to have a free thriving society. Study history, capitalism is by no means perfect, but socialism has led to mass murder, this narrative of “fair share” is a like saying “let me take from them and give to you”, the history of that idea has led to tragedy.

James Talarico: "The top 1% in this country now owns more wealth than the entire middle class… Elon Musk, Mark Zuckerberg, and Jeff Bezos own more wealth than 165 million Americans combined. That's an unacceptable amount of inequality."

For people who were not kids during the dotcom bubble: Did absolutely everyone went around telling the world that it was a bubble ready to burst at any moment like everyone is doing now for AI?

@stevenfiorillo The AI bears on here are neither serious nor intelligent so good luck with creating a conversation. They are trying to spook retail which is helpful as far as I can tell. If short interest develops in only adds rocket fuel.

Dear AI Bears: Thank You For The False Narrative And The Cheaper Prices (Part 3) I’ll start by thanking the AI bears for grasping at any detail no matter how small, distorted, or taken out of context when building their case against the AI revolution. On Wednesday, Oracle ($ORCL) reported Q2 earnings for the 2026 fiscal year and gave the bears something new to cling to. Oracle has decided to go all-in on AI and cloud, but it is doing so by tapping the debt markets rather than primarily funding this buildout through operating cash flow. In Q2, total revenue came in at $16.1 billion, and we continued to watch a legacy technology titan transform itself. Cloud IaaS and SaaS accounted for $7.98 billion of total revenue, up 34% YoY. Meanwhile, the on-prem and software licensing business declined 3% YoY to $5.88 billion, highlighting the continued shift from legacy software to the cloud. Cloud Infrastructure (IaaS) generated $4.1 billion in revenue, up 68% YoY, while Cloud Applications (SaaS) grew 11% YoY to $3.9 billion. Oracle is staking its future on cloud and AI but the issue has become the funding approach. Bears have repeatedly cited the scale of hyperscaler CapEx, and Oracle just increased long-term debt from $82.24 billion to $99.98 billion. Citi published a research report indicating Oracle may need to raise $20–$30 billion in debt annually over the next three years based on the company’s expansion plans. The bears finally got what they wanted. They can point to Oracle and argue: · Negative net liquidity · Reliance on debt markets · Operating cash flow that cannot currently support CapEx objectives This has contributed to commentary like the following on major finance shows such as Power Lunch: “I think Michael Burry kind of suddenly made us realize that there really are a lot of uncertainties with regards to the future growth rate of these Magnificent Seven companies that are now competing in this AI race and in addition we know that there’s a lot of question marks about whether all this capital spending is going to pay off with a decent return. So suddenly there is a lot of uncertainty about the projections for strong growth in these seven companies.” I’m happy to have a serious, intellectual discussion on this topic, because I believe the AI bears are wrong and ultimately fighting a losing battle. Technology does not remain stagnant, it advances. The Magnificent Seven are arguably the strongest collection of businesses ever created, led by some of the most capable management teams in corporate history. We are not watching one company making an isolated bet on a radical idea that may or may not work. These companies are actively building products and services around AI because AI has already been established as the next frontier of computing. Can we really take the bear case seriously when the executive teams at $NVDA $MSFT $META $AMZN $GOOGL $AAPL $TSLA have built trillion and multi-trillion-dollar businesses are signaling that we are still early in the AI cycle and that this is the future? I would rather listen to Andy Jassy, Sundar Pichai, Elon Musk, Mark Zuckerberg, Jensen Huang, and Satya Nadella than a cohort of bears on the sidelines who do not work in technology and have no involvement in the direction these companies are taking. Statements like “there are question marks about whether all this capital spending is going to pay off with a decent return” are frustrating because they often sound like conclusions drawn from market caps and P/E ratios rather than from earnings calls, quarterly filings, and the operating results that have been unfolding for years. The statement is simply not supported by what we have been watching in real time. We have also seen what happens when CapEx is not treated as a priority. Here are the facts: In fiscal 2021, $AAPL allocated $11.09 billion to CapEx. Apple then allocated $10.71 billion in fiscal 2022, $19.96 billion in 2023, $9.45 billion in 2024, and $12.72 billion in 2025 for a total of $54.92 billion over the past five years. Since fiscal 2021, Apple increased annualized CapEx by $1.63 billion (14.7%). Over the same period, Apple generated $365.82 billion in revenue in fiscal 2021, which grew by $50.34 billion (13.76%) over the next four years to $416.16 billion. Apple’s cash from operations increased 7.16% ($7.44 billion) over the same period from $104.04 billion to $111.48 billion. Now look at what happens when $MSFT, $GOOGL, $META, and $AMZN take CapEx seriously. In fiscal 2021, Microsoft allocated $20.62 billion to CapEx, which grew 213% ($43.93 billion) to $64.55 billion in fiscal 2025. Over this five-year period, Microsoft allocated $181.64 billion toward CapEx. The impact on financial performance was substantial. In fiscal 2021, Microsoft generated $168.09 billion in revenue, which increased 67.61% ($113.64 billion) to $281.72 billion. Cash from operations increased 77.43% ($59.42 billion) over this period from $76.74 billion to $136.16 billion. Microsoft was not an outlier. Google, Amazon, and Meta had similar outcomes. In fiscal 2021, $GOOGL allocated $20.62 billion to CapEx, which increased 216.04% ($53.23 billion) to $77.87 billion in the TTM. Over the past five years, Google has allocated $218.78 billion to CapEx. Google’s revenue increased by $127.84 billion (49.62%) from $257.64 billion in 2021 to $385.47 billion in the TTM. Google’s cash from operations increased 65.22% ($59.77 billion) over the same period from $91.65 billion to $151.42 billion. Meta is a similar story. Meta’s CapEx increased 235.65% ($44.04 billion) over the same period, rising from $18.69 billion in 2021 to $62.73 billion in the TTM. This supported revenue growth of 60.65% ($71.53 billion), from $117.93 billion to $189.46 billion. Meta’s cash from operations expanded 86.49% ($49.89 billion) from $57.68 billion to $107.57 billion from 2021 to the TTM. For anyone to say there are “question marks” about whether this level of capital spending will produce a decent return is to ignore what has been happening quarter by quarter. Apple’s CapEx intensity increased modestly versus peers, while cloud and platform peers dramatically increased infrastructure investment and saw corresponding growth in revenue and operating cash flow. I believe the bears finally got what they wanted with Oracle’s earnings because Oracle has become a convenient scapegoat for the broader AI bear case. Oracle has $19.77 billion in cash and short-term investments and $0 in long-term investments. Long-term debt now stands at $99.98 billion, putting net liquidity at -$80.22 billion. Oracle also generated $22.3 billion in operating cash flow over the TTM while allocating $35.48 billion toward CapEx, resulting in FCF of -$13.18 billion (operating cash flow minus CapEx, as reported). Bears finally have a metric they can latch onto but Oracle is one company, and its balance sheet structure does not define the rest of the AI ecosystem. Bears should also keep in mind that debt funding is not automatically a problem; mismatch is. If Oracle’s RPO converts to revenue and margins hold, the funding mix could prove highly profitable. It is premature to treat Oracle as the definitive “poster child” for the AI bear thesis. Now compare Oracle’s position to the hyperscalers. Google has $98.5 billion in cash and short-term investments and another $63.8 billion in long-term investments. With $21.6 billion in long-term debt, Google’s net liquidity position is $140.69 billion. Google could eliminate 100% of long-term debt tomorrow without impairing its short-term liquidity. In the TTM, Google generated $151.42 billion in operating cash flow, exceeding the $77.87 billion allocated to CapEx, producing $73.55 billion in FCF. Microsoft has $102.01 billion in cash and short-term investments and another $10.28 billion in long-term investments. With $35.38 billion in long-term debt, Microsoft’s net liquidity position is $147.04 billion. Microsoft could eliminate 100% of long-term debt tomorrow without impairing its short-term liquidity. In the TTM, Microsoft generated $147.04 billion in operating cash flow, exceeding the $69.02 billion allocated to CapEx, producing $78.02 billion in FCF. Meta has $44.45 billion in cash and short-term investments and another $25.07 billion in long-term investments. With $28.83 billion in long-term debt, Meta’s net liquidity position is $40.69 billion. Meta could eliminate 100% of long-term debt tomorrow without impairing its short-term liquidity. In the TTM, Meta generated $107.57 billion in operating cash flow, exceeding the $62.73 billion allocated to CapEx, producing $44.84 billion in FCF. Amazon has $94.2 billion in cash and short-term investments and another $20 billion in long-term investments. With $57.94 billion in long-term debt, Amazon’s net liquidity position is $56.26 billion. Amazon could eliminate 100% of long-term debt tomorrow without impairing its short-term liquidity. In the TTM, Amazon generated $130.69 billion in operating cash flow, exceeding the $120.13 billion allocated to CapEx, producing $10.56 billion in FCF. While Oracle has negative net liquidity and negative FCF, the combination of Google, Microsoft, Amazon, and Meta tells the opposite story. Together, they hold $339.15 billion in cash and short-term investments and another $119.16 billion in long-term investments. After accounting for $143.76 billion in long-term debt, they still have a net liquidity position of $314.55 billion while generating $536.73 billion in operating cash flow and producing $206.97 billion in FCF. Bears can point to Oracle all they want, but Oracle’s situation does not impact Amazon, Meta, Microsoft, or Google and it does not change the trajectory of the AI revolution. I also believe many bears have not been reading the earnings calls. If they had, they would see the AI narrative remains firmly intact. Don’t worry I’ll do the work for them: MSFT • MSFT guided to increase total AI capacity by 80%+ this year and to roughly double total datacenter footprint over the next two years • MSFT highlighted a new flagship AI datacenter expected to scale to 2 gigawatts and go online next year • Reported deploying the first large-scale cluster of NVIDIA GB300s and improving token throughput for GPT-4.1 and GPT-5 by 30%+ per GPU • Azure AI Foundry scale of ~80,000 customers • Commercial RPO increased 50%+ to nearly $400B, with a 2-year weighted average duration GOOGL • Reiterated a full-stack AI approach and highlighted scaling both NVIDIA GPUs and Google’s TPUs • Announced shipping A4X Max instances powered by NVIDIA GB300 to Google Cloud customers • Gemini processing 7B tokens per minute via direct API use • Gemini app 650M MAUs with queries up 3x QoQ • Rolled out AI Mode globally across 40 languages, scaling to 75M+ daily active users with Search • 70%+ of existing Google Cloud customers use AI products as they emphasized larger deal momentum • GenAI model product revenue growth 200%+ YoY • Launched Gemini Enterprise 2M+ subscribers across 700 companies • Google Cloud backlog grew 46% QoQ to $155B AMZN • AWS grew 20% YoY to $33.0B in Q3 (re-acceleration) • Project Rainier launched a large AI compute cluster with 500,000 Trainium2 chips to build & deploy Anthropic’s Claude models • Announced Amazon EC2 P6e-GB200 UltraServers using NVIDIA Grace Blackwell Superchips for training/deploying very large models • Backlog/RPO (AWS) to $200B with additional deal activity after quarter-end META • AI recommendations drove engagement with 5% more time spent on Facebook and 10% on Threads in Q3 attributed to recommendation improvements; strong video momentum; and Reels scale commentary • More than 1B monthly actives already use Meta AI, with usage rising as model quality improves • Meta described capital deployment priorities as centered on AI products/models/business solutions and outlined steps to increase capacity • Meta highlighted the scale of business messaging and the goal of using Business AIs to help businesses automate/sell/support at low cost ORCL • RPO at $523B, up $68B sequentially and up 438% YoY • RPO to be recognized in the next 12 months grew 40% year over year • 211 live and planned regions worldwide • More than halfway through building 72 multicloud datacenters embedded inside AWS, Google Cloud, and Microsoft Azure • The multicloud database business is up 817% in Q2 • All top-five AI models are available in Oracle Cloud, including OpenAI, xAI, Google, and Meta models • Cloud revenue at $8B (up 33%) now accounts for half of Oracle’s total revenue • Cloud Infrastructure revenue at $4.1B, up 66%, with GPU-related revenue up 177% • Cloud database services up 30%; Autonomous Database up 43%; multicloud consumption up 817% At the end of the day, the AI bear case increasingly depends on taking a company-specific funding decision and projecting it onto an entire technology cycle that is being funded very differently by the companies actually leading it. Oracle may have chosen a more aggressive balance sheet path to accelerate capacity which creates real execution and timing risk but it does not invalidate the broader thesis. The hyperscalers and platform leaders are not hoping AI works as they are actively monetizing it today. We are witnessing the hyperscalers expand backlog and remaining performance obligations, and converting infrastructure investment into revenue growth and operating cash flow in real time. If someone wants to debate valuation, competitive dynamics, or the pace of demand, I’m all for it but the lazy narrative that “CapEx won’t earn a decent return” ignores what we have already witnessed since 2021. The companies investing the most aggressively are the same companies expanding revenue, widening cash generation, and strengthening strategic moats. Oracle is not proof that AI is a bubble. At most, Oracle is proof that funding choices matter and that execution matters. Meanwhile, the builders are telling you, quarter after quarter, that demand is still ramping, capacity is still constrained, and the opportunity set is still early. So yes, thank you AI bears for the cheaper prices and the recycled fear narrative. I’ll keep reading the filings, listening to the calls, and following the cash because when this cycle is judged in hindsight, it won’t be decided by who posted the best skepticism on TV. It will be decided by who built the infrastructure, captured the workloads, and compounded cash flows over the next decade. The reality is that the AI Bears just made great companies such as $NVDA, MSFT, AAPL, META, AMZN, and GOOGL cheaper on a forward basis. Below is a table I constructed based on the current fiscal year and the next two fiscal years. NVDA, WMT, MSFT, COST, and AAPL do not report on calendar years so you will see Jan 26, June 26, Aug 26, and Sep 26 to represent their current fiscal years then the next two years of consensus estimate projections to showcase the forward growth rates. META, AMZN, and GOOGL report on a calendar year so it will be a traditional 25,26,27 for the years. Currently $WMT trades at 44.20 times Jan 26 earnings and 25.15 times Jan 28 earnings with 25.76% of EPS growth over the next two years. $COST trades at 44 times Sep 26 earnings and 36.29 times Sep 28 earnings with 21.24% EPS growth. I am welcoming the ability to add to my positions in NVDA at 37.32 times Jan 26 earnings with an expected 104.90% EPS growth over the next two years which puts NVDA trading at 18.21 times Jan 28 earnings. NVDA is effectively a value stock here. Investors are also able to add to META at 19.17, AMZN at 23.73 times, and GOOGL at 24.45 times 2027 earnings. MSFT is trading at 21.20 times June 28 earnings while AAPL is trading at 27.58 times Sep 28 earnings. There are always pockets of the market that are expensive but its not lurking within the financials of NVDA, META, AMZN, MSFT, AAPL, and GOOGL. If we experience a continued drawdown these companies will get even cheaper on a forward basis so thank you AI Bears for allowing me to pick up more shares of companies I was planning on adding to anyway at lower forward valuations. In the short-term your help is always appreciated, and in the long-term I believe your likely to miss out on a tremendous amount of appreciation. @amitisinvesting @KrisPatel99 @RealMattMoney @Futurenvesting @FunOfInvesting @Kross_Roads @StockMarketNerd @sam_badawi @dhurstell @DivesTech @fundstrat @ChrisCamillo @altcap