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🤖 After AI tech stocks plunged, will the next wave of opportunity be in applications?

U.S. stocks saw a sharp correction overnight, with chip, server, and data center stocks all under pressure. AI’s high valuations are once again being put to the test.

But the AI story isn’t over. The market’s focus is shifting:
From “who is investing the most in computing power” to “who can actually make money with AI.”

🔍 Google: Can AI search and advertising generate more revenue?
☁️ Microsoft, Amazon: Can cloud computing and AI services continue to deliver growth?
🚀 Meta, Palantir, Oracle: Can AI comm
GateSquare
🤖 After AI tech stocks plunged, will the next wave of opportunity be in applications?

U.S. stocks saw a sharp correction overnight, with chip, server, and data center stocks all under pressure. AI’s high valuations are once again being put to the test.

But the AI story isn’t over. The market’s focus is shifting:
From “who is investing the most in computing power” to “who can actually make money with AI.”

🔍 Google: Can AI search and advertising generate more revenue?
☁️ Microsoft, Amazon: Can cloud computing and AI services continue to deliver growth?
🚀 Meta, Palantir, Oracle: Can AI commercialization open up new profit opportunities?

If capital shifts from AI computing power to applications, who do you think is most likely to rebound first?
Join #美股史诗级抛售 on Gate Square to share your observations on AI stocks, market outlook, or trading strategies.

🎁 The Gate AI Applications Campaign is also underway. Trade designated AI application and cloud service stocks and complete tasks for a chance to enter a lucky draw and compete for the leaderboard. You could win up to 1,888 USDT in Google stock trial funds.

👉 Campaign entry: https://www.gate.com/zh/campaigns/6916
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November 6: Gold enters a correction, pulling back sharply overnight

Yesterday, gold surged rapidly during the Asian session, with prices climbing to around $4,146. It then began to fluctuate lower during the European session, with the decline accelerating from session to session. Gold closed near $4,088. After opening slightly lower during today’s Asian session, prices continued yesterday’s weak trend, moving further down to test the $4,048 area.

The market logic has not changed, but the focus has shifted. With the midterm election results settled, expectations of a “blue wave” have been fu
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$BTC $ETH Midday Analysis, Nov. 6, published at 12:12 p.m.

The midterm elections are the fuse; last night’s sharp drop was just the appetizer. Tonight will be the hunt. The short on Sandisk at 996 and the short on gold at 4129 both hit their take-profit targets last night. Congratulations to everyone who followed along. Here at Rui Ge’s, all take-profit and stop-loss trades are reviewed so you can learn to respect the market. By reviewing and reflecting with me, you’ll become stronger. If you like the streamer, feel free to follow and watch for a while to see whether a subscription is worthwh
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What Is Cross-Exchange Arbitrage? Why Can Price Differences Between Two Platforms Be Offset by Transfer Time and Capital Lock-Up Costs?

The same crypto asset may have different quoted prices on different exchanges. Traders can try to buy on the platform with the lower price and sell on the one with the higher price to capture the spread. But this seemingly simple trade is also affected by fees, transfer speed, and market volatility.

First, what is cross-exchange arbitrage?

Cross-exchange arbitrage involves trading on price differences for the same asset across different platforms. For examp
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The better the backtest returns look, the more you should ask: do these results hold up in real markets?

A trading strategy has a high historical return, a decent win rate, and a maximum drawdown within an acceptable range.

You might think the only thing left is to deploy it in live trading.

But why do some strategies perform noticeably worse as soon as they enter real markets?

The problem may not be that the strategy is completely ineffective, but that the conditions it relies on in backtesting do not match those of real trading.

A backtest shows that under specific data, assumptions, an
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🔥 What’s worth talking about today? Gate Square trending topics are live!

🔹 #USStocksFaceHistoricSelloff
Tech stocks are under heavy pressure. Is this just a correction, or the start of a deeper selloff?
🔹 #USNonfarmPayrolls
U.S. jobs data is due tonight. Will it help markets stabilize, or trigger another round of volatility?
🔹 #CryptoMarketUnderPressure
$BTC and $ETH are falling with broader risk assets. Buy the dip, reduce exposure, or stay on the sidelines?

Quality content can get traffic support + Featured placement.
💰 Got a view? Share it:
https://www.gate.com/post/topic
Gate_Square
🔥 What’s worth talking about today? Gate Square trending topics are live!

🔹 #USStocksFaceHistoricSelloff
Tech stocks are under heavy pressure. Is this just a correction, or the start of a deeper selloff?
🔹 #USNonfarmPayrolls
U.S. jobs data is due tonight. Will it help markets stabilize, or trigger another round of volatility?
🔹 #CryptoMarketUnderPressure
$BTC and $ETH are falling with broader risk assets. Buy the dip, reduce exposure, or stay on the sidelines?

Quality content can get traffic support + Featured placement.
💰 Got a view? Share it:
https://www.gate.com/post/topic
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#AsiaPacificStocksPlunge 🔬

Is the sea of red in Asia merely profit-taking?

Those fixated on the massive red percentages flashing across their screens during the historic collapse of Asian markets are missing the true paradox: the very companies that ignited the artificial intelligence revolution are now buckling under the political uncertainty of the future they themselves created.

The wave of selling triggered in global markets following the U.S. midterm elections has swept across the Pacific, striking the heart of Asia’s technology sector with the force of a bombshell. In South Korea, th
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Don’t let the numbers mislead you; those figures don’t point to a market collapse, but rather to an entirely different structural mechanism.

The real story lies within a historic wave of selling—triggered in the artificial intelligence and semiconductor sectors following the U.S. midterm elections—that rippled across the Pacific all the way to Seoul. What unfolded on Thursday, November 5, 2026, was more than just a correction; it was a watershed moment—a stress test for the AI trade, challenging both its valuations and the underlying policy landscape.

Just how severe was the sell-off on Wall Street?

The wave of selling that hit U.S. markets on Thursday marked the sharpest decline in recent years. The Nasdaq tumbled 5.52% to 24,315 points, falling 11.9% from its early-October peak and officially entering correction territory. The S&P 500 dropped 4.36%, while the Dow Jones slid 3.44%, shedding 1,833 points.

The devastation was most acute in the semiconductor sector. The semiconductor index plummeted 12.25% in a single day—its worst performance since March 2020. The stocks on your screen tell the story: Nvidia fell 9.33%, AMD 17.64%, Micron 17.23%, and SanDisk 22.24%, with various Asian ADRs also posting losses exceeding 10%. In total, approximately $2 trillion in market capitalization evaporated in just one day.

What was the hidden cause behind the sell-off?

There isn’t a single reason, but the midterm elections served as the primary catalyst. The Democrats gaining the upper hand in Congress has raised questions among investors as to whether regulations concerning the construction of data centers might become more stringent.

The market has begun to price in the possibility that the development of data centers—the backbone of the artificial intelligence revolution—could slow down due to new energy and environmental regulations. Signals from newly elected officials in states like Texas, Georgia, and Ohio, suggesting potential restrictions on data centers, have further fueled these concerns. According to one analysis, approximately 30% of the projected data center capacity in the United States through 2028 is now at risk due to potential construction delays.

Compounding this, a chip manufacturer’s announcement of a 26% decline in sales for its mobile phone chips has led the market to wonder: is spending on artificial intelligence beginning to cool off?

How did the shockwave from across the Pacific hit Seoul?

The turmoil on Wall Street spread to South Korea the moment its markets opened. The KOSPI index plummeted by more than 8%, falling below the 5,000-point mark and triggering a circuit breaker just three minutes into the trading session.

Korean corporate giants were at the heart of this collapse: SK Hynix shares fell by as much as 11.71% to 1,116,000 won—a sharp reversal, considering the company had reported record-breaking quarterly sales just a week earlier. Samsung Electronics shares dropped 9.98% to 181,400 won. A similar trend emerged in Japan, where Tokyo Electron, SoftBank, and Advantest saw their values decline by 2.58%, 8.59%, and 5.07%, respectively. Because the stock markets in South Korea and Japan are heavily weighted toward the semiconductor sector, they tend to amplify any technology-related shock originating in the United States. What is the secret behind the "-38" figures on the screen?

The extreme figures—such as -38.65% and +38.64%—seen in the leveraged products in the image do not represent a market collapse; rather, they are the result of reverse splits and the structural nature of leveraged ETFs.

For a product designed to deliver triple the daily performance of an index, a 12% decline in the semiconductor index would mathematically result in a drop of approximately 36%. The 38% decline shown on the screen also reflects a price adjustment following a reverse split. Conversely, a product designed to move inversely to the index (betting on a decline) will rise as the index falls. However, because such funds tend to lose value consistently over the long term, they frequently undergo reverse splits. The +38% increase seen on the screen is actually a byproduct of the consolidation process intended to offset the fund's historical loss in value.

In short, these figures are "structural noise" inherent to the nature of leveraged ETFs; they do not reflect the actual performance of the underlying stocks.

Is this a buying opportunity or a new regime?

The market is currently caught between two opposing scenarios. On one side are those who argue that this is merely a temporary correction—a liquidation of overheated positions in the artificial intelligence sector. On the other side are those who believe that AI valuations remain detached from reality and that this is, therefore, not a buying opportunity.

One thing is certain: the market is no longer driven by the same narrative. The triad of valuation, policy, and liquidity is being recalibrated. It would not be surprising to see further macro shocks of this nature until regulations regarding data centers in the United States are clarified. What you should monitor is the distinction between technical price adjustments in leveraged products and the primary market trend; the extent to which the declines in Seoul and Tokyo are driven by regulatory uncertainty in the United States; and whether semiconductor companies—despite these policy-related headwinds—are managing to maintain their order backlogs.

This content is for informational purposes only and does not constitute investment advice.

$MU $AMD $SNDK $TSLA $INTC
#USStocksFaceHistoricSelloff
#GateSquareTradingChallenge #Gate股票畅聊季 #GateStockTalkSeason #ShareWeekly
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Why Can You Still Get Liquidated Even When You Read the Market Right? Position Management Is What Really Determines Whether You Survive as a Trader

In the cryptocurrency market, there is a frustrating experience:

You correctly predict the market’s direction, and your analysis is not without basis. The price may even eventually move in the direction you expected. But before the market makes its move, your position has already been forcibly liquidated, or you exit early because you cannot withstand the volatility along the way.

In the end, the market moves as expected, but you lose money.

Wh
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What is a mean reversion strategy? Why do prices sometimes return to the historical mean after deviating from it, while at other times they continue moving farther away?

In cryptocurrency trading, prices often fluctuate within a certain range. When a price deviates significantly from its recent mean, some traders look for opportunities to trade in the opposite direction, hoping the price will return to its normal range. But mean reversion is no guaranteed market rule. Especially when trends are strong or fundamentals change, prices may continue moving farther away from the mean.

First, what
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To be honest
Aoi Sola saying she’s teaching herself about crypto
is just like Sun saying he’s training for lean muscle
Sun just wants traffic; she wants your money
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What Happens If BTC Breaks Above 82,000?
live-cover
LIVE1,176
What is a retest confirmation? Why can a price retesting a key level after a breakout sometimes provide a better entry reference, yet also fall back into its previous range?

In cryptocurrency trading, a price does not necessarily continue rising immediately after breaking through resistance. Sometimes it returns to the breakout level to test it. If the former resistance zone turns into support, this may provide a reference for trading with the trend. But a retest is no guarantee of success, and the price may still fall back into its previous trading range.

First, what is a retest confirmatio
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BTC falls below $76k: How can quants identify the next market regime shift?
The Nasdaq plunged 5.5%, and BTC fell below $76k! Last night’s sell-off: many people only understood half of what happened. The market was quite interesting last night. After the results of the U.S. midterm elections were announced on Wednesday, U.S. stocks surged for a time, and BTC climbed back toward $80k. But on Thursday, the market suddenly reversed. The Nasdaq plunged 5.5%, the S&P 500 fell 4.4%, and the Dow dropped more than 1,800 points. Chip and AI-related stocks faced concentrated selling. BTC couldn’t hold u
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$KORU The Korean stock market is wild—it drops hard, but rebounds just as strongly. It’s already bounced more than 20% this morning.
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The guys over in Yunnan are still way ahead of their time.
There’s even this kind of model.
When I saw it, I thought it was Snorlax???
What Is a Mean Reversion Strategy? Why Do Prices Sometimes Return After Deviating from Their Historical Average, but at Other Times Continue Moving Away?

In cryptocurrency trading, prices often fluctuate around a certain range. When a price deviates significantly from its recent average, some traders look for opportunities to trade in the opposite direction, hoping the price will return to its normal range. But mean reversion is not a guaranteed market rule. Especially when trends are strong or fundamentals change, prices may continue moving away from the mean.

First, what is mean reversion?
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🤖 After AI tech stocks plunged, will the next wave of opportunity be in applications?

U.S. stocks saw a sharp correction overnight, with chip, server, and data center stocks all under pressure. AI’s high valuations are once again being put to the test.

But the AI story isn’t over. The market’s focus is shifting:
From “who is investing the most in computing power” to “who can actually make money with AI.”

🔍 Google: Can AI search and advertising generate more revenue?
☁️ Microsoft, Amazon: Can cloud computing and AI services continue to deliver growth?
🚀 Meta, Palantir, Oracle: Can AI comm
post-image
GOOGL-2.22%
MSFT-3.65%
AMZN-2.11%
PLTR-9.79%
ORCL-7.02%
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If it’s going to drop, let it drop hard. No matter what, Bitcoin will come back stronger after being pushed to the brink! Hold strong, brothers!
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The daily correlation between the S&P 500 and the 10-year Treasury yield is close to zero. The latest reading on Bloomberg’s rolling correlation chart is just 0.0766, almost right on the zero line. This indicator ranges from -1 to 1. The closer it is to zero, the weaker the link between their daily moves. A negative reading represents the “inverse relationship” between bond and stock prices, where yields rise as the stock index falls; a positive reading means they move in the same direction. For most of the past, it was in negative territory, at one point reaching close to -0.8. Back then, whe
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