Universal Model of Crowd and Market Dynamics: Psychodynamic Formalization of Supply, Demand, and Collective Memory within the Crowd-Based Dynamics Framework

This work presents a universal structural model of collective dynamics integrating financial markets, social crowds, and complex adaptive systems within the theoretical framework of Crowd-Based Dynamics (CBD). The objective is to provide a causal and formal explanation of observable collective phenomena by linking empirical market structures with the psychological and informational mechanisms governing collective behavior. The model is built around a universal formulation of collective dynamics: P(t) = Aψ(S, R, V, D[D_cond, D_act], C, T, M, I) × [O(t) ⋅ D(t)] × F(t) In this formulation, the observable state of a collective system emerges from the interaction between psychological thresholds, emotional intensity, mimetic memory, informational flows, and contextual structural constraints. Supply and demand are interpreted not simply as economic quantities but as opposing psychological forces reflecting collective anticipation, fear, and engagement. Within this framework, collective dynamics evolve through feedback loops linking emotional intensity and mimetic memory. These interactions generate accumulations of latent tensions that may eventually activate structural divergences capable of producing regime transitions such as market reversals, bubbles, systemic crises, or collective behavioral shifts. The model introduces internal state variables that describe the evolution of collective systems, including emotional volume, mimetic memory, divergence thresholds, and informational modulation. These variables allow the identification of latent tensions, their accumulation through time, and their eventual activation when psychological saturation exceeds critical thresholds. In this perspective, empirical structures traditionally described in financial market analysis—such as trends, support and resistance levels, and the confirmation of movements by trading volume—can be interpreted as observable manifestations of deeper collective psychodynamic processes. Classical financial theories can therefore be understood as descriptive cases of broader endogenous dynamics generated by collective psychological interactions. Beyond financial markets, the framework extends to multiple domains of collective systems including social crowd behavior, political dynamics, economic cycles, and other complex human systems. In all these contexts, collective structures emerge from decentralized interactions between individuals through mechanisms of imitation, emotional reinforcement, and informational propagation. This work contributes to the theoretical development of the Crowd-Based Dynamics research program by proposing a unified architecture capable of linking micro-level psychological interactions with macro-level collective structures and regime transitions in complex adaptive systems. The framework is consistent with several foundational laws of the Crowd-Based Dynamics model, including the law of mimetic saturation, the law of conditional reversibility, and the law of temporal governability, which together describe the structural limits governing the evolution and stability of collective systems.