Shenwan Hongyuan Group: Taking advantage of the crisis to layout "inflation" assets in the AI era.

Shenwan Hongyuan Group released a research report, stating that since 2026, the narrative of AI disrupting some industries has strengthened. The energy supply pressure caused by the Middle East geopolitical conflict has led to intense volatility and differentiation in global asset prices driven by this core contradiction. From a tactical asset allocation perspective, under the impact of the geopolitical situation, it is relatively certain that global inflation will rise in the short term (1-3 months), the Federal Reserve will enter a wait-and-see period, and risk assets will enter a period of volatility; in the medium term (6-12 months), weak intrinsic demand in the current round of the U.S. economy, the higher inflation rate negatively impacts the demand side, dollar liquidity may tighten and then loosen, and opportunities for asset allocation after a mid-term market valuation adjustment are worth attention. On the strategic asset allocation level, embrace the "inflation" assets of the AI era. 1) Overweight "inflation assets": In the background of the global transition between old and new cycles, geopolitical conflicts, and the resonance of AI capital expenditures, continue to strategically favor commodities, energy, precious metals, and industrial metals. Pay attention to the possible resurgence opportunities for Shenzhen Agricultural Power Group. 2) Chinese assets highlight resilience: Amid global volatility, Chinese equity assets benefit from policy support, a leading manufacturing industry system, and an independent development path in technology, increasing attractiveness. However, short-term valuation digestion is needed, and a focus on the prosperity of technology and cyclic Alpha is recommended. 3) Embrace structural opportunities in the AI era: Long-term layout of "hard hegemony" (computing power, energy infrastructure), focus on irreplaceable tracks such as human experience, emotions, etc., and avoid the intermediate zone easily standardized by AI. 4) Caution towards fixed income: Given the rising inflation and expectations of loose credit, be cautious towards interest rate bonds (especially long-term) and shift towards a strategy of interest-bearing short-medium term credit bonds. 5) The latest issue of the quantitative asset allocation "Five Star Model" shows that in Q2 of 2026, it is recommended to overweight gold, A-shares, resource-based emerging markets, allocate standard weight to US stocks, crude oil, and industrial metals, and underweight long-term bonds. Shenwan Hongyuan Group's main points are as follows: Since 2026, the narrative of AI disrupting some industries has strengthened, and the energy supply pressure caused by the Middle East geopolitical conflict has led to intense volatility and differentiation in global asset prices. The current capital market pricing mechanism is swinging dramatically between "old core assets" and "new narrative assets." The exhaustion of old technology dividends (such as mobile internet), weak global economic growth, high debt levels, globalization retreat, and frequent geopolitical risks. At the same time, the new generation of "general purpose technology," represented by AI and new energy, is incubating, but has not yet reached a critical point of completely reshaping the economy. This "transition" state of old and new dynamics has led to an increase in global class asset volatility. Looking back at the first quarter of 2026, our global quantitative asset allocation "Five Star Model" achieved excess returns in large commodities such as gold and industrial metals, with a cumulative return of 5.79% since the 2026 annual report. Reviewing the performance of major asset classes under energy shocks during the two oil crises of the 1970s and the 2022 Russia-Ukraine conflict: 1) The overall rise in commodity prices in the early stages, with potential differentiation following changes in demand. During the two oil crises, large commodities (crude oil, gold, non-ferrous metals) all rose significantly, followed by adjustments, with more sensitive commodities such as non-ferrous metals adjusting more due to declining economic demand. 2) The bond market as a whole enters a bear market. During stagflation, inflation pressures push up interest rates, causing bond prices to fall. 3) Stock market volatility may intensify and show differentiation, with valuation levels and subsequent policy trends being key: First oil crisis (1973-74): U.S. stock valuations were at historically high levels (Shiller P/E ratio at 52.9 percentile), with an oil price shock combined with subsequent Fed tightening leading to a simultaneous decline in stocks and bonds. Second oil crisis (1978-79): U.S. stock valuations were already low (Shiller P/E ratio at only 5.1 percentile), despite decisive rate hikes by the Fed (Volker) to control inflation, market confidence was not severely impacted, and ultimately both stocks and commodities rose simultaneously. Russia-Ukraine conflict (2022): Prior to the conflict, U.S. stock valuations were extremely high, coupled with the Fed's aggressive rate hikes to combat high inflation, leading to a decline in both stocks and bonds, with only energy commodities recording positive returns. 4) Industry level: During both oil crises, the energy and raw materials sectors exhibited significant relative returns. 5) From the perspective of market reaction pace, in the early stages of geopolitical conflicts, markets mainly price in risk premiums, and asset trends are highly correlated with changes in the situation. However, subsequent trends (in the medium term) depend on the impact of the shock on the inflation center, monetary policy, and economic fundamentals. From a tactical asset allocation perspective, under the impact of the geopolitical situation, it is relatively certain that global inflation will rise in the short term (1-3 months), the Federal Reserve will enter a wait-and-see period, and risk assets will enter a period of volatility; in the medium term (6-12 months), the current round of the U.S. economy has weak intrinsic demand, and the higher inflation rate negatively impacts the demand side, with dollar liquidity possibly tightening and then loosening. It is worth paying attention to opportunities for asset allocation after a mid-term market valuation adjustment. Firstly, the global economic structure is showing a "K-shaped" differentiation. Consumer confidence is weak, but there are strong expectations for the rebound in investment (especially AI-related capital expenditures). The labor market also shows a "K-shaped" feature, with high vacancies in low-paying positions but a decrease in wage growth. Secondly, there is a significant expectation gap for the potential hawkish stance of the future Federal Reserve Chair Kevin Warsh. Stimulating supply through rate cuts (such as in the manufacturing sector) to alleviate inflation bottlenecks is a potential path, while reducing the balance sheet could lead to a significant increase in U.S. bond yields, making it difficult to implement. Under this long-term benchmark assumption, the short-term US dollar index is supported by risk aversion sentiment and positive correlation with oil prices; in the medium term, if geopolitical tensions ease and the Fedeal Reserve maintains a loose stance, the U.S. dollar is likely to return to a range of 97-103. On the strategic asset allocation level, pay attention to the profound impact of the trend of AI development on the economy and capital markets: 1) Substitution of labor: The penetration rate of AI in U.S. industries such as information, professional services, finance, and education is rapidly increasing, causing an impact on white-collar employment. The "competition" between AI and labor costs will be a non-smooth process that accompanies social bargaining. 2) Impact on wealth distribution: Without intervention, the unfettered development of AI may lead to a "K-shaped" differentiation in social wealth: the top level (controlling AI infrastructure) is extremely concentrated, the bottom level may see the prosperity of "one-person enterprises," while the middle layer (occupations that can be standardized and replaced) may see a contraction of wealth. However, thanks to leaps in productivity, the absolute living standards of ordinary people are expected to improve. 3) Impact on capital markets: Market efficiency will increase: AI will strengthen research and quantitative trading, leading to a narrowing of the space for information-based Alpha (excess returns). Shift in investment focus: towards AI infrastructure (computing power, energy), micro-entity ecosystems, and cutting-edge technology. Emergence of new moats: Moats that are difficult to be replaced by AI may come from private data, legal/responsibility thresholds, and unique cultural/aesthetic aspects. 4) Global market mapping ("HALO trading"): Comparing the market value weights of industries benefiting and stagnating from AI in various markets, China-Taiwan (mainly semiconductor), South Korea stock market, and A-share market have a higher proportion in the "AI infrastructure benefits" sector; while the United States has a relatively greater proportion in the "AI disruption damage" (such as software, media, non-bank financial) sector, with a risk of declining ROE levels. Embrace the "inflation" assets of the AI era amidst challenges. 1) Overweight "inflation assets": In the background of the global transition between old and new cycles, geopolitical conflicts, and the resonance of AI capital expenditures, continue to strategically favor commodities, energy, precious metals, and industrial metals. Pay attention to the possible resurgence opportunities for Shenzhen Agricultural Power Group. 2) Chinese assets highlight resilience: Amid global volatility, Chinese equity assets benefit from policy support, a leading manufacturing industry system, and an independent development path in technology, increasing attractiveness. However, short-term valuation digestion is needed, and a focus on the prosperity of technology and cyclic Alpha is recommended. 3) Embrace structural opportunities in the AI era: Long-term layout of "hard hegemony" (computing power, energy infrastructure), focus on irreplaceable tracks such as human experience, emotions, etc., and avoid the intermediate zone easily standardized by AI. 4) Caution towards fixed income: Given the rising inflation and expectations of loose credit, be cautious towards interest rate bonds (especially long-term) and shift towards a strategy of interest-bearing short-medium term credit bonds. 5) The latest issue of the quantitative asset allocation "Five Star Model" shows that in Q2 of 2026, it is recommended to overweight gold, A-shares, resource-based emerging markets, allocate standard weight to US stocks, crude oil, and industrial metals, and underweight long-term bonds. Risk warning: Intensified geopolitical conflicts; nonlinear weakening of the global economy; bursting of the AI technology stock bubble.