Shenwan Hongyuan Group Co., Ltd. has released a research report stating that since 2026, the narrative of AI disrupting certain industries has intensified. Coupled with energy supply pressures stemming from Middle East geopolitical conflicts, this core driver has led to significant volatility and divergence in global asset prices. From a tactical asset allocation perspective, geopolitical shocks make a near-term (next 1-3 months) rise in global inflation relatively certain. The Federal Reserve is entering a wait-and-see phase, and risk assets are moving into a period of high volatility. Over the medium term (6-12 months), inherent demand in the US economy remains weak; the higher inflation rises, the more negative the impact on demand. US dollar liquidity may tighten initially before easing later. Investors should watch for allocation opportunities after medium-term market valuation adjustments. On a strategic asset allocation level, there are opportunities within the crisis: embrace "inflationary" assets of the AI era. 1) Overweight "Inflation Assets": Against the backdrop of a transition between global economic cycles, geopolitical conflicts, and AI capital expenditure, maintain a strategic positive outlook on commodities, including energy, precious metals, and industrial metals. Watch for potential catch-up opportunities in agricultural products. 2) Chinese Assets Demonstrate Resilience: Amid global volatility, Chinese equity assets are seeing increased attractiveness due to policy support, a leading manufacturing industrial system, and an independently developed technology path. However, short-term valuation digestion is needed; focus structurally on high-growth tech and cyclical Alpha opportunities. 3) Embrace Structural Opportunities in the AI Era: For the long term, position in "hard power" assets (computing power, energy infrastructure) and focus on irreplaceable sectors related to human experience and emotion, while avoiding middle-ground areas easily standardized by AI. 4) Exercise Caution Towards Fixed Income: Given rising inflation and expectations for broader credit, remain cautious on government bonds (especially long-duration) and shift towards a coupon strategy focused on short-to-medium duration credit bonds. 5) The latest quantitative asset allocation "Five-Star Model" for Q2 2026 recommends overweight positions in gold, A-shares, and resource-rich emerging markets; neutral weightings for US stocks, crude oil, and industrial metals; and underweight positions for long-duration bonds. Shenwan Hongyuan's key views are as follows: Since 2026, the narrative of AI disruption has strengthened, and energy supply pressures from Middle East conflicts have driven significant volatility and divergence in global asset prices. Current market pricing logic is swinging sharply between "old core assets" and "new narrative assets." Dividends from old technologies (e.g., mobile internet) are diminishing, global economic growth is sluggish, debt levels are high, globalization is receding, and geopolitical risks are frequent. Meanwhile, new general-purpose technologies like AI and new energy are emerging but haven't yet reached a tipping point to fully reshape the economy. This transition phase leads to higher volatility across major global asset classes. Reviewing Q1 2026, the global quantitative asset allocation "Five-Star Model" achieved excess returns by overweighting commodities like gold and industrial metals, with a cumulative return of 5.79% since the 2026 annual report. Analyzing the 1970s oil crises and the 2022 Russia-Ukraine conflict reveals patterns in asset performance under energy shocks: 1) Commodity prices generally rise initially but may diverge later based on demand changes. During the oil crises, commodities (crude oil, gold, non-ferrous metals) rose significantly, but demand-sensitive metals corrected more as economic demand fell. 2) Bond markets generally enter a bear market. Inflation pressures push rates higher during stagflation, causing bond prices to fall. 3) Equity markets see increased volatility and potential divergence; initial valuation levels and subsequent policy trends are key. First Oil Crisis (1973-74): US stocks were at high valuations, leading to sharp declines with oil shock and Fed tightening. Second Oil Crisis (1978-79): US stocks were at low valuations; despite aggressive Fed rate hikes, market confidence held, and stocks rose alongside commodities. Russia-Ukraine Conflict (2022): Extremely high US stock valuations combined with aggressive Fed hiking led to declines in both stocks and bonds, with only energy commodities posting gains. 4) Sectorally, energy and materials sectors showed significant relative outperformance during the oil crises. 5) Initially, markets price risk premiums highly correlated with events, but medium-term trends depend on the shock's impact on inflation trends, monetary policy, and economic fundamentals. From a tactical allocation perspective, geopolitical shocks suggest near-term global inflation is likely to rise. The Fed is on hold, and risk assets are volatile. Medium-term, weaker US demand means higher inflation hurts demand, suggesting dollar liquidity may tighten then ease. Watch for allocation opportunities post-valuation adjustment. Firstly, the global economy shows a "K-shaped" divergence. Consumer confidence is weak, but investment (especially AI-related capex) recovery expectations are strong. Labor markets also show a "K-shape," with high vacancy rates in low-wage jobs but slowing wage growth. Secondly, there is a significant expectation gap regarding the potential "hawkish" stance of a future Fed Chair. Stimulating supply via rate cuts could ease inflation bottlenecks, while quantitative tightening may be difficult as it could sharply raise Treasury yields. Under this baseline, the US Dollar Index is supported short-term by safe-haven demand and oil correlation; medium-term, if conflicts ease and the Fed stays accommodative, it may revert to a 97-103 range. Strategically, focus on AI's profound impact: 1) Labor substitution: Rapid AI adoption in US info, professional services, finance, and education is already impacting white-collar jobs. The "race" between AI and labor costs will be uneven. 2) Wealth distribution: Unchecked, AI could widen the "K-shape": extreme concentration at the top (AI infrastructure owners), potential boom for micro-entities at the bottom, but wealth shrinkage for the middle layer (standardizable jobs). However, absolute living standards may rise due to productivity gains. 3) Capital markets: Market efficiency increases as AI enhances research and quant trading, narrowing information-based Alpha. Investment focus shifts to AI infrastructure, micro-entity ecosystems, and frontier tech. New moats may arise from proprietary data, legal/liability barriers, and unique culture/aesthetics. 4) Global market mapping ("HALO trade"): Comparing AI beneficiary vs. victim sector weights, markets like Taiwan (semiconductors), South Korea, and A-shares have high exposure to AI infrastructure beneficiaries. The US has higher exposure to AI-disrupted sectors (software, media, non-bank finance), posing ROE downside risks. Opportunities exist within the crisis: embrace AI era "inflationary" assets. 1) Overweight inflation assets: Strategically favor commodities, energy, precious metals, and industrial metals. Watch for agricultural catch-up. 2) Chinese assets show resilience: Benefiting from policy support and manufacturing strength, but near-term valuation digestion is needed; focus on tech and cyclical Alpha. 3) Embrace AI structural opportunities: Long-term focus on "hard power," irreplaceable human experience sectors, avoid AI-standardized middle ground. 4) Be cautious on fixed income: Cautious on government bonds, shift to short-medium credit. 5) The latest "Five-Star Model" for Q2 2026 suggests overweight gold, A-shares, resource EM; neutral US stocks, crude, industrial metals; underweight long-duration bonds. Risks: Geopolitical escalation; non-linear global slowdown; US AI tech bubble burst.