中产 · 702

India: The world's first country to be shorted by artificial intelligence?

Source: Qin Shuo's Circle of Friends In the first half of 2026, an impactful new label appeared in the Indian stock market — “the first country in the world to be shorted by artificial intelligence.” This assertion is not without foundation. The Nifty IT Index, which has long been regarded as a weather vane for India's technology industry, fell sharply in the first half of the year. Software service leaders Tata Consulting Services, Infosys, and Wepro are generally under valuation pressure. Meanwhile, international capital continues to withdraw from the Indian market. According to Reuters data, in the first half of 2026, foreign investors sold approximately $29 billion of Indian stocks on a net basis. After entering July, although the Nifty IT Index rebounded 16.7%, and the net inflow of foreign capital surpassed 1.6 billion US dollars, this round of market was largely due to sector rotation after global capital withdrew from crowded AI hardware transactions, which is not enough proof that India's software industry has escaped trouble. A large country with a population of 1.4 billion and many industries will of course not be easily “shorted” by a technology. India also has huge industries such as banking, pharmaceuticals, energy, electricity, communications, and consumption. Software outsourcing did not lose orders or lose value overnight. What has really been repriced by the market is India's most successful and internationally competitive growth model over the past 30 years. India has built itself as a “world office” with English-speaking talent, the number of engineers, and wages significantly lower than those in Europe and the US. Now that artificial intelligence has begun to enter the fields of programming, testing, operation and maintenance, customer service, and data processing on a large scale, India has suddenly discovered that what was once its proudest cost advantage may also become the part most easily replaced by technology. “AI shorting India” is inevitably exaggerated, but it accurately captures an even more important issue. When a country places too much hope for growth, employment, and the middle class on the same industrial circuit, a technological paradigm shift may evolve from industry shocks to development anxiety at the national level. Human arbitrage has been a huge software industry in India for a long time. The National Association of Software and Service Enterprises of India predicts that in the 2025-2026 fiscal year, India's IT industry revenue will reach US$315 billion, an increase of 6.1% over the previous year, and the number of employees will increase to 5.95 million. According to data released by the Indian government, IT and related services revenue for the 2024-2025 fiscal year was US$283 billion, and there are also more than 1,700 global competency centers across the country, employing about 1.9 million people. As a result, it is inaccurate to describe India's software industry as completely collapsing. It is still growing, has a large number of international customers, and has decades of project management capabilities, customer relationships, and industry experience. The transformation of core systems of financial institutions, databases of multinational enterprises, government information platforms, and highly complex legacy systems cannot all be completed with just a few AI agents. However, the capital market is more concerned about future growth prospects. The real problem with software outsourcing in India is that “revenue growth” and “manpower growth” are being decoupled. Their pattern in the past was very clear. European and American companies hand over standardized development, testing, operation and maintenance, data entry, and customer service to India. Indian companies charge according to the number of engineers invested and working hours. The more people a project requires, the bigger the bill the service provider can pay. The most direct way for an enterprise to increase revenue is to recruit more engineers and then undertake more projects. Although “selling people” doesn't sound decent, it is an underlying mechanism for the expansion of India's software services industry. Generative artificial intelligence breaks this cycle. Coding, debugging, and documentation work that used to require dozens of junior programmers can now be completed by a small number of senior engineers using AI tools; software testing, data collation, and customer Q&A, which originally relied on a large number of manual tasks, are also increasingly being taken over by automated systems. Customers are beginning to shift from buying hours to buying results, and are no longer willing to pay for a huge offshore team for a long time. The impact of this change is very special. Even if the order amount does not drop immediately, the number of people required for the same order may be drastically reduced. AI has improved delivery efficiency while simultaneously reducing billable labor hours. For product-based companies such as Microsoft and Google, increased efficiency usually means increased profits; for Indian outsourcers that charge per hour, increased efficiency may first mean shrinking bills. Technological advances have created a conflict of interest within the business model here. Of course, software companies in India can also use AI, but the more effectively they use AI, the faster traditional human outsourcing business shrinks. If they refuse to use it, they will also be defeated by European and American consulting firms and new service providers that use AI. Businesses must choose between weakening their old business and losing their future competitiveness. Therefore, the target of market shorting is mainly the old valuation logic of software outsourcing in India. This...

16d agoWendy#AI #India

179% during the year! RWA has skyrocketed, are institutions really entering the market?

Source: Token Dispatch Author: Vaidik Mandloi Compiled and edited by: BitPushNews Real World Asset (RWA) tokenization has soared 179% this year. Hyperliquid's trading volume on stocks and commodities now surpasses even crypto tokens. Everyone seems to have finally come to the conclusion: traditional finance (TradFi) is finally about to fully enter the chain. But when you go back to the roots and find out who is actually buying these RWAs, you'll find that this isn't a grand story of institutions entering the market at all — because most of the money actually comes from within the crypto industry. The treasury of major agreements and DAOs is frantically hoarding stocks and converting their reserves into tokenized US debt. This article will explore in depth: why this RWA spree looks more like a “dollarization” event of cryptocurrencies themselves than an institutional downgrade attack; and what it actually means when crypto protocols themselves become the biggest buyers of these tokenized US bonds. Who is actually trading RWA? Let me take you back to a few years ago: if you follow DeFi in 2020 and 2021, you'll see simply outrageous returns. Lending pools attract dollar deposits with an annualized yield of 15% to 20%, sometimes as high as 40%. Tens of billions of dollars are pouring in, yet almost no one is questioning where this money actually came from. Because these benefits come from token emissions — the agreement mints its own governance token, distributes it as a “reward” to depositors, and counts this subsidy as revenue. This is the ultimate trick to attract investors and increase TVL (total hedged value), but it only works on one condition: the token price must continue to rise. Later, when the market crashed and governance tokens plummeted by 80%-90%, the real organic yield of DeFi was actually only 2%-3%. This is even less than the yield on US short-term treasury bonds, and the risk is much higher. This revealed the harsh truth: the crypto world took years to build a financial system that simply couldn't generate competitive returns from its own economic activity. Because those benefits come from fresh capital to buy governance tokens, not from any productive use of the capital itself. Once the inflow of this new capital slows down, the entire model will return to its original form. As a result, major agreements can only protect treasury worth hundreds of millions of dollars, denominated in self-governing tokens, but are unable to earn any competitive returns within the crypto world. Then in 2023, many tokenized versions of US Treasury bonds and dollar credit products began to be launched on the chain; for the first time, the agreement was able to deposit reserves into assets that can earn real dollar returns without even leaving the on-chain ecosystem. Since then, this has become the norm. A recent study of on-chain buyers by Arrakis tracked a total of $91.3 billion in deposits across more than 10 tokenized dollar yield products. They found that of the $124 billion in high-profile buyer funds that can be clearly attributed, the full two-thirds are solely treasury funds attributable to crypto protocols and DAOs. The rest is scattered among local crypto investors, exchanges, and market makers. (Image source: Arrakis) Of the funds being tracked, the amount from institutions such as pensions, asset management companies, or banks was zero. In this $36.2 billion market, which is constantly being hyped up by the industry as “institutional entry,” traditional investors are simply hard to find. BlackRock has launched a BUIDL fund aimed at bringing institutional funding to Ethereum. It's a fully regulated, tokenized treasury bond fund with a risk-free interest rate, designed specifically for pensions, so they can buy cryptocurrency directly without explaining it to the board of directors. But as of today, 98% of the capital is in the hands of local crypto buyers. Ethena alone accounted for more than half of the fund's total value through its USDTB product. The remaining seats of the top 10 holders were also split by agreements such as Ondo and Sky's Spark Sub DAO. (Image source: Arrakis) BUIDL is no exception; looking at the entire market, almost every top five holder of a tokenized RWA product controls more than 90% of the supply. If you want to anticipate the future, the best example is MakerDAO. In 2021, the agreement held only around 17 million DAI in real-world assets. And today, this...

24d agoWendy#HYPERLIQUID #RWA topics #tokenize

Palantir CEO: AI could increase my wealth by 20 times, while increasing the polarization of social wealth

Comparing news, Alex Karp, CEO of Palantir, recently said that artificial intelligence (AI) may bring huge opportunities for wealth growth, but wealth benefits will be highly concentrated on a few technology and capital owners, further widening the gap between the rich and the poor in society. In an interview with the MDMeets podcast, Karp said that AI will improve the standard of living of ordinary people, but the wealth of those involved in developing and mastering AI technology may far exceed that of ordinary workers. He predicts that AI could even increase his wealth by about 20 times, making it worth close to $300 billion. Karp currently has a personal wealth of around $15 billion, mainly benefiting from Palantir's recent developments in the AI field and rising company valuations. He said that in the future, the income of the middle class may double within ten years, such as an annual salary of $70,000 to $140,000, but there is still a huge gap compared to the tens of billion dollar wealth growth of the top beneficiaries in the AI field. There may be a complete disconnect between wealth and ordinary wealth. According to Karp, the concentration of wealth brought about by AI will become a social issue. Karp is not an AI skeptic, but a major beneficiary of the AI industry. Palantir currently has a market capitalization of approximately $322 billion, and its business priorities include artificial intelligence platforms, data analysis, and government and enterprise AI applications. In recent years, many people in the tech and finance sector have expressed similar concerns. BlackRock CEO Larry Fink said that early AI benefits mainly went to model, data, and infrastructure owners; AI godfather Geoffrey Hinton warned that the wealthy may use AI to replace the workforce, leading to increased unemployment and a further concentration of profits.

33d ago

Zero-yuan share options, mandatory entry for newborns: Trump is betting on US stocks

Author: Xing Sheng BeatZ Original title: US stocks are national transportation. Trump is transforming the US into a fund the 250th anniversary of the founding of the US, and Trump is transforming the US into a fund. Last Monday, a few minutes before the US stock market opened, Trump was sitting in an oval office with a camera in front of him. The opening bells for the NYSE and NASDAQ were picked up by the White House and he rang them remotely. As the bell falls, he said to the camera that as the opening bell rings, these accounts will grow along with our booming economy. This week alone, $800 million in new capital will be invested in the stock market for American children. This is the first trading day since the “Trump Account” went live. Two days ago, on July 4, the 250th anniversary of the founding of the United States, he gave newborns across the country a birthday present: an investment account named after him, containing $1,000, which automatically bought US stocks. Six million children registered before it went live. In the same week, his treasury was dealing with another matter: $39 trillion in treasury bonds, which would cost more than $1 trillion in interest alone in fiscal year 2026, averaging $170 million a day. Every day, the Ministry of Finance has to find a way to repay the interest left over from yesterday. In the past 18 months, the president, a real estate agent, did three ostensibly unrelated things. The government directly took a stake in the company, opened investment accounts for newborns, and competed for shares in AI companies, but they all pointed to the same goal: making US stocks deeply tied to the US national fortune. The Eagles' 39 trillion dollar debt The starting point of this game of chess was not ambition; it was anxiety. As of May 2026, total US Treasury bonds surpassed $39 trillion, approaching $40 trillion. The size of the debt already exceeds the size of the US economy as a whole, and debt accounts for about 123% of GDP. Every day, about $5 billion in treasury bonds are added. The Congressional Budget Office predicts that interest expenses alone will exceed $1 trillion in fiscal year 2026, accounting for nearly 14% of total federal spending, which is higher than the defense budget. For every dollar the federal government receives, it costs $1.33. Huatai Securities estimates that the 2026 fiscal year deficit could reach $2.2 trillion, and the deficit rate rose to 7%. To resolve anxiety about US treasury bonds, there are three traditional solutions: increase taxes, cut spending, and inflate debt, that is, let prices rise to dilute actual debt. The first two solutions are tantamount to political suicide before the midterm elections, and the Trump administration will definitely not consider them. However, the third solution requires the US central bank, the Federal Reserve, to cooperate in cutting interest rates, and former Chairman Powell never bowed down even when threatened by Trump to find trouble and file a lawsuit. If then-Chairman Walsh directly announced interest rate cuts under the current state of the economy, it would obviously be very unattractive. So Trump needs to find a new path. And we all know that Trump's approach to solving problems has always come from the business he has been in business for the rest of his life. Real estate agents look at balance sheets in a different way than politicians: if they can't move on the debt side, then expand the asset side. On the US government's balance sheet in the past, 39 trillion dollars of debt was clearly and clearly understood; the asset side was vague, and there were almost no financial assets under the federal government's name that could be priced at market prices. Therefore, Trump's solution is to first use the powers in the hands of the government: subsidies, grants, government orders, export controls, and regulatory powers as costs and trading bargaining chips, and go to lower-priced shares in large companies. Intel was the first to be ripped off by Trump. On August 22, 2025, the US government announced the exchange of 9.9% of Intel, one of the world's largest semiconductor manufacturers, of 9.9% of the shares, at $20.47 per share, making it the chip giant's largest single shareholder. The subtlety of the deal is the source of funding: 5.7 billion from subsidies originally to Intel from the semiconductor industry subsidy bill “Chip Act” passed in 2022, and 3.2 billion from federal funding for secure chip projects. In other words, the government did not pay a single cent of the new money; what it paid was a “check that was supposed to be paid in vain” was exchanged for quite a bit of equity. Trump himself is also very proud. He announced in full capital letters on his social networking platform Truth Social: “I paid zero dollars for Intel. It's worth about $11 billion, all of which goes to the US.” Later, in a public discussion about the deal, he mentioned the negotiation process with Intel CEO Chen Liwu. Chen Liwu is a Malaysian Chinese-American who became the CEO of Intel in March 2025, and previously served as CEO of the chip design software company Cadence for 12 years. Trump said England...

37d agoburnking#Trump #US stocks

Meta enters the prediction market, where will Asia go

Source: Tiger Research Author: Ryan Yoon Compiled and collated by: BitPushNews core summary predicts that the market has become the mainstream industry, with a monthly trading volume of $14 billion. Meta's “Arena” project shows that big tech companies have recognized its value. The mechanism is simple: if an event occurs, the contract is settled at $1, and if not, it is $0, so the transaction price can be used as a real-time probability, and the oracles confirm the results after expiration. This is based on “skin in the game” (skin in the game): participants lose money if they make mistakes in judgment, which gives credibility to the information they provide. Western markets have incorporated the forecasting market into a formal system, while Asia's participation is limited, which is leading to capital outflows, loss of information sovereignty, and lack of user protection. Asia's task now is not to block these markets, but to determine how to use this data responsibly within the formal system, because avoiding discussions is tantamount to handing over dominance overseas. 1. The prediction market has found that the PMF prediction market was in the conceptual stage for many years. This changed around 2020, when a small number of small projects began to accumulate meaningful transaction volume and remove regulatory barriers one by one, marking the beginning of the forecasting market as an industry. Since then, growth has accelerated. The current monthly trading volume has surpassed $140 billion, and the leading platform's valuation has reached around $40 billion. Meta's entry made the industry's trend toward maturity even more evident. The New York Times recently reported that Mark Zuckerberg is personally leading a team to develop a prediction market app called “Arena.” The investment of this level of resources by a major technology company shows that the industry has gone beyond the experimental stage and established a business model with proven product and market fit points. 2. Where did the prediction market originate? Predicting markets is not a new invention. Blockchain technology existed in academia and finance for years before it brought it into the wider public eye and helped shape the industry. 2.1. The informal use of the term “forecast market” appeared later than in its actual history. In the 1980s, the concept had various names, including information markets and decision markets, and it wasn't until 2004 that an economics paper identified “forecast market” as the standard term. However, its history of practice dates back several centuries. Its earliest form was a political gamble on election results. In 18th-century London, cafes are full of bets on parliamentary scandals and prime minister changes, and the results and odds are sometimes reported in newspapers. In 19th century New York, an informal futures market that predicted presidential election results operated actively in the roadside market near Wall Street. 2.2. Academic applications in academia began with an experiment at the University of Iowa in 1988. Confused by the poll's failure to predict Jesse Jackson's victory in the Michigan preselection, three economists designed a marketplace where people could trade election results. This is the Iowa Electronics Marketplace (IEM). In 1992 and 1993, IEM was approved by the US Commodity Futures Trading Commission (CFTC) for research purposes. The market is open to anyone willing to invest $5, and between 1988 and 2004, its forecast performance outperformed traditional polls by about three-quarters. It operates as an effective laboratory that combines collective judgment into price. Even so, there was no regulatory framework at the time that allowed it to operate as an open market. 2.3. The early prediction market for binary options is very similar to binary options in the financial market: contracts are paid based on yes/no bets, that is, whether the price crosses a certain threshold within a set period of time. This structure, which settles to 1 if an event occurs and 0 otherwise, is completely consistent with the logic of today's prediction market. Binary options have also entered regulated exchanges. The 2007 US Stock Exchange's fixed return options (Fixed Return Options) and the 2008 Chicago Board Options Exchange (CBOE) binary options based on the S&P 500 index are notable examples. Frequent fraud on offshore platforms led to several major jurisdictions banning the retail sale of these products between 2017 and 2021. Despite setbacks, the basic contract structure (i.e. binary bet) is still the logic for predicting the operation of the market today. 3. Today's predictions...

44d agoWendy#Meta #gaming #Predicting the market #Forecast market topics

When AI is cheaper than Indian engineers, how far can India's IT model go?

Author: Shenchao TechFlow Original title: India, the first country to be shorted by AI, 52-year-old Indian engineer Shiv has maintained a habit: posting at least 5 resumes every day. This commitment began in April of this year. In March, US software giant Oracle laid off 12,000 people in India, and he was one of them. After working for the company for 14 years, he thought he would keep working until his retirement. Now he still has to pay Rs 50,000 per month. The family has been living in the same house for 15 years, and he doesn't want his family to move out. One evening, he discovered that he had infuriated his wife for no reason. In an interview with India's Outlook magazine, he said, “Technology was built by us; we learned it; we developed it. When they run out, they let us go.” Also in the same round of layoffs was 25-year-old Priyanka. She woke up early that morning to go to the gym, glanced through her email, and a cold email informing her that she had been fired. She is carrying two installments, one for an iPhone and one for a small e-mule, and she has to pay back a total of 20,000 rupees every month. She is using her savings to stay in Bengaluru. Taking the camera further away, behind Shiv and Priyanka is a rare national-level shorting liquidation. The shorting country is called India. The purest AI short title in the world, if you want to find a trading target in the global market in Mumbai, can express the story “AI replaces human white-collar workers” in its purest form. The answer is on both the NASDAQ long list and the Bombay Exchange's short list. The former is Nvidia, and the latter is India's Nifty IT Index. A look at the trend of this index in 2026 is like a judgment being executed one by one. The Nifty IT Index hit a record high of 4,6089 points on December 13, 2024, and had retreated 43% by the end of June this year. In the first half of 2026, the index fell by about 30%, making it the worst performing sector in the entire Indian market. The Nifty 50 market fell only about 9% during the same period. India's four IT giants, TCS, Infosys, Wipro, and LTimindtree, have withdrawn about 50% from their respective peaks. The ten major IT companies have collectively evaporated about 19.28 trillion rupees in market capitalization, equivalent to more than 200 billion US dollars. The market value of TCS has fallen below the 10 trillion rupees mark. What is even more interesting is the pace of decline. Every big negative line can almost cover the last press conference of an American AI company. On February 4, Anthropic released a next-generation programming tool that claims to automate exploration and analysis in the transformation of most legacy systems. The modernization of COBOL systems has been an iron job in India's outsourcing industry for decades. The news spread to Mumbai, and the IT sector began selling off. Since then, the cumulative decline has exceeded 15%, and 5.08 trillion rupees have evaporated. In May, OpenAI announced that it would invest more than $4 billion to form a team of “pre-deployment engineers” to directly enter enterprise customers and restructure workflows around AI. The market immediately understood the subtext: high-value consulting, deployment, and transformation projects that may bypass Indian service providers in the future. Nifty IT's response fell to its lowest level since May 2023. In June, Accenture plummeted by nearly 18% in a single day, the biggest single-day decline since listing. When Mumbai opened the next day, Nifty IT fell 6%, Infosys fell 8.19% in a single day to a five-year low, and 1.35 trillion rupees evaporated in one trading day. The customers that Accenture serves are the same European and American banks, retailers, and manufacturers that Indian IT companies serve. The seller's attitude is also changing. Investment bank Jefferies warned that in the worst case scenario, there is still room for a 30% to 65% decline in Indian IT stock valuations. Citrini Research's report predicts that contract cancellations between TCS, Infosys, and Wipro will continue to accelerate until 2027. Local brokerage firm Nirmal Bang adjusted the TCS rating from buy directly to sell, and cut the target price from 3046 rupees to 1,693 rupees. According to Bloomberg data, the combined weight of the top five IT companies in the Nifty 50 has fallen below 7.6%, the lowest since 2002. The capital market uses real money...

46d agoburnking#AI #India

Aave V3 has been deployed on Monad

Comparatively, Aave has deployed a V3 loan agreement on Monad, and the initial market supports 12 assets: USDT0, USDC, Aave stablecoin GHO, USDE, mUSD, WETH, CBBTC, wsTEth, weETH, syrupusdc, and susDE. For the first time in this deployment, Aave launched the Chainlink Intelligent Value Recovery Mechanism (SVR) at the beginning of the launch, which can return part of the MEV value generated during the liquidation process to the agreement. The Monad Foundation will invest $15 million as an incentive within the first 12 months of the project's launch, and agreed to purchase 10 million GHO and hold them for at least six months; Aave DAO also promised to invest 500,000 GHO as incentives to support the application on Monad.

51d ago

On the eve of going to the US, Hynix fell like a native dog

Author: Azuma (@azuma_eth) Original title: On the eve of going to the US, Hynix fell like a native dog SK Hynix's listing process in the US has reached the final stage, but just before the Korean storage giant is about to land on the NASDAQ, the AI and semiconductor industry narrative ushered in a sharp change of mood in a very short period of time. On the evening of July 1, the news that “Meta may release excess computing power” sparked speculation that major manufacturers might reduce capital expenditure, which in turn caused sharp market fluctuations. As the narrative of “absolute scarcity” of AI computing power began to loosen up, the semiconductor memory chip sector was directly impacted, and related concept stocks collectively experienced a huge correction in the secondary market — SK Hynix Korean stocks closed down 14.57%, dropping hundreds of billions of dollars in market value in a single day. SK Hynix countdown to the US on June 30. SK Hynix has submitted an F-1 prospectus to the US Securities and Exchange Commission (SEC). It plans to list on the NASDAQ through the issuance of an “American Depositary Receipt” (ADR). The planned capital raising scale is about 45.45 trillion won (about 29.4 billion US dollars), which is expected to become one of the largest ADR issuances in history. All of the capital raised will be used to expand production capacity in Korea, including the Yongin Fab, Cheongju Advanced Packaging Production Line, and investment in EUV and related equipment. Odaily Note: The so-called ADR is essentially a trading vehicle for non-US companies in the US stock market. ADR is not a US stock directly issued by a company, but an “alternative security” issued by a custodian bank in the US. The underlying level corresponds to the common stock assets of overseas companies. Through ADR, investors can directly trade overseas company shares in US dollars in the US stock market without opening a cross-border account or handling foreign exchange and settlement processes. The transaction is jointly underwritten by Bank of America, Citibank, Goldman Sachs and J.P. Morgan Chase. A total of 17.79 million new shares (2.5% of its total issued share capital) will be issued under the stock code SKHY. In terms of schedule, ADR is expected to be traded on NASDAQ on July 10. The reason why SK Hynix chose to actively promote its listing in the US during the current cycle is essentially the result of the resonance of the three factors of the industrial cycle, capital window, and competitive structure. First, SK Hynix is currently in a historic boom cycle. Driven by AI server demand, high-bandwidth memory (HBM) has become the core supply bottleneck. The company's market share in this field has exceeded 50%, while driving the overall DRAM business into a high-profit stage. This also enabled its performance to enter the upward channel at the same time as its stock price, forming a typical “cyclical high-level financing window” — large-scale production expansion financing at the stage where fundamentals are strongest. Second, judging from the capital market structure, the US market is still the main pricing center for global AI assets. Whether it's Nvidia, AMD, or memory chip companies such as Micron, US stocks as a whole give the AI industry chain a significantly higher valuation center and liquidity premium. In contrast, there has been a so-called “Korean discount” in the Korean market for a long time, and the valuation of similar semiconductor assets is generally lower than that of US stocks. Therefore, one of the core meanings of SK Hynix going to the US to issue ADR is to hope to include the company in a higher valuation system for repricing. Finally, storage giants are in fierce competition to expand production, and the expansion of production capacity is highly dependent on continuous huge capital investment. SK Hynix's financing of close to 30 billion US dollars will be used to expand production of fabs, advanced packaging and equipment. Essentially, it is also seeking to transform capital advantages into production capacity advantages. If it turns out like this, can I still buy Hynix? Originally, SK Hynix's visit to the US can be seen as a historic moment for the storage industry, but this round of sharp correction, which began last night, temporarily injected great uncertainty into its future market. Should we take the opportunity to break the bottom and wait for US stocks to take off after listing? Or is it time to reduce positions decisively to avoid potential bubble bursting? I would like to state in advance that the next part is solely my opinion and does not constitute investment advice. In my personal opinion, this round of SK Hynix's sharp decline, including a sharp correction in the sector, is closer to a liquidity stampede driven by heightened sentiment rather than a substantial reversal of industry trends. First, let's focus on the trigger in the news — “Meta may release excess computing power.” The news itself is overinterpreted. When Bloomberg first published this news, the headline was “Meta Is Building a Cloud Business and Selling Excess AI Computing Power” (Meta Is Building a Cloud Business to Sel...

51d agoburnking

Goldman Sachs: Investors cut holdings in big tech companies

Comparing the news, Goldman Sachs said that investors are reducing their exposure to the “Big Seven” and are instead favoring AI beneficiaries, such as semiconductor companies, rather than hyperscale cloud computing providers that fund large-scale AI spending. Goldman Sachs believes the market is rewarding companies that generate returns from investing in artificial intelligence, while questioning those that bear the costs. Cautious attitudes towards big tech companies are likely to continue until hyperscale cloud computing providers show stronger profit growth.

51d ago

What did the head of the Korea Financial Supervisory Service say? I really regret the introduction of leveraged ETFs and should have stopped them at the time

Comparing news, Lee Chan-jin (Lee Chan-jin), director of the Korea Financial Supervisory Service, said on the 22nd that he regrets introducing Samsung Electronics and SK Hynix single-stock leveraged ETFs, acknowledged policy failure, and revealed that investor safety measures are being prepared. Regarding South Korea's debt investment boom, Lee Chan-jin said he was wary of the statistical illusion that credit transaction financing balances declined as a share of the total market value in the total market value due to the increase in the total market value of the stock market, and the decline in experience. Lee Can-jin's full statement at the press conference was as follows: Acknowledging the failure of the single-stock leveraged ETF policy, Lee Chan-jin expressed clear regret over the Samsung Electronics and SK Hynix single-stock leveraged ETF introduced at the end of last year to deal with high exchange rates, and expressed strong concern about overheated investment. The system was introduced at the end of last year to cope with the continued high exchange rate of the won, with the goal of directing the investment demand of retail investors from overseas stocks back to the domestic stock market. Li Canzhen pointed out that the product's extremely high turnover rate is causing only securities companies' pockets to bulge up. I'm worried that this might turn into a situation where people who pump money in casinos make a lot of money. I'm personally very worried that real retail investors don't get actual benefits; only the profit part of the management and operation system. The product's turnover rate is close to 200% when it is high. Based on this, it is estimated that the transaction fee that securities companies can obtain can reach up to 10 trillion won. I'm personally reflecting on whether I should have stopped it by lying down at the time no matter what, and now I really regret it. Warning that leveraged ETFs only allow brokerage firms to make money. Investor protection measures are being prepared Lee Chan-jin expressed strong concern about the high turnover rate of leveraged ETFs, and warned that the current overheating situation has not abated. Although the Financial Supervisory Service recently issued a relevant consumer alert, it has not cooled down. Most investors belong to the middle class and ordinary people. If the stock market fluctuates, it could have a huge impact on households, so additional safety measures are being considered. Regarding the direction of specific measures, Lee Can-jin said: Plans are being studied to mitigate external shocks in credit-related areas, and will discuss with the policy authorities how to handle various measures from financing guarantees to credit in stages. Worried about the boom in debt investment and wary of statistical misconceptions Regarding the overall stock market and loan investment situation in South Korea, Lee Chan-jin pointed out that market instability and concentration of transactions are intensifying. There has been a sharp rise in transaction turnover, etc., and market instability and volatility have increased dramatically. In particular, the concentration of transactions, mainly semiconductor stocks, is expanding. Although loan investment has also increased dramatically, as the total market value rises, the share of credit financing balances in the total market value has declined, and there is an ironic decline in physical perception. In order not to be overwhelmed by statistical illusions, we are watching closely, and in fact, taking it seriously. Lee Chan-jin expressed strong dissatisfaction over the recent failure of the SpaceX IPO subscription allocation for Korean retail investors. Not a single share has been distributed, and I don't understand this either. The distribution process is simply unbelievable. From an investor's point of view, this is also a very inconvenient and unsatisfying situation. If you hadn't participated in the IPO, you could have bought the stock on the first day of listing, but wasn't that money covered up (the IPO)? Li Canzhen later stated that in order to protect investors and prevent recurrence, the inspection results of future assets and securities will be shared.

60d ago