AbstractThis paper develops an agent-based simulation framework for studying early warning signal (EWS)dynamics in market models subject to adversarial interference. Building on the phase transitionmathematics validated across natural systems (SIP-AI-04), we introduce adversarial agents calibratedfrom documented coordination behaviours in regulatory proceedings. Simulation results demonstrate thatadversarial agent injection systematically suppresses EWS (rising autocorrelation, rising variance) thatwould otherwise precede phase transitions. Structural resistance features (physical delivery requirements,position limits, mandatory reporting, execution transparency) partially restore EWS patterns toward naturalbaselines. We specify a detection protocol for identifying EWS deviation in time-series data. Theframework is offered as a methodological contribution for research purposes; it does not constitute claimsabout actual markets or financial advice.Keywords: agent-based modelling, early warning signals, phase transitions, market microstructure,adversarial systems, critical slowing down, simulation
Smith et al. (Sun,) studied this question.