$WATERWATER 가격

On August 21, AI infrastructure investment is becoming a new variable in the US bond market. As tech giants expand data centers, chip production, and computing power, the financing demand from AI companies is rapidly increasing, beginning to compete with the US government for funds from core bond buyers such as insurance companies, pension funds, and long-term asset management institutions. Data shows that as of August, the issuance scale of US investment-grade corporate bonds reached approximately $1.7 trillion, setting a historical high for the same period. According to Goldman Sachs, the four major US tech companies have issued over $170 billion in bonds this year, surpassing the total for 2025. Meanwhile, Broadcom is seeking to provide chip and infrastructure financing for AI companies like Anthropic, with potential debt size nearing $100 billion. Market institutions point out that the impact of AI is not just an increase in US Treasury supply, but an expansion of the entire bond market's 'duration supply.' When both the government and tech companies increase their long-term financing needs while the size of the long-term funding pool is limited, the market may demand higher yields to attract buyers. St. Louis Fed President James Bullard previously stated that a capital competition is forming between US government financing needs and AI infrastructure development. Recently, the US Treasury market has been under pressure, with the yield on 30-year Treasuries rising to 5.34%, the highest since 2007, and the yield on 10-year Treasuries reaching 4.7%. A high interest rate environment may further increase corporate financing costs and affect the market pricing of AI companies through valuation discount rates. At the same time, signs of weakness have appeared in US consumer data. Walmart's stock price fell about 9% in a single day, marking its largest decline since 2022, due to same-store sales growth dropping to its lowest level in six years, below market expectations, indicating a slowdown in consumer spending. Against the backdrop of slowing economic growth and persistent inflationary pressures, the Federal Reserve faces a dilemma in its policy. The US Treasury recently expanded the scale of long-term Treasury buybacks, raising the single buyback limit for 10-20 year and 20-30 year Treasuries from $2 billion to at least $4 billion. The market believes this move is more symbolic, providing short-term relief from yield pressure but not changing the long-term supply-demand contradiction. Analysts believe that future market focus will center on US fiscal financing needs, AI capital expenditure expansion, and long-term interest rate trends. If long-term Treasury yields continue to rise, the market may revisit policy tools such as yield curve control (YCC) or quantitative easing (QE).

On August 21, AI infrastructure investment is becoming a new variable in the US bond market. As tech giants expand data centers, chip production, and computing power, the financing demand from AI companies is rapidly increasing, beginning to compete with the US government for funds from core bond buyers such as insurance companies, pension funds, and long-term asset management institutions. Data shows that as of August, the issuance of investment-grade corporate bonds in the US reached approximately $1.7 trillion, setting a historical high for the same period. According to Goldman Sachs, the four major tech companies in the US have issued over $170 billion in bonds this year, surpassing the total for all of 2025. Meanwhile, Broadcom is seeking to provide chip and infrastructure financing for AI companies like Anthropic, with potential debt approaching $100 billion. Market institutions point out that AI is not only increasing the supply of US bonds but also expanding the 'duration supply' of the entire bond market. When both the government and tech companies increase their long-term financing needs while the pool of long-term funds is limited, the market may demand higher yields to attract buyers. St. Louis Fed President James Bullard previously stated that a capital competition is forming between the US government's financing needs and AI infrastructure development. Recently, the US bond market has been under pressure, with the yield on 30-year US Treasury bonds rising to 5.34%, the highest since 2007, and the yield on 10-year US bonds reaching 4.7%. The high-rate environment may further increase corporate financing costs and affect the market pricing of AI companies through valuation discount rates. Meanwhile, there are signs of weakness in US consumer data. Walmart's stock price dropped about 9% in a single day, marking its largest decline since 2022, due to same-store sales growth falling to the lowest level in six years, below market expectations, indicating a slowdown in consumer spending. Against the backdrop of slowing economic growth and persistent inflation pressures, the Federal Reserve faces a dilemma in its policy. The US Treasury has recently expanded the scale of long-term Treasury bond repurchases, raising the single repurchase limit for 10-20 year and 20-30 year Treasury bonds from $2 billion to at least $4 billion. The market views this move as more symbolic, providing short-term relief from yield pressure but not changing the long-term supply-demand contradiction. Analysts believe that future market focus will center on US fiscal financing needs, the expansion of AI capital expenditures, and the trend of long-term interest rates. If long-term US Treasury yields continue to rise, the market may revisit policy tools such as yield curve control (YCC) or quantitative easing (QE).

On August 21, Dongshan Precision (002384.SZ) announced that the company plans to add an investment of $500 million to the optical chip and module expansion projects implemented by its subsidiary, Sols Optoelectronics, and its subsidiaries, including Weixin Thailand and Yancheng Dongshan, in Changzhou, Thailand, and Yancheng. The total investment for the project will increase from $1.2 billion to $1.7 billion. This adjustment in external investment is made according to the company's strategic planning and project implementation needs, in order to better meet the demands of downstream customers and industry development, and to adapt to the needs of the AI computing power industry.