Open Arsenal

Understanding markets as evolving feedback organisms

Feedback Living Model (FLM) is a systemic intelligence and simulation framework designed to represent markets as evolving feedback organisms. Rather than treating the economy as a collection of isolated indicators or static datasets, FLM models it as a continuously changing network of interconnected entities, capital flows, narratives, and structural dependencies. Every component in the system both influences and is influenced by others, creating recursive feedback loops that shape macroeconomic behavior over time.

At its core, FLM builds a structured economic ontology that maps industries, companies, supply chains, financial instruments, and macroeconomic forces into a unified graph system. This structure allows the model to track how changes in one area propagate through others, forming the basis for cascade and contagion analysis. On top of this ontology, FLM continuously integrates data signals such as capital movement, credit conditions, earnings dynamics, and alternative behavioral indicators to maintain an evolving representation of system state.

The platform includes a Capital Flow Engine and Regime Detection System that classify macroeconomic conditions and track liquidity cycles across different time horizons. It identifies whether the system is in phases such as expansion, tightening, speculation, or structural transition, and adjusts interpretation of signals accordingly. This is paired with a Fragility Index System that measures systemic vulnerability across sectors based on dependency concentration, leverage exposure, and sensitivity to external shocks.

To simulate instability and stress behavior, FLM incorporates a Shock Library and Cascade Simulation Engine. These tools allow the system to inject controlled disruptions—such as interest rate changes or demand shocks—and model how those disturbances propagate through the economic network. Combined with the Feedback Loop Modeler, the system captures reflexive dynamics where market reactions themselves become part of the causal structure, amplifying or dampening outcomes over time.

Additional layers include a Narrative Intelligence System that tracks dominant market beliefs and their divergence from underlying fundamentals, an Agent-Based Simulation Engine that models adaptive behavior of economic participants, and a Multi-Timeframe Analysis System that connects short-term fluctuations with long-term structural cycles. Together, these components form a unified framework for exploring systemic risk, emergent behavior, and the pathways through which economic systems evolve under stress.