AMKR 2X Long ETF

Broad strength today and non-stop rally!

Top gainers for me: $QQQ $SPY $Corning(GLW.US) $Sandisk(SNDK.US) $Bel Fuse-B(BELFB.US) $Amkor Tech(AMKR.US) $NetApp(NTAP.US) $Marvell Tech(MRVL.US) $Brady(BRC.US)

$Amkor Tech(AMKR.US) Q2 Earnings Crushed 🔥

EPS: $0.70 vs $0.45 est

Sales: $1.898B vs $1.808B est

🟩 +4.11%

A TON OF THINGS HAPPENED IN THE STOCK MARKET TODAY.

Here's a full recap:

1. Tesla $Tesla(TSLA.US) was down 14% today, its worst day since January 2024, while Google $Alphabet(GOOGL.US) was down 7% after posting its first negative free cash flow quarter since 2004. The macro backdrop is not helping either. Crude oil has pushed back above $90/barrel for the first time since June and is up 25% over the past month. At the same time, the 10-year Treasury yield has crossed 4.7%, while jobless claims came in at 187K vs 211K expected, showing a stronger labor market but also raising concerns that inflation pressure could persist. Today was the worst day for the Mag 7 since April 2025 with all 7 stocks erasing $800B of market cap.

2. AMD $AMD(AMD.US) CEO Lisa Su said at the AMD Advancing AI event today that the AI accelerator market could grow to $1.4T by 2030, within a broader compute market expected to reach $2T. She also noted that monthly AI token consumption has surged 158x over the past two years, underscoring how quickly compute demand is scaling. AMD unveiled Helios, its new rack-scale AI system built around the MI450 accelerator, which Su called the fastest AI accelerator in the industry. Helios is now in full production, with shipments expected to start at the end of Q3 and ramp through Q4.

3. Intel $Intel(INTC.US) posted a strong Q2, with revenue of $16.1B vs $14.5B expected, up 25% YoY, and adjusted EPS of $0.42 vs $0.22 expected. Adjusted gross margin came in at 41.8% vs 39% expected, up 1,210 bps YoY, while non-GAAP operating margin reached 17.2% vs 10.7% expected. Segment results were strong across the core business, with CCPG revenue up 13% YoY to $8.9B, DCAI revenue up 59% YoY to $6.3B, total Intel Products revenue up 28% YoY to $15.1B, and Intel Foundry revenue up 31% YoY to $5.8B. Management said Q2 marked Intel’s strongest revenue growth in more than 15 years, driven by better execution, higher factory yields, improved cycle times, and stronger customer demand.

4. Trump warned that the U.S. will hold Iran responsible if the Houthis resume attacks on commercial shipping. He said the Houthis had acted “responsibly” after previous U.S. strikes, but are now “starting up again” after reportedly firing on two Saudi Arabian ships last night. Trump said the Houthis are a proxy of Iran, and that any further attacks would trigger major military punishment against both Iran and the Houthis.

5. Nvidia $NVIDIA(NVDA.US) is committing $1.5B to Amkor $Amkor Tech(AMKR.US) through a prepayment tied to a multi-year advanced packaging and development agreement. The funding will help Amkor expand U.S. packaging capacity at its Arizona campus as both companies work on next-generation packaging and test technologies for AI and accelerated computing. The partnership will focus on high-density interconnects and heterogeneous integration, which are key for combining multiple chips and components into more powerful systems.

6. The top 10 most active options today by contracts traded were $Tesla(TSLA.US) with 3.6M contracts, $NVIDIA(NVDA.US) with 2.4M contracts, $Alphabet(GOOGL.US) with 994K contracts, $Amazon(AMZN.US) with 940K contracts, $SpaceX(SPCX.US) with 917K contracts, $Apple(AAPL.US) with 732K contracts, $Intel(INTC.US) with 706K contracts, $Micron Tech(MU.US) with 664K contracts, $Alphabet - C(GOOG.US) with 560K contracts, and $Microsoft(MSFT.US) with 532K contracts.

7. South Korea is moving to tighten rules around leveraged single-stock ETFs and ETNs beginning July 31. Retail investors will now need about $20,300 in cash to open or add to a position, up from roughly $6,800 previously. The key change is that stocks, bonds, and other securities will no longer count toward the deposit requirement, making it harder for retail traders to access these leveraged products.

8. U.S. mortgage rates rose for the third straight week, with the average 30-year fixed climbing to 6.58%, putting rates back near their highest level in a year.

9. AMD $AMD(AMD.US) and Cerebras $Cerebras(CBRS.US) are teaming up on a disaggregated AI inference architecture that divides workloads between both platforms. In the setup, AMD Helios manages prompts and long-context processing, while Cerebras’ Wafer-Scale Engine focuses on ultra-low-latency token generation. The companies say the combined system can deliver up to 5x more tokens per second per watt than Cerebras alone, with initial availability expected through Cerebras Cloud in the second half of 2026.

10. Uber $Uber Tech(UBER.US) cut 10% of roles in its customer service operations as it restructures the division and leans further into AI. The company said fragmented workflows were making it harder to roll out AI at scale, and this marks Uber’s first layoff round specifically tied to AI-driven efficiency.

11. SpaceX $SpaceX(SPCX.US) is reportedly turning away satellite operators looking for dedicated Falcon 9 launches beyond 2028 as the company shifts more of its long-term launch strategy toward Starship, per Bloomberg. SpaceX has also stopped taking future Falcon 9 rideshare reservations and has paused production of some expendable Falcon components, though Falcon 9 is still expected to remain active for NASA and Pentagon missions. The risk is timing: if Starship is not commercially ready by 2028, the market could face a major launch-capacity gap, creating a bigger opening for competitors like Rocket Lab, Blue Origin, and ULA.

12. Meta’s $Meta Platforms(META.US) new $12B Texas data center financing, tied to a nearly 1GW project, is reportedly being discussed at yields above 7%. That is roughly 40 bps higher than Meta’s $27B Hyperion financing from just nine months ago, adding about $48M in annual interest expense. Hyperion bonds are now trading around 96 cents on the dollar, showing how financing costs for massive AI infrastructure projects are starting to move higher.

WALL STREET IS THE GREATEST SHOW ON EARTH.

Source: amit

📢 𝗝𝗨𝗦𝗧 𝗜𝗡: Amkor, NVIDIA Sign Multi-Year Partnership With $𝟭.𝟱 Billion Prepayment - $Amkor Tech(AMKR.US) $NVIDIA(NVDA.US)

👉 𝗞𝗲𝘆 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀:

➤ 𝗔𝗺𝗸𝗼𝗿 and 𝗡𝗩𝗜𝗗𝗜𝗔 enter a 𝗺𝘂𝗹𝘁𝗶-𝘆𝗲𝗮𝗿 strategic partnership.

➤ 𝗡𝗩𝗜𝗗𝗜𝗔 will provide a $𝟭.𝟱 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 prepayment to Amkor.

➤ Funding supports expansion of 𝗨.𝗦. advanced semiconductor packaging capacity.

➤ Partnership focuses on 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗽𝗮𝗰𝗸𝗮𝗴𝗶𝗻𝗴 and test technologies for AI.

➤ Companies will co-develop 𝗵𝗶𝗴𝗵-𝗱𝗲𝗻𝘀𝗶𝘁𝘆 interconnect and heterogeneous integration.

➤ Expansion is centered on 𝗔𝗺𝗸𝗼𝗿'𝘀 𝗔𝗿𝗶𝘇𝗼𝗻𝗮 manufacturing campus.

➤ Partnership aims to strengthen a 𝗴𝗲𝗼𝗴𝗿𝗮𝗽𝗵𝗶𝗰𝗮𝗹𝗹𝘆 𝗱𝗶𝘃𝗲𝗿𝘀𝗲 AI supply chain.

➤ Amkor has previously supplied packaging for 𝗡𝗩𝗜𝗗𝗜𝗔 data center and networking products.

➤ Agreement is expected to scale next-generation AI packaging technologies.

👉 𝗘𝘅𝗽𝗲𝗿𝘁 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁𝘀:

𝗗𝗲𝗯𝗼𝗿𝗮 𝗦𝗵𝗼𝗾𝘂𝗶𝘀𝘁, Executive Vice President of Operations at NVIDIA:

"Amkor's global capabilities, combined with their committed investment in the United States, are critical components of building resilient AI infrastructure and accelerating next-generation technologies."

𝗞𝗲𝘃𝗶𝗻 𝗘𝗻𝗴𝗲𝗹, Chief Executive Officer of Amkor Technology:

"Our agreement with NVIDIA accelerates our long-term roadmap and supports our ability to deliver full turnkey advanced packaging and test solutions, leveraging our global footprint while expanding U.S. capabilities to support critical AI infrastructure."

Former Senior Post Silicon Validation Engineer at NVIDIA on CPO:

"Eventually, CPO is where the technology is converging and going to converge. Whoever comes with a reliable CPO product first, they will see a huge demand. There is absolutely no doubt about that. All these NPO and LPO are temporary compromise, for the lack of a better word."

Current State & Commercial Timeline

> Experimental Phase: CPO technology is currently in pilot and experimental stages, with no commercial products available yet.

> Timeline for Adoption: Initial CPO products are tentatively expected around 2028, though unexpected delays could occur due to major, unresolved engineering hurdles.

> Demand Dynamics: Once CPO is successfully and reliably commercialized, demand will experience an explosive surge, limited only by production supply rather than market interest.

Key Technical Hurdles

> Thermal Management: Compute chips generate kilowatts of heat, whereas optical engines are exceptionally sensitive to temperature changes (even minor shifts can alter laser wavelengths).

> Glass Substrates & Via Drilling: Transitioning from traditional organic substrates to glass is necessary for scale, but drilling microscopic, precise vias into glass without causing micro-cracking remains a massive challenge.

> Laser Integration: Internal laser setups face severe thermal interference from compute chips, while external laser setups struggle with high optical loss when trying to focus light onto extremely thin substrate layers.

Competitive & Technological Landscape

> Interim Solutions: Technologies like NPO (Near-Packaged Optics) and LPO (Linear Drive Pluggable Optics) are viewed as temporary compromises; once CPO matures, the industry will fully converge on it, causing demand for traditional pluggables to decline.

> Key Players: Major industry stakeholders—including TSMC, Samsung, Intel, and Amkor—are heavily investing in packaging R&D, with TSMC viewed as a dominant pioneer via solutions like CoWoS and CoPoS.

> Laser & Component Suppliers: Lumentum is positioned well ahead of competitors in the optical landscape, supported by strategic partnerships and investments (such as NVIDIA's capital backing).

Bill of Materials (BOM) Breakdown

> Packaging: Forms the largest share of the CPO BOM (~50% to 55%) and represents the hardest problem to commoditize.

> Light Sources / Lasers: Accounts for roughly one-third of the BOM.

> Cooling Solutions: Makes up the remaining portion, playing an equally vital role due to severe thermal constraints.

Optical Circuit Switching (OCS)

> Role in Future Infrastructure: Once signals are converted to light via CPO, OCS will become critical to route traffic dynamically across large clusters of GPUs without re-converting signals back to electrical (which destroys power-saving benefits).

> Current Limitations: Existing OCS solutions lack packet-decoding capabilities and rely on rigid, round-robin scheduling schemes, meaning optical switching technology must heavily evolve alongside CPO.

$Marvell Tech(MRVL.US) $Amkor Tech(AMKR.US) $NVIDIA(NVDA.US) $Taiwan Semiconductor(TSM.US) $Marvell Tech(MRVL.US) $Lumentum(LITE.US) $Intel(INTC.US) $Applied Optoelectronics(AAOI.US)

JPMorgan Analyzes Taiwan Semiconductor: CoWoS Shortfall Widens to 20%, AI CPUs Take Over from GPUs

Public disclosures from Taiwan Semiconductor confirm a continuous expansion of its advanced packaging capabilities, particularly CoWoS and SoIC. The company projects that CoWoS capacity will achieve a compound annual growth rate (CAGR) surpassing 80% from 2022 through 2027.

Capacity has been raised to approximately 220,000 wafers per month—so why is it still insufficient?

According to supply chain channel checks by JPMorgan, Taiwan Semiconductor's internal CoWoS monthly capacity is projected to reach approximately 115,000 wafers by the end of 2026, scale up to roughly 190,000 wafers by 2027, and hit between 220,000 and 225,000 wafers by the close of 2028.

Secondary reports on these estimates show minor discrepancies; for instance, some sources note that JPMorgan's earlier forecasts placed end-2027 capacity at 175,000 wafers per month and end-2028 capacity at 220,000 wafers per month. Because TSMC does not officially disclose these metrics, these figures represent potential "upside" targets in supply chain models rather than definitive, guaranteed production volumes.

OSAT providers are increasingly stepping in to supplement the supply chain. Advanced packaging capacity similar to CoWoS from players like ASE Group and Amkor is projected to ramp from roughly 12,000–15,000 wafers per month at the end of 2026 to around 85,000 wafers per month by the end of 2028. Concurrently, Taiwan Semiconductor is optimizing its own production lines, reallocating internal resources by shifting some capacity originally slated for SoIC to aggressively accelerate its CoWoS expansion.

The underlying challenge is that AI hardware is becoming increasingly packaging-intensive. Next-generation AI accelerators, specialized AI CPUs, and custom ASICs are consuming a larger share of advanced packaging capacity; many newer architectures feature expanded die areas, which inherently limits the number of chips yielded per wafer and drains more production resources per unit. Consequently, even as manufacturing lines scale up, the actual footprint and capacity consumed on a per-chip basis are rising simultaneously.

Furthermore, the projected ~20% supply-demand deficit is not a universally accepted market consensus. For instance, TrendForce reported in June that this gap could contract to roughly 10% by the end of 2026. Their model estimates Taiwan Semiconductor's standalone monthly capacity will reach 120,000–140,000 wafers by 2026, supplemented by an additional 50,000–60,000 wafers per month from OSAT partners. The variance between these supply chain assessments ultimately boils down to differing calculations regarding how fast customer demand is scaling and how efficiently outsourced, external packaging lines can be brought online to deliver viable commercial yields.

NVIDIA remains the largest customer, and CPUs are now also joining the queue.

NVIDIA remains the dominant driver of advanced packaging demand within JPMorgan’s modeling. By 2028, its annual CoWoS requirement is projected to climb to roughly 1.735 million wafers, marking a substantial leap from 2027 levels. This massive capacity consumption is propelled not just by next-generation GPUs, but also by a broader hardware portfolio including the Vera and Rosa AI CPUs, LPUs, and advanced networking systems like the Spectrum-X CPO (Co-Packaged Optics) switches. In terms of technology allocation, the model assumes that NVIDIA’s primary accelerators and CPO hardware will utilize CoWoS-L, whereas its CPUs and LPUs will predominantly adopt CoWoS-R, with production volumes split across Taiwan Semiconductor, Amkor, and ASE Group.

This represents a major paradigm shift in AI infrastructure architecture. Traditional data center supply chain analyses focused almost exclusively on the "GPU plus HBM" bottle-neck; today, AI CPUs themselves are demanding ultra-high memory bandwidth, denser interconnect architectures, and optimized system efficiency. As a result, host processors are now actively competing for cutting-edge packaging capacity.

Meanwhile, designs related to the upcoming Feynman architecture have not yet been fully finalized. Wall Street supply chain models currently omit any explicit assumptions for CoPoS integration; near-term roadmaps suggest a continued reliance on standard CoWoS-L coupled with partial SoIC logic stacking. Even as alternative architectural packaging technologies debut down the road, bypassing CoWoS entirely will remain highly impractical for mainstream AI accelerators throughout the 2027–2028 cycle.

AMD, TPUs, and Trainium are all competing for capacity—shortages are not exclusive to NVIDIA.

Evaluating the advanced packaging crunch through the lens of NVIDIA alone severely understates the scope of the current supply squeeze. Demand for CoWoS and equivalent advanced packaging technologies is simultaneously accelerating across a broader ecosystem, notably from AMD, Google’s TPU program, and Amazon’s Trainium accelerators.

> AMD: The chipmaker is facing capacity constraints across both its datacenter CPUs and AI accelerators. Next-generation products like the Venice server CPU, MI450, and MI500 are all modeled to consume significantly more advanced packaging allocation. The MI500, in particular, features an expanded physical package size, inherently requiring more wafer real estate and packaging resources per chip. Consequently, while AMD’s total wafer-level fan-out demand is projected to climb through 2027 and 2028, actual supply fulfillment rates may only hit 50% to 60%.

> Google TPUs: Google's custom silicon volume continues to scale. Total TPU shipment forecasts for 2027 have been revised upward, with the MediaTek-co-designed v8 series driving the bulk of this incremental growth before the product cycle transitions to the v9 generation in 2028. While certain future TPU iterations are slated to potentially diversify into Intel’s EMIB-T packaging architecture, this secondary supply pipeline remains bottlenecked by substrate shortages and yield maturity.

> Amazon Trainium: AWS's custom AI infrastructure is similarly accelerating. Full-lifecycle demand projections for Trainium3 have been adjusted upward, with a portion of the design and order allocation potentially spilling over to Marvell. Looking further out, Trainium4 is expected to begin its production ramp in 2028, introducing 3D SoIC logic stacking alongside sophisticated interconnect frameworks. However, these specific shipment volumes and architectural roadmaps remain model-driven assumptions that depend on final tape-outs and manufacturing execution.

Ultimately, this multi-front demand explains why the market remains anxious about a structural supply deficit despite Taiwan Semiconductor's aggressive capacity expansions. The advanced packaging bottleneck is no longer just a reflection of NVIDIA GPU volume; it is being compounded by hyperscaler ASICs, high-performance AI CPUs, and expanding chiplet footprints that collectively drain available foundry resources.

Taiwan Semiconductor’s total CoWoS consumption is projected to reach approximately 1.24 million, 2.38 million, and 2.63 million wafers per year in 2026, 2027, and 2028, respectively, with NVIDIA maintaining the largest share while AMD and Broadcom/TPU contribute greater incremental volume.

$Broadcom(AVGO.US) $Marvell Tech(MRVL.US) $Alphabet(GOOGL.US) $Amazon(AMZN.US) $NVIDIA(NVDA.US) $AMD(AMD.US)