$IREN (+4,01%) is human
Discussão sobre IREN
Postos
528
18H·
Irish
What do you do for a living? What kind of work do you do there? Do you actually produce anything, or is it just a power guzzler?
I don't get this over-the-top data center....
People who got in at 5 euros are now looking to make a profit. Okay.
But don’t you think there’s a bit of panic on the Titanic?
6D·
Key Takeaways from Alphabet's Earnings Call for the AI Sector
– Alphabet continues to describe itself as supply-constrained: Despite massive expansion over the past three years, demand continues to outpace investment.
– The 2026 CapEx guidance has been raised to $195–205 billion (previously $180–190 billion). Another significant increase is expected for 2027.
– In Q3, Alphabet plans to increase its use of third-party capacity – explicitly as a stopgap measure, with expected pressure on the cloud margin
$IREN (+4,01%)$NBIS (+5,95%)$CRWV (+3,55%)
88
1Semana·
The AI Sell-Off Is Out of Touch with Reality
Moonshot AI posted the following update on Sunday:
"Kimi K3 has been much more popular than we expected, and our GPUs are feeling the strain.
Over the past 48 hours, demand has nearly reached the limits of our current capacity. To protect the experience of existing subscribers, we’re temporarily pausing new subscriptions and prioritizing computing power for current members. Existing subscribers are not affected by this.
We’re scaling up additional capacity as quickly as possible and will gradually reopen new subscription slots in batches.
Going forward, we’ll also be splitting the membership into two more targeted plans: Kimi Membership for Kimi Web, App, and Work, and Kimi Code Membership for coding workflows. This will help us allocate computing power more precisely and keep the experience stable.
Thank you very much for your patience and understanding!"
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1Semana·
China's new AI model, Kimi K3, challenges the U.S. AI industry's billion-dollar bill
China's AI company Moonshot unveiled its new flagship model "Kimi K3" —and in independent tests, it’s nearly on par with the best models from Anthropic and OpenAIin independent tests, which may have contributed to the sharp decline in AI stock prices.
What happened?
Moonshot AI, a Chinese AI company with a valuation of approximately $31.5 billion, has unveiled its new model, Kimi K3. By comparison, Anthropic and OpenAI are each projected to be valued at over $1 trillion —more than 30 times that amount.
Key figures:
Size: 2.8 trillion parameters (= the “adjustment screws” that store the model’s knowledge—roughly speaking: the more there are, the more powerful the model, but also the more expensive it is to run). This makes K3 the largest model ever to come out of China.
Open-Weight: Moonshot plans to make the model available for free download by July 27—companies could then run it on their own hardware without paying licensing fees to Moonshot. As of now, however, it’s only available through Moonshot’s paid interface.
Context: Capable of processing 1 million tokens at a time (tokens = text units; 1 million tokens correspond roughly to 750,000 words).
Unknown: The actual training costs. Anthropic also published evidence in February 2026 that Chinese labs had copied U.S. models via “distillation” (= a model learns by querying and imitating vast amounts of responses from another model). Whether and to what extent this plays a role in K3 remains unclear.
The comparison: How much do the models cost—and how smart are they?
Pricing is per 1 million tokens, broken down by input (what you send to the model) and output (what it responds with):
Kimi K3 (Moonshot): $3 input / $15 output – Intelligence Index: 57
Claude Fable 5 (Anthropic): $10 / $50 – Intelligence Index: 60 (1st place)
GPT-5.6 Sol (OpenAI): $5 / $30 – Intelligence Index: 59
Claude Opus 4.8 (Anthropic): $5 / $25 – Intelligence Index: 56
Grok 4.5 (xAI): $2 / $6 – the most affordable model among the top performers
DeepSeek V4 Pro (China): approx. $0.44 / $0.87 – low-cost segment, but index only 44
The Intelligence Index comes from Artificial Analysis, an independent testing provider that compares models across nine task areas (programming, logic, knowledge work) on a scale of up to 100.
Strengths – K3 trails the leader, Fable 5, by only 3 points, but costs only one-third as much per output token ($15 instead of $50) and half as much as GPT-5.6 Sol. In Artificial Analysis’s practical test, completing a task with K3 cost an average of $0.94—compared to $1.04 for GPT-5.6 Sol and $1.80 for Opus 4.8. When it comes to building web interfaces, K3 even took first place in blind tests with real developers.
Weakness – K3 isn’t quite as cheap as the headline suggests: It costs three to four times as much as its predecessor, is the most expensive model among its Chinese competitors, and, according to tests, “burns” up to 1.9 times as many tokens as GPT-5.6 Sol for the same task—so the cost advantage per token effectively disappears in practice. And the promised free model weights have not yet been released.
What could this mean for the market?
The AI stock boom hangs by a thread: U.S. labs like Anthropic, OpenAI, and xAI have committed to spending hundreds of billions of dollars—on chips, data centers, and electricity. Chip manufacturers, data center operators, energy providers, and construction companies have seen their stock valuations rise because this money is expected to flow to them. The plan is to refinance this through high prices for cutting-edge AI.
If a model now delivers nearly the same performance for a fraction of the price—and is soon expected to be available for free download—it could create the impression that the U.S. labs’ pricing power is crumbling (“commoditization of intelligence”: cutting-edge AI is becoming an interchangeable mass-market commodity). This wouldn’t immediately cost revenue, but it sows doubt about the business case behind the massive investments—and in overheated market phases, even a single doubt can trigger a chain reaction.
Opportunities – Cheaper AI could accelerate AI adoption overall: More adoption means greater demand for computing power for ongoing operations (inference)—and K3 is just as hardware-intensive in operation as U.S. models. Chip and infrastructure providers would benefit from this, regardless of which model is running.
The latest quarterly figures support this interpretation: On Tuesday, ASML raised its annual forecast for the second time (to €43–45 billion in revenue) and reported that its capacity is nearly fully booked through 2027. On Wednesday, TSMC increased its capital expenditure budget to a record-high $60–64 billion and stated that investments over the next three years would once again be significantly higher than those of the past three years—and that it is monitoring the construction progress of data centers to ensure its own chips do not end up in inventory. This can be interpreted as a sign that the demand side remains strong.
Risks – If price compression were to actually hit U.S. labs, training investments could be stretched out or cut back—which would eventually affect the recipients of this spending (chips, data centers, energy). Furthermore, those who train using distillation save precisely the billions in GPU costs that make the U.S. approach so expensive. The cost bases of the providers are therefore not directly comparable, but the price risk for U.S. labs still exists. A countervailing factor is that Chinese models are unlikely to be considered for security-critical U.S. applications (government agencies, robotics) due to potential backdoors.
Context
The bottom line, in my view, is that Kimi K3 is less a “DeepSeek moment 2.0” than a reality check for the valuation logic:
In 2025, the question was which chips China would use for training—now the question is whether cutting-edge intelligence permanently justifies premium prices.
The supply chain’s response (ASML, TSMC) has been clear so far: demand exists—the response at the model level is less certain.
Limitations
Initial benchmarks are partly based on manufacturer specifications = independent long-term tests are still pending.
Training costs and the potential distillation ratio for K3 cannot be verified.
Moonshot’s valuation ($31.5 billion) is from a private funding round; the trillion-dollar valuations of Anthropic and OpenAI are prospective—neither is directly comparable to market capitalizations.
Sources:
Artificial Analysis – Kimi K3 Benchmarks: https://x.com/ArtificialAnlys/status/2077832874183860404
OpenRouter – Kimi K3 Prices & Specs: https://openrouter.ai/moonshotai/kimi-k3
Anthropic – Official API Pricing Documentation: https://platform.claude.com/docs/en/about-claude/pricing
OpenRouter – Grok 4.5 Pricing: https://openrouter.ai/x-ai/grok-4.5
Price Comparison: Kimi K3 / Fable 5 / GPT-5.6 Sol: https://drawpie.com/blog/kimi-k3-vs-fable-5-vs-gpt-5-6-sol-price-benchmarks/
Decrypt – Cost per Task in Benchmark Comparison: https://decrypt.co/373716/china-kimi-k3-largest-open-source-ai-model-ever-beats-claude-fable-gpt-5-6-sol
The Decoder – K3 Classification & Price Level: https://the-decoder.com/kimis-open-model-k3-nears-gpt-5-6-sol-and-fable-5-while-signaling-the-end-of-super-cheap-chinese-ai/
ASML – Q2 2026 Earnings Call Transcript: https://www.investing.com/news/transcripts/earnings-call-transcript-asml-q2-2026-beats-guidance-as-ai-demand-lifts-outlook-93CH-4792156
TSMC – Q2 2026 Earnings Call Transcript: https://www.investing.com/news/transcripts/earnings-call-transcript-tsmc-lifts-2026-outlook-as-ai-demand-stays-hot-in-q2-2026-93CH-4794777
Anthropic – Report on Distillation Attacks (February 2026): https://anthropic.com/news/detecting-and-preventing-distillation-attacks
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99
1Semana·
The market is punishing IREN for a problem it doesn't have
The recent sell-off in the AI sector has also affected Neocloud shares, such as $IREN (+4,01%) —coinciding with the Kimi K3 announcement from China and the debate over whether the billions in investments by U.S. AI labs are still sustainable. A closer look, however, reveals that the trigger for the sell-off affects IREN’s business model significantly less than that of the model providers—it could even bolster it.
The background:
IREN rents out computing power instead of building models and diversifies its customer base across three levels—Microsoft as the anchor client ($9.7 billion, five years, 20% upfront payment; handover of the first Horizon 1 phase scheduled for mid-July according to the company’s plans), Nvidia as a cloud customer ($3.4 billion, plus a partnership for up to 5 GW, including an option to purchase 30 million shares at $70), and, looking ahead, enterprise and government customers with their own dedicated GPU clusters.
Why the trigger for the sell-off barely affects IREN’s business model
The Kimi-K3 shock targets the training side of the AI economy: the one-time, multi-billion training costs that U.S. labs must recoup through premium pricing. When China creates nearly equivalent models at a lower cost and Nvidia distributes its top-of-the-line models—such as Nemotron 3—for free, this very business model comes under pressure.
IREN’s business, however, increasingly relies on the other side: inference, i.e., the ongoing operation of the models. According to Deloitte, this will already account for about two-thirds of total AI computing power by 2026 (2023: one-third), and over the lifetime of a model, 80–90% of computing costs are attributable to operation, not training.
The key point here is that a free model requires exactly as many GPUs/computing power to run as a paid one. The more interchangeable and affordable the models are, the more they will be used—and the more valuable the scarce computing power required to run them tends to become. Added to this is data sovereignty: Companies are likely to increasingly want to avoid having sensitive data run through third-party model providers—especially when it comes to models from China, or even $AAPL (-0,3%) compared to OpenAI.
Freely available models on self-rented, dedicated clusters solve exactly this problem, and IREN provides the infrastructure for it.
Opportunity: If the open-source trend takes hold, margins would shift from the model level to the infrastructure level. Furthermore, if direct enterprise sales are successful, this would mitigate the concentration risk associated with Microsoft—but it would come at the cost of sales force development and the financial security provided by long-term, prepaid hyperscaler contracts.
Risk – Second-Round Effect: If U.S. labs were to stretch out their training investments, this would eventually also affect demand for training clusters like the ones IREN builds for Microsoft. The inference wave cushions this impact but does not automatically replace it on a one-to-one basis.
Overall, the current decline in IREN’s stock price appears to be more of a sector-wide correction than a reassessment of its own business model: Doubts center on the training economics of model providers, while IREN’s value hinges on growing, model-independent inference demand.
Sources:
Deloitte via Computerworld – Inference Share in 2026: https://www.computerworld.com/article/4114579ces-2026-ai-compute-sees-a-shift-from-training-to-inference.html
Not investment advice.
1Semana·
China's new AI model, Kimi K3, challenges the U.S. AI industry's billion-dollar bill
China's AI company Moonshot unveiled its new flagship model "Kimi K3" —and in independent tests, it’s nearly on par with the best models from Anthropic and OpenAIin independent tests, which may have contributed to the sharp decline in AI stock prices.
What happened?
Moonshot AI, a Chinese AI company with a valuation of approximately $31.5 billion, has unveiled its new model, Kimi K3. By comparison, Anthropic and OpenAI are each projected to be valued at over $1 trillion —more than 30 times that amount.
Key figures:
Size: 2.8 trillion parameters (= the “adjustment screws” that store the model’s knowledge—roughly speaking: the more there are, the more powerful the model, but also the more expensive it is to run). This makes K3 the largest model ever to come out of China.
Open-Weight: Moonshot plans to make the model available for free download by July 27—companies could then run it on their own hardware without paying licensing fees to Moonshot. As of now, however, it’s only available through Moonshot’s paid interface.
Context: Capable of processing 1 million tokens at a time (tokens = text units; 1 million tokens correspond roughly to 750,000 words).
Unknown: The actual training costs. Anthropic also published evidence in February 2026 that Chinese labs had copied U.S. models via “distillation” (= a model learns by querying and imitating vast amounts of responses from another model). Whether and to what extent this plays a role in K3 remains unclear.
The comparison: How much do the models cost—and how smart are they?
Pricing is per 1 million tokens, broken down by input (what you send to the model) and output (what it responds with):
Kimi K3 (Moonshot): $3 input / $15 output – Intelligence Index: 57
Claude Fable 5 (Anthropic): $10 / $50 – Intelligence Index: 60 (1st place)
GPT-5.6 Sol (OpenAI): $5 / $30 – Intelligence Index: 59
Claude Opus 4.8 (Anthropic): $5 / $25 – Intelligence Index: 56
Grok 4.5 (xAI): $2 / $6 – the most affordable model among the top performers
DeepSeek V4 Pro (China): approx. $0.44 / $0.87 – low-cost segment, but index only 44
The Intelligence Index comes from Artificial Analysis, an independent testing provider that compares models across nine task areas (programming, logic, knowledge work) on a scale of up to 100.
Strengths – K3 trails the leader, Fable 5, by only 3 points, but costs only one-third as much per output token ($15 instead of $50) and half as much as GPT-5.6 Sol. In Artificial Analysis’s practical test, completing a task with K3 cost an average of $0.94—compared to $1.04 for GPT-5.6 Sol and $1.80 for Opus 4.8. When it comes to building web interfaces, K3 even took first place in blind tests with real developers.
Weakness – K3 isn’t quite as cheap as the headline suggests: It costs three to four times as much as its predecessor, is the most expensive model among its Chinese competitors, and, according to tests, “burns” up to 1.9 times as many tokens as GPT-5.6 Sol for the same task—so the cost advantage per token effectively disappears in practice. And the promised free model weights have not yet been released.
What could this mean for the market?
The AI stock boom hangs by a thread: U.S. labs like Anthropic, OpenAI, and xAI have committed to spending hundreds of billions of dollars—on chips, data centers, and electricity. Chip manufacturers, data center operators, energy providers, and construction companies have seen their stock valuations rise because this money is expected to flow to them. The plan is to refinance this through high prices for cutting-edge AI.
If a model now delivers nearly the same performance for a fraction of the price—and is soon expected to be available for free download—it could create the impression that the U.S. labs’ pricing power is crumbling (“commoditization of intelligence”: cutting-edge AI is becoming an interchangeable mass-market commodity). This wouldn’t immediately cost revenue, but it sows doubt about the business case behind the massive investments—and in overheated market phases, even a single doubt can trigger a chain reaction.
Opportunities – Cheaper AI could accelerate AI adoption overall: More adoption means greater demand for computing power for ongoing operations (inference)—and K3 is just as hardware-intensive in operation as U.S. models. Chip and infrastructure providers would benefit from this, regardless of which model is running.
The latest quarterly figures support this interpretation: On Tuesday, ASML raised its annual forecast for the second time (to €43–45 billion in revenue) and reported that its capacity is nearly fully booked through 2027. On Wednesday, TSMC increased its capital expenditure budget to a record-high $60–64 billion and stated that investments over the next three years would once again be significantly higher than those of the past three years—and that it is monitoring the construction progress of data centers to ensure its own chips do not end up in inventory. This can be interpreted as a sign that the demand side remains strong.
Risks – If price compression were to actually hit U.S. labs, training investments could be stretched out or cut back—which would eventually affect the recipients of this spending (chips, data centers, energy). Furthermore, those who train using distillation save precisely the billions in GPU costs that make the U.S. approach so expensive. The cost bases of the providers are therefore not directly comparable, but the price risk for U.S. labs still exists. A countervailing factor is that Chinese models are unlikely to be considered for security-critical U.S. applications (government agencies, robotics) due to potential backdoors.
Context
The bottom line, in my view, is that Kimi K3 is less a “DeepSeek moment 2.0” than a reality check for the valuation logic:
In 2025, the question was which chips China would use for training—now the question is whether cutting-edge intelligence permanently justifies premium prices.
The supply chain’s response (ASML, TSMC) has been clear so far: demand exists—the response at the model level is less certain.
Limitations
Initial benchmarks are partly based on manufacturer specifications = independent long-term tests are still pending.
Training costs and the potential distillation ratio for K3 cannot be verified.
Moonshot’s valuation ($31.5 billion) is from a private funding round; the trillion-dollar valuations of Anthropic and OpenAI are prospective—neither is directly comparable to market capitalizations.
Sources:
Artificial Analysis – Kimi K3 Benchmarks: https://x.com/ArtificialAnlys/status/2077832874183860404
OpenRouter – Kimi K3 Prices & Specs: https://openrouter.ai/moonshotai/kimi-k3
Anthropic – Official API Pricing Documentation: https://platform.claude.com/docs/en/about-claude/pricing
OpenRouter – Grok 4.5 Pricing: https://openrouter.ai/x-ai/grok-4.5
Price Comparison: Kimi K3 / Fable 5 / GPT-5.6 Sol: https://drawpie.com/blog/kimi-k3-vs-fable-5-vs-gpt-5-6-sol-price-benchmarks/
Decrypt – Cost per Task in Benchmark Comparison: https://decrypt.co/373716/china-kimi-k3-largest-open-source-ai-model-ever-beats-claude-fable-gpt-5-6-sol
The Decoder – K3 Classification & Price Level: https://the-decoder.com/kimis-open-model-k3-nears-gpt-5-6-sol-and-fable-5-while-signaling-the-end-of-super-cheap-chinese-ai/
ASML – Q2 2026 Earnings Call Transcript: https://www.investing.com/news/transcripts/earnings-call-transcript-asml-q2-2026-beats-guidance-as-ai-demand-lifts-outlook-93CH-4792156
TSMC – Q2 2026 Earnings Call Transcript: https://www.investing.com/news/transcripts/earnings-call-transcript-tsmc-lifts-2026-outlook-as-ai-demand-stays-hot-in-q2-2026-93CH-4794777
Anthropic – Report on Distillation Attacks (February 2026): https://anthropic.com/news/detecting-and-preventing-distillation-attacks
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2121
1 Comentar
1Semana
In this case, the market has at least realized its mistake today.😉😎
IREN Limited (NASDAQ:IREN) shares rose 7% on Monday after the company announced new multi-year cloud service contracts with AI developers worth $2.8 billion. In addition, the annualized recurring revenue (ARR) target for the AI Cloud segment through the end of 2026 was raised from $3.7 billion to over $4 billion.
According to the company, the new agreements now cover approximately 85% of the adjusted ARR target. IREN’s customer base now includes, among others, Microsoft, NVIDIA, Perplexity, Figure AI, Together AI, Fluidstack, Fireworks AI, Fal AI, Hume AI, and an unnamed AI developer. The services encompass both bare-metal and managed cloud services.
The most recent contracts include upfront payments from customers that cover approximately 45% of the associated capital expenditures (Capex) for GPUs. This reduces IREN’s net financing requirements for the corresponding implementations. Across the entire portfolio, IREN’s customer contracts have a weighted average term of approximately 4 years.
The company reported that demand from hyperscalers, enterprises, AI developers, and leading research laboratories continues to exceed available and planned capacity. IREN is already in discussions with customers regarding its entire expansion program for 2026 and 2027.
As of June 30, 2026, IREN had cash and cash equivalents of approximately $7.6 billion.
Co-founder and Co-CEO Daniel Roberts explained that the company has expanded its in-house AI cloud capacity from approximately 3 MW to 480 MW, which will be deployed later this year. The company is aiming for a capacity of 1.2 GW by 2027.
IREN Limited (NASDAQ:IREN) shares rose 7% on Monday after the company announced new multi-year cloud service contracts with AI developers worth $2.8 billion. In addition, the annualized recurring revenue (ARR) target for the AI Cloud segment through the end of 2026 was raised from $3.7 billion to over $4 billion.
According to the company, the new agreements now cover approximately 85% of the adjusted ARR target. IREN’s customer base now includes, among others, Microsoft, NVIDIA, Perplexity, Figure AI, Together AI, Fluidstack, Fireworks AI, Fal AI, Hume AI, and an unnamed AI developer. The services encompass both bare-metal and managed cloud services.
The most recent contracts include upfront payments from customers that cover approximately 45% of the associated capital expenditures (Capex) for GPUs. This reduces IREN’s net financing requirements for the corresponding implementations. Across the entire portfolio, IREN’s customer contracts have a weighted average term of approximately 4 years.
The company reported that demand from hyperscalers, enterprises, AI developers, and leading research laboratories continues to exceed available and planned capacity. IREN is already in discussions with customers regarding its entire expansion program for 2026 and 2027.
As of June 30, 2026, IREN had cash and cash equivalents of approximately $7.6 billion.
Co-founder and Co-CEO Daniel Roberts explained that the company has expanded its in-house AI cloud capacity from approximately 3 MW to 480 MW, which will be deployed later this year. The company is aiming for a capacity of 1.2 GW by 2027.
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2727
•1Semana·
Between heaven and hell!
Why Derivatives Can Be a Good Thing, Too.
A quick look at my TR portfolio, which currently consists of only 5 positions.
$IREN (+4,01%) -9%
$NBIS (+5,95%) -13%
$1347 (-10,85%) -5%
$VH2FYK Call on $BIIB (+0,11%) +55%
$UM5CJP Call on $NFLX (-0,43%) + 8% (Let’s see how long that lasts)
This results in a total daily loss of just 1% in this portfolio. And that’s despite the fact that $IREN (+4,01%) and $NBIS (+5,95%) are exactly as large as the other three combined.
1010
13 Comentários
1Semana
A call on Netflix? A put would be better.
•
22
•2Semana·
IREN's Chairman Responds to the Criticism
Chairman David Bartholomew has stepped down following the announcement of the compensation package for the CEOs has now addressed the shareholders directly in an open letter:
How the Board Justifies the Lack of Performance Targets:
- Share price targets have failed twice: In previous stock-based compensation plans, the CEOs were required to meet specific price targets: First, the targets were missed, even though IREN outperformed the sector. The reason was a weak overall market (2021) that had dragged the stock down. With the 2025 incentive plan, the opposite happened: The targets were met far too early, which meant there was no incentive.
- Sequence: The first package from June 2025 was deliberately kept small (552,197 shares ~0.9–1.4% of the company). The current package is only being released after the CEOs have delivered. Now that the stock price has already risen sharply, the total value of the current package appears so large in the headlines.
- Market Value: The value of the compensation continues to depend on $IREN (+4,01%) stock price, with the CEOs directly sharing in the company’s value—or losing out on it.
What the letter doesn’t answer:
The board only explains why price targets didn’t work. It remains unclear why they didn’t set operational targets —for example, a specific amount of completed data center capacity (in MW/GW). Management would have full control over such targets.
The letter serves as preparation for the annual shareholders’ meeting later this year, where shareholders will be able to vote on compensation (non-binding). The chairman also announces direct discussions with shareholders.
The rationale is a reasonable explanation, but it does not change the core issue: The CEOs simply need to remain in office—nothing more.
Source: www.iren.com/investors/news
3Semana·
Compensation Package for the Co-CEOs
$IREN (+4,01%) has the founders and co-CEOs Daniel and Will Roberts, respectively, 9,099,328 RSUs (Restricted Stock Units—shares that are transferred only after a vesting period). Together, this amounts to approximately 18.2 million shares worth approximately $700–800 million —depending on the share price on the valuation date—and represents approximately 5% dilution for existing shareholders.
Key facts:
- Vesting: in four equal annual installments over 4 years, beginning around July 2026
- Hold period: An additional 2-year holding period following each vesting—the final tranche will therefore not be freely available until the 2033 fiscal year
- Condition: Continued employment only— no performance targets (neither share price nor operational thresholds)
- Neither of them is to receive any further stock awards until the fiscal year 2031
The FinX community is reacting to this extremely critically —and the core criticism is justified: The package is purely time-based. Previous grants to the same CEOs were tied to share price targets, whereas this time, all that’s required is to remain in office for four years. The two-year lock-up period per tranche effectively ties the founders to the stock price until 2033. While this does motivate the founders to drive up the stock price—since they profit directly from its level—it is significantly less effective than genuine performance-based thresholds. From a governance perspective, this is a clear drawback, and existential for the fundamental investment case .
Source:
https://finance.yahoo.com/markets/stocks/articles/iren-nasdaqgs-iren-approves-800-231421785.html
1818
1 Comentar
2Semana
It seems I’m not the only one who saw problems here. The board’s defensive IR narrative is certainly entertaining. Using past stock price fluctuations as a justification to completely remove operational metrics like installed MW capacity from compensation is… let’s just say: a creative way to avoid measurable goals.
To me, this looks more like a “just-stay-in-your-seat guarantee” than a real incentive system. It reminds me a lot of the Tesla-Musk debate. From a corporate governance perspective, this is all a bit risky—it almost seems to me as if they’ve discreetly overlooked the “self-service” sign at the entrance.
😅
To me, this looks more like a “just-stay-in-your-seat guarantee” than a real incentive system. It reminds me a lot of the Tesla-Musk debate. From a corporate governance perspective, this is all a bit risky—it almost seems to me as if they’ve discreetly overlooked the “self-service” sign at the entrance.
😅
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1010
•
3Semana·
📊 My Portfolio Update: June 2026
June was marked by a Fed shock and a rotation away from the winners of the previous months. On June 17, the Fed, under its new chair Kevin
Warsh , the Fed kept interest rates at 3.50–3.75%, the dot plot signaled a possible rate hike rather than a cut—after months of hopes for easing —a real blow to the markets. On top of that came a bombshell regarding defense stocks: The Ministry of Defense scrapped the multi-billion-euro F126 frigate program, and Rheinmetall $RHM (-2,24%) subsequently lost over 16% —one of the stock’s worst trading days in decades. While speculative and cyclical stocks were sold off, investors fled to quality: defensive large-cap stocks and established software stocks held up significantly better.
In line with this more selective market environment, my portfolio slipped slightly into the red but held up more robustly than the DAX and Nasdaq:
📊 Monthly performance: -0.39%
📊 Portfolio value: ~€43,298
📊 Peak performance (Jan. 6, 2022): +39.16%
📊 YTD performance: ~+7.68%
Performance & Comparison 🚀
June was a month of contrasts: While the DAX and Nasdaq suffered from the Fed shock and the rotation out of risk assets, the S&P 500 and FTSE All-World held up significantly better thanks to their broader, more defensive composition. My portfolio was in the middle of the pack at -0.39%—more stable than the DAX and Nasdaq, but weaker than the two broad U.S. and global indices.
Performance Comparison (June 1–June 30, 2026, end of day):
My portfolio: -0.39%
FTSE All-World: +1.24%
S&P 500: +0.85%
DAX: -0.53%
NASDAQ 100: -0.96%
Purchases, Sales & Allocation 💶
In June, €300.00 was invested in the MSCI ACWI USD (Acc) $ACWI and €50.00 into the MSCI World Small Cap $WSML via the ongoing savings plans. The following were added via buy orders: Solaria Energia $SLR (€250.97), BE Semiconductors (€501.00), a Euro Overnight Rate Swap ETF (€101.00), and Tempus AI $TEM (€101.00).
On the selling side, I took profits on two positions in which I’ve been a shareholder for a good two years: In Datadog $DDOG (+1,6%) , I closed out the entire position after the stock had performed strongly in recent months. With Snowflake $SNOW (+0,79%) , I sold about a quarter of the position and am holding onto the rest. Both were purely profit-taking after a strong run; there has been no fundamental change in my assessment of the companies.
Top Movers in June 🟢
Despite the generally nervous sentiment, there were a few stocks that bucked the rotation trend and benefited from the flight to quality.
Tempus AI $TEM (+1,26%) posted the strongest gain at +19.99% (+37.02 €)—AI diagnostics remain in demand, even as more speculative stocks were sold off. TSMC $2330 followed with a gain of +15.56% (+€72.12): Demand for chips related to AI expansion remains consistently high, regardless of the interest rate debate. Ferrari $RACE (-0,95%) rose by +9.63% (+€78.63)—luxury goods proved resilient in the face of macroeconomic concerns. Berkshire Hathaway $BRK.B (-0,33%) benefited significantly from the flight to defensive quality, rising +7.37% (+€142.01), while Crowdstrike $CRWD (+1,01%) posted the largest euro gain in the portfolio with a +6.97% (+161.62 €) rise—cybersecurity remains structurally in demand. Cloudflare $NET (+1,27%) rounded out the list of winners with a gain of +4.92% (+€105.74).
June’s Biggest Losers 🔴
The losers in June were almost exclusively the stocks that had performed the strongest in previous months or are particularly sensitive to interest rates.
IREN was hit the hardest $IREN (+4,01%) , down -26.48% (-€316.39): Falling Bitcoin prices and ongoing disagreement among analysts regarding the company’s transition from a Bitcoin miner to an AI cloud provider weighed on the stock. Rheinmetall $RHM (-2,24%) lost -23.36% (-€376.76) after the Ministry of Defense scrapped the F126 frigate program, which affected the entire defense sector. Alibaba $BABA (+0,3%) fell by -21.25% (-€158.86)—Chinese tech remains under pressure due to general risk aversion toward Chinese stocks. American Lithium fell -21.21% (-€64.45), weighed down by persistently weak commodity prices and higher interest rate expectations, which particularly affect unprofitable growth stocks. BYD $1211 (+0,51%) fell by -18.40% (-254.16 €) amid the ongoing price war in the Chinese electric vehicle market. Solaria $SLR (+0,83%) rounded out the list of top losers with a -15.86% drop (-€63.35)—the hawkish Fed is weighing noticeably on interest-rate-sensitive solar and renewable energy stocks.
Conclusion 💡
June was a month of rotation: away from the more speculative winners of previous months, toward quality and established names. The Fed shock and the Rheinmetall slump showed how quickly sentiment can shift—a good reminder of why diversification across sectors and regions remains important.
❓ Question for the Community
That was my month in numbers—how did your portfolio fare through the Fed shock? Did you buy more Rheinmetall shares, or did you pull the plug?
👇 Let us know in the comments!
➡️ Follow @codeandcapital26 for transparent portfolio updates!
🔗 Link in bio: Wikifolio, Getquin & Parqet Portfolio
🗞️ Newsletter: codeandcapitalquant.beehiiv.com
📈 Wikifolio: https://www.wikifolio.com/de/de/w/wf0gquant6
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1212
3Semana·
Ask prices?!
I checked my watchlist again this morning. Among others, there are $IREN (+4,01%) and $RKLB (+3,38%) have dropped significantly from their ATHs.
How are things looking for you guys? Are you buying at these prices, selling, and still confident in the company, or is certain news getting you down?
P.S.: I’m not invested, but I’m seriously considering it.
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28 Comentários3Semana
No, you rarely do well with hype stocks.
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1313
•3Semana·
And there was news here, too!
$IREN (+4,01%) soared today. The reason was a potential partnership with Anthropic.
IREN’s stock soared 12.5% to $43.69 in morning trading today. The move was triggered by reports that the company has been shortlisted for Anthropic’s $15 billion data center project. This news served as a strong company-specific catalyst for the stock, which had previously been under significant selling pressure for nearly two weeks.
The move was significantly amplified by the momentum of a technical short squeeze. Short interest in IREN had risen to about 18.7% of the free float, and the put/call ratio in the options market reached its highest level of the year—conditions that, based on experience, typically precede sharp upward corrections following positive news. Over the previous five trading days, the stock had lost about 28% of its value, leaving it heavily oversold and thus ripe for a rebound.
The broader market also provided a supportive environment: The Nasdaq Composite rose 0.9% in today’s trading, and the S&P 500 gained 0.4%. This reflected a risk-on sentiment from which high-beta stocks in the AI infrastructure sector benefited. Competitors in the AI data center and Bitcoin mining segments, such as CoreWeave and Nebius, operate in the same market environment and have also benefited in recent weeks from rising expectations regarding hyperscaler spending. Analyst sentiment toward IREN remains clearly bullish, with a consensus “Buy” rating and an average price target of $81.75, which is significantly above the current trading level.
The combination of the report that Anthropic had shortlisted the company, a high short interest with potential for short covering, and a positive overall market environment thus led to today’s above-average price movement. This has offset part of the steep decline that had pushed the stock well below key moving averages—despite an unchanged long-term growth thesis based on significant contracts with Microsoft, Nvidia, and Dell.
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8 Comentários
You can find more details here: https://invezz.com/de/news/2026/07/06/nicht-nur-terawulf-iren-aktien-steigen-ebenfalls-wegen-anthropic/
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