David Edward Scherer Formula (DES) V4.1 — Self-Evolving Economic Intelligence System: An Adaptive Framework for Modeling the Economic System Underlying Financial Markets

The Self-Evolving Economic Intelligence System is a computational framework designed to model, analyze, and continuously update the economic system that generates financial market behavior. The framework extends beyond market-level analysis by embedding financial markets within a broader macroeconomic structure composed of households, firms, policy institutions, and global capital flows. The system integrates endogenous economic modeling, feedback loop dynamics, and hierarchical causal structures to represent the interactions between monetary policy, credit conditions, corporate performance, and asset pricing. A cross-system transmission model captures how shocks propagate through the economy and into financial markets, enabling a unified view of macroeconomic and market dynamics. Central to the framework is a self-updating mechanism that continuously adapts model parameters and structural relationships based on observed data. This includes evolving representations of inflation sensitivity, interest rate transmission, behavioral responses, and policy effectiveness. An agent–economy coupling system links micro-level decision-making with macroeconomic outcomes, allowing for co-evolution of individual behavior and systemic structure. The system further incorporates forward economic state generation, producing probabilistic projections of key macroeconomic variables such as growth, inflation, liquidity conditions, and credit cycles. A policy reaction simulation engine models the behavior of central banks and fiscal authorities as endogenous components of the system. At the highest level, an economic theory evolution layer generates, tests, and refines competing explanations of economic behavior, enabling continuous improvement of the system’s conceptual and predictive capabilities. This framework represents an adaptive approach to economic modeling, emphasizing continuous learning, structural integration, and probabilistic analysis of how economic systems evolve and influence financial markets. This work presents a methodological framework intended for research and educational purposes in computational economics, quantitative finance, and macroeconomic system modeling.