AI Investment Cycle & US Debt Cycle Resonance: Asset Allocation Insights

1. Synchronous Impact of AI Investment Cycle and US Debt Cycle on Tech Stocks:
   • From the second half of 2025 to the present, major U.S. stock indices (S&P 500, Nasdaq, Dow Jones, Russell 2000) have shown a strong upward trend, while volatility remains generally controlled—with the Nasdaq posting the largest gain, indicating that tech stocks still serve as the growth engine [0]. On the other hand, AI-related investments have become one of the main drivers of U.S. economic growth, pushing up the overall valuation of the tech sector, but also bringing risks of concentration and valuation spillover [1]. When the U.S. debt cycle is at a high level (e.g., sustained rise in debt/GDP ratio, increasing budget pressure) combined with monetary and fiscal double easing before the mid-term elections, capital flows to high-growth, AI-oriented tech stocks may be further amplified. However, we need to be alert to the capital market’s reaction to “bubbles” and liquidity shifts—especially when interest rate prospects are volatile, tech tracks with high valuations are prone to structural pullbacks.

2. The Rise of the U.S. Debt Cycle Sends Dual Signals for Commodity Allocation:
   • Under the “resonance” of the debt cycle and AI cycle, U.S. fiscal expansion plus the discussed interest rate cut expectations are expected to lower real interest rates and boost demand for raw materials and industrial goods. However, cyclical exposure needs to be differentiated: upstream assets represented by key industrial metals like copper are in a recovery phase at the bottom of the global cycle, with structural inventory tightness (especially the supply-demand mismatch caused by the rapid rise in imports from the Americas), plus potential capacity adjustments and production cut expectations—providing a logic for “buying left-side cost curve assets at the bottom” [2]. Coal is affected by both global energy structure transformation and China’s policy regulation. If China continues its policy orientation of “conservative but supportive”, both ends of the curve will tend to hedge for stable growth, creating fundamental support for coal’s rebound at the cycle bottom.

3. Asset Allocation Recommendations:
   • Tech Stocks (AI Theme):
     It is recommended to maintain a strategy of selected weighting and dynamic position adjustment, focusing on leading companies with stable cash flow, significantly differentiated AI capabilities, and reasonable valuations (e.g., companies with advantages in large-scale AI services/infrastructure). At the same time, use highly diversified ETFs or strategic hedging (e.g., via volatility tools) to mitigate the risk of bubble bursting. Given that the tech sector has recently underperformed the broader market, a rebound is still possible if policy expectations remain loose, but we need to be alert to the disturbance of amplified U.S. debt uncertainty on capital costs [0].
   • Commodities:
     The core allocation logic focusing on upstream varieties like copper and coal still holds—especially when the U.S. debt cycle drives a loose environment, the anti-inflation/hedging properties of physical commodity assets are strengthened. In addition, supplementary allocation can be made to raw materials benefiting from the infrastructure cycle and “cycle bottom” light assets (e.g., some basic chemicals/steel), but dynamic monitoring of China’s policy rhythm and inventory changes is needed.

4. Allocation Framework Under Multiple Cycle Resonance:
   • Pro-cyclical Strategy (Commodities, Industry):
     Narrowing spreads and falling real interest rates drive valuation repair of physical assets; it is recommended to allocate varieties with gradually rising global inventories and constrained supply (copper, coal, key coking raw materials).
   • Counter-cyclical Strategy (Selected Tech/AI):
     In a high-valuation environment, rely on AI infrastructure with profit recovery and stable cash flow, and sub-tracks with marginal profit improvement—supplemented by valuation hedging logic (e.g., AI hardware + software combinations) to resist debt cycle disturbances.

5. Policy and Liquidity Sensitivity Monitoring:
   • China’s “conservative but supportive” policy means that government demand for commodities is potentially controlled but supported—making it suitable to match the allocation cycle with policy rhythm; the U.S. “double easing” reflects loose liquidity, which is beneficial to asset classes in the short term, but in the medium term, we need to pay attention to the drag of debt sustainability and the dollar’s trend on tech valuations.

Against the backdrop of the resonance between the AI investment cycle and the U.S. debt cycle, it is recommended that investors focus on “selected tech” + “commodity cycle arbitrage” as the main axis. The former maintains a balance between growth and valuation, while the latter seizes supply-demand mismatches at the cycle bottom—accompanied by multiple risk hedging (e.g., macro timing, cross-market hedging) to achieve dynamic balance between returns and risks.

[0] Broker API Data — Trends of Major U.S. Indices and Sectors (2025-06-26 to 2025-12-15)
[1] Allianz Global Investors – “December 2025: 2026: New Rhythm Differentiation of the Global Economy” (https://tw.allianzgi.com/zh-tw/insights/market-insight/20251209-1-month-report-insight)
[2] FastBull – “Import Trends of Major Chinese Commodities Show Differentiation, Driven by Prices and Inventory Increase” (https://www.fastbull.com/tw/news-detail/專欄中國主要大宗商品進口出現分化趨勢，受價格和增儲驅動-news_8600_2_2025_4_1161_3/8600_NAT.GAS)