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美国政府停摆,非农数据缺席,全球市场如何应对这场“政治风暴”
Sou Hu Cai Jing· 2025-10-08 10:55
Group 1 - The government shutdown disrupts the flow of essential economic data, which serves as a vital lifeline for policymakers and investors [1][7] - The monthly employment report, including key indicators like non-farm payroll growth and unemployment rates, is crucial for understanding the job market's health [3][5] - The Labor Statistics Bureau (BLS) will pause its operations during the shutdown, halting the release of significant economic data, including the September employment report [5][21] Group 2 - The political deadlock in Washington has led to an unprecedented "information famine" in global markets, with critical economic indicators like retail data and GDP revisions also facing delays [7][24] - The absence of data creates a scenario where market participants must adapt their decision-making frameworks, leading to a revolution in decision-making tools [9][13] - Investors are turning to alternative data sources, such as private sector employment data and commodity prices, to gauge economic conditions in the absence of official reports [15][19] Group 3 - Institutional investors are restructuring their portfolios defensively, shortening the duration of government bonds and increasing holdings in inflation-protected securities [17][19] - Ordinary investors are advised to maintain a cash buffer and adopt a cautious approach to building positions in the market [19][27] - The political dysfunction in Congress is identified as a core risk indicator for the global economy, with potential GDP growth impacts from the shutdown [24][29] Group 4 - The Federal Reserve's reliance on data for policy decisions is severely undermined by the current data vacuum, complicating upcoming monetary policy meetings [21][22] - The current environment is markedly different from previous shutdowns, with higher interest rates amplifying the risks of policy missteps [22][24] - The ongoing "data darkness" serves as a stress test for global markets, compelling participants to rethink and evolve their decision-making models [26][29]