Trump wants to issue coins again? Bitmart officially announced that it is considering restructuring; YuShu Technology has plummeted!

Dear readers, what have the KOLs on X been talking about in the past 24 hours? Note: The following content is compiled from the X platform. They are all personal opinions. They do not represent the platform's position, let alone constitute investment advice. Trump wants to issue coins again? Bull market script, how do you go this time? Bitmart officially announced that it is considering restructuring, YuShu Technology plummeted! Twitter: https://twitter.com/BitpushNewsCN比推 TG Community: https://t.me/BitPushCommunity比推 TG Subscriptions: https://t.me/bitpush

17h agoBitpushNews

[Comparative Daily News Picks] Anthropic plans to include anti-AI sentiment as the main risk factor in the prospectus; Strategy's stock price hit a two-month high, and STRC returned above $96; Bernstein: Even if the “Clarity Act” is not passed, the SEC and CFTC will speed up rule-making; Dalio: The US debt crisis may break out within three years, and it is recommended to increase gold holdings

Daily AI · Crypto · Macro · Market Highlights, Bitpush helps you set priorities ↓ AI · News [Anthropic plans to include anti-AI sentiment as the main risk factor in the prospectus]. According to CNBC, Anthropic is expected to list the public's negative sentiment about artificial intelligence and data centers as a risk factor in the IPO prospectus to be released in the next few weeks. According to people familiar with the matter, Anthropic recently held a pre-listing “market trial” meeting with bankers and investors. Investors focused on competitive pressure, the impact of open source models on profit margins, and the risks that may be brought about by a slowdown in data center construction. Anthropic is currently valued at close to $1 trillion in the private equity market and is preparing to hit a major IPO. However, as Americans' concerns about AI replacing employment and data center expansion heat up, the related backlash sentiment is becoming a new challenge facing the company's listing. The company has previously achieved an annualized revenue operating rate of more than 65 billion US dollars. [Apple cuts Siri and Vision Pro team positions, and resources shift to AI and new devices] Compared to news, Apple (AAPL.O) is laying off employees from various teams responsible for Siri's digital assistants and Vision Pro headsets. The total impact of this layoff is more than 200 people. Of these, about 100 jobs in the Vision Pro department have been abolished, and about 100 other positions in the Siri and software teams have been cut. The move is part of the company's efforts to focus resources on new devices and artificial intelligence. People familiar with the matter said that in this adjustment, Apple has basically shut down a team dedicated to the Vision Pro game business, while also reducing the size of the department responsible for producing immersive video content for the device. Apple admitted in a statement that the company is making adjustments to some teams “to drive business development and provide the best experience for users.” [Castle Securities: Over 80% of the overall risk in the Situational Awareness Fund portfolio has been divested] According to the Financial Times, Castle Securities founder Ken Griffin responded to the company's acquisition of Situational Awareness assets under Leopold (Leopold) in a letter to clients on Friday. According to a letter obtained by CNBC, Griffin told clients that Castle Securities had divested more than 80% of the overall risk in the original purchased portfolio by conducting more than 100 major transactions (with a market value of more than $4 billion). In his letter, Griffin wrote, “A transaction of this scale would not have been possible without the full cooperation of the transaction teams and lead brokerage teams of the banks serving the two companies. I am very grateful for their dedicated efforts to complete the portfolio transfer quickly.” Griffin also confirmed that the company's flagship multi-strategy fund, the Wellington Fund, had a return of 5.94% in July, which is the fund's best monthly performance since 2022. [AI cloud company Nscale seeks to raise 3 billion US dollars in US IPOs] In comparison, AI cloud company Nscale is reportedly seeking to raise 3 billion US dollars in a US IPO. In the crypto market [Strategy stock price hit a two-month high, STRC returned above $96], the Bitcoin treasury company Strategy (MSTR) stock price rose to a two-month high today as the Bitcoin price briefly broke through $79,400. It broke through $120 during the intraday period, then partially regained its gains. Meanwhile, the price of STRC, Strategy's preferred stock product, also surpassed $96 for the first time since June. Previously, STRC's price once fell below $70 due to concerns about its ability to pay dividends and the ability of the stock price to maintain the $100 target for a long time. [Bernstein: Even if the Clarity Act is not passed, the SEC and CFTC will speed up rulemaking] Comparing news, the Bernstein analyst team led by Gautam Chhugani released a report stating that regardless of the procedural voting results of the “Clarity Act” on September 15, the certainty of US crypto regulation is expected to increase. They expect the SEC and CFTC to accelerate rulemaking in areas such as native crypto asset issuance, tokenized stocks, perpetual futures, computing power derivatives, and predictive markets. This regulatory clarity of expectations has become one of the broader supporting factors in the crypto market. 【A...

18h agoBitpushNews

Dalio's latest warning: the US debt crisis may explode within three years. The antidote is...

Author: Ray Dalio, founder of Qiaoshui Foundation Original title: How Countries Go Broke: The Dynamic Behind What is Incurable Now Compiled and organized by: bitPushNews In “How Countries Go Bankrupt: The Big Cycle,” I detailed an analytical framework to describe dynamic processes that are highly likely to occur due to unsustainable imbalances between debt supply and demand. Recently, three things happened at the same time: 1) The Japanese government sold part of its US Treasury holdings to return capital to Japan to support the yen and the Japanese capital market, and reduce exposure to US Treasury bonds while avoiding being forced to raise interest rates beyond its wishes in order to support the yen; 2) US bond yields hit new highs under long-term leadership, while the dollar weakened. The reasons include not only the current and anticipated supply of huge debt, but also weak demand for US bonds; 3) Treasury Secretary Bessent announced this week that the US Treasury would buy US Treasury bonds and be able to buy other US Treasury bonds The amount of capital used is limited, and many people ask me : Do these events fit the classic template I set out in my book? The answer is yes. To anticipate what might happen next, let's first review this operating mechanism. The operating mechanism explains in detail that the central government's debt dynamics are the same principles as the debt dynamics of individuals or companies. The only difference is that the central government has a central bank that can print money (this will depreciate the currency), and it can obtain funds from the public through taxation. Because of this, if you imagine how the debt dynamic would work if you or the business you run could print money, or get capital from people through taxation — then you can understand this process. But remember, your goal is for the entire system to work well, not only for yourself, but for all citizens. In my opinion, the credit/market system is like the human body's circulatory system, delivering nutrients to every corner that makes up the market and economy. If credit is used effectively, it can generate productivity and income to repay debt and interest on debt, which is a healthy state of affairs. However, if credit is not properly used to generate sufficient income to repay debts and interest, debt payments will continue to pile up like plaques in blood vessels, squeezing other expenses. When debt payments become very large, debt repayment problems arise, and eventually evolve into debt rollover problems — because debt holders are unwilling to continue to roll over and instead want to sell. Naturally, this will lead to a shortage of demand and sell-off of debt instruments such as bonds; when demand is scarce relative to supply, it either causes a) interest rates to rise, thereby suppressing the market and economic downturn, or b) the central bank “prints money” and buys debt, which will reduce the value of the currency, thereby driving up inflation (compared to the original level). Banknote printing also artificially lowers interest rates and harms lenders' returns. Both options are bad. When debt sell-offs are too large and difficult to contain, and the central bank has already purchased large amounts of debt, rising interest rates can cause the central bank to lose money and damage its cash flow. If this continues, the central bank will fall into a situation where net assets are negative. When this situation became serious, the central government and central bank needed to borrow money to repay the principal and interest of the debt, while the central bank printed money to provide loans due to insufficient free market demand, so a self-reinforcing spiral between debt/banknote printing/inflation formed. In summary, the classic indicators to pay attention to are the following: the ratio of government debt payments to government revenue (which is like the amount of plaque in the circulatory system), the ratio of government debt sold to the demand for government debt (this is like a plaque falling off and causing a heart attack), and the amount of government debt purchased by the central bank to cover the gap between the demand for government debt and the supply of government debt to be sold (this is like the central bank applying a larger dose of liquidity/credit to mitigate liquidity shortages, and the central bank has a risk appetite for these debts). These indicators usually rise over a long cycle of decades — debt and debt payments continue to grow in relation to income — until this state of affairs cannot continue because: 1) debt repayment expenses unacceptably crowd out other expenses, 2) the supply of debt that must be purchased is too large, causing interest rates to rise sharply, leading to a sharp decline in the market and economy, or 3) central banks are unwilling to let interest rates rise and suffer bad market/economic consequences, so they print large amounts of money and buy large amounts of government debt to cover the demand gap, thereby making the value of the currency significant Decreased. Either way, the return on bonds will be poor until the money and debt eventually become cheap enough to attract demand, or the government can cheaply buy back or repay...

22h agoBitpushNews

Are Bitcoin's 80,000, 120,000, and 300,000 still far away?

Author: Debashree Patra Compiled by: Deep Tide TechFlow Original title: Bitcoin Sword Fingers at $80,000: Analysts Predict Breaking 120,000 Next Year and Shocking 300,000 in 2030 DeepWave Guide: Bitcoin rebounds strongly from around $63,000 to $75,401, completing a 5.8 times standard deviation increase within 48 hours, driving analyst Pierre Rochard to reaffirm his bullish roadmap — hitting $80,000 in 2026 and breaking through $120,000 next year. The sword in 2030 is $300,000. In the short term, bear liquidation and downtrend line breakouts provide momentum, but whether the leverage-driven surge can be turned into continued spot demand will determine whether the larger goal is realistic. Pierre Rochard's $80,000-$300,000 roadmap analyst Pierre Rochard (BitcoinPierre) expects Bitcoin to close around $80,000 in 2026. He believes that Bitcoin is not ready for a “parabolic rise,” but it is expected to break through $120,000 next year. In the longer term, he predicted that Bitcoin could reach $300,000 by 2030. The key variables in this forecast are the Federal Reserve and the broader macro environment. Rochard believes that if the economy is weak enough to allow the Federal Reserve to cut interest rates without reigniting inflation, Bitcoin will benefit from improved liquidity. He also pointed out that artificial intelligence (AI) may improve macroeconomic prospects by increasing productivity and reducing inflation. In that situation, interest rate cuts will create a more favorable environment for risky assets such as Bitcoin. The $80,000 target refocused on Bitcoin's latest price trend has shown signs of regaining momentum. BTC climbed from around $63,000 to $75401 in less than 48 hours. Previously, buyers successfully defended in the $63,000 area. Notably, Bitcoin formed higher highs and higher lows. This round of rebound was partly fueled by large-scale short liquidations. According to reports, as Bitcoin and Ethereum soared, around $14 billion to $17 billion of short crypto positions were liquidated, removing bearish leverage. Glassnode indicated an unusual pattern of this fluctuation. They said that Bitcoin's jump from around $75,401 was a 5.8 times standard deviation (5.8 sigma) of its 30-day volatility — the biggest upward move since October 2023. The last time Bitcoin closed at such a large daily rate was in February, which was only a rebound after a sharp drop of -14% the day before. And there's no crash to bounce back this time around — this is a 5.8 times standard deviation fluctuation compared to its own 30-day volatility, the biggest upward move since October 2023. — Glassnode (@glassnode) However, liquidation alone does not confirm the existence of sustainable spot demand. On-chain analyst Onchain Insights said that Bitcoin has broken through the annual downward trend line resistance and recovered to the $70,000 range. If it continues to close above this structural resistance, it may indicate a weakening of selling pressure and further upward momentum. Another analyst also said that short positions have limited resistance until $80,000, making it an important near-term target. The BTC giant whale sells for $74,000 and $80,000. The gap between these resistances is very large. ——CW (@CW8900) On Polymarket, the probability that Bitcoin will hit $80,000 in August rose to 13%, up 9 percentage points within 6 hours. BTC would need to rise about 14% more from $71,000 to reach $80,000. Can the $120,000 be recovered? Rochard expects Bitcoin to easily break through $120,000 next year if the macro environment turns favorable. His long-term goal of $300,000 by 2030 reflects broader bullish arguments around liquidity, supply, and adoption. His opinion was also supported by SkyBridge Capital CEO Anthony Scaramucci, who expected Bitcoin to surpass $100,000. He cites the halving cycle and new supply...

1d ago深潮TechFlow

They all say stablecoins are suitable for cross-border payments; is it really faster and cheaper than Wise?

Author: Jonah Compiled by: Saoirse, Foresight News Original title: Do cross-border payments really need stablecoins? Everyone says stablecoins are better suited for cross-border payments. Is that really true? If the recipient of your transfer wants stablecoins themselves, then stablecoins are indeed an excellent cross-border solution. You can transfer money around the clock at almost zero cost and instant settlement. But the more difficult question, which is also the focus of this article, is the cross-currency scenario: what happens when one end inputs US dollars and the other end exports foreign currency (such as Mexican pesos). Most crypto industry opinion leaders will claim that stablecoins can fundamentally reduce the speed and cost of transfers in this scenario. However, people who are optimistic about stablecoins deliberately avoid the fact that fintech companies have already achieved low-cost, high-efficiency businesses of the same kind, and there is no need for stablecoins at all. So what problem do stablecoins solve? This article will sort out how the traditional agency banking system works, and also analyze the innovations made by modern fintech companies such as Wise to clarify the actual value of stablecoins. The proxy banking business assumes Alice, who is in the US, wants to send a peso to her friend Bob in Mexico. Both banks do not have branches in each other's countries, so payments cannot be completed directly. The two banks need to use a larger bank, or correspondent bank, to establish a connection. Alice's depositary bank holds funds in US dollars at this correspondent bank called GlobalBank; GlobalBank also holds pesos at BancomX Bank in Mexico. After Alice initiated the transfer, her bank withheld the funds in her account and issued instructions to GlobalBank. GlobalBank transfers $100 from the dollars stored by Alice Bank, completes the exchange according to its own exchange rate, earns the exchange rate spread, then tells BancomX to credit Bob's account and deduct its own processing fee. The entire process relies on the SWIFT system to coordinate information, and SWIFT itself also charges for messages. This underlying transfer mechanism is expensive and slow. The root cause is that all layers of intermediaries are profiting from it. In an ordinary consumer remittance scenario, the comprehensive cost of the agent banking system is about 15%, including transaction fees and foreign exchange spreads embedded in the exchange rate. In addition to this, a transfer usually takes 1 to 5 business days to complete, and each intermediary takes time to complete its own operation process. Modern fintech solutions In 2011, two friends in London had complementary financial needs: one person earned in euros but needed pounds to live in the local area; the other received a salary in pounds and had to repay a mortgage in euros to Estonia. As a result, they bypassed banks and paid each other locally: the British pound was deposited into the London account, the euro was deposited into the Estonian account, and the two funds did not flow across the border. This system later evolved into Wise. The two founders believe that this model of hedging and offsetting capital flows can be implemented on a large scale, and this model has indeed worked. Many other fintech companies have taken the same approach. Let's take another example of Alice sending money to Bob, this time using a service similar to Wise. Alice transferred dollars to the fintech company's US account; the company used its own peso funds stored in Mexico to complete the payment directly to Bob. The funds did not cross the border from beginning to end. Alice's perception of a cross-border transfer is essentially a financial institution that receives and withdraws money at the same time. Because of this, the user experience was almost instantaneous, and the fintech company needed to bear the asset liability risks associated with holding large amounts of foreign currency. In order not to touch the traditional banking system as much as possible, fintech companies will distort transactions. For example, if other users remit pesos overseas in reverse, fintech companies can internally hedge off the two capital flows. Once a currency's capital pool is seriously unbalanced, it is only necessary to seek help from the traditional banking system. At the bottom, fintech companies cobble together partner banks and various license resources, and local partners handle regions that cannot be covered by their own business. Under the premise of normal operation, this model is far superior to the traditional system. Wise only charges a small, publicly disclosed processing fee, using the actual mid-market exchange rate, no hidden exchange rate spread, and the comprehensive rate is only 0.52% (this value is mixed with some transfers in the same currency, and the foreign exchange rate is not disclosed separately). According to World Bank data, the average ratio of digital remittance services...

1d agoForesight News

They are all stealing earlier data. Where exactly is VC Alpha hidden?

Author: insights4vc Compilation: Shenchao TechFlow Original title: Private Equity Market Intelligence Warfare Heats Up: In the AI Era, Where Did VC Alpha Come From? Guide to Deep Wave: Venture capital returns are extremely concentrated, and finding a good company in the early stages is almost the life and death line of a fund. This article breaks down the latest evolution of private equity market data tools and whether they can actually bring in excess profits. This is a sobering map for investors who are using AI and research tools to find projects. Venture capital has always been an information business. The advantage often lies in timing: founders tell former colleagues instead of updating data first; new companies start recruiting people before they appear in the database; investors start watching a team before the funding is announced. This advantage is important because VC returns are highly concentrated. According to data from the 2026 Oxford Academic Study, 4.5% of the investment amount contributed to a return of about 60% in a long-term LP data set. [1] Therefore, missing a few excellent companies can affect the entire fund. But finding them early is only part of the problem. Investors also need to develop beliefs, get credits, obtain meaningful holdings, and keep things right for a few years. The private equity market data industry is now getting closer to the moment the company was born. PitchBook, Crunchbase, Dealroom, Tracxn, and CB Insights remain core recording systems for transactions, funds, valuations, and company history. PitchBook generated revenue of $174.7 million in the second quarter of 2026, equivalent to nearly $700 million in annualized revenue. [2] The new platform is not replacing this layer. They're extending this layer with faster updates, behavioral data, and signals that predate traditional company records. Three changes stand out the most. First, companies such as Harmonic and Specter are building a continuously updated map of companies and people, rather than relying mainly on regularly updated data. Second, specialty products are looking for earlier behavioral signals. Evertrace tracks metrics formed by founders, including company registrations, technical activity, research, and domain names. Frontrun monitors changes in selected venture capitals' interest maps on X. Third, the API and Model Context Protocol (MCP) are moving this data into the fund's own software and AI workflows. Crustdata represents the infrastructure side of this market, while Affinity complements first-party relationship data from emails, calendars, and CRM events. Adoption is visible, but evidence of excess return on investment is not clear. Harmonic says hundreds of venture capital teams use its platform, and Specter reports more than 300 investment institutions, Evertrace more than 200 funds, and Affinity more than 3,300 private equity firms. Listed company Tracxn disclosed that it had 2,289 customer accounts in fiscal year 2026. [3] [4] [5] [6] Most of these figures are self-reported by companies. Vendors rarely disclose the complete set of companies unearthed by their models, making it difficult to assess accuracy, recall rates, false positives, and the economic value of individual leads. No single signal alone is enough. Employee departures may be early but vague. Company registration is objective but common. GitHub activities are valuable in developer-led markets, but have limited relevance in other areas. Hiring speed and employee migration provide broader signals, while revenue, customer, and usage data are often more valuable for decision-making, but come later. When several credible industry experts focus on the same company, investors' attention can provide early signs, even though this signal is platform-dependent and may reinforce itself. The strongest defensive sources are likely to be hidden deeper in the data stack: historical time series that cannot be reconstructed later, accurate physical analysis across people and companies, authorized first-party fund data, and distribution through CRM systems, APIs, and agents. Public data is not necessarily proprietary. However, five years of correctly time-stamped change history can become a proprietary asset. AI is more likely to make these infrastructures more easily queried rather than eliminate the need for them. As research, classification, and workflow costs drop, clean data, sources, and institutional context become more valuable. Investment decisions, quotas, and relationships are still not something a simple layer of automation can solve. The likely outcome is that a broader market for private market intelligence will emerge, rather than an independent search for project software categories. A mature database will increase discoveries and...

1d agoburnking

If it's just tokenized assets and doesn't connect to DeFi, what's left of RWA?

Author: Jesus Rodriguez, co-founder of Sentora Compiled by: Luffy, Foresight News Original title: Does RWA still make sense without DeFi? Discussions in the RWA industry often begin with a simple vision: take a treasury bill, fund share, stock, invoice, megawatt hour, or GPU for one hour, then mint a token representing it. Is it useful? It's really useful. But can it be called transformative? It's far from there. This is like putting a bar code on a container and claiming that a global trade problem has been solved. Barcodes make containers recognizable and machine-readable, but they don't create ports, cranes, customs, insurance, financing, shipping routes out of thin air, or bring in buyers from afar. A token is simply an addressable token of interest, and DeFi is a marketplace operating system. The question really worth discussing is not how many types of assets can go on the chain, but how many assets can complete valuation, financing, hedging, transaction monetization, and loss disposal in a stressful environment, and there is no need for offline meetings and coordination every time a transaction occurs. Tokenization completes the representation of equity; what DeFi brings is actual utility. Tokenization is just a bar code, and a similar scene has happened in the history of the supply chain finance market. The reason why mortgages can be scaled up is not as simple as turning a paper document into an electronic record. To actually achieve large-scale expansion, a complete set of operating mechanisms was created around this type of asset: credit review, post-loan services, securitization, credit rating, warehousing and financing, repurchases, hedging, clearing and settlement, and loss allocation rules. RWA also needed to go through the exact same evolutionary process. An asset that can be adapted to DeFi requires six levels: legally enforceable rights, reliable data sources, clear transfer and redemption rules, enforceable secondary market liquidity, collateral parameters that match actual behavior, and a credible settlement and loss disposal path. Most tokenization projects, on the other hand, tend to stop at the top five levels. There is a simple test that can be used to test the maturity of an asset. It only requires answering three questions: How much is this asset currently worth? Can the agreement complete withdrawal and monetization at this point? If the first two judgments are all wrong, who bears the loss? When smart contracts can definitively answer the above three questions, RWA can truly become a basic component of finance. Before that, it was mostly just a digital packaging shell. The deepest technical contradiction of RWA's quadruple time clock is that RWA runs under multiple sets of different time clocks at the same time. The blockchain can complete settlement in seconds and operate uninterrupted for 7 x 24 hours; oracles may update prices every hour or every day; underlying traditional exchanges are closed at night and on weekends; custodians follow bank working days; and the asset redemption process may take 1 day, 5 days, or even 30 days. If you use such a slow-paced RWA asset to support fast-maturing DeFi liabilities, such as stablecoin loans. This is the term shift, and it is also the core model that banks have relied on for hundreds of years: using short-term debt to fund long-term slow assets. This model has practical value, but the risk must be reasonably priced. Imagine a scenario: At 2 a.m. on Sunday, assets hit the liquidation threshold. Smart contracts can seize tokens immediately, but the underlying real-world market won't open until Monday, and the issuer's redemption business will not be processed until Tuesday. On-chain liquidation has been completed, and real-world asset disposal has only just begun. This creates a clearing gap. DeFi requires immediate withdrawal for monetization, but the real world does not allow it. The time difference between the two. This gap has counterintuitive consequences. Even treasury bonds with very low volatility are riskier than native crypto assets that are more volatile when used as collateral. The price of ETH fluctuates drastically, but it can be traded around the clock; the price of RWA assets appears to be stable, and it may only be up to a dozen hours without a new price tag. A flat price sometimes represents safety, and sometimes it's just a disguise of stale data. Liquidity is an exit channel, not TVL. The digital public also has common misunderstandings about liquidity. Liquidity is not equal to TVL, does not equal the existence of a trading pair, nor does it mean that the issuer promises to eventually redeem it according to net worth. Liquidity refers to the ability to convert a position into the settlement asset you need at an acceptable discount within the time window allowed by your debt. Take a crowded theater for example: the size of the hall cannot determine whether it is safe in the event of a fire; what really matters is the width of the exit channel. One copy of RWA to...

1d agoForesight News

Black eats black? Fake DeFi actually snatched out North Korea's Lazarus real hacker

Source: Security Company ANY.RUN Compiled by: Daily Planet Daily Original title: Fishing Show of the Year, Fake DeFi Picks Out North Korea's Lazarus, Real Madrid Fans, Real Madrid Fans. With a mathematical background, they only use AI to write code. Core point of view: By setting up a fake DeFi company, the security agency successfully infiltrated the “Famous Chollima” hacker group under North Korea's Lazarus Group, revealed its complete process of using false identities, AI tools, and remote collaboration to infiltrate Western companies, and revealed its evolving toolset and infrastructure. Key element: The researchers disguised themselves as recruiters and recruited three North Korean agents within a few months to record their operation behavior, tool usage, and collaboration patterns in real time through the ANY.RUN sandbox environment. Agents used forged driver's licenses, stolen social security numbers, and mule accounts to complete the onboarding process. Some of these documents were processed by Google Gemini and had SynthID watermarks, revealing signs of forgery. Attackers rely on AI tools such as ChatGPT and Google Gemini to encode, translate, and modify files, and use AstrillVPN, remote desktop software, and dedicated servers to covertly access corporate environments. The three agents showed insufficient skills during development, frequently searched for basic issues, and exposed more proxy server and infrastructure information induced by selective network outages and captcha. The investigation found that Famous Chollima aims to lurk within the enterprise for a long time and legally obtain access to code, systems, and intellectual property rights, and is not limited to short-term attacks, and the threat persists significantly. Crypto friends who are often phished have probably heard of the North Korean hacker group Lazarus Group. Its well-known “campaigns” include, but are not limited to: Bybit ($1.5 billion) theft, Ronin Network/Axie Infinity Bridge attack ($6.2 billion), DMM Bitcoin/Ginco related attack ($308 million), Harmony Horizon Bridge attack ($100 million), and Atomic Wallet attacks ($100 million), etc. And the key to the success of these attacks is social engineering — hackers usually disguise themselves as normal job applicants, lurk at crypto companies for years, and wait for the right time. Recently, security agency ANY.RUN joined forces with BCA LTD (a company dedicated to threat intelligence and hunting) and NorthScan (a threat intelligence program to uncover the infiltration of North Korean IT workers) to effectively crack down on North Korean hacker agents. The researchers created a fake DeFi startup and successfully recruited “Famous Chollima” agents under North Korea's Lazarus Group who specialize in human infiltration, to gain an inside perspective on the actions of North Korea's IT workers. The ANY.RUN sandbox environment shows the agent's behavior patterns in real time, revealing their evolving toolsets, remote access workflows, AI tool usage, and supporting infrastructure. This survey went beyond the simple recruitment process and showed in depth how these agents collaborated, obtained, and used company resources after joining the company. The findings suggest that the North Korean IT worker program not only poses a recruitment risk; once agents sneak inside the organization, they can legally obtain access to code, systems, intellectual property, and critical business processes. The following is a report co-authored by the three parties, compiled by Daily Planet Daily. ——————Introduction In December of last year, we fully recorded the infiltration cycle of “Famous Chollima” for the first time. From recruiting collaborators to help them join Western companies, to falsifying documents, shipping laptops to intermediaries, and even using AI tools to assist and translate in real time during interviews, everything is under control. In that survey, we pretended to be a middleman willing to interview them and lend them a laptop in exchange for a percentage of their salary. The point is that those laptops are actually ANY.RUN sandbox environments that record every click and every step they take. This provided us with massive metrics, hours of computer operation videos, and face-to-face contact images, making an unprecedented survey and making headlines in many media. (“Famous Chollima...

1d agoOdaily星球日报

US Stock Value Investing Is Heading Into Another Trap

Source: Shenchao TechFlow Original title: (Opinion: Value investing in US stocks is not equal to fundamental investment) When “fundamentals are dead” becomes a consensus, investors who blindly organize giants will eventually experience astonishing capital destruction. Guide: When the market shouted “fundamentals are dead” and the capital frenzy formed a group of tech giants, the author used an astronomy discovery to unravel the logical loopholes behind this narrative. Starting from the composition of valuation multiples, this article reminds investors to distinguish between the true quality of an enterprise and the premium that the market is willing to pay. It is particularly cautionary about long-term allocation in the crypto and technology sector. I promise this introduction won't be as long as the last one on the weather. But please give me 90 seconds. More than 100 years ago, a woman named Henrietta Levitt was doing the tedious job of measuring the brightness of thousands of stars on photographic negatives (the way they were imaged before film appeared). She noticed one characteristic of a class of pulsating stars: the slower they pulsate, the brighter they themselves are. ¹ This might just seem a little interesting today, like “OK, that's pretty cool.” But at the time, astronomers couldn't tell the difference between a dark star very close to Earth and a very bright star far away. For them, the two left the same stain on the photographic film. Visual brightness is a messy mix of these two variables: how bright the thing itself is, and how far away it is from us. Henrietta's work decouples these two things: if you can observe the rate of pulsation, you can know its true luminosity; if you know its true luminosity, you can reverse the distance based on how dark it looks. Astronomers call it “standard candlelight.” A few years later, a man named Edwin Hubble discovered one of these pulsating stars, applied Levitt's math, and discovered what he had always thought was a cloud of gas within our galaxy; in fact, it was an entire independent galaxy, one million light years away. So in simple terms, the observable universe has grown about a trillion times larger, just because one person has figured out how to tell the difference between what things look like and what they actually look like. That in itself is obviously pretty cool. But another interesting thing is that around the same time period, two other astronomers each independently drew a scatterplot. One axis was actual luminosity, and the other axis was temperature. They discovered that stars are not randomly distributed in this space, but rather clustered into different families. The meaning behind this is: stars with the exact same visual brightness may and do belong to a completely different family, have a completely different past, and most importantly, have a completely different future... So what is written in the star? Over the past few years, there has been much discussion about markets, narratives, capital, company building, and financial nihilism. This feeling seems to have reached a feverish climax as the tech and financial world begins to face a very different future than a few decades ago. What is particularly clear is that separating progress from asset prices has become more noisy and in many ways more repulsive. But as an investor who makes a living by buying assets that (hopefully) outperform, a simple framework is: forward returns are roughly equal to growth in fundamentals multiplied by changes in valuation multiples (and multiplied by the dividends you've collected along the way). In this case, the valuation multiplier can very cleanly correspond to the smudges on the photographic film. It's an observable data point, but it entangles two things that the market can't directly see: how good the company actually is, and how far (or how long) its future cash flow is now. I think most of the money that can be made comes from investors who are most capable of unraveling these two variables earlier than others (or “perception of differences”), and we will continue to see astonishing capital ruin for investors who treat their stains as stars. Value investing is not equal to fundamental investing. I think there is a misunderstood view: fundamental investing has historically dominated the creation of excess returns. Most of these legends come from the Graham, Buffett, and Tiger Foundation lineage, as well as numerous narratives built around this group of people. It is believed that by some point in the 2000s, this approach was no longer effective, and anyone who invested in this way was overwhelmed by momentum, trends, and “direct buying tech giants.” The conclusion was (and still is?) It's “fundamentals are dead.” ² The modern version of “fundamentals don't matter” itself isn't stupid. It's rooted in a lot of ideas that many of us on the Compound team have written before. The biggest companies get the most mechanical purchases, and the software industry has a winner-take-all economic law. AI means that giants can transform scale into moats faster than challengers, and there are also reasons why the market's microstructure embeds momentum more deeply into our market infrastructure. These are all real...

1d ago深潮TechFlow

Is 40 trillion just an “appetizer”? The Hynix buyback landed ahead of schedule. Is 130 billion US dollars still ahead?

Source: Wall Street News Editor: Dong Jing Original title: Wall Street interprets Hynix's repurchase plan: Shareholder return of up to 8% next year, or return at least $130 billion to shareholders by 2027 Summary: J.P. Morgan believes that the shareholder return policy was upgraded from “no more than 50% free cash flow” to “no less than 50%”, changing from the upper limit to the lower limit, sending a clear signal to the market: future shareholder returns will only be greater, not less. Goldman Sachs predicts an 8% shareholder return in 2027, and expects an additional repurchase of approximately 7 trillion won in the future. J.P. Morgan expects additional return of over 16% of its market value by the end of 2027. Follow-up focus will be on the results meeting at the end of October. While the market was still debating the continuation of the AI storage cycle, and SK Hynix's stock price plummeted from a June high, the storage giant suddenly threw a huge bomb on the market. A historic repurchase, which was implemented early, reshaped the market's valuation logic for Hynix! SK Hynix officially announced the market's long-awaited shareholder return policy after closing on August 19, 2026 — it plans to repurchase and cancel 40 trillion won worth of shares, involving 24.07 million shares (3.3% of the shares issued as of the end of the second quarter of 2026), equivalent to about US$28.9 billion. This scale is not only the largest share repurchase in the history of a Korean listed company, but also exceeds the approximately 26.5 billion US dollars that Hynix raised through ADR financing in the US in early July this year. According to Chase Trading Desk, the two top Wall Street agencies, J.P. Morgan Chase and Goldman Sachs, both gave highly positive comments on the announcement in their latest research report on August 20. J.P. Morgan believes that the shareholder return policy has been substantially upgraded from “no more than 50%” to “no less than 50%”, and the policy ceiling has become the policy floor. Following the announcement of a 40 trillion won ($29 billion) share repurchase plan, SK Hynix may return at least $130 billion to shareholders by 2027, according to J.P. Morgan Chase. Goldman Sachs predicts a shareholder return of up to 8% in 2027, and expects an additional repurchase of approximately 7 trillion won in the future. Both J.P. Morgan Chase and Goldman Sachs maintain buying ratings: J.P. Morgan's target price is 2.75 million won (about 84% upside compared to the current price), and Goldman Sachs's target price is 3.5 million won (implying an upward margin of about 133%). The next key catalyst is the third quarter results conference call at the end of October 2026, when the company will reveal a more complete roadmap for shareholder returns. Analysts believe that this aggressive capital action directly proved to Wall Street that the company is “printing money” faster than market expectations. For the stock price, which has plummeted 49% since its high on June 22, this not only completely offset the dilution effect of the recent ADR issuance, but also established a valuation bottom (current annualized price-earnings ratio of only 3.8 times). The scale of the repurchase: The largest in history and earlier than expected. J.P. Morgan analyst Jay Kwon clearly stated that the 40 trillion won repurchase announcement “landed earlier than expected” — previously, the market generally expected the announcement to be released around the end of September, but the company chose to directly disclose it after closing on August 19, showing management's high level of confidence in the company's cash flow situation. In terms of scale, this repurchase has multiple historical significance: 40 trillion won is the largest share repurchase announced by a Korean listed company so far; equivalent to US$28.9 billion, higher than the approximately US$26.5 billion raised by Hynix's US ADR offering in early July, which means that the company actually used the repurchase to “hedge” the previous equity dilution; this amount is equivalent to 63% of the rolling FCF (operating cash flow minus capital expenses) over the past 12 months, & nbsp; It is higher than the previous “no more than 50%” FCF allocation limit policy. At the same time, J.P. Morgan Chase pointed out that if viewed from a valuation perspective, the price-earnings ratio corresponding to Hynix's current stock price is 6.4 times (based on adjusted earnings per share for the past 12 months) or 3.8 times (based on annualized adjusted earnings per share for the first half of 2026). This valuation level can be regarded as a reference benchmark for management to initiate repurchases. Policy upgrade: From “ceiling” to “floor”, the core policy change in this announcement is that the shareholder return ratio statement was upgraded from “up to 50% (no more than 50%)” to “50%”...

1d ago22