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Inflation is heating up again. Will the Fed return to a more hawkish stance? What’s next for U.S. st
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LIVE2,249
Would you still dare touch MU at $775?
From $1,255 down to $700, everyone said, “The AI memory bubble has burst.” Just today, a big green candle surged from $700 to $775, up 7%, with trading volume soaring to $1 billion, while Goldman Sachs still has a $1,250 price target. Is this just a dead-cat bounce, or the second wave of a supercycle?

First, the surface: down 40%, but today it staged a violent rebound.

It fell more than 20% in the past 30 days, tumbling from a high of $1,255 to around $700, trapping who knows how many people. But just now, it rallied from $700.93 to $778 in 24 hours, wi
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BTC-0.67%
MU-0.63%
NVDA-0.35%
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BTC/VIX ratio keeps falling..
The bottom area is forming slowly..
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Why do some trading strategies perform well in range-bound markets, but start losing consecutively as soon as the trend reverses?

Have you ever experienced this?

A strategy performed well over the past few months. Its backtest curve was smooth, and its win rate looked impressive.

But one day, the market starts to change.

Buy signals that used to work begin failing one after another, stop-losses become more frequent, and the account’s drawdown keeps growing.

You start questioning the indicators, adjusting parameters, and even considering replacing the strategy entirely.

But there is one p
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Why might changing your trading rules after a string of losses be more dangerous than the losses themselves?

Many traders don’t lose to the market. Instead, after a string of losses, they gradually abandon the trading discipline that originally worked.

First loss: They think it was just bad luck.

Second loss: They start doubting the strategy.

Third loss: They change their stop-loss, adjust parameters, and increase their position size.

Fourth loss: They completely overturn their original trading system.

Here’s the question: Are you optimizing your strategy, or trying to escape the discomf
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$SOXSB$SOXSB is currently at 47.05, with the Bollinger lower band at 44.10 and MA20 at 50.43 as key short-term levels. It has plunged 20.01% in 24 hours and is now trading right around the Bollinger lower band. MA5 at 47.04 is almost exactly in line with the current price, but remains well below MA20, with the bearish moving-average alignment unchanged. RSI at 29.8 has entered oversold territory, while the MACD histogram at -0.077 remains bearish. The 30-candle range is as high as 30%, indicating a selloff amid high volatility rather than a low-volume gradual decline. The Fear & Greed Index is
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Why isn’t $CRWV stock taking off despite the AI boom?
The company is growing rapidly, but building data centers, buying NVIDIA chips, and taking on debt are costing it billions.
And here’s an important point: the market isn’t just about profits—it’s also about investor sentiment!
Look at $MSFT and $META: their ups and downs and volatility wore out many investors, followed by a gradual rise.
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NVDA+3.00%
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At this price with these specs, who the hell would buy an OPPO?
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This post reached me through Creator Wire, one of the rails in this story.
In Q3, @turtledotxyz named its first two outside businesses on its tools: Hare by GSR and Lunar Strategy.
That is demand you can point to, not just a revenue line.
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Anthropic is a mirror reflecting the element of “choice” in OpenAI’s losses

Looking only at OpenAI’s losses, it’s easy to conclude that “model companies just burn money.” But Anthropic’s Q3 figures call that conclusion into question.

Anthropic’s Q3 revenue was nearly $17 billion, up 47% quarter over quarter and 70% higher than OpenAI’s; its operating loss was only $567 million, mainly due to short-term compute purchases and a one-time $2 billion employee charitable matching contribution. OpenAI lost $10.9 billion in the same period. The revenue gap was 70%, while the loss gap was nearly 20-f
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Why can some people consistently follow the same trading signals over the long term, while others keep changing their plans at critical moments?

Many traders are not short on indicators or trading strategies.

They know where to enter, where to set stop-losses, and how to manage position sizes.

But once they actually enter the market, everything changes.

When they are in profit, they worry about giving it back and close their positions early.

When they are losing, they are unwilling to admit their judgment was wrong and widen their stop-losses on their own.

When the market rises, they fea
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#直通IPO第三期Anthropic I’m most bullish on Anthropic selling Claude into enterprise workflows. Revenue is primarily usage-based, and as customers move from trials to long-term purchases, the growth potential is far greater than simply selling models.
Most promising growth drivers
Existing customers are using more and more: As of the end of September, there were 11,900 customers paying more than $100,000 annually, with net revenue retention of around 900%.
Agents drive usage: Claude Code and Cowork can continuously complete tasks, and complex tasks consume more compute, increasing revenue.
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How can you tell whether a trading strategy has a genuine statistical edge rather than making money by chance?

One of the easiest ways to misjudge things in the trading market is to treat making money as proof that a strategy works.

A string of winning trades could mean the strategy has an edge, or it could simply mean the market happened to be favorable to it.

So how can you tell the difference?

The key is not how much a few trades made, but whether the strategy has a repeatable positive expectancy after costs under sufficiently reasonable testing conditions.

I. First, understand what a
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Enterprise business doubled, but what doubled was “code,” not the “AI can do anything” narrative

OpenAI President Greg Brockman said enterprise business doubled in Q3 and already accounts for the vast majority of total revenue. CFO Sarah Friar broke it down further: enterprise revenue growth is mainly driven by three areas—coding tools, cybersecurity products, and the Dots agent platform.‌

What do these three areas have in common? None is a “general-purpose AI” story; they are all “efficiency tools for specific workflows.”

Coding tools are the most mature of the three. The ability of large
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The peak attracts insincere supporters; dusk reveals the true believers.
$hype is at a critical level, with support at 70.
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Please make your own assessment. A week from now, it may reach this level or higher. Perhaps we can wait for the final 📉 before entering. Times are in U.S. time. In the future, these kinds of signal posts can’t be shared without a link. I’ve been doing this for the love of it all along.
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Such a unified market, it seems like all Chinese people are shorting the Nasdaq
There’s been so much good news today, and it’s only gone up this much
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Pile of coins or one rare JPEG, anon? Pick one and defend it. My cat already stared down the coins. NFA.
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🔹Ledger CEO says no device is absolutely secure! With a string of incidents involving hardware wall
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#直通IPO第三期Anthropic I’m most bullish on Anthropic bringing Claude into enterprise workflows. Revenue is primarily usage-based, and as customers move from trials to long-term purchases, the growth potential is far greater than simply selling models.
Most promising growth drivers
Existing customers are using more: As of the end of September, there were 11.9k customers with annual spending above $100k, and net revenue retention was about 900%.
Agents are driving usage: Claude Code and Cowork can continuously complete tasks; complex tasks consume more computing power, increasing revenue accordingly
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ThisIsTranslateContent:
#直通IPO第三期Anthropic I’m most bullish on Anthropic selling Claude into enterprise workflows. Revenue is primarily usage-based, and as customers move from trials to long-term purchases, the growth potential is far greater than simply selling models.
Most promising growth drivers
Existing customers are using more and more: As of the end of September, there were 11,900 customers paying more than $100,000 annually, with net revenue retention of around 900%.
Agents drive usage: Claude Code and Cowork can continuously complete tasks, and complex tasks consume more compute, increasing revenue.
Low penetration of enterprise budgets: Top enterprises spend an average of less than 0.1% of their total expenses with Anthropic, leaving significant room to expand.
Improving inference efficiency: In the first half of 2026, compute and infrastructure costs accounted for about 55% of revenue, down from 201% in the same period last year.
Offering plan
Anthropic plans to offer shares at $70–78 each, with a fully diluted valuation of up to about $1.405 trillion. Pricing is set for November 18, trading begins on November 19, under the ticker “ANT.”
I will participate in this offering, but only as a watch position. The high valuation already prices in very high growth expectations; going forward, revenue growth, operating profit, and cash flow still need to deliver.
The main risks are also clear: Long-term compute purchase commitments amount to about $900.9 billion, with nearly half due by the end of 2030; about 48% of revenue comes through cloud marketplace channels, which also incur channel costs.
So my view is: The business model is attractive, but this is a high-expectation, high-volatility asset, so it is more appropriate to keep the position within an affordable range.
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