大摩：2026年的主要风险是“AI资本狂潮未能提升生产力”

Group 1 - The core view of the article is that a capital expenditure boom driven by AI is emerging, but it carries significant risks if not translated into productivity growth [1][6] - Morgan Stanley's report predicts that global AI-related capital expenditures will approach $3 trillion, with approximately $1.5 trillion needing to be financed through public and private credit markets [2][4] - The investment wave is expected to directly impact the real economy, contributing 0.4 percentage points to the projected 1.8% GDP growth in the U.S. by 2026 [2] Group 2 - The investment opportunities arising from this policy-driven cycle are expected to benefit multiple industries, not just a few leading AI companies [4] - Morgan Stanley forecasts the S&P 500 index to reach a target of 7800 points by the end of 2026, driven by earnings growth across various sectors and company sizes [4] - In the credit market, high-yield bonds are expected to outperform investment-grade bonds due to increased AI financing demand, with total returns projected at around 6-7% [4] Group 3 - Despite the positive outlook for 2026, there are warnings about potential cyclical pressures from trade policies and interest rate fluctuations [5] - The report anticipates that the Federal Reserve may begin to lower interest rates in early 2026, with 10-year Treasury yields expected to rise to 4.05% by year-end [5] - The dollar index (DXY) is projected to decline to around 94 in the first half of 2026 before rebounding, but could experience volatility due to political or trade risks [5] Group 4 - A key risk highlighted is the potential failure of the AI capital expenditure boom to deliver substantial productivity gains, which could lead to rising corporate leverage and credit market concerns [6] - However, the likelihood of this risk materializing in 2026 is considered low, as corporate fundamentals remain strong with healthy balance sheets and low leverage [6][7] - Investors are advised to monitor corporate leverage, market valuations, and whether the investment wave translates into actual output, as these indicators will influence investment recommendations [7]