Iran Foreign Minister Araghchi will not hold talks with US in Islamabad – Tasnim

So in uncertainty you sell dollar and buy Euro? Dear Lord!!!

The regular diet of market-shaking news seems far too regular to just be accident. That there is somebody behind the scenes doing something seems the simplest explanation. Is it AI? Is it certain market makers? Is the government (Bessent) behind this? Have the algos been hacked to only go up and not down? lol the possibilites are endless, but what is certain is that something is rotten in Denmark.

Same old story from the bull market over the last several years. Tech. In the last several days, semis. Check out semis - see INTC today. Market bulls are relatively immune to oil price fluctuations, not necessarily so relevant in tech. War in the ME - so what. April rally in semis the strongest seen since 1994. SMH up >15% in April and there's a week left to go. We have the tech megacaps ERs next week. Remember last quarter some of them got whacked when their blowout earnings somehow disappoined? And ther huge capex numbers seemed to spook investors? Well, same song & dance now. But add into the mix the incessant truthtweets. Lots of people have trouble trading a bull market. Like moi. But I remain in the game because I'm always putting something on up and down. Kind of miss the days of boring (and more predictable) market moves, though.

this is what AI had to say about this:
Right before major crashes, markets don’t look “scared”—they look delusional.
You typically see parabolic leaders, collapsing breadth, absurd valuations, and narrative detachment from reality. The signal is not fear—it’s overconfidence + internal decay.

1) The canonical pattern (this is the meta-model)

Think of a market as a system:

Market Health=Breadth×Liquidity×Narrative Coherence

Before crashes:

Price (index) ↑
But underlying components ↓

→ Divergence = instability

2) Real historical examples (high signal cases)
A) 2000 Dot-Com Bubble — pure narrative insanity

Cisco Systems
Pets.com

Behavior:
Cisco became the largest company in the world at ~100x earnings
Companies with no revenue went public and doubled instantly
Pets.com IPO → bankrupt within months
Irrational signal:

“Eyeballs > profits”

System insight:
Narrative outran reality
Capital allocation became non-functional
B) 2007 Housing Bubble — stability illusion

Countrywide Financial
Lehman Brothers

Behavior:
Mortgage lenders rising while:
credit quality collapsing
defaults rising
Banks reporting record profits on garbage loans
Irrational signal:

“Housing never goes down nationally”

System failure:
Risk was being mispriced as zero
C) 2021 Meme / Liquidity Bubble — reflexive mania

GameStop
AMC Entertainment

Behavior:
GameStop → ~$20 → $400+
AMC → massive dilution but price still ↑
Retail buying regardless of fundamentals
Irrational signal:

“Price action = truth”

System insight:
Liquidity > fundamentals
Reflexivity loop: price ↑ → belief ↑ → price ↑
D) 1929 — late-stage blowoff

Radio Corporation of America

Behavior:
RCA skyrocketed despite weak earnings
Retail investors borrowing heavily to buy stocks
Irrational signal:

“New era—valuation doesn’t matter”

3) The recurring irrational behaviors (pattern library)
1) Parabolic leaders
A few stocks go vertical
Everyone crowds into the same trades

Example:

2000: Cisco, Microsoft
2021: Tesla, Nvidia (early phase)
2) Breadth collapse (this is huge)
Index ↑
Most stocks ↓

This is your RSP/SPY divergence idea:

Equal-weight index underperforms cap-weight

Meaning:

Market strength is fake—carried by a few names
3) Valuation detachment
P/E, revenue multiples explode
Or ignored entirely

Examples:

Dot-com: no earnings
2021: EV startups at $50B+ with no production
4) Narrative dominance

Markets shift from:

“What are earnings?”
→ to
“What’s the story?”

This is the final phase.

5) Liquidity masking risk
Cheap money hides structural problems

Example:

2007 → subprime
2021 → zero rates + QE
6) Insider behavior divergence
Executives quietly sell into strength
Public still buying
4) The deepest signal (almost nobody watches this properly)
Time-to-failure compression

Before crashes:

Bad news gets ignored faster
Rallies become:
sharper
shorter-lived
Volatility increases under the surface

Think:

System becomes high-energy but unstable

5) Quant-style crash precursor checklist
SignalMeaning
Parabolic leadersCrowded trade
Breadth divergenceWeak foundation
Valuation extremesNarrative > math
Liquidity dependenceFragile system
Insider sellingSmart money exit
Volatility clusteringInstability rising

If ≥4 of these fire:

Crash probability rises sharply

6) The key intuition (this is the real takeaway)

Crashes don’t start when things look bad.

They start when:

Everything looks strong—but only on the surface

Like a bridge:

Load increases
Internal stress accumulates
Then sudden collapse
7) Tie to your trading framework

You already referenced:

RSP/SPY (breadth spread)
This is exactly the kind of signal pros watch

Add:

Leadership concentration
Liquidity conditions
Narrative saturation

→ you get a crash early-warning system

Bottom line

The market right before a crash is:

Externally euphoric, internally deteriorating

Not fear.
Not panic.

Complacent instability.

If you want, I can:

Pull current market signals vs this checklist
Or build a probability model for crash risk using real indicators (breadth, vol, liquidity)

I genuinely don't care if the market is crazy, but reality teaches harsh lessons. If war restarts on weekends (which is highly likely), monday will become a bloodbath for Wall Street and QQQ. Anyways, you learn the hard or the easy way, just choose.