美股IPO·2025-12-13 11:14Core Viewpoint - Deutsche Bank believes the current AI boom is not a single bubble but rather an intertwining of valuation, investment, and technology bubbles [1][2][3] Valuation Bubble - The report indicates that the Shiller Cyclically Adjusted Price/Earnings ratio has exceeded 40, nearing the 44 times level seen at the peak of the 2000 internet bubble, signaling potential market overheating [4] - Despite high overall valuations, these are primarily driven by profit growth rather than pure speculation, with the S&P 500 index operating within a 22.7% annual growth trend since October 2022 [6] - Large tech stocks have a valuation premium of about 60%, supported by over 20% profit growth differences [8] - Private companies exhibit significantly higher valuations, with OpenAI's revenue forecast for 2025 leading to a price-to-sales ratio of 38 times, and Anthropic at 44 times, while public tech giants like Nvidia, Microsoft, Google, and Amazon have more reasonable valuations [11][13] - Current AI investments are primarily supported by free cash flow, contrasting with the debt-driven nature of the internet bubble era [15] Investment Bubble - The report highlights that global tech capital expenditure has maintained a growth rate of 12.3% since 2013, indicating that current growth is still within this trend [16] - Large tech companies have seen a continuous rise in investment returns since the onset of the AI cycle, driven by cloud customer demand and cost savings from AI tools [17] Technology Bubble - There are concerns regarding the usability and scalability of generative AI, which still faces issues like errors and hallucinations, potentially hindering large-scale application [19] - However, advancements such as Google's Gemini 3 demonstrate that AI has not yet reached its ceiling, achieving significant progress in multimodal capabilities [21] - Demand for AI is robust, with Google processing 130 trillion tokens monthly, a substantial increase from 9.7 trillion in April 2024, and less than 10% of U.S. businesses currently utilizing AI, indicating vast growth potential [23] - The cost of the cheapest large language models has decreased by 1000 times, driving consumption growth and ensuring no chip idleness [25] Potential Triggers for Bubble Burst - Complex financing structures, such as OpenAI's $1.4 trillion computing purchase commitment over eight years, may introduce systemic risks and valuation opacity [28] - Even cash-rich cloud service giants are beginning to issue more debt, with investment-grade bond issuance exceeding $35 billion in 2025, raising concerns about rising net debt to EBITDA ratios [30] - The report notes diminishing returns on scale, with training costs for AI models skyrocketing from $10 million to over $1 billion, while the probability of developing AGI within five years is declining [32] - Growing skepticism towards AI is evident, with over 20% of respondents in the UK and EU expressing significant concerns about job displacement due to AI [34] - Energy supply may become a major barrier to AI adoption and monetization, with projected electricity demand by 2030 expected to be four times that of 2020 [36]