🇨🇭 Global One SI - Prompt
🚨SPACEX PRE-IPO MARKET OPENS WITH HISTORIC $2.2T VALUATION SIGNAL Pre-IPO perpetual futures tied to SpaceX are now live on Hyperliquid under the ticker $SPCX, launched at $150/share before rapidly surging above $200. At current pricing, the market is implying…
SpaceX stocks ranked by market cap:
$AMPG ~ $130 Million 🫡
$SIDU ~ $322 Million
$VELO ~ $591 Million
$SPIR ~ $665 Million
$SATL ~ $1.34 Billion
$BKSY ~ $1.66 Billion
$VOYG ~ $2.32 Billion
$RDW ~ $2.92 Billion
$FLY ~ $6.71 Billion
$LUNR ~ $7.34 Billion
$PL ~ $14.57 Billion
$ASTS ~ $36.52 Billion
$RKLB ~ $73.43 Billion
$SPCX SpaceX IPO ~ $2 Trillion
$AMPG ~ $130 Million 🫡
$SIDU ~ $322 Million
$VELO ~ $591 Million
$SPIR ~ $665 Million
$SATL ~ $1.34 Billion
$BKSY ~ $1.66 Billion
$VOYG ~ $2.32 Billion
$RDW ~ $2.92 Billion
$FLY ~ $6.71 Billion
$LUNR ~ $7.34 Billion
$PL ~ $14.57 Billion
$ASTS ~ $36.52 Billion
$RKLB ~ $73.43 Billion
$SPCX SpaceX IPO ~ $2 Trillion
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JEFF BEZOS: “I'm very admiring of what SpaceX has done and I want the world to have at least two SpaceX's — maybe even more. Great industries are made up of many companies.”
Trump is planning to invest billions into quantum.
Pure-Play Quantum Companies
$IONQ lonQ
$QBTS D-Wave Quantum
$RGTI Rigetti Computing
$XNDU Xanadu Quantum
$INFQ Infleqtion
$QUBT Quantum Computing
Quantum Security
$ARQQ Arqit Quantum
Tech Giants with Quantum Programs
$NVDA Nvidia
$BABA Alibaba
$GOOGL Alphabet
$MSFT Microsoft
$IBM IBM
$INTC Intel
$BIDU Baidu
$RTX Raytheon
$HON Honeywell
Quantum Computing Equipment
$GFS GlobalFoundries
$MRVL Marvell
$COHR Coherent
$RDNT RadNet
$TSEM Tower Semiconductor
Pure-Play Quantum Companies
$IONQ lonQ
$QBTS D-Wave Quantum
$RGTI Rigetti Computing
$XNDU Xanadu Quantum
$INFQ Infleqtion
$QUBT Quantum Computing
Quantum Security
$ARQQ Arqit Quantum
Tech Giants with Quantum Programs
$NVDA Nvidia
$BABA Alibaba
$GOOGL Alphabet
$MSFT Microsoft
$IBM IBM
$INTC Intel
$BIDU Baidu
$RTX Raytheon
$HON Honeywell
Quantum Computing Equipment
$GFS GlobalFoundries
$MRVL Marvell
$COHR Coherent
$RDNT RadNet
$TSEM Tower Semiconductor
🇨🇭 Global One SI - Prompt
$FCEL starting to transition from “old clean energy” into the new AI power infrastructure narrative. What’s interesting now is the setup is evolving FAST: • reclaiming highs aggressively • OBV still elevated despite pullbacks • buyers defending higher lows…
$FCEL Fantastic day!!
🇨🇭 Global One SI - Prompt
$JDZG continues evolving exactly how these tiny-float recovery structures usually do once momentum returns. A few days ago this was still considered “dead money.” Now: • breakout structure expanding • volume increasing again • OBV continuing higher • momentum…
$JDZG step by step!! also working well the plan
🇨🇭 Global One SI - Prompt
$IBM quietly becoming one of the most interesting “legacy tech → AI infrastructure” transitions in the market right now. This chart just triggered a very important technical development: • breakout from the descending trendline • reclaim from the long compression…
$IBM as expected
🇨🇭 Global One SI - Prompt
Anthropic is reportedly in talks to rent servers powered by $MSFT Maia AI chips as it looks for more compute to run Claude. This shows how severe the AI compute shortage still is with frontier labs needing every viable source of capacity they can get.
OpenAI and Anthropic are locking up capacity years in advance because whoever controls compute controls how fast AI products, agents and inference revenue can scale.
Nearly half of the $2.1T contracted backlog at $MSFT, $ORCL, $GOOGL and $AMZN is tied to OpenAI and Anthropic.
Nearly half of the $2.1T contracted backlog at $MSFT, $ORCL, $GOOGL and $AMZN is tied to OpenAI and Anthropic.
⚠️The AI infrastructure expansion is CRUSHING Big Tech cash flows:
The aggregate free cash flow margin across major cloud and hyperscale companies, including Google, Microsoft, Amazon, Oracle, and China's Big 3, is projected to fall to near 0% by 2026 and turn negative at -0.8% in 2027.
This means these companies will generate less cash than they spend, leaving little to no room for share buybacks or dividends that have historically supported their stock prices.
This comes as hyperscalers are collectively spending hundreds of billions of dollars per year on data centers, chips, and AI infrastructure, a pace of investment that is unlikely to ease before 2028 at the earliest.
AI capital expenditure is consuming nearly every dollar, with the combined 2026 CapEx for Microsoft, Alphabet, Amazon, Meta, and Oracle expected to surpass $715 billion.
The AI spending is coming at a steep cost.
The aggregate free cash flow margin across major cloud and hyperscale companies, including Google, Microsoft, Amazon, Oracle, and China's Big 3, is projected to fall to near 0% by 2026 and turn negative at -0.8% in 2027.
This means these companies will generate less cash than they spend, leaving little to no room for share buybacks or dividends that have historically supported their stock prices.
This comes as hyperscalers are collectively spending hundreds of billions of dollars per year on data centers, chips, and AI infrastructure, a pace of investment that is unlikely to ease before 2028 at the earliest.
AI capital expenditure is consuming nearly every dollar, with the combined 2026 CapEx for Microsoft, Alphabet, Amazon, Meta, and Oracle expected to surpass $715 billion.
The AI spending is coming at a steep cost.
🇨🇭 Global One SI - Prompt
I turned Claude into my 24/7 personal assistant. It's the best thing I've done for my productivity in months. My personal OS stores all my important data (tasks, finances, calendar, journal) in one place. It took me weeks to get this right - now the blueprint…
AI just crossed a line most people haven’t noticed yet.
Claude + TradingView via MCP doesn’t “look at charts.”
It reads live market data directly.
Compares setups in real time.
Builds logic on top of the feed.
And keeps full context while reasoning.
No screenshots.
No vague “BTC looks bullish” takes.
This feels less like prompting AI…
and more like plugging intelligence straight into the market.
That unlocks a different level:
• live multi-chart analysis
• instant market research
• automated indicators + alerts
• strategy testing without losing context
The shift is subtle but massive.
The advantage is no longer better prompts.
It’s better data pipes.
Most people are still uploading screenshots.
Meanwhile, a few traders are building AI systems that can actually see the market.
Bookmark this.
Claude + TradingView via MCP doesn’t “look at charts.”
It reads live market data directly.
Compares setups in real time.
Builds logic on top of the feed.
And keeps full context while reasoning.
No screenshots.
No vague “BTC looks bullish” takes.
This feels less like prompting AI…
and more like plugging intelligence straight into the market.
That unlocks a different level:
• live multi-chart analysis
• instant market research
• automated indicators + alerts
• strategy testing without losing context
The shift is subtle but massive.
The advantage is no longer better prompts.
It’s better data pipes.
Most people are still uploading screenshots.
Meanwhile, a few traders are building AI systems that can actually see the market.
Bookmark this.
🇨🇭 Global One SI - Prompt
Photo
11 Best Weather Forecasting Models for Polymarket Markets Right Now (Global + Regional Breakdown)
Understanding their regional strengths and update frequencies can dramatically improve your probability estimates and win rate
Here’s the complete regional breakdown of the best models you should be using
> Global models - work for any city
• ECMWF - the gold standard for global forecasting, best accuracy at 5–10 day horizon
• ECMWF AIFS - AI-powered version of ECMWF, same global coverage, faster updates
• GFS - solid global coverage, free, widely used as baseline
• ICON-Global - reliable global model from DWD, good backup to ECMWF
> USA + Canada (LA, NYC, Chicago, Dallas, Miami, SF, Atlanta, Austin, Denver, Seattle)
• HRRR - best short-horizon model for US cities, updates every hour, 3km resolution
• GEM - very strong for both US and Canada
• GFS - solid baseline, pairs well with HRRR
> Europe (London, Paris, Madrid, Milan, Amsterdam, Munich, Warsaw, Helsinki, Istanbul, Ankara, Moscow)
• ICON-EU - the strongest regional model across all of Europe
• AROME - high resolution for Western Europe: France, Spain, Italy, UK
• UKMO - best for London and Northern Europe specifically
• ECMWF - always worth including as the global reference
> Central Europe (Warsaw, Munich, Milan, Amsterdam)
• ICON-D2 - highest resolution for Germany, France, Benelux, Poland, Austria, Czech Republic
• ICON-D2 EPS - ensemble version of ICON-D2, gives you probability distribution instead of single forecast. Use this when the market is binary and close to the threshold
> Asia (Beijing, Shanghai, Guangzhou, Shenzhen, Chengdu, Chongqing, Wuhan, Qingdao, Hong Kong, Taipei, Singapore, Jakarta, Manila, Lucknow)
• JMA-GSM - strong across East Asia and Pacific
• JMA-MSM - high resolution specifically for Japan and nearby areas
• ECMWF + ICON-Global - best global options for Southeast Asia and South Asia
> Middle East & Africa (Jeddah, Tel Aviv, Cape Town, Karachi)
• ECMWF - dominant choice, no strong regional alternatives here
• GFS - reliable backup
The practical workflow: always start with ECMWF as your anchor. Then layer in the regional model that covers your city. Where you have an ensemble version (ICON-D2 EPS) - use it
A single deterministic forecast tells you the expected value. An ensemble tells you the distribution. For binary threshold markets, the distribution is what actually matters
Save this list.
Understanding their regional strengths and update frequencies can dramatically improve your probability estimates and win rate
Here’s the complete regional breakdown of the best models you should be using
> Global models - work for any city
• ECMWF - the gold standard for global forecasting, best accuracy at 5–10 day horizon
• ECMWF AIFS - AI-powered version of ECMWF, same global coverage, faster updates
• GFS - solid global coverage, free, widely used as baseline
• ICON-Global - reliable global model from DWD, good backup to ECMWF
> USA + Canada (LA, NYC, Chicago, Dallas, Miami, SF, Atlanta, Austin, Denver, Seattle)
• HRRR - best short-horizon model for US cities, updates every hour, 3km resolution
• GEM - very strong for both US and Canada
• GFS - solid baseline, pairs well with HRRR
> Europe (London, Paris, Madrid, Milan, Amsterdam, Munich, Warsaw, Helsinki, Istanbul, Ankara, Moscow)
• ICON-EU - the strongest regional model across all of Europe
• AROME - high resolution for Western Europe: France, Spain, Italy, UK
• UKMO - best for London and Northern Europe specifically
• ECMWF - always worth including as the global reference
> Central Europe (Warsaw, Munich, Milan, Amsterdam)
• ICON-D2 - highest resolution for Germany, France, Benelux, Poland, Austria, Czech Republic
• ICON-D2 EPS - ensemble version of ICON-D2, gives you probability distribution instead of single forecast. Use this when the market is binary and close to the threshold
> Asia (Beijing, Shanghai, Guangzhou, Shenzhen, Chengdu, Chongqing, Wuhan, Qingdao, Hong Kong, Taipei, Singapore, Jakarta, Manila, Lucknow)
• JMA-GSM - strong across East Asia and Pacific
• JMA-MSM - high resolution specifically for Japan and nearby areas
• ECMWF + ICON-Global - best global options for Southeast Asia and South Asia
> Middle East & Africa (Jeddah, Tel Aviv, Cape Town, Karachi)
• ECMWF - dominant choice, no strong regional alternatives here
• GFS - reliable backup
The practical workflow: always start with ECMWF as your anchor. Then layer in the regional model that covers your city. Where you have an ensemble version (ICON-D2 EPS) - use it
A single deterministic forecast tells you the expected value. An ensemble tells you the distribution. For binary threshold markets, the distribution is what actually matters
Save this list.
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