Global Economy and Asset Allocation in the Era of Chaos

Currently, as “great power competition becomes more complex and intense,” the operation of the global economic system is showing stronger non-linearity, bidirectionality, and high sensitivity, entering a stage of chaotic evolution.

First, the historical shift of dominant variables: from order benefits to game constraints. The “14th Five-Year Plan” suggests that the current global environment is characterized by “more complex and intense great power competition.” This competition influences resource allocation and expectations through multiple channels, causing changes in the logic of economic system operation. The explanatory power of traditional linear analysis frameworks declines, and chaotic evolution gradually becomes an important feature of the current economic and financial environment. First, global trade resilience shows a downward trend. After the 2008 financial crisis, the trade expansion driven by each 1% increase in global GDP has significantly contracted, weakening the amplifying effect of trade on economic growth. Second, security considerations have clearly strengthened constraints on resource allocation. Along with the decline in trade resilience, the importance of security logic in macro resource allocation continues to rise. Third, global uncertainty has evolved from phase-specific fluctuations to structural normality. Since 2025, uncertainty has further increased on a high baseline and persists, gradually solidifying as an important background variable in the global macro environment.

Second, asset resonance under critical chaos: from mutual decline to rising on the edge. Because the economic growth mechanism is still operating, but tail risks always exist, asset prices are highly sensitive to signals across different dimensions, with responses that are not synchronized. First, risk assets still have a high return basis. The response of capital markets to macroeconomic changes does not depend on growth speed itself but more on the anticipated changes in growth quality, such as productivity improvements, profit structure enhancements, and capital return efficiency. Second, safe-haven assets have not become ineffective; instead, they continue to hold value for allocation. Parallel to risk assets, the logic of safe-haven asset returns continues structurally. In the chaotic phase, the system is highly sensitive to extreme scenarios, and any local disturbance can be rapidly amplified. This determines that the demand for risk hedging will not disappear but will become normalized. Finally, in the context of chaotic evolution, risk assets reflect bets on the direction of structural evolution, while safe-haven assets price in path uncertainty and tail risks. This is the bidirectional and sensitive mapping of critical chaos at the asset level.

Finally, breaking the chaos with a proactive historical mindset. In the face of a turbulent external environment with high winds and waves, the value of proactive response and forward-looking choices is reflected in continuous tracking of changes in dominant variables and acting in accordance with trends. In such an environment, allocation logic cannot be fixed as a static optimal solution; instead, it requires dynamic calibration based on shifts in dominant forces. Long-term returns depend on whether one aligns with the direction of structural evolution rather than overreacting to short-term noise. Therefore, a proactive historical mindset involves understanding historical laws, adapting to the tide of the times, and maintaining clear awareness of one’s position. In the critical chaos stage, asset returns often coexist in multiple pathways, with risk assets and safe-haven assets simultaneously having a basis for returns under different scenarios. Understanding this parallel pricing characteristic helps shift from passive defense to more forward-looking active allocation, rising on the edge, and forming a more resilient decision-making framework amid uncertainty.