Amateur investor here to learn amid market chaos.
In the midst of chaos, there is also opportunity. – Sun Tzu
Selective follows/DMs to keep it real—no scams.
Wife after I bought a Tesla: “I’m not getting in that thing is you’re going to use FSD.”
Wife after FSD V14.3.4 upgrade: “I’m not riding with you if you’re driving. The @Tesla is a better driver than you!”
It’s not perfect but it really is that good. 👍🏼
@wallstengine The study relies on self-reported data without objective validation and is skewed toward working-age adults and higher-income households. Longer term, transactionally verified studies of wider demographics should be considered.
Economic analysis is a thing of the past. Every time news comes out, money journalists are more like sheep than analysts who dig into numbers. James explains why.
As Wall St keeps pushing rate hikes!
Wall Street’s Keynesian reflex has become a substitute for analysis: every strong jobs print is lazily labeled ‘inflationary’ and automatically translated into ‘the Fed must hike,’ with almost no serious engagement with the underlying cost structure.
Unit labor costs in Q1 2026 are rising at roughly 0.5% year‑on‑year, hardly the stuff of a wage‑price spiral and yet the Street clings to a narrative that treats employment growth as inherently dangerous rather than interrogating productivity, margins, and real wage trends.
What passes for ‘macro’ is increasingly just Pavlovian trading around payroll headlines, while the actual labor‑cost data that should anchor the inflation debate is ignored because it doesn’t fit the story. Yes Wall St lives in a post factual world.
@bluechipdaily My worst day in the market ever!
Luckily, thanks to Larry, I'm still way up overall and paper losses don't bother me. Still came out positive on the day for realized gains.
Gotta love the casino!
@TonySeruga Dude, ride the wave bro! We all know the shore’s out there somewhere but what a ride in the meantime!
Translation: there’s fortunes being made. Watch trends and remember to take profits.
@bluechipdaily While analysts and talking heads make us worry about bubbles, recessions, and bear markets, Larry studiously follows the data and consistently delivers positive gains.
Best decision I ever made was to quit listening to the doomers and follow Larry's advice. Plus I've learned!
@JDunlap1974 BREAKING ALERT : Louisiana Senate passed the map… 3 whole days ago.
Quick, someone notify Websters to update the definition of “breaking news” to “stale information we just discovered on X.”
Thanks for the urgent Thursday recap, champ.
Journalism is thriving. 🤣
Daaammn! Technocracy strikes back!
This is a fantastic rebuttal to the blanket "data centers bad" narrative.
But I'll admit data centers in space will be a great thing.
“THAT DATA CRNTER IS WASTING WATER, STOP ALL DATA CENTERS”
I see, let’s talk about that t-shirt you are wearing first or the jeans, the water could support 100s of AI queries or days of computation.
In the grand theater of human consumption, few spectacles rival the quiet hypocrisy of decrying data centers while embracing mountains of disposable clothing. Fast fashion: cheap, trend-driven garments churned out in endless cycles, represents a voracious, often invisible drain on water, energy, and ecosystems.
Meanwhile, data centers, the engines powering AI and digital life, face scrutiny for their cooling needs.
A clear-eyed comparison reveals misplaced priorities: the garment industry’s water use is vast, frequently consumptive or polluting in water-stressed regions, with products destined for landfills after minimal use.
Data center water, by contrast, is largely local, often recyclable or evaporative (returning to the hydrological cycle), and supports immense economic and innovative value. It also is just a fraction of the garment industry.
Water in the Garment Industry: Hidden Rivers and Polluted Legacies
The fashion and textile sector consumes staggering volumes of water annually. Estimates range from 79 to 215 billion cubic meters (roughly 79–215 trillion liters), supplying the drinking needs of millions of people.
This makes it one of the world’s most water-intensive industries, second only to agriculture in some assessments.
Breaking it down garment by garment:
• A single cotton T-shirt requires ~2,500–2,700 liters of water across its lifecycle (growing, processing, dyeing).
• A pair of jeans: 7,500–10,000 liters.
• Leather items push even higher (8,000+ liters for shoes).21
Cotton, which dominates natural fibers, is particularly thirsty. Global averages hover around 8,920 liters per kg of cotton lint (much from rainwater/“green” water, but ~2,344 liters/kg from irrigation/“blue” water in stressed areas like parts of India, Pakistan, and China).
Processing and dyeing add 100–150 liters per kg of fabric, often with toxic chemicals.
The dyeing phase alone accounts for hundreds of billions of liters yearly and contributes to ~20% of global industrial water pollution.
Untreated wastewater laden with dyes, heavy metals, and chemicals flows into rivers, devastating local ecosystems and communities.
Fast fashion amplifies this: Production has doubled in recent decades, with consumers buying 60% more clothes than 15–20 years ago, while usage duration drops.
About 100 billion garments produced yearly; 92 million tonnes of textile waste generated, much ending in landfills (a garbage truck’s worth every second). In the U.S., landfills received 11.3 million tons of textiles in 2018.
Synthetics (polyester ~55–68% of fibers) add microplastics via washing, now a major ocean pollutant. Cheap clothes are worn briefly, discarded, and replaced—embodying “take-make-waste” at planetary scale.
This water is not local and often lost or ruined: Irrigation depletes aquifers in arid regions; polluted effluent renders water unusable downstream.
The full supply chain spans continents—cotton from India/Uzbekistan, dyeing in Bangladesh/China, exporting environmental costs to vulnerable areas.
Data Centers: Local, Cyclical Water Use for Digital Progress
Data centers primarily use water for evaporative cooling (or increasingly air/closed-loop/immersion systems). Global estimates: ~560 billion liters annually now, potentially doubling or more by 2030 with AI growth: still a fraction of fashion’s footprint and far below agriculture (~70% of global freshwater). U.S. data centers consumed ~64 billion liters directly in 2023.
BRAND NEW CLOTHING IS TOSSED IN THE DESERT WITH PRICE TAGS STILL ON IT.
All to make the brand look rare. Can’t have poor folks wearing it.
Meet the infamous fast fashion “clothing graveyard” (also called the “great fashion garbage patch”) in Chile’s Atacama Desert here:
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Dedicated 3 yrs learning investing basics, charting, intl monetary theory, while following geopolitics, news cycles, parsing Powell's every phrase & facial expression.
Knew it would be hard & I'd have winners & losers. I mostly lost.
Larry made up the losses & more in 1 yr.
Follow Larry.
@merlinscapital Hardly the “average” response. If you don’t think there are spillover repercussions that shake the boomer’s world, then you are living in an alternate reality. Plus, overall they are a compassionate group. Stopping the grift & corruption will benefit all; we are a wealthy nation.
The most coherent, data-backed commodity bull cases I’ve had the pleasure of reading, especially the AI-physical infrastructure mismatch and valuation gap. Atoms and molecules continue to be overweighted in my investing strategy. Jeff tells us why.
Welcome to the most asymmetric trade in modern financial history.
The thread below lays out why. The opportunity exists because capital has chased the AI trade while ignoring the physical assets AI requires to run — assets that have quietly become the best-performing asset class of the decade. Since October 2020 when we first called for the commodity super cycle: QCI Total Return +217%, GSCI Total Return +205%, Gold +140%. NASDAQ trails at +130%. S&P 500 at +85%. The top three are all commodities. Yet oil cannot get out of its own way while copper and the broader atom complex prints fresh highs . That is the dislocation. That is the trade.
Get long. Buckle in. Hang on for the ride.
Forgive the longer posts in this thread — attempting to mimic my old 10-bullet commodity takes. On to it.