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Q has been making large on-chain withdrawals over the past two days
It has withdrawn $5 million on-chain over the past 30 days
All of them were multiple small transactions, making the activity highly discreet
Only my bot can analyze it
It is impossible to see with the naked eye that Q is making large withdrawals
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Robinhood dex trading volume is cooling down
after hitting $3.5B weekly volume in september
now down to just $600M a week
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Crypto Trade Today
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LIVE786
$LSK Is this rally a trend reversal or a reversion to the moving average?
From a technical perspective, this looks more like a corrective rebound within a downtrend. $LSK The current price is 0.2081. MA5=0.21366 remains above MA20=0.2077, but the price has fallen back below MA5, and the short-term moving averages are starting to flatten as bullish momentum fades. The MACD histogram is still +2.414e-05, but the value is tiny, indicating weak bullish momentum near the zero line; RSI=52.0 is neutral, with neither overbought conditions nor divergence, and there is little momentum for a continued a
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TIA-14.80%
You are my one true passion; I have no other passion but you. 🕊️
Yang Guang bit | October 18 BTC Strategy: Choppy Recovery, Intensifying Battle Between Bulls and Bears
[Today's Plan]
Entry timing: Set up short positions on a rebound into the 82000—82300 range; take light short-term long positions on a pullback to 80800—81000
Stop-loss settings: Set stop-losses for short positions above 82600 and for long positions below 80400
Staggered take-profit targets:
Short target: 81200—81400
Long target: 81800—82000
[Key Takeaways]
BTC saw sharp volatility this week. After CPI came in above expectations, it plunged to a low of 79725, then rebounded from oversold leve
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BTC+0.26%
Jupiter, the DEX aggregator on Solana, and the staking structure of its token $JUP deserve a closer look.
More than 1.1 billion tokens are currently staked, accounting for 33.3% of the circulating supply, with 357,000 participants and an 18.12% annualized yield; protocol buybacks have removed 175 million tokens from circulation, bringing the total supply no longer involved in everyday trading to 38.5%. These are hard on-chain numbers, not expectations being talked up. To save you the hassle of switching around to find it, click the tag below to go straight to the full trading page.
Personal vi
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SOL-0.88%
JUP-3.94%
OP-7.92%
ORDI-3.72%
#美股存储板块跌幅扩大 #ShareWeekly
US Memory Stocks Extend Their Decline: Is the AI Investment Boom Facing a Reality Check?
The US stock market is drawing attention as losses in the memory chip sector continue to widen, raising questions about semiconductor valuations, the sustainability of AI-related demand, and the outlook for technology stocks.
Memory chips have become a critical component of the global technology industry. From AI data centers and cloud computing to smartphones, personal computers, and enterprise storage, modern digital infrastructure depends on efficient memory solutions. As artif
DRAM-2.10%
It’s pretty moving. I got into crypto and U.S. stocks after watching virtual idols back then, though I can’t remember what led me to them. Then, for a while, I went back to everyday life and stopped watching virtual idols or trading U.S. stocks and crypto. Now I’m back in crypto, and I’ve remembered the virtual idols I used to watch. Their songs really do have a way of making you feel at ease. Time passes, mountains and rivers change, but at least I still have you.
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#每周来晒 #沃什IMF讲话 Weekly Market Insights: What Could Warsh’s IMF Speech Mean for Bitcoin and the Global Economy?
The global financial market is entering another important phase as investors carefully evaluate inflation data, interest rate expectations, and the future direction of monetary policy. Against this backdrop, has become a topic worth watching, whileoffers an opportunity to share meaningful market insights, personal analysis, and informed perspectives with the Gate Square community.
📊 Warsh’s IMF Speech: Why Does It Matter?
Remarks by Kevin Warsh at an IMF event can attract significant
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BTC+0.28%
#沃什IMF讲话 #每周来晒 The core of Warsh’s IMF remarks wasn’t that he was dovish or hawkish, but that he refused to signal either direction. Markets interpreted them in the short term as meaning “the probability of an October rate hike has fallen,” but the real impact is that the Fed’s rate path will be harder to predict going forward.
To be clear about the context: this was a fireside chat at the IMF/World Bank annual meetings in Bangkok on October 16. Warsh repeatedly emphasized that he wouldn’t prejudge rate decisions or say in advance what the Fed would do at the remaining meetings this year. The
SPX+2.25%
CRWV-11.90%
BTC+0.28%
Last night, I followed a friend's trades and turned a swing trade into a big move, making 154 points overnight.
The sleep trades were posted at 12 a.m.
The long at 2398 made 26 points, the short at 2416 made 61 points, the long at 2366 made 55 points, and the short at 2416 this morning made 12 points. 154 points in total.
No stop-losses. It went very smoothly.
The streamer has just started livestreaming. You can subscribe to the sleep trades for 1GT. Please follow.
You can watch the replay to see whether the streamer is fake.$ETH
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ETH-0.45%
Bitcoin may be entering its next major cycle.
Fidelity’s Head of Global Macro says the 4-year cycle could be turning bullish again, with power-law patterns supporting the idea.
The interesting part? There’s no dominant narrative yet.
And maybe that’s the point — major bull markets often begin before the story becomes obvious.
$BTC ‌#USSeptemberPPIBeatsExpectations #GateWCTCS9GlobalTradingCompetition #GateBTCAndETHFuturesVolumeRanksTop3
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BTC+0.28%
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Can you really learn Chan Theory in 1 hour? First, the conclusion: you can learn how to "use" it. As for "drawing" the charts—starting today, that's no longer something you need to learn. Why does the traditional path put 99% of people off? The standard way to learn Chan Theory goes like this: read the books three times → memorize the definitions → draw tens of thousands of strokes on historical charts → discover in live trading that your charts don't match the teacher's → sign up for another course. Three years later, your biggest takeaway is four words: "a thousand people, a thousand interpr
XAU-0.11%
#美股存储板块跌幅扩大 Friday's session gave me a clear answer on how deep this storage selloff really is, so I rebuilt my sector notes from the numbers. Here is where I stand after the close on October 16.
The damage is big. Micron fell 5.63% on Friday and 14.6% on the week, while SanDisk dropped 6.85%, Western Digital about 7% and Seagate more than 7%, with the storage chip index down 17.6% on the week. SanDisk closed at $1,299.30, its seventh lower close between October 8 and October 16. Against its June high close of $2,335, that is about 44% lower by my math.
The bigger picture is even harsher. Six
Falcon_Official
#美股存储板块跌幅扩大 The Nature of the U.S. Tech Pullback Is Shifting: From Valuation Repricing to Credit-Chain Repricing
Many people are still viewing U.S. stocks through the old “AI pullback = buying opportunity” playbook. But if you only watch the Nasdaq and the Philadelphia Semiconductor Index, you may miss the most important change:
July was “AI valuation/positioning repricing”; October is a triple hit from “the AI credit chain + high interest rates + geopolitics/oil prices.” The latter is closer to a “credit-side preview” of the bursting of the 2000 internet bubble, but we’re not yet in a full-blown bear market.
I. July pullback: Expensive, crowded, but no blowup!
Trigger: Google/Meta/Tesla raised CAPEX forecasts, FCF turned negative, and the market asked, “When will AI spending pay off?”
QQQ fell from a June high of ~$748.65 to a July 29 low of $661.14, a peak-to-trough decline of 11.7%; QQQ fell 6.5% for the full month of July, and SOXX fell 21%.
The 10-year Treasury yield was at 4.6–4.75%; the VIX spiked to 20.66 on a weekly basis (+24%), but the broad VIX did not stay above 22. VXN reached 26, but there was no panic spike.
The S&P edged down, while equal-weight stocks rose; money rotated within equities (tech → Dow/healthcare/consumer). Bonds didn’t rally, and yields rose → this wasn’t a flight to safety, but “semiconductors are too crowded, trim them first.”
Outcome: The 200-day moving average at $645 held, and stocks recovered after August. This was a correction that could be bought.
II. October pullback: From “valuation” to “who can’t repay their loans?”
The logic behind this tech pullback since October is more like:
Borrow at a 15% cost to build compute capacity → rental income can’t cover interest → credit cracks appear first → semiconductor order expectations get cut → quite a few sell-side firms are using the 2000 internet bubble as a reference (the Nasdaq crashed, while long-bond yields fell from 6.5% to the mid-4% range).
Market action: It’s not a broad selloff; “highly leveraged growth + AI infrastructure” are being singled out for punishment. From 10/14–10/16, the Dow rose 0.67% for the week, XLV/energy were strong, the SPX fell ~1.95% for the week, and the Nasdaq fell 4.48% for the week (its worst since June); the Philadelphia Semiconductor Index (SOX) fell for 8 straight days (the longest streak since 2008);
Among individual stocks: CRWV fell 25% for the week, CDS breached 1000bp, and its 5-year default probability was priced at 60%+.
The 10-year Treasury yield fell from 5.3% to 5.07–5.19%, but this was a safe-haven decline as stocks fell and money fled into Treasuries, not a central-bank rescue; the VIX broke above 22, Brent crude topped 110, and tensions in the Middle East and Russia-Ukraine escalated.
Investor sentiment: the CNN Fear & Greed Index fell to 18, but it’s not yet at the extreme “2–4” levels seen in 2018/2020—meaning the market is shifting from “uncomfortably expensive” to “a little worried about credit,” but this is not a COVID-style liquidity collapse.
III. How have similar “credit-side + tech selloff” pullbacks played out historically?
The 2000 internet bubble burst: The Nasdaq was cut in half, then cut in half again from its peak, while the S&P lagged; valuations were hit first, then earnings, then credit, and bonds ultimately entered a bull market. The difference today: major tech issuers aren’t pure concepts; their cash flows/cloud revenues are real. So this isn’t a repeat of 2000, but “the 2000 credit playbook + the 2022 interest-rate playbook.”
The 2022 rate-driven growth selloff: The 10-year Treasury yield surged from 1.5% to 4.3%, QQQ fell 35% from its peak, and SPY fell 25%; the core issue was the “discount rate,” not credit defaults. The 10-year Treasury yield is now above 5%; megacaps are hurting, but banks/consumer/healthcare haven’t collapsed.
2018 Q4 deleveraging: The VIX spiked to 35, QQQ fell about 20% for the quarter, and stocks made a V-shaped recovery after the Fed turned dovish; the Fed isn’t as hawkish now, but inflation + oil prices mean it can’t turn dovish freely.
March 2020 liquidity black hole: The VIX hit 80, and stocks, bonds, and gold all fell together, with the Fed providing a backstop; there’s no COVID-style liquidity freeze now, and CRWV is an individual credit event, not a market-wide counterparty crisis.
Historical rules of thumb
“VIX above 20 + 10-year Treasury yield rising + tech leading declines” → usually the middle of a pullback, not the bottom.
“VIX plateauing at high levels + 10-year Treasury yield starting to fall + semiconductors no longer making new lows” → only then is it a signal to add to QQQ.
Until credit events (CDS widening, high-yield bond spreads widening) stabilize, every QQQ rebound is prone to being sold.
Historical timing reference: the July pullback took 3–5 weeks to recover; with an October-style “credit + rates + geopolitics” combination, a bottom usually isn’t in until the VIX returns to 16–18, CRWV bonds stop falling, and SOXX posts a high-volume candle without making a new low. This often takes 3–8 weeks; if credit spreads widen to Oracle/major tech bonds, it can drag on for a quarter.
IV. The counterintuitive point during earnings season: stock prices are falling, but earnings haven’t collapsed. In the first week of the new 26Q3 earnings season, about 9% of large S&P 500 companies had reported earnings. Stock prices are falling, but earnings haven’t collapsed—the declines reflect “discount rates + credit expectations,” not “current results.”
Companies that have reported: earnings up 29% year over year, revenue up 12.6%;
26Q1 earnings up 28.6%, 26Q2 up 50.4% → the strongest earnings cycle since 2021Q2;
Market pricing for full-year 2026: earnings up 32.8%, revenue up 12.7%;
Q3/Q4 earnings expectations: +29% / +28.6%;
The S&P’s forward P/E is 19.0: below the 10-year average of 19.1 and the 5-year average of 19.8.
This isn’t an “earnings collapse”; the market is getting ahead of three fears:
① AI CAPEX returns in 2027 will fall short of expectations;
② 10-year Treasury yields at 5%+ will discount long-duration assets;
③ AI credit-chain players like CoreWeave will blow up first.
So this is neither 2000 (earnings fraud/disappearance) nor 2022 (earnings downgrades + interest-rate battering). It’s “earnings are very strong, but valuation logic is being repriced for credit risk.”
V. Why is the week of October 19–23 a turning point?
This isn’t an ordinary earnings week. It’s a week to “use real-economy cash flows to rescue tech valuations.”
1) Wednesday’s two pillars: META + TSLA
What to watch for in META:
Will CAPEX be revised higher again, how are advertising/AI monetization progressing, and what is happening with free cash flow?
If it says “we’re continuing to invest more in AI, but ROI is clear” → it eases July-style spending concerns;
If it says “returns are slower than expected” → QQQ could sell off again.
What to watch for in TSLA:
It’s not just a car company; it’s a high-beta proxy for “AI / robotics / energy storage.”
Deliveries, gross margin, FSD, and what it says about Optimus matter more than sales volume.
A weak TSLA → high-beta tech sentiment could collapse again.
2) Industrial / defense / payments: proof that “the non-AI parts of the economy are holding up”
GE, RTX, NOC, LMT, MMM, UNP, CAT names (URI), AXP, COF:
Industrial orders = the temperature of the real economy;
Credit cards (AXP/COF) = consumer resilience and delinquencies;
Defense (RTX/NOC/LMT) = a geopolitical premium, but with budget constraints.
If they hold up, investors will be more willing to stay in SPY / XLI / XLV rather than go back to catch the falling knife in QQQ.
3) Macro anchors
Tuesday: housing starts / existing-home sales → has housing frozen under 5%+ rates?
Thursday: initial jobless claims + leading indicators → are there cracks in employment?
Friday: manufacturing / services PMI → soft landing or a second downturn in manufacturing?
These data will determine whether the 10-year Treasury yield holds 5.0% or surges to 5.3%–5.5%, and will directly determine the discount rates for SPY / QQQ.#WCTCS9
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Good afternoon!
After making $44.84 million, Machi is now down $36.85 million and has been liquidated on Hyperliquid again.
On October 18, according to Lookonchain, Huang Licheng was completely liquidated again, nearly losing the 250,000 USDC he deposited two days ago.
The cruelest part of high-leverage trading is that past profits cannot protect future positions. Once the market turns against you, no matter how much you’ve made, you could give it all back through a string of losses—and even lose your principal.
Trading isn’t about who has made the most in the past; it’s about who can stay at
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