U.S. Treasury Buyback Aims for Liquidity, Not Rate Cuts

U.S. Treasury Secretary Yellen's Treasury buyback policy is not a signal for interest rate cuts but a policy support aimed at supplying market demand and liquidity. This is interpreted as a measure to inject vitality into the market, rather than targeting interest rate cuts within the year.

In this situation, short-term investors should closely monitor key economic indicators such as the yield curve, expected inflation rate, and corporate bond spreads. These indicators can provide crucial clues for market trends and investment strategy formulation.

Former Labor Secretary Robert Reich criticized the decline in McDonald's sales as evidence of reduced consumption by low-income individuals and the deepening of a K-shaped economy. This pointed to economic polarization due to widening income inequality.

In response, Treasury Secretary Yellen countered by citing rising real wages for low-income individuals and the economic recovery of lower-income groups. Secretary Yellen argued that the U.S. economy is entering a C-shaped economy, not a K-shaped one, emphasizing that the benefits of economic recovery are spreading across society.

According to Bank of America's analysis, bond issuance by hyperscaler companies such as Amazon, Meta, Microsoft, Alphabet, and Oracle is expected to surge. The bonds of these companies, valued at $288 billion at the end of 2025, are projected to rise sharply to $659 billion by 2027.

This increase in bond issuance is primarily due to expanded investments in artificial intelligence (AI) data centers. Big tech companies are raising funds in the bond market to cover the enormous infrastructure construction costs required for AI technology development, which is expected to change the landscape of the bond market.

Yellen's Treasury buyback policy, while supplying market liquidity, also led to a decline in the value of the dollar. This was one of the main reasons behind the surge in Bitcoin prices.

Furthermore, President Trump's meeting with cryptocurrency CEOs, urging the passage of the Clarity Act, also had a positive impact on Bitcoin's rise. Trump expressed his intention to make the U.S. a hub for cryptocurrency innovation, showing a favorable stance towards digital assets.

These movements increase the possibility of digital assets being incorporated into the institutional financial market, attracting investor expectations. Institutional changes, such as the approval of Bitcoin spot Exchange Traded Funds (ETFs), are enhancing the maturity of the cryptocurrency market.

U.S. financial authorities are actively working to establish a regulatory framework for digital assets, which is expected to increase the stability and trustworthiness of the cryptocurrency market, laying the groundwork for more investors to enter.

Looking at sector-specific returns over the past three months, the biotech sector recorded the highest return, rising by 20%. The financial sector followed, showing strong performance with an 11% increase.

Additionally, the equal-weighted index (RSP) recorded higher growth than the S&P 500 (SPY) or Nasdaq 100 (QQQ) indices. This suggests that market attention, which was previously concentrated on a few AI big tech companies, is gradually spreading to other sectors. Therefore, investors need to re-evaluate their existing portfolios focused on AI big tech and consider a diversified investment strategy across various sectors.

The partnership between Moderna and Merck (MSD) presents a new strategic approach in cancer treatment. Moderna acts as a 'guideline' by identifying targets for immune cells to attack, leveraging mRNA technology to induce an immune response.

Meanwhile, Merck's Keytruda acts as an 'executor' that attacks actual cancer cells based on the targets identified by Moderna. Considering the high volatility and difficulty of biotech investments, this collaboration can be seen as an attempt to create synergy through clear role division. The biotech field involves significant technological complexity and uncertainty due to clinical trial results, thus requiring cautious investor approach.

Biotech companies' business models can be broadly divided into drug development and pre-diagnosis. Moderna focuses on developing treatment platforms for cancer patients, concentrating on curing the disease itself. Its goal is to restore health through direct medical intervention for patients.

In contrast, companies like Natera specialize in diagnosing cancer before it develops and providing pre-screening services. They use genetic testing to predict disease risk and enable early diagnosis, emphasizing prevention and proactive management.

For the commercial viability of such pre-diagnosis services, Medicare insurance coverage is crucial. Wider insurance coverage allows more patients to access these services, significantly impacting the company's market expansion and revenue growth.

Nvidia CEO Jensen Huang proposed 'LPS' as the core infrastructure for the upcoming artificial intelligence (AI) era. Here, L stands for 'Land,' meaning the site for building AI data centers. Securing vast land is essential for large-scale AI infrastructure.

P stands for 'Power,' referring to a stable and high-capacity electricity supply. AI data centers consume enormous amounts of power, so an efficient power supply system must be established. Finally, S stands for 'Shell,' meaning the entire data center building infrastructure. A robust and scalable building forms the physical foundation for AI computations.

This definition suggests that Nvidia is shifting its business direction from being a mere GPU sales company to an AI data center developer. Cases like SoftBank's SB Energy and OpenAI's data center site investments support the importance of this infrastructure.

Data center REIT companies are employing different strategies to penetrate the market. Digital Realty focuses on developing large-scale AI data centers in suburban areas, targeting major hyperscaler companies as their primary clients. They utilize vast land to build large-scale facilities.

On the other hand, Equinix operates data centers primarily in urban hubs, emphasizing the benefits of network interconnection. Data centers located in urban areas have strengths in inter-company data exchange and communication speed. Additionally, Iron Mountain successfully transitioned from a document storage company to a data center REIT, presenting a new business model. This is an example of leveraging existing assets to enter the core infrastructure market of the AI era.

When investing in artificial intelligence (AI) related companies, it is crucial to differentiate investment points based on the value each company provides. CoreWeave is a company primarily focused on selling AI computing resources. They build high-performance GPU clusters and generate revenue by providing these services to companies that need them.

In contrast, companies like Iron and Hut 8 offer not only AI computing sales but also comprehensive power and land infrastructure. They provide a more holistic infrastructure solution by offering both power supply and physical land, which are core elements of AI data centers. Therefore, investors need a strategy to select appropriate companies based on their investment objectives and which value chain in the AI industry they wish to focus on.

Renowned investor Druckenmiller recently revised his investment strategy by significantly adding AI data center-related stocks to his portfolio. He sold shares of traditional semiconductor companies like Micron and instead invested in companies such as Bitdeer, Hut 8, Rayan, and Iron.

This shift, confirmed through 13F reports, indicates that AI infrastructure construction is gaining importance, with related companies emerging as new investment opportunities. Druckenmiller's portfolio reallocation suggests that the core growth engine of the AI era is expanding beyond computing resource supply to the entire data center infrastructure.

The explosive growth of artificial intelligence (AI) data centers generates immense power demand, making utility companies responsible for power supply new AI beneficiaries. Among them, American Electric Power Company (AEP) has recently been highlighted for supplying power to major AI companies and partners like Nvidia, SB Energy, and OpenAI.

NextEra Energy leads in renewable energy and battery storage technology, with the potential to provide eco-friendly and stable power solutions to AI data centers. Especially, as data center power consumption increases, the importance of energy storage systems linked to renewable energy grows.

Constellation Energy aims for 24/7 carbon-free power supply, which aligns with the high-quality, sustainable power supply required by AI data centers. These utility companies are positioning themselves as hidden key players in the AI era by stably supplying essential power for AI infrastructure.

According to UBS's latest estimates, approximately 50% of hyperscaler companies' total capital expenditure (CAPEX) is expected to flow into Nvidia's revenue by 2028. This compares to 31% of hyperscaler investment recorded as Nvidia's revenue in 2023, suggesting that Nvidia's market dominance will further strengthen.

This outlook is based on the analysis that Nvidia will play a pivotal role across the entire AI data center ecosystem, beyond being a mere GPU supplier. Nvidia is expanding its market share by providing not only GPUs but also related software, networking solutions, and various other components of AI infrastructure.

Consequently, Nvidia is expected to extend its influence across all AI infrastructure, including data center sites, power, and networks, maximizing profitability through massive hyperscaler investments. This shows that Nvidia will be a key beneficiary in the AI era's infrastructure build-out.

The energy storage system (ESS) market is growing at roughly twice the rate of the solar market, indicating its emergence as essential infrastructure for AI data centers. The installed capacity of ESS has rapidly grown from 10 gigawatts (GW) to 100 GW in just four years.

AI data centers consume vast amounts of electricity, making stable power supply a critical challenge. ESS serves as essential auxiliary equipment to ensure the power stability of these data centers, balancing grid load and compensating for the intermittency of renewable energy. Therefore, ESS is now evolving beyond auxiliary equipment to become an indispensable core infrastructure for building AI data centers.

Fluence Energy, a leading company in the energy storage system sector, recently reported a return to deficit from profit due to poor performance. This is understood to be caused by external factors rather than fundamental issues within the company.

The primary reason is delays in data center projects. As large-scale data center construction projects are postponed, the recognition of revenue corresponding to Fluence Energy's backlog is being delayed. Therefore, the current shift to deficit can be interpreted as a temporary phenomenon, with performance expected to recover once projects resume.

The current adoption rate of artificial intelligence (AI) by U.S. companies is approximately 55%, indicating that about half of companies have adopted AI technology. This suggests that the potential of the AI market remains significant, and the remaining half of the market, which has yet to adopt AI, could serve as a future growth driver.

However, if AI adoption is slow rather than rapid, it could be a negative signal for the broader semiconductor and software industries. If AI technology adoption does not spread, demand for related hardware and software might not increase as much as expected.

Therefore, when and how the remaining half of companies adopt AI will be a crucial key directly linked to the future growth of the semiconductor and software industries. The market landscape could change significantly depending on the speed and scope of AI adoption by companies.

Despite news of SK Hynix's 40 trillion won stock sale, its stock price fell due to concerns about the profitability slowdown of artificial intelligence (AI) companies. Market sentiment appears to have contracted, reflecting worries that the growth of AI-related companies might slow.

However, analysis suggests that the primary reasons for this decline are Chinese companies' low-price offensives and global companies' cost control, rather than a market bubble collapse. Competition intensified as Chinese memory semiconductor companies entered the market with low prices, while companies' cost burdens from AI technology adoption led to expenditure control.

Thus, the decline in SK Hynix's stock price can be interpreted as a temporary adjustment in the AI market and external factors, with some opinions suggesting it's premature to view it as long-term skepticism about AI's growth momentum itself. The market may be restructured according to structural changes in the AI industry.

Historically, September has been the worst-performing month for the stock market. This seasonal characteristic, confirmed by past data analysis, warrants investor caution.

Furthermore, as Wall Street professionals return from summer vacations, a market re-evaluation process is expected to begin. This process may involve portfolio adjustments or the formulation of new investment strategies, potentially leading to temporary market volatility.

Starting December 6, the Nasdaq market will implement 23-hour trading. This means the market will essentially be open for most of the time, excluding weekends, with the aim of increasing accessibility for global investors.

However, this extended trading has raised concerns among viewers about sleep deprivation and insomnia. Korean investors, in particular, may have to trade through the night due to time differences, leading to worries about health issues and increased investment fatigue.

News has emerged that the chairman of Evergrande Group, a large Chinese real estate developer, has been sentenced to life imprisonment. This demonstrates that the Chinese government is taking unusually strong measures against economic criminals.

This ruling could exacerbate uncertainty in the Chinese investment environment and highlight potential risks. It suggests increasing government intervention in corporate activities, and foreign investors will likely need to adopt a more cautious approach.

During SpaceX's earnings call, Elon Musk declared that they would only use Nvidia's 'VeraRubin' chips, creating a market atmosphere where VeraRubin's performance is overwhelmingly recognized. This statement reaffirmed Nvidia's even stronger dominance in the AI chip market compared to its competitor AMD.

Furthermore, concerns are rising that AMD's AI chip demand could contract as big tech companies like Google and Amazon actively pursue their own AI chip development. These companies aim for cost savings and performance optimization through in-house chips, which could be a challenge for external suppliers like AMD.

Despite Treasury Secretary Yellen implementing Treasury buybacks and actively intervening in the market, the regrettable situation is that no effect has been observed. The expected liquidity provision and stabilization effects have been minimal, and market instability persists.

Amid this situation, the stock prices of artificial intelligence (AI)-related companies are struggling to avoid a decline, and international oil prices continue to show unstable trends. This demonstrates that despite Yellen's policy interventions, the market situation remains challenging.