Cost-as-signal: A chemically grounded framework for detecting stress in global precursor-material systems

This study develops a chemically grounded, non-cooperative approach to deep-tier visibility by analyzing precursor-material spot markets for IMX-104 production across the European Union, United States, and Asia from 2017 to 2026. Precursor inputs were identified via backward chemical-synthesis tracing to ensure the analysis mirrors a real, synthesis-based upstream system. Market dynamics were quantified using a multidimensional Upstream Stress Index (USI) integrating four components: structural tension, price volatility, irregular residual shocks, and cyclical frequencies. A Lead-Lag Transmission Module and one-lag predictive vector regressions were applied to regional USI series to map the temporal ordering and predictive structure of cross-border stress conduction. The framework successfully isolates four historical instability regimes: pre-pandemic baseline stability, COVID-19 operational divergence, the 2022 multi-regional energy crisis, and the synchronized global collapse during the 2026 Strait of Hormuz chokepoint crisis. Cross-correlation analysis reveals that while the European Union consistently leads North American and Asian stress cycles with a one-month delay, the United States and Asia exhibit a powerful contemporaneous co-movement peaking heavily at lag zero, indicating an intense shared sensitivity to global macroeconomic shocks. Concurrently, one-lag predictive vector regressions establish that despite this contemporaneous co-movement, strong predictive associations exist; the lagged European Union and United States indicators possess unique, incremental information to forecast next-month stress trajectories in Asia. By relying solely on publicly observable market signals and chemical-pathway logic, this framework provides an empirical, non-cooperative mechanism for detecting deep-tier disruptions in secrecy-bound supply networks.