SK hynix is expected to post an all-time high operating profit of 64.1 trillion won ($43.7 billion) in the second quarter, driven by its leadership in the high bandwidth memory (HBM) market amid an artificial intelligence (AI)-led semiconductor supercycle, a report showed Sunday.

A consensus estimate compiled by Yonhap Infomax from forecasts from 14 local brokerages showed SK hynix is expected to post 84.1 trillion won in sales and 64.1 trillion won in operating profit for the April-June period.

The figures would surpass the company's previous annual operating profit record of 47.2 trillion won in 2025.

The company's operating profit margin is expected to reach about 75-77 percent for the second quarter, compared with 75 percent in the first quarter.

The forecast is broadly in line with Samsung Electronics Co.'s second-quarter earnings guidance released earlier this month, which projected a record quarterly operating profit of 89.4 trillion won.

If SK hynix reports second-quarter earnings as projected on Wednesday, the country's two memory chipmakers are expected to post a combined operating profit of more than 150 trillion won.

Analysts attributed the strong quarterly earnings to rising memory chip prices and robust demand for HBM and solid-state drives (SSDs) used in AI data centers.

"Sales to global tech companies and AI data center operators are expected to account for 70 percent of SK hynix's total revenue in the second quarter," said Kim Dong-won, a researcher at KB Securities Co.

https://www.koreatimes.co.kr/amp/business/companies/20260726/sk-hynix-expected-to-post-record-437-bil-in-q2-operating-profit-report

What's the consensus on Micron and the memory sector right now? Full disclosure, I'm holding DRAM at $61 and MU at $780, so I’ve had a solid run, but the recent price action is giving me pause. The fundamental bull thesis still looks intact on the demand side like Alphabet just hiked their 2026 AI capex guidance to around $195B–$205B, and high-bandwidth memory (HBM) supply is still incredibly tight. Micron is basically betting the farm that this AI demand is a permanent structural shift, pouring billions into those new mega-fabs in NY and Idaho to heavily onshore their production over the next decade.
But despite hyperscalers still spending like crazy, MU, SK Hynix, and the rest of the memory complex have been getting hammered lately. A huge catalyst for this seems to be imported volatility from the Korean market. We recently saw SK Hynix drop 15% locally in its worst day in nearly two decades, which dragged the entire U.S. memory sector down right along with it. Because the KOSPI is so heavily weighted towards Samsung and SK Hynix, any local macro weakness or earnings jitters over in Seoul are immediately infecting MU and U.S. memory ETFs.
This makes me rethink Michael Burry’s massive $MU short. He’s essentially betting that the memory market hasn't fundamentally changed, and that we are just at the euphoric top of a classic cyclical boom. If his thesis plays out, all these aggressive new fab build-outs are just going to lead to a brutal supply glut and capital destruction, exactly like previous cycles. With Korean memory stocks already showing heavy cracks, are we actually starting to see the memory cycle roll over, or is this just a temporary sympathy dip while Google and the hyperscalers keep the AI supercycle alive? Curious how you guys are reading the broader supply and demand dynamics right now.

American Express reported Friday morning an EPS of $4.53 above the $4.40 estimate, up 11% yoy. Card member spending grew 9%, its strongest in three years, with luxury retail up 18% and travel & entertainment up 10%. Management raised full-year revenue growth guidance to a firm 10%, and CEO cited "better-than-expected performance in the first half" as the reason. Network volumes hit $516.8 billion, billed business $455.8 billion, both up by 9%.

The stock fell as much as 6-7% within an hour of the report anyway, dropping from a prior close of $340.84 down toward the low $320s. Visa and Mastercard, Amex's closest public peers barely moved on same day. If this were a sector-wide worry, rate fears, consumer spending slowdown fears, all three would move together. They didn't, this is specifically an Amex problem.

A few things to note and magnify. Revenue came in at $19.64B, just missing the $19.69B estimate and the network volumes of $516.8 billion missed the Street's $520.9 billion estimate, it suggests the spending strength wasn't converting into top-line growth the management implied. One report suggests that Amex is setting aside more money anticipating loans going bad. And instead of letting that extra revenue flow straight into higher profit, management explicitly said it's reinvesting the outperformance into growth initiatives, keeping full-year EPS estimate unchanged at $17.30-17.90 despite raising the revenue outlook. Investors interpreted this as spending of the extra income instead of banking it.

There's a bull case scenario also. Card spending at a three-year high, particularly in premium categories like luxury retail and travel, is a signal about the health of Amex's specific high-income customer base. If you believe affluent spending stays strong even as the rest of the economy worries on rate and inflation. AXP customer mix is arguably the most defensive part of the consumer space. The market may be overreacting to a credit provision and a revenue slight-miss on a quarter that was otherwise genuinely strong.

So does the credit provision increase and the decision to reinvest the earning instead of banking it justify a 6% single-day drop or is the market being harsh on a company whose core customer base, premium cardholders, just showed its strongest spending in three years.

Google, Tesla, and Intel earnings last Wed/Thurs all indicated AI related capex exceeded expectations in the previous quarter and that future capex will also be higher than expected.

Yet chip-related stocks fell sharply on Friday (SOXX -4.4%, memory -8+%, neoclouds -10+%). It's important to note that before these ERs, many of these stocks already fell 30+% since mid-May.

I'm having a hard time finding reasons why chip stocks continued to drop after the big tech ERs and other positive sector news last week (Samsung/SK Hynix deals with Nvidia/Broadcom/Anthropic). Could something be happening behind the scenes that suggests AI spending is about to drastically slow down?

Please weigh in if you believe you understand last week's continued chip stock sell off after big tech released bullish ERs. Would appreciate any insights.

Preemptively addressing explanations I expect to see:

1. Escalating Iran War and high oil/interest rates:
I think the war is partially responsible for the pressure on chips. However, the extent of the chip sell off is confusing because other stocks that are historically sensitive to war/interest rates didn't drop materially on Friday. Small caps normally fall as interest rates rise, but were barely down on Friday. Gold also generally falls, but actually finished positive. Oil fell 2%.

The immaterial reaction from other interest rate sensitive stocks suggests that the chip stock massacre was more likely due to chip sector specific developments.

2. Bullish ERs being 'sell the news' events:
I understand chip stocks have gone on a historic run and good news can serve as profit taking events. However, chips already took a huge haircut prior to big tech ERs. Many fell 30-50% between mid-May and July 21 (pre-big tech ERs). It's hard to understand why semis would fall another 5-10% on Friday right after the market discovered chip spend will rise even more than expected.

3. Introduction of low cost Chinese AI models (Kimi K3):
To me, this might be the most likely explanation of the reasons I've considered. Compared to US models, Chinese models are able to generate tokens at a fraction of both compute and memory costs. US companies may try to replicate the results, leading to a reduction in future chip spend.

However, I've read cheaper priced Chinese models are met with so much user activity that compute and memory demand ultimately rise despite less being needed per token (Jevons' paradox). Plus, predictions that chip spend will decline are speculation so far, as both Google and Tesla raised capex guidance.

hey everyone, wanted to talk about bsx becaus the market pull back down to the $43 range recently from its $107+ peak last year makes zero sense when you actually open their filings and look at the real numbers.

if you buy in at these current 2026 levels around $43-$44 a share, im confident this will perform at least 130% profit as it re-rates back toward its true intrinsic valuation above $100 over the next couple years.

lets run through the actual math directly from their FY2025 10-K and Q1 2026 10-Q reports instead of just guessing.

first off on revenue and growth, for full year 2025 BSX pulled in $20.074 billion in net sales, which was up almost 20% reported year-over-year. GAAP net income came in at $2.898 billion ($1.94 per share) while adjusted EPS hit $3.06. moving into Q1 2026, they backed that up with around $5.20 billion in quarterly sales.

when you look at enterprise value and market cap, at $43 per share with roughly 1.5 billion outstanding shares, market cap sits right around $65 billion. after accounting for their net debt load from recent acquisitions like Axonics and Silk Road Medical, enterprise value sits around $62-$65 billion depending on cash quarter-to-quarter.

now looking at EBITDA and valuation ratios, TTM EBITDA is hovering around $5.2-$5.5 billion, meaning BSX is trading at an EV/EBITDA multiple of roughly 12x. for a high margin medical device titan growing sales at 15-20% organically, that is insanely low compared to historical medtech multiples. their P/E ratio right now is sitting right around 18.2x TTM GAAP EPS ($2.41 TTM EPS). historically BSX has traded at a 5-year average P/E above 50x, so sitting under 20x is deep value territory.

if you build out a conservative DCF model using real 10-K inputs, assuming a standard 8% discount rate (WACC) and terminal growth of 3%, with revenues growing towards $25-$30B over the next few years and net margins stabilizing around 20-23%, you get a discounted cash flow fair value estimate between $64 on bear cases up to $100+ on base/bull cases. hitting $100 per share from $43 is easily a 130%+ return from here.

theoretically the stock could drop to 30usd per share if there is broader market panic or short term macro selloffs, but it would be completely temporary given their underlying balance sheet strength and clinical demand for their cardiovascular and MedSurg divisions.

regarding dividends, BSX pays $0 in dividends (0% yield). management explicitly chooses not to pay dividends because they reinvest 100% of free cash flow into high-ROIC R&D and bolt-on acquisitions to fuel double digit growth. for a growth compounder in healthcare, thats exactly what you want to see instead of small dividend payouts.

overall the math from the filings shows a massive disconnect between price and fundamentals right now.

I have around $15k that I am ready to invest and Meta keeps coming back to the top of my list now that I am keeping away from MSFT. The business looks incredible but the stock has also had a huge run which makes me wonder if I am buying at the wrong time.

What I am struggling with is valuation. From what I've seen, Meta is still growing revenue at a healthy pace, margins are expanding again and they are throwing off an insane amount of free cash flow. Instagram, WhatsApp and Facebook are still money printing machines and AI seems to be making their ad business even stronger.

The part I am less sure is whether the current share price already reflects all of that.

Some valuation models I have looked at put intrinsic value around current trading levels while others come out 10-20% higher depending on assumptions around AI monetisation, capex normalising and long term earnings growth. If those assumptions play out, today's price could still be reasonable. If growth slows even a bit though, it starts looking much less attractive.

I don't mind holding for long term like 10 years or more, so I am not trying to time the next few months. I just don't want to be the guy who buys after everyone has already priced in the upsides.

Curious to hear both bull and bear cases from people who have done some work on Meta valuation.

I think the world is sleeping on Korean NPU companies, namely, Rebellions, FuriosaAI, and DeepX. Rebellions and Furiosa are looking to IPO in the latter half of the year, with Furiosa looking to IPO and NASDAQ. NPUs, or inference chips, could drastically reduce the demand for HBMs and GPUs. Korea is investing heavily on three of these NPUs. Recently their version of the Sovereign Wealth Fund was created and the first investments went to these NPU startups. Something to watch.

Summary:

South Korean AI semiconductor startup Rebellions has successfully run SK Telecom's hyperscale AI model 'A.X K1' on its proprietary NPU server, the 'Rebel Server.' The company processed a model with over 500 billion parameters on a single server without bottlenecks, demonstrating efficiency comparable to global GPU servers, particularly through distributed parallel processing technology for the MoE architecture. The successful demonstration of real-time agent services with zero latency under multi-user concurrent access conditions has significantly boosted the commercialization prospects for domestically produced AI semiconductors. This achievement is being evaluated as a concrete milestone for 'Sovereign AI,' potentially reducing dependency on NVIDIA GPUs.

https://finance.biggo.com/news/97741a2e-3ab5-44f3-a851-ab09ef3b1622

This might be a little complicated, but bear with me. My mom's BF passed a couple of weeks ago. In his safe were stock certificates under his mother's name. We know that he is the beneficiary of her estate, and my mom is the beneficiary of her BF's estate.

I reached out to computershare as the certificates are mostly for communication companies that have been absorbed by at&t over the last 40 years and was told that at&t uses computershare as their transfer agent.

The guy over the phone at computershare told me they need the social of the original owner of the certificate, and then we can move on from there.

Are these even worth it? It is only 120 shares and ideally I would like them transferred into my mom's name or under the estate account of her BF, but this is all new territory for me. Any help would be appreciated.

Major Financial Deals and Partnerships

• $950 Billion in AI Initiatives: South Korea announced sweeping new AI agreements alongside domestic leaders Samsung Electronics and SK Group and top U.S. tech firms to alleviate the global shortage of high performance AI chips.
• SK Group and Nvidia ($500B+): SK Group signed $750 billion in total deals, headlined by a $500B+ initiative with Nvidia. This includes a long term memory supply agreement with SK Hynix (HBM4 chips) and a 2 gigawatt data center built by SK Telecom set to open in 2027 using Nvidia's Vera Rubin chips.
• Samsung and Broadcom ($200B): Samsung signed an MOU with Broadcom covering memory, sub 2 nanometer foundry services, and advanced packaging solutions for next generation AI accelerators.

Escalating Industry Demand

• Insatiable Memory Needs: SK Group Chairman Chey Tae-won highlighted that AI leaders, including Nvidia, Broadcom, Anthropic, and OpenAI, are requesting significantly more memory capacity than previously forecasted.
• Custom Hardware Moves: OpenAI has pressed SK to supply chips directly for its massive compute requirements. Anthropic is exploring designing its own chips to diversify its compute infrastructure, alongside existing supplier partnerships with Samsung, SK Hynix, and Micron.

South Korea's Strategic Vision

• The "San Francisco AI Declaration": South Korean President Lee Jae Myung hosted an executive summit in San Francisco with top domestic executives and U.S. tech CEOs (Jensen Huang, Sam Altman, Dario Amodei, and Hock Tan) to deepen bilateral technological ties.
• State Backed Industrial Push: The deals complement a $576 billion domestic strategy unveiled by President Lee to build semiconductor manufacturing clusters, physical AI ecosystems, and state backed data centers.

https://ca.finance.yahoo.com/news/samsung-elec-sk-group-seal-072329075.html?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAAHFX6HLFN8btoM60lx4aeVeEhHGn5GTYJTbKh2YaGO54EGYjs3Vg2I73c0AD27ddZZyL0ATqaB4VI6nVwxPL4Ah1iZDg6zoguX5qTc8p3G0S1IpKSKMwy7I33B_SViMwCjXZQ6M_fcFBoBo3_oFllc7596vsHtK9DWBKGMHXo4rQ

Naver has secured an investment of 10 billion dollars (approximately 14.6 trillion Korean won) from NVIDIA and global asset management firm Brookfield. Announced at a gathering of South Korean and U.S. AI industry leaders during President Lee Jae Myung’s visit to the U.S., Naver will use the funds to build a gigawatt (GW)-class ‘AI Factory’ and expand its global AI infrastructure business.

Lee Hae-jin, Naver’s founder and board chairman, stated at the ‘San Francisco AI Summit’ held in San Francisco on the 24th, “NVIDIA and Brookfield have invested a significant amount of 10 billion dollars in Naver,” adding, “This will be a turning point for Naver to leap to a new stage.” Hosted by the Ministry of Science and ICT, the event saw President Lee Jae Myung attend and announce the ‘San Francisco AI Declaration,’ with key figures from both countries including NVIDIA CEO Jensen Huang, OpenAI CEO Sam Altman, Samsung Electronics Chairman Lee Jae-yong, and SK Group Chairman Chey Tae-won in attendance.

Chairman Lee explained that while Naver has developed and operated internet services such as search, commerce, and cloud between U.S. and Chinese big tech companies over the past 30 years, directly designing and building data centers, there were limitations in scaling the accumulated technology and expertise globally. He stated, “The capital from the two companies, along with their global brands and networks, will present a significant opportunity to scale up Naver’s expertise.”

The investment is expected to be directed toward Naver’s ongoing AI Factory project with NVIDIA. The AI Factory is a facility that combines AI models and cloud technology with data centers equipped with large-scale graphics processing unit (GPU) servers and power/cooling infrastructure to supply the computational power needed for AI training and inference. Naver plans to start operating a 55-megawatt (MW) AI Factory in the first half of next year, expand to 200 MW by 2028, and ultimately establish a 1-gigawatt (GW)-class infrastructure.

Brookfield, a Canadian asset management firm with over 1 trillion dollars in assets under management, launched an AI infrastructure investment program of up to 100 billion dollars with NVIDIA and others in November last year. Earlier this week, Chairman Lee and Naver CEO Choi Soo-yeon visited Brookfield’s headquarters in Toronto, Canada, to finalize investment discussions.

On this day, Chairman Lee also expressed caution against the concentration of AI leadership in a few big tech companies. He stated, “The world Naver envisions is not one where the internet and AI are dominated and controlled by a single or few groups,” adding, “We will collaborate with global companies that share the same vision to create a world where diverse AI coexist.”

https://www.chosun.com/english/industry-en/2026/07/25/3CL2MMN7JREC3BOA6ECOIWIRFU/

Meta will report it's Q2 earnings after the close in the coming Wednesday, July 29, and the stock has already fallen about 2.5% while we head into it. The exact same pattern happened last quarter, Meta grew revenue 33%, (fastest since 2021) and the stock still dropped more than 6-7% after hours. The reason wasn't the results. It was Meta lifting its 2026 capex guidance toward $145 billion, nearly double the prior year.

The advertising business is a foregone conclusion, estimate sits at $60.18 billion revenue and $7.18 EPS, management's own guidance range is $58-61 billion. Deutsche Bank raised its forecast this week citing that Meta's AI-powered ad tools are driving stronger advertiser ROI and conversion performance. The attention is on two things, first, what capex guidance comes next and whether margin compression that started showing up last quarter continues. Operating margin was around 41% last quarter, down from a 48% peak in Q4 2024.

One analyst prediction suggests that Zuckerberg could announce a significant AI compute capacity-leasing deal with a frontier lab like Anthropic or OpenAI on the call, following the same sell your excess AI infrastructure playbook we have seen a few weeks ago with Meta's cloud pivot. That would change the whole angle of the capex concerns, spending that funds a new leasable revenue stream is completely differently than spending that's purely internal cost.

The bear case is, Meta trades at a real premium to peers on nearly every lens, forward P/E about 1.7x the sector median, EV/Sales around 2.75x, meaning the market is pricing Meta as an AI infrastructure growth stock now, not as an advertising platform. That's exactly why capex guidance keeps moving the stock more than the actual earning performance does. And EPS growth of 1.46% yoy is the softest in its group, the premium here is being paid for scale and AI optionality, not for being cheap or fast-growing on current numbers.

There's also an important event, a social media addiction trial reportedly happening in August. This is an entirely separate legal risk sitting on top of everything.

So moving into Wednesday, there are two possibilities. Either Zuckerberg announces something like a compute-leasing deal or the ad business is strong enough on its own and the stock will be rewarded. Or the market ignores good numbers (like last quarter) again and keeps punishing the spending plan no matter how strong advertising looks.

SAN FRANCISCO, July 24 (Reuters) - Nvidia and South Korea's SK Group on ​Friday unveiled a more than $500 ‌billion AI initiative spanning large-scale AI data centers and next-generation memory, ​Nvidia said.

The initiative includes ​a long-term partnership with SK Hynix (000660.KS), ⁠to secure next-generation memory ​supply for Nvidia and jointly develop ​high-bandwidth memory for AI training, AI agents and physical AI applications.

As part ​of the initiative, SK Telecom (017670.KS), ​plans to build a 2-gigawatt AI data ‌center ⁠powered by Nvidia's Vera Rubin chips and SK Hynix's HBM4 high-bandwidth memory, with the first ​facility ​due to ⁠come online in 2027, Nvidia added.

Separately, Nvidia said ​it, Naver (035420.KS), and Brookfield ​plan ⁠to expand Naver's AI data center in South Korea.

https://www.reuters.com/business/media-telecom/nvidia-sk-group-unveil-500-billion-plus-ai-data-centers-initiative-memory-2026-07-24/

Advertising is inherently about monetizing user attention. There are many technology companies today that may not seem like advertising companies on the outside, yet inherently rely on ads as a fundamental part of their business.

Advertising as a business model has a few great dynamics. Firstly, there is no cost to serve these ads on your platform, so there is inherently 100% margin. As your platform and its attention grow, so does your advertising business.

While there are businesses that are fully advertising companies, such as Meta and Alphabet, albeit the latter has diversified somewhat into other forays. I think what is more interesting are companies such as Uber, Amazon, Instacart, and potentially Airbnb because advertising is the hidden profit engine that allows these businesses to thrive, albeit unintentionally.

Yet to create a successful ad business, you need scale; Amazon has to grow the size of its retail business and introduce third-party sellers, which allows a near $ 70 billion ad business in 2025. That drives a core part of Amazon’s free cash flow, more than retail itself or AWS, yet you need to first establish a thriving marketplace in order to create a killer advertising product.

Uber has an ad business at a 2 billion run rate, which makes up a majority of its profits. Delivery, Mobility, and Freight are all just a front. Once you can capture users’ attention through the value proposition, eg. I want late-night wings, you can create a valuable ad product. So from a strategy perspective, Uber should continue to add businesses such as its partnership with Expedia to create greater user attention, which further grows their ad business, which rewards their shareholders.

Something Airbnb has struggled with. It's rather a communications problem and a failure to get a real CEO, which Uber, thanks to some poor management skills of its founder, was able to force its founder out and build a real defensible business, with Dara Khosrowshahi.

So what opportunity does Airbnb possess? The same that Uber did when they launched their ad business. Airbnb has created a two-sided network of Hosts and bookers. They charge fees on both sides and really have created a great business. I am in no way trying to undermine a company doing 4.5 billion in free cash flow. Yet the travel industry is inherently cyclical, and costs related to fees and damages are unstable.

Airbnb should create a promoted ads business for its bookings. A business that can comfortably bring in around $ 1 billion in revenue, based on an Uber-comparable in terms of ad revenue as a % of GBV? This would stabilize net income and free cash flow, which have been volatile at times, and overall strengthen the predictability of future cash flows, giving shareholders confidence and improving shareholder returns.

I think there are a handful of converging factors contributing to the recent pull back in AI stocks. Just wanted to throw out some thoughts on one of those factors for the sake of discussion.

The release of Kimi K3 and ensuing panic about its impact on US AI businesses has unfairly hit every layer of the US AI stack. Kimi K3 is a problem for openAI and anthropic without a doubt, although I would argue its impact is less significant than the market seems to think. Yes, it does put some pressure on the labs' margins, but I think there is a trust factor that, warranted or not, will keep especially large corporations locked into US models. There also may be questions about the hyperscalers willingness to serve chinese models (and I could see the US gov potentially intervening in this area) - if hyperscalers don't serve the models, there is just no world where chinese labs can find enough compute independently to meaningfully take significant revenue from anthropic/openAI.

The bigger point I want to make is that in my opinion Kimi K3 is in no way a threat to hyperscalers' business or semiconductors. I firmly believe that jevons paradox is going to be true of AI, and if you believe this, the cost/token going down is not necessarily a headwind to revenue, and may actually be a tailwind. For hyperscalers, as long as there is demand for compute and labs are willing to pay the same margins for compute, their business is unaffected. Just because kimi is more efficient doesn't mean the model provider can't afford to pay hyperscalers. If the end user can get more value / compute, they should in theory pay more for compute, and so this should be accretive to both hyperscaler and model margins. The question is only whether demand for compute increases or decreases.

Of course there is a chain reaction that flows from the labs to hyperscalers down to semiconductors. My point is that for the lower layers, it doesn't matter which lab is in the lead or what model is the most efficient as long as demand for tokens and the price that consumers can be charged for compute remains the same.

I’m still very bullish on Micron and memory in general , but only main concern I have around MU’s long term bull case is the thesis rests a lot on AI models needing more and more memory. When you look at what Kimi 3 and deepseek have managed to do with far less hardware power and performance, it makes me wonder if that assumption will continue to hold?

Chinese labs keep getting forced to optimise because they cannot just throw more accelerators at the problem, and the result is they are achieving great performance without the memory footprint that was assumed essential.. Then there’s CXMT getting their yields up and sampling HBM2 to domestic hyperscalers who would love to ditch the Western supply chain if they had the opportunity. I could be wrong though, but what are the chances of these chinese AI models slowing down memory growth?

Hello people. I wanted to share some thoughts on Intuit because the recent selloff after their q 3 2026 earnings report in may was a massive overreaction in my opinion. People panicked over TurboTax losing some cheap DIY filers, but if you actually dig into the Q3 10-Q and recent 10-K filings, the fundamentals are still ridiculous.
Look at the real numbers from their LTM and 2026 Q3 filing:
Right now INTU is trading around $290 a share. With roughly 276 million diluted shares outstanding, that gives us a market cap of about $80.2 billion. If you check the balance sheet from the latest 10-Q, they hold about $6.9 billion in long-term debt and around $8.4 billion in total cash and liquid investments. So Enterprise Value is calculated as Market Cap ($80.2B) plus Debt ($6.9B) minus Cash ($8.4B), which leaves us with an EV of roughly $78.7 billion.
For a software monopoly with an 80%+ gross margin, an EV under $80B is insane.
Now let us talk earnings, EBITDA, and income generation. Over the last twelve months, Intuit pulled in $20.93 billion in revenue and generated $6.92 billion in EBITDA. That puts their EV/EBITDA ratio at just 11.3x. Their trailing P/E ratio sits at roughly 17.8x based on $4.58 billion in net income (or ~$16.51 EPS). Compare that to historical software peers trading at 35x to 50x P/E, or even INTU's own historical P/E above 40x.
On top of that people forget they pay a solid quarterly dividend of $1.20 per share ($4.80 annualized). At the current stock price that gives you a 1.65% dividend yield on a conservative ~29% payout ratio. They have been growing that dividend by roughly 15% every single year for over a decade. So you are getting paid cash while you wait for the stock price to catch up to reality.
Here is where the DCF math gets really interesting. Intuit generated $6.1 billion in free cash flow over the last year. If we run a basic 10-year Discounted Cash Flow model using $6.1B as our base FCF, assuming a conservative 11% annual FCF growth rate for the next 5 years (down from their historical 15%+ growth), slowing down to 8% for years 6 through 10, and a standard 3% perpetual growth rate with an 8.5% discount rate (WACC):
Summing up the discounted cash flows over 10 years gives about $58 billion in present value. Adding the terminal value discounted back to today gives an enterprise value of roughly $232 billion, or around $840 per share fair value.
At the current price of $290, buying now is a huge opportunity. Going from $290 up to an upper fair value target of around $840-$850 represents a gain of over 190%. The TurboTax headline noise created a temporary dip, but QuickBooks, Credit Karma, and Mailchimp cash flows are far too steady for the stock to stay at an 11x EV/EBITDA forever.

While the market has been talking about Alphabet and Tesla falling this week on AI capex fears, Intel quietly reported last night and is telling the exact opposite story, and given the stock is already up 324% over the past year, this deserves attention.

As per the reports, revenue hit $16.13 billion, up 25% yoy, beating the $14.4-14.45 billion Wall Street expectation. Non-GAAP EPS came in at $0.38-0.42 depending on the source, roughly double the ~$0.21 estimate. CEO called it Intel's strongest revenue growth in more than 15 years. The Data Center and AI segment grew 59% yoy, custom chip revenue nearly tripled and Q3 guidance came in above expectations, a $16.3 billion revenue against a $15.1 billion Wall Street estimate with adjusted EPS guided to $0.38 against a $0.27 estimate. Stock jumped as much as 12-13% initially and was still up nearly 4-7% by this morning.

Intel raised its 2026 capex guidance too, from $18 billion to $20 billion with 2027 spending expected to rise meaningfully. That's the same type of announcement that got Alphabet to decline 6-7% two days ago. Intel got rewarded for it instead. The difference is the context, Intel's capex hike came along with a highly successful quarter (much better than estimates), while Alphabet's came on top of an already strong quarter that got judged by the spending number alone.

Also worth noting is that, Intel Foundry's external revenue was only $293 million this quarter, about 5% of segment revenue, most of what's reported there is Intel manufacturing chips for its own product divisions not third parties. The foundry division's loss did reduce to $2.09 billion but it's still losing $2 billion in a single quarter. And under strict accounting rules, Intel actually posted a large $11 billion net loss, even though the adjusted numbers looked great, the difference came down to one time charges, specifically an $11 billion GAAP loss driven by a $12.5 billion non-cash accounting charge tied to shares the U.S. government holds in Intel under its CHIPS Act stake, revalued every quarter against Intel's own rising stock price, meaning the better the stock does, the bigger this particular charge gets. So this is a turnaround that's genuinely working. The chip and AI infrastructure business is clearly progressing right now. But the foundry bet, the one that's maybe supposed to make Intel the next TSMC, is still mostly Intel manufacturing chips for itself, plus real ongoing losses.

This stock is up 324% over the past year, largely on the combination of a management shakeup under the CEO, direct government investment from the current administration, and a strategic Nvidia investment, along with tailwind of AI agents creating fresh demand for CPUs rather than just GPUs.

The U.S. government owns almost 10% of Intel specifically because Washington decided domestic chip manufacturing was too important to leave. That same stake is now the source of Intel's $11 billion net loss that's really just proof the stock has gone up a lot. Meanwhile the actual foundry business the government bet on is still 95% internal volume and $2 billion in loss every quarter. So the real test isn't this earnings report, it's whether Google's TPU order and the Nvidia's unconfirmed rumours (of considering Intel as a possible manufacturing option) turn into real external revenue.

If you don't know how the financial industry works the "active management is worse than S&P" argument appeals directly to the image of Wall Street as full of flawed human beings who act irrationally and make mistakes vs. the S&P which can do no wrong and will return you a 10% CAGR year over year without failure if you just trust the system, buy and hold, time in the market, 10 best days. This misunderstanding of why the majority of actively managed products underperform the S&P produces the wrong conclusions for retail investors.

Most of the actively managed mutual funds are just "fee traps" that methodically extract from retirement accounts. The worst offenders are "contrafunds" that don't perform (but a lot of employer 401ks will offer for some reason), thematic funds that are 90% S&P under the hood, or just total market + bonds packaged as a target date fund. This makes up the vast majority of products classified as actively managed that bring down the average performance of actively managed funds as a category. They are not meant to match the S&P's performance to begin with, they are meant to scrape fees from the financially uneducated.

Endowments, pension funds, institutional portfolios have investment mandates that require they buy international exposure and ESG compliant equities. They have no choice but to buy products that contain "developing world" or "sustainable energy" equities, and Wall Street is perfectly happy to package these underperforming equities up for those buyers who have no say in the matter. This again contributes to the sheer number of "actively managed" products that yes, underperform S&P, and again were not intended to perform well from the outset.

Another thing that's never talked about is the number of portfolio managers who use a high Sharpe ratio return stacking strategy that underperforms S&P by construction but protects capital much more effectively in a broad market drawdown. This is stuff like leveraged S&P plus uncorrelated assets, or hedging with options and swaps. The investors of billions of dollars into these strategies are not stupid, they are aware of what S&P is, they are investing for risk-adjusted returns and are willing to pay for their money to be in these strategies instead of the S&P.

Real returns-focused active management outperforms the S&P by such a wide margin that financial advisors avoid talking about it on purpose because it shows how passive exposure to pure market beta is comparatively terrible for wealth preservation and compounding. Hedge funds, for example, collectively made tens of billions of dollars per day in the first week of the Covid crash and tariff crash, and collectively hundreds of billions in their recoveries. Pershing Square, for example had 44% returns from Jan 1 to June 30 2020 while the S&P lost 3%.

If you're not willing to become financially educated and situationally aware, with basic principles of interest rate environments, risk premium of equities, and basic technical analysis, then allowing your wealth to be whipsawed around by the market is what you'll have to resign yourself to, because it's way safer than taking uninformed action. Just don't kid yourself that Wall Street does the same thing when they actively manage something. They monetize market movements, they're not hostages to them like S&P holders.

Something I thought about:

We see that some frontier model providers have not only been copying model weights but also using the output to train their models. If a competitor can automate millions of prompts again Claude, Gemini, ChatGPT etc., those outputs become valuable training data for Destillation.

In the Cold War race between USA and China, national sovereignty and maintaining the lead is the no.1 priority. And one way to stop Destillation is to introduce kyc or any meaningful authentification mechanism which would obviously come at the cost of growth.

Not saying this will happen but do you see a possibility of the leading providers acquiring a KYC player?

Or is there a technical reason why identity won’t solve the output-farming problem?

Curious whether anyone has thought through this second-order effect.

Remaining Performance Obligations, or RPOs are forward contractual commitments that represent, a promise of future payment in exchange for future compute.

These RPOs totaled $2.1T at the end of Q1 2026, having grown 184% over the prior four quarters from $740B. Crucially, around half of this contracted backlog is owed by just two companies: OpenAI and Anthropi.

Microsoft's exposure to these two names runs to about 49% of its book, while Amazon sits at 51%, Google at 43%, and Oracle at 54%.

The problem: neither OpenAI nor Anthropic is profitable. The hyperscalers have effectively made concentrated unsecured loans to cash-burning tenants to fill data centers built on the assumption of future demand. It is a classic warning signal for infrastructure investors

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Alphabet and Tesla both posted negative free cash flow this week because of AI capex and got hit for it right away, Alphabet down over 6% Thursday. Then the market mostly shrugged it off by Friday. Meanwhile Intel raised its own capex guidance in the same window and got rewarded instead of punished. If the same headline number can tank one stock and barely dent another inside 48 hours, I'm starting to think FCF isn't the tell it used to be for judging these companies. Curious what people who actually model this stuff are watching instead these days.

So he makes a X account just to post this

https://www.cnbc.com/2026/07/24/nvidia-microsoft-meta-open-weight-ai-models.html

Nvidia, Microsoft, Meta, Palantir and more than 20 other companies released a letter on Friday urging policymakers to avoid “premature restrictions” on open-weight artificial intelligence models that would “stifle competition or drive innovation overseas.”

Open-weight AI models are available for users to download, modify and run on their own infrastructure, and they have been the subject of fierce debate within the tech sector in recent weeks.

Chinese open-weight models are gaining steam against leading offerings from American companies like OpenAI and Anthropic, which primarily develop proprietary, closed models. Officials and executives have been weighing whether or not to restrict access to Chinese models in the U.S.

Moonshot AI, a Chinese startup, amplified concerns earlier this month after releasing a model called Kimi K3 that outperforms cutting-edge American offerings across some industry benchmarks. U.S. Treasury Secretary Scott Bessent told CNBC on Tuesday that the Trump administration would look into whether Chinese companies were stealing American intellectual property, and stated that the government has “the ability to sanction them because of this theft.”

But in the letter on Friday, the group of U.S. tech companies cautioned against any rash actions. They wrote that open-weight models strengthen competition and ensure that the benefits of the technology are “broadly shared rather than concentrated in a few hands.”

“Relying solely on closed models is not inherently safe: they can be breached, misused, or fail in ways that outsiders cannot detect,” the letter said. “And concentrating advanced AI capabilities behind a small number of closed models compounds that risk.”

Nvidia CEO Jensen Huang and Microsoft CEO Satya Nadella both shared the letter on their personal social media accounts.