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Quiver Quantitative
BREAKING: The Department of War has said that it may recall Senator Mark Kelly to active duty for a court martial for appearing in this video. https://t.co/VIW2BJvVWa
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BREAKING: The Department of War has said that it may recall Senator Mark Kelly to active duty for a court martial for appearing in this video. https://t.co/VIW2BJvVWa
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Offshore
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Dimitry Nakhla | Babylon Capital®
I think it’s entirely reasonable to see $GOOG surpass $NVDA in market cap at some point within the next three years
As of today:
$NVDA $4.46T
$GOOG $3.83T
$GOOG / $GOOGL is ~17% away https://t.co/ZDlGczN9KZ
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I think it’s entirely reasonable to see $GOOG surpass $NVDA in market cap at some point within the next three years
As of today:
$NVDA $4.46T
$GOOG $3.83T
$GOOG / $GOOGL is ~17% away https://t.co/ZDlGczN9KZ
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AkhenOsiris
RT @BankBraavos: If Google starts monetizing Gemini with ads (while the model thinks) and lowers its subscription price to $0 (or significantly below chatgpt), OpenAI will have an incredibly difficult time. They will have to scramble to build an ad tech stack and an advertiser base, which is a multi-year journey, all while facing pressure on user numbers and ARPU. I think it’s a kill shot, which makes it a no-brainer for Google to attempt.
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RT @BankBraavos: If Google starts monetizing Gemini with ads (while the model thinks) and lowers its subscription price to $0 (or significantly below chatgpt), OpenAI will have an incredibly difficult time. They will have to scramble to build an ad tech stack and an advertiser base, which is a multi-year journey, all while facing pressure on user numbers and ARPU. I think it’s a kill shot, which makes it a no-brainer for Google to attempt.
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Fiscal.ai
Wix is currently trading at its cheapest FCF multiple ever as a public company.
EV/FCF: 11.5x
$WIX https://t.co/wC5pmuHBwj
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Wix is currently trading at its cheapest FCF multiple ever as a public company.
EV/FCF: 11.5x
$WIX https://t.co/wC5pmuHBwj
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Fiscal.ai
Zoom is now buying back more stock than it ever has.
$1.65B in buybacks over the last 12 months.
That's equal to 6.9% of their current market cap.
$ZM https://t.co/fUfLeF2tF9
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Zoom is now buying back more stock than it ever has.
$1.65B in buybacks over the last 12 months.
That's equal to 6.9% of their current market cap.
$ZM https://t.co/fUfLeF2tF9
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App Economy Insights
$ZM Zoom Q3 FY26 (October quarter).
• Customers > $100K TTM +9% Y/Y to 4,364.
• Revenue +4% Y/Y to $1.2B ($20M beat).
• Non-GAAP EPS $1.52 ($0.08 beat).
• Investment gains likely from Anthropic.
• FY26 FCF outlook ~$1.9B ($110M raise). https://t.co/MTAinso4Jo
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$ZM Zoom Q3 FY26 (October quarter).
• Customers > $100K TTM +9% Y/Y to 4,364.
• Revenue +4% Y/Y to $1.2B ($20M beat).
• Non-GAAP EPS $1.52 ($0.08 beat).
• Investment gains likely from Anthropic.
• FY26 FCF outlook ~$1.9B ($110M raise). https://t.co/MTAinso4Jo
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WealthyReadings
RT @WealthyReadings: 🚨BREAKING: The $610 Billion AI Ponzi Scheme Is Not A Ponzi Scheme
Here’s why $NVDA isn’t the disaster the algorithms - and the bears, want you to think it is. Far from it.
Shanaka’s argument claims that Nvidia’s rising inventory, receivables, and DSO suggest demand is slowing and the company is pushing more product than customers can absorb, in terms of need and payment.
In brief: no more demand nor cash to pay for their GPUs.
1. Rising Inventory ≠ Red Flag
Shanaka says rising inventory is evidence of weak demand, but ignores $NVDA pricing - and many other factors we'll talk about.
When unit prices double or triple, the same volume of hardware shows up as a larger dollar value in inventories.
You'll have more bananas for $1M that airplanes, right? Just like you'll have more H100 than GB200.
When we normalize inventory by revenue - or by units shipped, the trend is stable, suggesting this is a pricing effect, not a demand problem and rising inventory in volume.
This can also be illustrated with accounts receivable per revenue, which make the same point: when product prices increase, dollar-denominated metrics rise, so metrics taken individually may look bad but within context, the story looks normal.
That being said, many could point that even then, inventory is rising. To which we need to add context, something algorythms are incapable of.
2. Higher DSO & Supply Chain Constraints
DSO - which represents the time before being paid, rising slightly is consistent with real-world constraints.
$NVDA doesn’t just ship GPUs anymore; they ship racks, custom configurations, integrated systems… These use third-party components, which require more coordination, harder logistics, and can temporarily increase time before revenue recognition and therefore inventory.
Add to this the fact that foundries, as proven many times these quarters during $TSM & co earnings, run at full capacity, and you get even more delays.
More customization + constrained supply chains = longer installation cycles before revenue can be recognized and rising inventories until then.
This is an operational bottleneck, not a credit problem.
A move from 46 to 53 days is marginal especially considering this value has been roughly stable for three quarters.
3. Circular Economy
As for the claims about a circular economy and the same dollars being used across multiple companies, I have no counters but this: circular economies are normal, that’s how economies work.
It only becomes a problem if AI services do not generate enough cash to honor commitments.
Because that’s what those are: commitments, not booked revenues. If those commitments can be honored, then what is the problem?
4. Algorithms Don’t Understand Context
Shanaka claims that this was thankfully found by algorithm - and I can agree with him based on the market's behaviour and violence. But he forgets that algorythm are built to find fraud in 99% of cases.
But $NVDA is the 1%.
When revenue grows 60–80% YoY, it's normal for inventories, receivables, and payables to grow at least comparably in dollar terms. Maybe even slightly higher when added real-world constraints.
What matters is whether these metrics grow disproportionately relative to revenue.
And once normalized, $NVDA ratios are stable, which is consistent with a rapid ongoing expansion, not accounting games or demand collapse.
That being said, everything isn’t necessarily perfect. But again: algorithms are configured to gauge 99% of the market, so of course the 1% will raise red flags.
Add some organic grey cells, context and reality, and the picture is very different, even if the stock continues to fall.
The market is about emotions, not rationality. And X is great at sharing emotions, less for rationality.
Conclusion.
I might be proven wrong in time and $NVDA might be an accounting fraud. I personally continue to believe in the AI revolution, have my own concerns a[...]
RT @WealthyReadings: 🚨BREAKING: The $610 Billion AI Ponzi Scheme Is Not A Ponzi Scheme
Here’s why $NVDA isn’t the disaster the algorithms - and the bears, want you to think it is. Far from it.
Shanaka’s argument claims that Nvidia’s rising inventory, receivables, and DSO suggest demand is slowing and the company is pushing more product than customers can absorb, in terms of need and payment.
In brief: no more demand nor cash to pay for their GPUs.
1. Rising Inventory ≠ Red Flag
Shanaka says rising inventory is evidence of weak demand, but ignores $NVDA pricing - and many other factors we'll talk about.
When unit prices double or triple, the same volume of hardware shows up as a larger dollar value in inventories.
You'll have more bananas for $1M that airplanes, right? Just like you'll have more H100 than GB200.
When we normalize inventory by revenue - or by units shipped, the trend is stable, suggesting this is a pricing effect, not a demand problem and rising inventory in volume.
This can also be illustrated with accounts receivable per revenue, which make the same point: when product prices increase, dollar-denominated metrics rise, so metrics taken individually may look bad but within context, the story looks normal.
That being said, many could point that even then, inventory is rising. To which we need to add context, something algorythms are incapable of.
2. Higher DSO & Supply Chain Constraints
DSO - which represents the time before being paid, rising slightly is consistent with real-world constraints.
$NVDA doesn’t just ship GPUs anymore; they ship racks, custom configurations, integrated systems… These use third-party components, which require more coordination, harder logistics, and can temporarily increase time before revenue recognition and therefore inventory.
Add to this the fact that foundries, as proven many times these quarters during $TSM & co earnings, run at full capacity, and you get even more delays.
More customization + constrained supply chains = longer installation cycles before revenue can be recognized and rising inventories until then.
This is an operational bottleneck, not a credit problem.
A move from 46 to 53 days is marginal especially considering this value has been roughly stable for three quarters.
3. Circular Economy
As for the claims about a circular economy and the same dollars being used across multiple companies, I have no counters but this: circular economies are normal, that’s how economies work.
It only becomes a problem if AI services do not generate enough cash to honor commitments.
Because that’s what those are: commitments, not booked revenues. If those commitments can be honored, then what is the problem?
4. Algorithms Don’t Understand Context
Shanaka claims that this was thankfully found by algorithm - and I can agree with him based on the market's behaviour and violence. But he forgets that algorythm are built to find fraud in 99% of cases.
But $NVDA is the 1%.
When revenue grows 60–80% YoY, it's normal for inventories, receivables, and payables to grow at least comparably in dollar terms. Maybe even slightly higher when added real-world constraints.
What matters is whether these metrics grow disproportionately relative to revenue.
And once normalized, $NVDA ratios are stable, which is consistent with a rapid ongoing expansion, not accounting games or demand collapse.
That being said, everything isn’t necessarily perfect. But again: algorithms are configured to gauge 99% of the market, so of course the 1% will raise red flags.
Add some organic grey cells, context and reality, and the picture is very different, even if the stock continues to fall.
The market is about emotions, not rationality. And X is great at sharing emotions, less for rationality.
Conclusion.
I might be proven wrong in time and $NVDA might be an accounting fraud. I personally continue to believe in the AI revolution, have my own concerns a[...]
Offshore
WealthyReadings RT @WealthyReadings: 🚨BREAKING: The $610 Billion AI Ponzi Scheme Is Not A Ponzi Scheme Here’s why $NVDA isn’t the disaster the algorithms - and the bears, want you to think it is. Far from it. Shanaka’s argument claims that Nvidia’s rising…
bout the circular economy but did not find any indications that AI won't yield cash flow and that commitments can't be honored as of today.
I continue to be bullish. And shared all my moves and reasoning with subscribers yesterday.
The future is bright for those with a system.
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I continue to be bullish. And shared all my moves and reasoning with subscribers yesterday.
The future is bright for those with a system.
BREAKING: The $610 Billion AI Ponzi Scheme Just Collapsed
Last night at 4pm EST, something unprecedented happened. Nvidia stock rallied 5% on earnings, then crashed into negative territory within 18 hours. Wall Street algorithms detected what humans couldn’t: the numbers don’t add up.
Here’s what they found.
Nvidia reported $33.4 billion in unpaid bills, up 89% in one year. Customers who bought chips haven’t paid for them yet. The average wait time for payment stretched from 46 days to 53 days. That extra week represents $10.4 billion that may never arrive.
Meanwhile, Nvidia stockpiled $19.8 billion in unsold chips, up 32% in three months. But management claims demand is insane and supply is constrained. Both cannot be true. Either customers aren’t buying or they’re buying without cash.
The cash flow tells the real story. Nvidia generated $14.5 billion in actual cash but reported $19.3 billion in profit. The gap is $4.8 billion. Healthy chip companies like TSMC and AMD convert over 95% of profits to cash. Nvidia converts 75%. That’s distress level.
Here’s where it gets criminal.
Nvidia gave $2 billion to xAI. xAI borrowed $12.5 billion to buy Nvidia chips. Microsoft gave OpenAI $13 billion. OpenAI committed $50 billion to buy Microsoft cloud. Microsoft ordered $100 billion in Nvidia chips for that cloud. Oracle gave OpenAI $300 billion in cloud credits. OpenAI ordered Nvidia chips for Oracle data centers.
The same dollars circle through different companies and get counted as revenue multiple times. Nvidia books sales, but nobody actually pays. The bills age. The inventory piles up. The cash never comes.
AI company CEOs admitted it themselves last week. Airbnb’s CEO called it vibe revenue. OpenAI burns $9.3 billion per year but makes $3.7 billion. That’s a $5.6 billion annual loss. The $157 billion valuation requires $3.1 trillion in future profits that MIT research shows 95% of AI projects will never generate.
Peter Thiel sold $100 million in Nvidia on November 9. SoftBank dumped $5.8 billion on November 11. Michael Burry bought put options betting Nvidia crashes to $140 by March 2026.
Bitcoin, which tracks AI speculation, dropped from $126,000 in October to $89,567 today. That’s a 29% crash. AI startups hold $26.8 billion in Bitcoin as collateral for loans. When Nvidia falls another 40%, those loans default, forcing $23 billion in Bitcoin sales, crashing crypto to $52,000.
The timeline is now certain. February 2026, Nvidia reports fourth quarter and reveals how many bills aged past 60 days. March 2026, credit agencies downgrade. April 2026, the first restatement. The fraud that took 18 months to build unwinds in 90 days.
Fair value for Nvidia: $71 per share. Current price: $186. The math is simple.
This is the fastest moving financial fraud in history because algorithms detected it in real time. Human investors are 90 days behind.
Read the full data driven deep dive article here - https://t.co/sDEf5Mdrtc tweet