Crypto KOL Community & Market Trends

1. Energy prices in August were higher than in July, so the CPI to be released this week should theoretically also be higher than July’s, strengthening expectations of a rate hike.
2. Last week’s strong nonfarm payrolls data also strengthened expectations of a rate hike.
3. Warsh’s current stance is that before major political events, the Federal Reserve should avoid making decisions with significant impact.
4. After the nonfarm payrolls data was released, Trump called for rate cuts, and Bessent also called for rate cuts.
5. Warsh’s hawkish remarks have consistently emphasized the 2% inflation target, fueling market expectations of a rate hike.
Although the data above suggests that the probability of a September rate hike is higher than that of no hike.
However, whether from the perspective of human relationships and social dynamics or the current global situation, a rate hike in September is highly unlikely. There is one other low-probability possibility: if Trump has no hope of winning the election, Warsh could turn against him and raise rates slightly to prove the Federal Reserve’s independence.

ZEC at $1,215—would you still dare to chase it?
First, the surface view: it has gone crazy, and it has become scary.
ZEC started rising from around 800 at the end of August, broke above 1,000 on September 6, and surged straight to 1,298 on September 9, doubling in two weeks. It is now at 1,215, with the daily RSI at 75-78—clearly overbought. There are two types of people in the group: those slapping their thighs for not getting in, and those who chased at 1,300 and are now pretending nothing happened.
First: the ETF is bullish, but it is not a perpetual-motion machine.
The Grayscale ZCSH spot ETF launched on August 25, and its AUM has already surpassed $500 million. Institutional access has opened up, the privacy sector has broadly outperformed BTC, and the AI surveillance + regulatory narrative has propelled ZEC into the leading position.
Some of the bullish news has already been priced in. Even the F2Pool founder criticized it as “narrative-driven, with fundamentals unable to keep up.” The NU7 governance vote is also scheduled for September 14, so short-term sentiment could turn at any moment.
Second: shorts have been liquidated for several billion dollars, but leverage is a double-edged sword.
Futures OI once surged to $2-3 billion, with shorts repeatedly squeezed and liquidated on a large scale. Whales are also buying.
As long as shorts remain, longs keep rising; once the shorts are all dead, the longs should be next.
Below 1200-1225, long liquidations are concentrated; above 1290-1305, short liquidations are also substantial.
Third: the fundamentals are improving, but the price has run too fast.
The Ironwood upgrade fixed a key vulnerability in the Orchard pool, reducing supply-integrity risks. The share of shielded supply has risen to 25-30%, with 16.92 million/21 million in circulation, and the halving is scheduled for 2028. The long-term thesis is “essential privacy demand in the AI era + BTC-like monetary policy.”
But what about the short term? On-chain activity relative to market cap is still not particularly high. Many purchases are driven not by payment demand, but by capital speculation.
Fourth: the macro window is here—don’t play the hero before the data.
August PPI, September 11 CPI, and the September 15-16 FOMC are coming, with the probability of a 25-bp rate hike around 60%. BTC is oscillating around $78,000.
Hawkish → As a high-beta altcoin, ZEC will retreat more sharply than BTC. Dovish → The privacy narrative will continue to command a premium.
Support: 1200 (psychological level) → 1160-1170 → 1100-1090
Resistance: 1250-1260 → 1290-1300 → 1430
The bulls and bears face off—you decide
On one side:
ETF AUM above $500 million, institutional access opened
The privacy sector is strengthening, shorts are getting liquidated, and whales are buying
The halving is in 2028, making the supply dynamics favorable
On the other side:
RSI 75-78, clearly overbought
OI at $2-3 billion, with crowded leverage
Some bullish news is already priced in, and the F2Pool founder has started criticizing it
CPI/FOMC window—if BTC weakens, ZEC will collapse with it
Trading strategy
Short term:
Sell high and buy low within the 1200-1260 range.
If the rebound meets resistance at 1250-1260 and the 4H chart turns weak, lightly test a short position, with a stop-loss above 1290 and targets of 1210-1200.
If 1200-1210 stabilizes on a pullback (a long lower wick or a high-volume bullish candle), lightly test a long position, with a stop-loss below 1180 and targets of 1250-1290.
Mid term:
The better buying zone is 1100-1160, or add after confirming that 1200 is solid support. If it holds above 1300, look for 1430-1500. Reduce your position if the daily candle closes below 1160 on high volume.
Long term:
Core holdings can be retained, but take profits on the higher-priced portion. Wait for a better point to add.
ZEC now resembles a meme coin that doubled right after listing—
Rising enough to make you question reality, falling enough to make you question yourself.
If 1200 fails to hold, the story turns into an accident; if 1200 holds, 1298 is only a midway stop.
You didn’t dare buy at 800, said 1,000 was too high, rushed in at 1,300, and now at 1,215 you’re asking what to do.
You’re not trading ZEC—you’re trading your own greed.
At 1,215, do you dare to chase?#Gate全球首发股票事件合约 #苹果发布会 #LAPTOP空投今晚开放 $BTC $ETH $ZEC

Making money is really simple: just get into the leading project of this cycle $Pons I have a pick that is 100% guaranteed to make money. Do you want to get in? A lot of people think pons is too expensive, and I don’t want to buy it. I only have that little money, so buying it seems pointless. But after going back and forth between p and p, in the end, your money will definitely be worse off than if you had just stayed in pons. The price adjusted to 0.65, but in the long run, a drop is a good thing because it lets many people who missed the entry get in. I’ve been thinking about it the whole time $pons

#LeanMuscle Joining the trend as a beginner lifter, body fat is still at 18%, and I’m working hard to cut it down.

When the iPhone 4 launched in 2010, it cost 52.79 $BTC to buy one.
Today, it only costs 0.02 BTC to buy the new iPhone 18.

Regarding test orders and trading frequency, this is already the level of control I was talking about. To be honest, it still takes practice.

I have to say, the two strategies I set for myself in 2026 have been very successful:
1. I’m still keeping my funds in separate accounts: a spot holdings account and a flexible trading account. However, I’ve increased the proportion allocated to the flexible account to 40%;
2. I’ve reduced my trading frequency. Although I personally feel that I’m still placing a few too many test trades, compared with before, my ability to control position sizes has improved significantly. I don’t take large positions when testing a trade, and I don’t test trades with large positions.
The result is:

How to Find Undervalued Stocks? P/E Ratios Clearly Diverge from Peers Without Any Definitive Bad News, Cash Machines Trading at Rock-Bottom Multiples: 👇
1. Micron $MU
One of the world’s three major memory chipmakers. AI servers are rapidly lifting its profits, while its forward P/E remains clearly below those of the semiconductor industry and NVIDIA. The market discounts it because memory is cyclical and prices will fall after capacity expansion. Its strengths are production capacity and current earnings power; it is cheap because of cyclical fears.
2. SK Hynix $SKHY
South Korea’s leading memory chipmaker and a leader in HBM. Its forward P/E is often even lower than Micron’s and far below those of TSMC and NVIDIA. Its strength is its AI memory market share. The discount likewise reflects the belief that memory will eventually become oversupplied, along with the Korean market’s habitual low multiples.
3. General Motors $GM
A U.S. auto giant whose P/E is often in the single digits, far below those of consumer and technology stocks. Cash and profits are still there; the discount comes from price wars, EV investment, and the auto cycle. It is cheap because the market is unwilling to assign growth-stock valuations to automakers.
4. Ford Motor $F
Similar to GM, but more focused on traditional vehicles and cash flow, with its P/E also stuck at a low level. Its strengths are its brand and North American sales. Its appeal lies in a cyclical stock being sold at liquidation-level prices; the risks are EVs and price wars.
5. Comcast $CMCSA
One of the largest broadband providers in the United States, also owning NBC and streaming businesses. Its P/E is low compared with the media and communications sector. Its strength is its broadband cash cow; the discount comes from the old narrative of declining cable TV and money-losing streaming.
6. American International Group $AIG
A longstanding insurance giant, with a P/E below the insurance industry average and a price-to-book ratio near book value. Its strengths are its underwriting and investment foundations. The discount comes from mediocre growth and memories of its historical baggage, not from a lack of current profits.
7. HP Inc. $HPQ
A leader in PCs and printers, with a P/E often below those of its technology hardware peers. Its strengths are stable dividends and buybacks; the discount comes from the lack of growth in the PC industry. It makes money from a mature business, not from a story.
8. PayPal $PYPL
A veteran in electronic payments, with a P/E below that of many fintech and payments stocks. Its user and merchant networks are still in place; the discount comes from slowing growth and users shifting to Apple Pay and banking apps. It is cheap because of sentiment.
9. Bank of America $BAC
One of the largest retail banks in the United States, with a P/E below that of technology stocks and often below its historical highs. Its strengths are deposits and branches; the discount comes from concerns about net interest margins and loan quality. A classic case of “everyone knows it, yet its multiple isn’t high.”
10. Lockheed Martin $LMT
A U.S. defense contractor leader whose orders are tied to defense budgets. Its P/E is not expensive relative to industrial companies and some growth stocks. Its strength is order visibility; the discount comes from budget politics and project delays, not from a lack of business.
Cyclical stocks shouldn’t be sold at liquidation-level prices either!

Notice: The private community has reached 50 members, so the fee has increased from 456U to 666U. I keep my word.😀😃😄😁 September 10, 2026------Teachers' Day

$GOOGL Still too comprehensive!
Imagine having to meticulously draw every power plant, every high-voltage cable, every substation, and even every switch and wire in the homes of a megacity into one complete circuit diagram.
What’s even more astonishing is that the actual space represented by this map is only about the size of a grain of coarse salt.
That is the major feat just accomplished by Google Research in collaboration with leading scientific institutions: They have completely mapped the entire central nervous system of an adult male fruit fly.
This is not merely a brain. It includes the brain, the visual nervous system, and the ventral nerve cord, which is equivalent to the human spinal cord. The complete map contains more than 166,000 neurons and a total of 125 million synaptic connections.
To create this map, scientists sliced the fruit fly into thousands of ultrathin, nanoscale sections and used electron microscopy to scan an enormous amount of image data. Google then deployed specialized neural network algorithms to assemble millions of two-dimensional slices into three-dimensional neuron structures. Even with the assistance of advanced AI, human researchers still spent a total of 44 person-years verifying and correcting the images.
Once you truly understand this neural wiring diagram, you realize how ingenious the mechanisms of biological evolution are. For example, scientists discovered that when fruit flies are flying, walking, or avoiding obstacles, the brain is not directing every leg in real time. Most movements are autonomously determined by local neural circuits near the limbs. Isn’t that natural edge computing?
This also explains why Google has been able to maintain such a high ceiling in the industry. People usually see Google as a commercial company that operates search, advertising, and YouTube. But at its core, it is actually an engineering computing engine for solving extremely large-scale, complex problems. From using AlphaFold to predict protein structures, to reconstructing slices of the human cerebral cortex, to mapping the complete central nervous system of a fruit fly today.
When a company can deeply combine cutting-edge computing power, AI algorithms, and fundamental scientific research, it is not merely working on its business today. It is laying the foundation for human technology over the coming decades!

$LAPTOP has truly played the role of a “master”: rather than studying K-lines, they draw their own K-lines.
Going from suddenly getting rich to suddenly losing big can happen in an instant.

$LAPTOP staged a true “god-level trader”: not studying K-lines, but drawing their own K-lines.
Going from fabulously rich to disastrously broke is really just a matter of an instant.

Chen Guilin’s Trading Notes: 2026年9月10日 It’s been a long time since I’ve discussed the market. Let’s sort things out. 1， $BTC has formed an upward 12345 impulse starting from 57 and continuing to the present (the black line in Figure 1). As everyone knows, an impulse wave does not exist on its own, so either it is the A wave of an ABC pattern (blue in Figure 1), or it is wave 1 of a 12345 sequence. This is the larger degree;

Biden's son has responded: $LAPTOP 's plunge has nothing to do with him; he himself didn't make a cent.
So the question is: who exactly is dumping?
All I can say is, getting rich overnight or suffering huge losses can happen in an instant.

Today’s AI U.S. stock information gap:
1. Trump is giving away money! He promised that if Republicans win the midterm elections, he’ll give voters a $5000 dividend, totaling $1 trillion. Where is all that money supposed to come from?
2. $Jacob went viral. After resigning from $Anthropic , he said AI will destroy all of humanity within 10 years. Musk: Looks like a setup.
3. $Meta surged 7%! Its AI agent assistant is highly popular, ranking fourth on the App Store charts and far exceeding expectations.
4. Is Robinhood’s bull market over? $pons has fallen to 600m. The party’s over, and once again, I’m the one picking up the tab.
5. I hadn’t checked $OpenAI for a few days, and it had surged 33% from the bottom, reaching $920! It revealed an unreleased new model, solved a thousand-year-old mathematical problem, and generated 130 billion tokens. I really feel like humanity’s destruction is imminent 😂.

$200,000 bought in at base:0xb095274743941e953c746f9c228da9c18bb6ec29, and a few hours later it turned into $700. This guy probably wasn't too happy. So, he added to his position early this morning: he spent another $49,000 to buy 24,367 LAPTOP at $2. Hey, after averaging down at $2, it has now dropped to $0.8 again. Is he going to keep averaging down🥹 He currently holds 25,286 LAPTOP, with an average cost basis of

The fatal weakness of “stock-coin Memes”: once trading volume shrinks, buybacks, dividends, and burns all go to zero
On the evening of September 2, Robinhood Chain. Within the first hour of trading, JINQIAN’s market cap surged to $80 million. In the second hour, it fell to $10 million. By press time, only $3 million remained.
Two hours, start to finish. Those who got in may still be calculating how many zeros they could earn. Those who got out have lost their entire principal.
This is not an isolated case. On September 10, MEME fell from a peak of $170 million to $62 million, down 23% in 24 hours. CASHCAT fell 12%, ZCAT fell 18%, and USELESS fell 23%. BONER fell 18%, microduck fell 46%, and STRATTON fell 56%.
Across chains, all were affected.
The funds did not move from one project to another. They exited the market altogether.
DeFi researcher Ignas put it bluntly: the stock-coin Meme narrative relies on trading volume and fees, not fundamentals. Once trading volume shrinks, funds for dividends, buybacks, and burns immediately decrease, traders’ incentive to hold declines, and selling pressure follows.
In plain English:
The “value support” for these coins is trading volume itself. Once the trading volume is gone, everything is gone.
Think about what this means—
You buy a coin that promises to use platform fees for buybacks, dividends, and burns. Sounds like a stock, right?
But the question is: where do the fees come from? Trading. Where does the trading come from? The next person coming in to buy.
The chain works like this—
Trading volume↓ → Fee revenue↓ → Funds for buybacks/dividends/burns↓ → Incentive to hold↓ → Selling pressure↑ → Trading volume↓↓
This is a death spiral. And that spiral is already turning.
Ignas made it very clear: Uniswap’s trading volume has already started declining. ZCAT, STONK, PONS, INDEX, SHROOM, CASHCAT, and established DEXs such as RAY that use fees for buybacks all follow exactly the same logic—once there is no trading volume, the incentives stop.
You might say: if you annualize the current fees, isn’t the return really attractive?
Ignas fired back directly: “Extrapolating the current wave of fees to estimate a full-year return is basically predicting that market conditions will never cool down. That’s absurd.”
Here’s a point of reference. Coinbase had $547 billion in trading volume in Q4 2021. A year later, it was down to $145 billion, a 74% drop.
What is Coinbase? The largest regulated exchange in the United States, with licenses, institutional clients, and real revenue.
Even its trading volume can fall 74% in a year.
What about those Meme coins propped up by a single narrative, a KOL’s call, and a feel-good story about “squeezing Wall Street”?
Ignas estimates that once Meme coin trading volume is cut in half, the market cap could fall by more than 95%.
Not a 50% drop. A collapse to almost zero.
JINQIAN’s story deserves a few more words, because it exposed the essence of this type of asset far too clearly.
A KOL named Rune posted that he had spent $1.8 million to acquire a 37.4% stake in a Nasdaq-listed company, planned to tokenize the stock, and then issue a paired Meme coin to engineer a short squeeze.
The story was perfect. Retail investors taking down institutions, crypto taking down Wall Street—the standard feel-good script. The community was buzzing, waiting for the coin to launch.
JINQIAN went live. $80 million in one hour. Then it crashed to $10 million within an hour.
Later, Rune clarified that the acquisition tweet had been generated by Claude and was completely fabricated.
The story was fake. The coin was real. The losses were real too.
Think about that. A group of people rushed in not because they had analyzed any fundamentals, not because they had read any financial statements, but because of a story that “sounded exciting.”
That is the essence of stock-coin Memes—you are not buying an asset; you are buying a narrative. Once the narrative stops, the asset goes to zero.
Now look back at the structure:
Last week, Robinhood Chain’s fee revenue was approximately equivalent to 73% of Uniswap’s UNI burn revenue.
The hype is indeed still there.
But Ignas made an especially painful point: “All projects are tied to one thing: whether people are still willing to speculate. Interest in trading will continue until people stop making money or become tired of losing.”
Pay attention to this logic.
It is not tied to some technological breakthrough. It is not tied to some business model. It is tied to whether “people are still willing to speculate.”
How is that different from going to a casino? At least a casino has a house to backstop it. Here, there is not even a house—the “buybacks,” “dividends,” and “burns” are all just ways of using new bagholders’ money to hand candy to the old bagholders.
When the new bagholders stop coming, the candy disappears. When the candy disappears, the old bagholders leave. When the old bagholders leave, the price collapses.
You think you are buying a stock token. In reality, you are buying a bet that “people will keep speculating.”
The casino doors can close at any time.#Gate全球首发股票事件合约 #苹果发布会 #LAPTOP空投今晚开放 $UNI $RAY $PONS

What’s most worth watching in US stocks today isn’t any single tech stock, but the 10-year US Treasury yield.
It has surged to nearly 4.84%, reaching a high for recent years.
Why does this matter?
Because for tech stocks:
The higher Treasury yields are = the higher risk-free returns are = the less attractive high-valuation stocks become.
High-valuation sectors such as AI, semiconductors, and software are especially likely to see their valuations pressured first.
The market’s trading chain is very clear right now:
Rising oil prices → higher inflation expectations → less room for the Federal Reserve to turn dovish → rising Treasury yields → pressure on tech stocks.
So when I look at US stocks recently, I’ll check the 10-year Treasury first, then the Nasdaq.
If yields continue moving toward 4.9% or even 5%, it will be difficult for tech stocks to rise comfortably.
But if Treasuries begin to fall significantly, AI and semiconductors will instead be the first areas to see capital flow back in.
In one sentence: What determines tech stocks’ short-term valuations right now isn’t just earnings, but also interest rates.

An “AI trust crisis” triggered a 60% surge in VVV
A mathematician asked a question. Then VVV surged 60%.
Here’s what happened.
New York University mathematician Tristan Buckmaster and his collaborators fed the draft of their entire project into Codex—OpenAI’s coding model. They wanted it to help with some calculations.
Then he heard something: An internal OpenAI team had made similar progress in the same area.
So he asked directly: “Were my conversations used to train your models?”
The response was: The model did not access user data.
But as for the “training” part—there was no answer.
Later, OpenAI issued an official response, essentially denying that researchers or agents had accessed specific user data, but—
“Although unlikely, it cannot be ruled out.”
Think about that wording.
“Unlikely, but cannot be ruled out.”
Translated into plain English: “We didn’t look, but we can’t guarantee we didn’t.”
The community’s fear is real.
When the stakes are high enough, can these labs—OpenAI, Anthropic, Google—see all of your work and then produce the results before you do?
Buckmaster is no nobody. He is an NYU mathematician working on partial differential equations and fluid mechanics, and has published in Annals of Mathematics. Even he couldn’t get a clear answer.
What about you?
The things you type into ChatGPT every day—code, strategies, paper drafts, business plans—where do they go?
Someone has already given an answer with real money.
Trader based16z directly showed his positions: spot + perpetual contracts + OTC call options with a $25 strike price, all long VVV.
His logic is simple: This incident has made the importance of “private inference” widely understood. And among all the assets capturing this narrative, Venice is the most liquid.
He even compared VVV’s circulating market cap with ZEC’s situation when it was at $50.
How far did ZEC rise from $50? Look it up yourself.
So what exactly is Venice doing?
Venice AI, founded by Erik Voorhees, provides consumers with a chat application and developers with an API. Its selling point comes down to two words: privacy and fewer restrictions.
Privacy comes in four layers: anonymous mode hides your identity; zero-retention mode relies on the service provider’s discretion; TEE mode puts inference inside a protected hardware environment; and end-to-end encryption mode encrypts data from your device until it is decrypted inside the protected environment.
The business is already up and running.
Data disclosed by Banyan shows that Venice’s annualized revenue rose from $14 million in January this year to more than $100 million in August.
VVV is a token issued by Venice on Base. For every $100 of API credits purchased, $5 is used to buy back and burn VVV. On September 1, annual emissions had already fallen from 3 million tokens to 2.5 million, and on October 1 they will drop again to 2 million.
Revenue is rising. Supply is falling. Demand is increasing.
This is not the fundamental case for a “narrative token.”
But the truly painful question is not whether Venice is doing well.
It is: Why was this able to ignite the market?
Because AI is moving from “answering general-knowledge questions” to participating in academic papers, code, product development, and trading strategies.
Every word you type into the input box is becoming an exploitable asset.
In the past, when you asked AI, “What’s the weather like today?” nobody cared. Now, when you feed it the core strategy of a project or an unpublished paper draft—
you are feeding ammunition to a machine that may belong to a competitor.
OpenAI said, “Although unlikely, it cannot be ruled out.”
The market said: “Then I’ll solve it myself.”
VVV broke through $25 and briefly hit a new high. A 60% gain.
This is not hype.
This is the market’s first pricing of the product-market fit for “private inference.”
As AI grows more powerful, the things you entrust to it become more valuable—
whoever can let you use AI without showing your hand to others will win.
Venice has found its place.
VVV has simply put a price on that place.#Gate全球首发股票事件合约 #苹果发布会 #LAPTOP空投今晚开放 $BTC $ZEC $VVV

A few days ago, I said the crypto market had entered difficulty mode and that what followed might be a fish-tail market, so I even locked my futures positions for the holiday; but after the holiday, it’s still a market that’s not suitable for opening futures positions🤣 The short-term price action is just wildly erratic. I really feel that even if a god came down, it wouldn’t help. At this point, making or losing money is all down to skill, with a 1:1 risk-reward ratio.