Key Points: Reason for all asset declines: Rising concerns about stagflation.; Energy crisis intensifies stagflation risk.; Narrative shift: From AI infrastructure back to economic pressure.
The market is currently affected by multiple factors, including Middle East geopolitical risks, rising energy prices, increasing inflation expectations, and central bank monetary policy. Under various uncertainties, the market's narrative logic continues to shift, leading to declines across stocks, bonds, metals and other assets. While the central bank has released fine-tuning policies for the real estate market, it has also emphasized that it will closely monitor developments and maintain flexibility in monetary policy. Investors should carefully assess risks and seek investment strategies suitable for themselves.
Episode Focus
01All assets decline as stagflation concerns intensify.
02Energy Crisis Intensifies Stagflation Risk
03Narrative Shift: From AI Infrastructure Back to Economic Pressure.
01Micron's earnings report shows memory industry supply shortage, with revenue up 196% year-over-year to $23.8 billion, gross margin surging to 74.9%, and significantly raising capital expenditure, increasing full-year FY2026 capex from $20 billion to $25 billion.
02Key Takeaways from Analyst Q&A After Huang's GTC Conference: During the analyst Q&A, Huang Ren-hsuan shared the impressive growth rates of OpenAI and Anthropic, and revealed the token consumption rankings in the model market, with OpenAI first, the combined total of various open-source models second, Anthropic third, and xAI fourth.
03Nvidia GTC 2026: Token Economy Era: Huang Ren-hsuan outlines a computing economy system centered on tokens at GTC 2026, estimating infrastructure demand of at least 1 trillion dollars in 2027, and emphasizing that data centers will transform into token-producing factories.
Revenue up 196% year-over-yearGross margin 74.9%2026 Fiscal Year Capex 25.00B TWD USD
Upstream feed has not published a newer episode yet. This is the latest available episode.
After Meeting EP. 190 | Volatile Oil Prices, Expectations and Market Trends, See You Online on 3/31
US-Iran Conflict and Oil Price Impact: The US-Iran conflict has caused sharp volatility in oil prices, with Brent crude briefly surpassing $100 per barrel, affecting stock markets and inflation expectations. The trajectory of the conflict will determine the magnitude and duration of oil price movements, subsequently impacting the global economy. Inflation Risk and Federal Reserve Policy: Rising oil prices may push inflation higher, prompting the Federal Reserve to closely monitor inflation risks and reassess its rate-cut outlook. Depending on various scenarios, the Fed may reduce or even eliminate its planned rate cuts for the year.
01US-Iran Conflict and Oil Price Impact
02Inflation Risk and Federal Reserve Policy
03Commodity Linkage Effect
Sources: GooayeAI · Haojiao Macro Brief · IEObserve · MacroMicro · For reference only
11
Industry Pulse
IEObserve · 5 key notes
Updated 11:40
🔬Semiconductors2026-03-19 00:43
Micron Memory Super Cycle Erupts
Micron's earnings report shows memory industry supply shortage, with revenue up 196% year-over-year to 23.80B TWD USD, gross margin surging to 74.9%, and significantly increasing capital expenditure, raising full-year fiscal 2026 capex from 20.00B TWD to 25.00B TWD USD.
Revenue up 196% year-over-yearGross margin 74.9%2026 Fiscal Year Capex 25.00B TWD USD
Memory structural super-cycle has emerged in financial reports and stock prices across companies. Micron's last quarter earnings far exceeded market expectations, with revenue up 196% year-over-year to 23.80B TWD, gross margin surging to 74.9%, and profit up 686% year-over-year. Next quarter outlook is even more dramatic with revenue projected up 271% year-over-year and gross margin reaching 81%. EPS increased 10-fold to $19.15. Due to the memory industry currently experiencing severe supply shortage, Micron has decided to significantly increase capital expenditure, with 5.00B TWD capex this quarter, projected to increase to 7.00B TWD next quarter. It will also launch an unprecedented capacity expansion plan, raising full-year capital expenditure for fiscal 2026 from 20.00B TWD to 25.00B TWD, with fiscal 2027 capital expenditure expected to increase further significantly. More detailed earnings and outlook: https://www.patreon.com/posts/153388027?pr=true Vocus version: https://vocus.cc/article/69bb43b7fd8978000194dbb1
🤖AI2026-03-18 08:33
Key Analyst Q&A Highlights After Huang's GTC Conference
Huang Jen-hsun shared the impressive growth rates of OpenAI and Anthropic during the analyst Q&A, and revealed the token consumption rankings in the model market, with OpenAI first, the combined total of various open-source models second, Anthropic third, and xAI fourth.
Besides the 2026 GTC conference, Huang also participated in an analyst Q&A where he answered many common market questions. These included Is Nvidia taking too much profit from the industry, Who will pay for AI capital expenditures, Clear timeline roadmap for copper cables and optics, Incremental opportunities from Groq, Future business models for software companies, and more https://www.patreon.com/posts/153327731 Since Huang had more information, he mentioned some things outsiders cannot see, including the remarkable growth rates of OpenAI and Anthropic, as well as the current rankings of token consumption in the model market. He said first place is OpenAI, second is the sum of various open-source models, third is Anthropic, and fourth is xAI. More detailed content can be found in the column's summary.
🤖AI2026-03-16 22:34
Nvidia GTC 2026: Token Economy Era
Huang Ren-Huang outlined a token-centric computing economy at GTC 2026, projecting infrastructure demand of at least $1 trillion by 2027, and emphasized that data centers will transform into token-producing factories.
Infrastructure Demand to Reach at Least $1 Trillion by 2027
Old Huang painted a new computing economy centered on tokens at GTC 2026, with the core proposition: how AI factories convert electricity into revenue. He also devoted considerable time to discussing the OpenClaw lobster agent trend. He pointed out that computing demand has exploded 1 million times over the past two years, driven by three inflection points: generative AI changed computing methods, reasoning AI (o1/o3) enabled AI to decompose problems, and Claude Code allowed AI to truly execute tasks. The inflection point of reasoning has arrived. He revised his outlook from last year's $500 billion to at least $1 trillion in infrastructure demand by 2027. The most essential part of the speech was #Token Economics. Your data center used to store files, now it's a factory producing tokens. He illustrated tiered pricing: free tier attracts customers, mid-tier around $3 to $6 per million tokens, premium tier $45, top-tier service up to $150. The smarter the AI the higher the price, but the lower the throughput, so architecture optimization determines everything. Grace Blackwell achieved 35 to 50x power efficiency improvement compared to Hopper, with revenue per data center increasing 5x. The newly released Vera Rubin provides another 10x improvement at the most valuable inference tier, with revenue multiplying 5x again. After integrating Groq LPU, ultra-high-speed token generation improved another 35x. In a 1 GW factory, token generation rate increased from 2 million to 700 million within two years. He summed up the cost logic in one sentence: A 1 GW factory amortized over 15 years is $40 billion, even with nothing on top. You better make sure you put the best systems on it. #Product Roadmap: Rubin Ultra is in tape out, paired with Kyber racks connecting 144 GPUs. Next generation Feynman includes new GPU, LP40 LPU, Rosa CPU, supporting both copper wire and chiplet optics. Committed to releasing new architecture annually. Another major announcement is #OpenClaw. Jensen Huang defined it as the operating system for agent computers: Just as Windows let us create personal computers, OpenClaw lets us create personal agents. He predicted every SaaS company will transform into AaaS (Agent as a Service), with token budgets becoming Silicon Valley's new hiring tool. More detailed content can be found in the column article at https://www.patreon.com/posts/153212614
🤖AI2026-03-15 09:31
# The Real Bottleneck in AI Computing Power Expansion
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SemiAnalysis's Dylan Patel breaks down the AI industry supply chain, from GPU pricing to EUV, and presents contrarian views to market consensus, discussing bottlenecks in AI compute expansion.
SemiAnalysis's Dylan Patel discusses with Dwarkesh Patel the true bottlenecks of #AI computing expansion, breaking down the complete supply chain reality of the AI industry from GPU pricing to EUV. He shares some perspectives that differ from prevailing market beliefs—worth considering if they make sense. The linked article contains more detailed content. https://www.patreon.com/posts/153062071?pr=true
🤖AI2026-02-14 02:48
Anthropic's Dario Discusses AI Profitability Models
Anthropic's Dario predicts that software development automation will be achieved within 1-2 years, and uses Anthropic's revenue as an example to illustrate the scale of the AI wave, with projected 2025 revenue reaching 90-10.00B TWD dollars.
2025 Revenue Estimate 90-10.00B TWD USD
An interview with Anthropic's Dario covered many topics, with substantial discussion on the investment economics of AI model companies. Regarding technical development predictions, he believes that verifiable tasks like software development can achieve end-to-end automation within one to two years.
AI Profitability Model: #Healthy Economic Structure Masked by Demand Forecasting Problems
Using Anthropic's revenue growth as an example to illustrate the scale of this wave: 2023 was zero to $100 million, 2024 was $100 million to $1 billion, 2025 is $1 billion to $90-100 billion. And in January this year, this index curve is still accelerating—we added tens of billions in annualized revenue. He used concrete numbers to illustrate this dilemma: The curve I see now is: we have 10x growth every year. Earlier this year, we were looking at $100 billion in annualized revenue. We have to decide how much compute to buy. Building data centers and booking capacity takes one to two years. So basically I'm deciding 'how much compute can I get in 2027.' I can assume revenue continues to grow 10x annually, so by end of 2026 it would be $1 trillion, by end of 2027 it would be $10 trillion. But if my revenue isn't $1 trillion, even if it's $800 billion, there's no force on earth, no hedge that can prevent me from going bankrupt.
https://www.patreon.com/posts/dario-amodei-du-150714659
Data via CNN F&G + yfinance + TWSE API · Delay ≤15 min · For reference only, not investment advice
13
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