夏木KRIS
夏木KRIS
全市场分析，不受局限 提供真正有价值的投资建议
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I have always been committed to sharing trading knowledge to help everyone avoid high-risk trades and investment scams. All guidance is completely free, with no charges. I do not belong to any company, organization, or platform, have no partners, no groups, and will never ask anyone to transfer money to me.
I always advise everyone to keep their money in their own accounts, learn independently, and make their own judgments. When the market declines, you can focus on coins with real projects and long-term value, buy rationally, and sell at the right time after reaching profit targets.
Sharing knowledge is done out of goodwill, with no expectation of return. Protecting your own funds is more important than anything else.
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What supplements do super individuals need?
(Deep research version)
My combination is:
Anti-aging + High energy + Improve sleep quality + Build lean muscle strength
Basic foundation:
High-dose multivitamins
Fish oil Omega-3
D3 + K2
Nervous system & sleep:
Magnesium glycine
Anti-aging and antioxidant:
GlyNAC (NAC + Glycine) + Ergothioneine
Mitochondria & energy:
Coenzyme Q10 + PQQ
Brain & physical performance:
Creatine 5g
Core logic: supplement the foundation → antioxidant → repair mitochondria → enhance long-term energy and performance.
Also suitable for crypto community
$BTC $ZEC $QNT
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In the era of information transparency, is it really harder for financial crises to occur?
A major reason why financial crises were prone to brewing in the past was the slow spread of information. Underdeveloped communication and low market transparency mean information is often controlled by a few. Many risks can accumulate within the system for years, yet most market participants remain unaware. When the problem truly emerges, the market often has no time to react, panic spreads rapidly, and it eventually evolves into a systemic crisis. Today's environment is completely different. Smartphones, the internet, and real-time information enable information to be transmitted almost instantly worldwide. Macro data, policy changes, and market price fluctuations can all be captured by the market within seconds. Many local risks have not yet been amplified by the market in advance. From this perspective, traditional financial crises that rely on information lag and accumulate gradually have indeed become harder to form. But things are not that simple. More information does not mean more understanding. When information spreads extremely fast, the market is also more easily surrounded by noise. True and false news are mixed and emotions spread rapidly, often amplifying market reactions. Short-term panic, concentrated sell-offs, and instant liquidity contraction are actually more common in modern markets. The early days of the pandemic in 2020 were a typical example. The U.S. stock market triggered four circuit breakers in just one month. It's not that the economic fundamentals suddenly collapsed within weeks, but rather that the market quickly developed a panic of consolidation under the intense information shock. When everyone reacts in the same way, market volatility is amplified to the extreme. A deeper problem actually stems from the complexity of the financial system itself. 2008 Financial Crisis
U.S. stocks plunge! The AI bubble burst may have just begun.
On November 5th, U.S. stocks faced another sharp sell-off, with the Nasdaq plunging over 5% intraday, the S&P 500 dropping more than 3%, and the semiconductor index falling about 11% at one point.
The Nasdaq has fallen more than 10% from its October peak, officially entering a technical correction range.
The most dangerous aspect of this decline is that the market is starting to question the core logic that supported tech stock valuations over the past two years.
Tech giants like Microsoft, Google, and Meta continue to expand AI capital expenditures, with hundreds of billions of dollars flowing into data centers, GPUs, and power infrastructure, but how many years will it take to recoup these investments?
In the past, simply announcing increased AI investment could boost stock prices. Now investors are recalculating profits, cash flow, and debt costs.
What’s more troubling is that U.S. inflationary pressure remains, and the high interest rate environment is not over.
I worry that what we are seeing now may only be the first round of valuation adjustments.
If tech giants start cutting capital expenditures next, the impact could ripple from AI software companies all the way to chips, servers, storage, and power industries.
If this round of the AI bubble really starts to burst, today’s plunge may just be the prelude. $BTC $ETH $QQQ
Intel has dropped below $57 🥶
I had been watching Intel for a while, and luckily I didn’t rush to add more shares at that time.
Many might have forgotten that in August 2025, the U.S. government reached a shareholding agreement with Intel, acquiring nearly 10% equity at about $20.47 per share, with a total investment of approximately $8.9 billion.
However, it’s important to note that this deal mainly converted previous government subsidies into equity, rather than the U.S. government directly spending $8.9 billion on the market to buy shares, so it can’t be fully compared to the cost basis of ordinary investors.
But this matter is still worth considering.
At $57, the stock price is already about 2.8 times the government’s agreed entry price.
Even if it falls to $40, it would still be about 95% higher than $20.47.
Of course, this doesn’t mean Intel’s fair stock price is only $20, nor does it mean the price will definitely drop to $40.
For me, Intel’s wafer foundry business, capital expenditures, and future profitability still have many aspects that need observation.
Until these uncertainties are fully resolved, I’m reluctant to pay too high a price based on future growth expectations.
So if I really want to buy the dip, I would personally wait until around $40 to reassess whether it’s worth gradually building a position.
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AMD's data center business has started to show very impressive growth.
The latest financial report shows that third-quarter revenue reached $13.4 billion, a year-over-year increase of 45%, with data center business revenue at $8.55 billion, up 97% year-over-year.
What is even more noteworthy is that AMD expects fourth-quarter revenue to reach $17 billion, a quarter-over-quarter increase of about 27%.
In the past, the AI chip market's attention was almost entirely focused on NVIDIA, but AMD is striving for more market share through its Instinct GPUs and EPYC server processors.
According to the latest data, the data center business has already contributed about 64% of AMD's quarterly revenue.
However, AMD's current expected price-to-earnings ratio is about 31 times, while NVIDIA's is about 14 times. Even though AMD's growth rate is very impressive, investors have already paid a high price for future growth.
If the revenue growth for 2027 can be realized, AMD could become a company worth continuous research in the AI industry chain.
#AMD数据中心收入近翻倍，营收及指引均超预期 $AMD $BTC $ETH
This round of Ethereum's rebound may have more potential than many expect.
On November 4th, ETH recovered from the previous downtrend and earlier climbed back above $2,300.
Notably, ETH's open interest increased by about 4.2% that day, while BTC's only rose by 1.6%. Meanwhile, both saw significant increases in trading volume.
This indicates that more capital is re-establishing contract positions during ETH's rebound.
However, the increase in open interest also means leverage is accumulating, so it should not be directly interpreted as all new buying.
Currently, I tend to continue bullish on ETH's rebound, watching in the short term whether $2,400 can be broken.
If it can hold above $2,400 again, the next target could be $2,500.
But if BTC weakens again and ETH falls back below $2,250, caution is needed as this rebound may return to a consolidation range. $ETH $BTC $ZEC
Apple's latest financial report reveals a noteworthy phenomenon.
In the fourth fiscal quarter, revenue reached $114.48 billion, surpassing market expectations, with iPhone revenue at $57.58 billion.
However, Apple also warned that the gross margin for the next quarter may decline from 47.9% to 45%–46%.
The issue lies with memory chips.
As global AI data centers continue to expand, demand for memory chips has surged, and related costs are being passed on to the smartphone and computer industries.
Even a tech giant like Apple finds it difficult to completely avoid this.
This means the AI investment boom is triggering a chain reaction:
data centers are willing to pay higher prices for chips, supply chain resources are being reallocated accordingly, and procurement costs for consumer electronics companies may also rise.
Apple can alleviate pressure by raising prices, adjusting product mix, and managing the supply chain, but whether these measures can fully offset rising costs remains to be seen in future financial reports.
The money earned by the AI industry may be turning into costs for other tech companies. $AAPL $BTC $ETH
Uber is facing an interesting business problem.
On November 4th, the company announced third-quarter revenue of $14.77 billion, a 10% year-over-year increase, but it forecasted adjusted earnings per share for the fourth quarter of only $0.95–0.99, below the market expectation of $1.06.
One reason is a shortage of drivers.
In markets like Canada, ride demand is growing faster than the number of drivers, forcing Uber to increase driver incentives and even reduce discounts previously offered to passengers.
At the same time, rising fuel costs are impacting business in some regions.
In the past, internet platforms liked to emphasize economies of scale: the more users and transactions, the greater the potential for profit margin improvement.
But Uber's business model still relies heavily on a large number of real-world drivers.
The company expects about 700 fully autonomous vehicles on its platform by the end of this year, and over 2,000 by the end of 2027.
Whether autonomous driving can reduce driver costs is becoming increasingly central to Uber's future profit margins.
$BTC $ETH $ZEC
US healthcare giant CVS suddenly announced it will split its large business system, which it has operated for many years, into two companies.
On November 4, CVS announced it will separate its retail pharmacy business from insurance, pharmacy benefits management, and other businesses, planning to complete the process in the first half of 2028.
After the announcement, the stock price dropped as much as 12.6%, falling to around $79.94.
What’s even more interesting is that CVS’s adjusted earnings per share for the third quarter reached $2.09, significantly higher than the market expectation of $1.65.
Earnings exceeded expectations, yet the stock price plunged.
Over the past two decades, CVS has continuously expanded its business through acquisitions, extending from pharmacies to insurance and healthcare services, aiming to form a business system covering the entire healthcare industry chain.
Now the company has decided to split again.
This involves regulatory pressure, business complexity, and investors’ reassessment of valuation methods for large integrated healthcare groups.
A growing company size does not necessarily mean the capital market is willing to grant a higher valuation.
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There is an interesting change emerging in the financing methods of AI startups.
On November 4th, AI sales automation company Nooks announced it received $500 million in funding from a fund under General Catalyst.
However, this deal differs from traditional venture capital.
According to the company’s disclosure, the investor does not simply seek returns by purchasing equity but shares in part of the profits generated after the capital is invested.
Nooks currently has over 2,000 clients, including tech companies like Notion, Cursor, Replit, and HubSpot.
The company stated that its annual recurring revenue is expected to nearly triple this year, with a net revenue retention rate of 135%.
Its business mainly uses AI to automate the sales process, from finding customers and contacting potential buyers to subsequent customer maintenance.
In the past, investors in AI startups were often willing to pay high prices for future user growth and valuation.
Now, another model has emerged: capital directly participates in the process of acquiring customers and gains returns from the growth results.
If this financing method gains more validation, some AI startups in the future may not have to rely entirely on continuously increasing valuations to obtain funding.
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