AMUAWIYA
14 Följer
78 Följare
169 Gilla-markeringar
11 Delade
Inlägg
Alla
Offerter
Videor
Jane Street was behind the 2022 crypto crash.
Jane Street is behind the 2026 crypto crash.
The bull run won’t start until these companies are stopped from using insider information to take advantage of vulnerable situations.
Jane Street is behind the 2026 crypto crash.
The bull run won’t start until these companies are stopped from using insider information to take advantage of vulnerable situations.
BREAKING:
🇺🇸 US Treasury just bought back $2,000,000,000 of its own debt
🇺🇸 US Treasury just bought back $2,000,000,000 of its own debt
MARKET ALERT: Pre-2008 Parallels Detected
JPMorgan CEO Jamie Dimon identifies critical structural risks mirroring the 2005-2007 pre-crisis era.
The Masked Risk: Competing institutions are executing sub-optimal, high-risk lending to artificially inflate Net Interest Income (NII), obscuring systemic credit deterioration.
The Next Catalyst: The impending credit cycle contraction is projected to originate not in housing, but within the hyper-valued Tech/AI infrastructure sector.
Directive: Prepare for inevitable credit cycle normalization.
JPMorgan CEO Jamie Dimon identifies critical structural risks mirroring the 2005-2007 pre-crisis era.
The Masked Risk: Competing institutions are executing sub-optimal, high-risk lending to artificially inflate Net Interest Income (NII), obscuring systemic credit deterioration.
The Next Catalyst: The impending credit cycle contraction is projected to originate not in housing, but within the hyper-valued Tech/AI infrastructure sector.
Directive: Prepare for inevitable credit cycle normalization.
Cardano Sharks: Quietly Swallowing the Supply
While retail panics, the "Smart Money" is feasting. Over the last 6 months, $ADA has dropped 71% (from $0.90 to $0.26), but the on-chain data tells a different story:
The Accumulation: Wallets with 100K–100M ADA have added 819.4M ADA ($213.9M).
The Grab: These "Sharks" and "Whales" now control an additional 1.6% of the total supply.
The Setup: Historically, when whales buy during a massive dip, they are building the floor for the next leg up.
The takeaway: Large holders aren't selling the "crash" they’re buying the discount.
While retail panics, the "Smart Money" is feasting. Over the last 6 months, $ADA has dropped 71% (from $0.90 to $0.26), but the on-chain data tells a different story:
The Accumulation: Wallets with 100K–100M ADA have added 819.4M ADA ($213.9M).
The Grab: These "Sharks" and "Whales" now control an additional 1.6% of the total supply.
The Setup: Historically, when whales buy during a massive dip, they are building the floor for the next leg up.
The takeaway: Large holders aren't selling the "crash" they’re buying the discount.
JUST IN: Microsoft $MSFT partners with Elon Musk's Starlink.
BREAKING: 🇮🇳 AI HAS WIPED OUT $50 BILLION from Indian IT companies so far in 2026.
Nifty IT is down 20.77% YTD.
TCS is down 19.95%.
Infosys is down 21%.
Wipro is down 24%.
HCL Tech is down 17%.
Markets appear to be pricing growing risks to India’s decades long IT outsourcing model.
For nearly 30 years, global corporations relied on Indian firms for enterprise support, maintenance, and back office technology services built around scaling skilled labor.
Agentic AI is beginning to change that cost structure. Companies deploying advanced AI internally are increasingly able to complete work that previously required large outsourced teams at significantly lower cost.
Citrini Research recently warned that economies heavily dependent on white collar outsourcing could face disproportionate disruption as AI driven productivity accelerates. India sits directly at the center of that transition.
Similar reactions are already visible globally, where a single Anthropic announcement erased more than $15 billion from cybersecurity stocks within hours last week.
If AI continues compressing enterprise labor costs, the business model that powered India’s IT expansion for decades could face its biggest crisis.
BY @bulltheoryio
Nifty IT is down 20.77% YTD.
TCS is down 19.95%.
Infosys is down 21%.
Wipro is down 24%.
HCL Tech is down 17%.
Markets appear to be pricing growing risks to India’s decades long IT outsourcing model.
For nearly 30 years, global corporations relied on Indian firms for enterprise support, maintenance, and back office technology services built around scaling skilled labor.
Agentic AI is beginning to change that cost structure. Companies deploying advanced AI internally are increasingly able to complete work that previously required large outsourced teams at significantly lower cost.
Citrini Research recently warned that economies heavily dependent on white collar outsourcing could face disproportionate disruption as AI driven productivity accelerates. India sits directly at the center of that transition.
Similar reactions are already visible globally, where a single Anthropic announcement erased more than $15 billion from cybersecurity stocks within hours last week.
If AI continues compressing enterprise labor costs, the business model that powered India’s IT expansion for decades could face its biggest crisis.
BY @bulltheoryio
TRUMP JUST POSTED THIS !!!
Gold and Silver have wiped out $850 billion in just 4 HOURS.
REMINDER 🚨
🇺🇸 President Trump will deliver his State of the Union address at 9pm ET today.
🇺🇸 President Trump will deliver his State of the Union address at 9pm ET today.
🚨 THE BIGGEST CRYPTO MYSTERY HAS FINALLY BEEN RESOLVED.
Who crashed Luna and UST to 0 and brought down the entire crypto market in 2022?
Jane Street.
The same Jane Street accused of "10AM manipulation" also front-ran the 2022 Terra collapse.
In February 2026, the Terraform Labs bankruptcy administrator filed a lawsuit in Manhattan.
They accused Jane Street of causing the Terra collapse.
For those who don't remember, UST depegged in May 2022.
This caused LUNA to hyperinflate due to its mechanism, and $40B was wiped out within days.
Later, the same collapse had a domino effect, which started a brutal crypto winter.
As per the lawsuit, UST depeg was a smart playbook by Jane.
Here’s the timeline outlined in court:
• In May, Terraform quietly pulls 150M UST liquidity from Curve
• Minutes later, Jane Street allegedly dumps 85M UST
• Panic spreads
• Depeg accelerated, and a collapse happened.
The complaint also claims Jane Street had advance knowledge via a private group chat called “Bryce’s Secret.”
A Jane Street trader who was a former Terraform intern and provided insider information.
But that's not all.
The suit alleges Jane Street:
• Avoided $200M+ in losses
• Profited during the meltdown
• Positioned themselves while retail was wiped out
Jane Street has denied everything and called the lawsuit “baseless.”
But the timeline indicates that Jane Street maybe behind all this.
And this begs a very important question.
What if the real culprit behind the October 10th crash is also Jane Street?
Who crashed Luna and UST to 0 and brought down the entire crypto market in 2022?
Jane Street.
The same Jane Street accused of "10AM manipulation" also front-ran the 2022 Terra collapse.
In February 2026, the Terraform Labs bankruptcy administrator filed a lawsuit in Manhattan.
They accused Jane Street of causing the Terra collapse.
For those who don't remember, UST depegged in May 2022.
This caused LUNA to hyperinflate due to its mechanism, and $40B was wiped out within days.
Later, the same collapse had a domino effect, which started a brutal crypto winter.
As per the lawsuit, UST depeg was a smart playbook by Jane.
Here’s the timeline outlined in court:
• In May, Terraform quietly pulls 150M UST liquidity from Curve
• Minutes later, Jane Street allegedly dumps 85M UST
• Panic spreads
• Depeg accelerated, and a collapse happened.
The complaint also claims Jane Street had advance knowledge via a private group chat called “Bryce’s Secret.”
A Jane Street trader who was a former Terraform intern and provided insider information.
But that's not all.
The suit alleges Jane Street:
• Avoided $200M+ in losses
• Profited during the meltdown
• Positioned themselves while retail was wiped out
Jane Street has denied everything and called the lawsuit “baseless.”
But the timeline indicates that Jane Street maybe behind all this.
And this begs a very important question.
What if the real culprit behind the October 10th crash is also Jane Street?
$FOGO up 9% from our entry.
Strong momentum and now in the top gainer list.
Let’s see how much more it can run
Strong momentum and now in the top gainer list.
Let’s see how much more it can run
$FOGO is moving up.
It bounced from support and broke the trendline.
Looks ready for a move higher. Watching it closely.
by @vexeCrypto
It bounced from support and broke the trendline.
Looks ready for a move higher. Watching it closely.
by @vexeCrypto
🇺🇸🇨🇳 Anthropic says Chinese AI companies including DeepSeek launched "industrial-scale" attacks on their AI model Claude.
🚨 $USD1 DEPEG: WHAT HAPPENED?
On February 23, 2026, the Trump-linked stablecoin USD1 briefly fell to $0.98, sparking fears of a collapse.
The Cause: "Social FUD"
The panic didn't start with a bank failure, but with a deleted retweet from Eric Trump about a Binance deal. In crypto, a founder deleting a post often signals a "canceled deal," triggering instant fear.
Why it was a "False Alarm"
* No Large Sellers: On-chain data showed no whales selling. The drop was caused by many small traders ($10k or less) panicking at once.
* Stable Supply: The total supply of $USD1 stayed at 2.1B, meaning no one was actually cashing out of the ecosystem.
* Fast Recovery: Because the backing was solid, USD1 climbed back to $0.998 within two hours.
The Bottom Line: This was a "vibes-based" crash. The market is so sensitive to the Trump family's social media that a single deleted click wiped out millions in value temporarily proving how fragile stablecoins can be when tied to political figures.
On February 23, 2026, the Trump-linked stablecoin USD1 briefly fell to $0.98, sparking fears of a collapse.
The Cause: "Social FUD"
The panic didn't start with a bank failure, but with a deleted retweet from Eric Trump about a Binance deal. In crypto, a founder deleting a post often signals a "canceled deal," triggering instant fear.
Why it was a "False Alarm"
* No Large Sellers: On-chain data showed no whales selling. The drop was caused by many small traders ($10k or less) panicking at once.
* Stable Supply: The total supply of $USD1 stayed at 2.1B, meaning no one was actually cashing out of the ecosystem.
* Fast Recovery: Because the backing was solid, USD1 climbed back to $0.998 within two hours.
The Bottom Line: This was a "vibes-based" crash. The market is so sensitive to the Trump family's social media that a single deleted click wiped out millions in value temporarily proving how fragile stablecoins can be when tied to political figures.
🚨 AI IS ABOUT TO TRIGGER THE BIGGEST ECONOMIC CRISIS SINCE 2008.
Not because AI is failing. But because AI is moving at a pace the traditional economy is not adjusting to fast enough.
This is what Citrini layed out in its research and here's everything you need to know about it.
The Core Problem: The "Doom Loop"
The top 20% of earners drive over 60% of US consumer spending. But AI is quickly replacing these exact high-paying, white-collar jobs.
When a company replaces a $180,000 worker with a $200/month AI tool, it creates a dangerous cycle:
* Companies cut jobs to boost profits.
* Household income drops, meaning people stop spending money on cars, housing, and travel.
* The economy slows down, forcing companies to buy more AI and cut more jobs to protect their margins.
The harsh reality: Machines produce, but they do not consume.
The Ripple Effect
If this happens at scale, the impact spreads rapidly across the economy:
* Housing Prices Drop: The $13 trillion mortgage market relies on stable salaries. If high-income jobs vanish, people can't buy homes.
* Credit & Tech Stress: As companies shrink teams, they cancel software subscriptions. This lost revenue threatens the $2 trillion private credit market that funds the tech sector.
* Government Deficits: The government loses income tax revenue exactly when unemployed workers need more financial support.
Why This is Different from 2008
2008 was a banking failure. This is a speed crisis.
In past tech revolutions, new jobs replaced old ones over time. The danger with AI is that it might wipe out high-paying cognitive jobs faster than the economy can create new ones.
To track if this is happening, watch for:
* Fewer white-collar job openings and dropping wages.
* Rising defaults in private credit and mortgages.
* Falling government tax receipts.
The risk is not AI failing. The risk is AI working faster than institutions can adjust.
Would you like me to break down which specific white-collar industries are currently showing the highest risk of this AI displacement?
by @Bulltheoryio
Not because AI is failing. But because AI is moving at a pace the traditional economy is not adjusting to fast enough.
This is what Citrini layed out in its research and here's everything you need to know about it.
The Core Problem: The "Doom Loop"
The top 20% of earners drive over 60% of US consumer spending. But AI is quickly replacing these exact high-paying, white-collar jobs.
When a company replaces a $180,000 worker with a $200/month AI tool, it creates a dangerous cycle:
* Companies cut jobs to boost profits.
* Household income drops, meaning people stop spending money on cars, housing, and travel.
* The economy slows down, forcing companies to buy more AI and cut more jobs to protect their margins.
The harsh reality: Machines produce, but they do not consume.
The Ripple Effect
If this happens at scale, the impact spreads rapidly across the economy:
* Housing Prices Drop: The $13 trillion mortgage market relies on stable salaries. If high-income jobs vanish, people can't buy homes.
* Credit & Tech Stress: As companies shrink teams, they cancel software subscriptions. This lost revenue threatens the $2 trillion private credit market that funds the tech sector.
* Government Deficits: The government loses income tax revenue exactly when unemployed workers need more financial support.
Why This is Different from 2008
2008 was a banking failure. This is a speed crisis.
In past tech revolutions, new jobs replaced old ones over time. The danger with AI is that it might wipe out high-paying cognitive jobs faster than the economy can create new ones.
To track if this is happening, watch for:
* Fewer white-collar job openings and dropping wages.
* Rising defaults in private credit and mortgages.
* Falling government tax receipts.
The risk is not AI failing. The risk is AI working faster than institutions can adjust.
Would you like me to break down which specific white-collar industries are currently showing the highest risk of this AI displacement?
by @Bulltheoryio
Logga in för att utforska mer innehåll