A Complex System Needs Homeostasis: Market Self-Organization Through Negative Feedback Using A Floating Taxation Policy

Despite the market economy to be contemporaneously considered as a complex adaptive system, there are no collective feedback mechanism that provide long range stability and complexity to the system. In this scenario, the logical prediction is a long-term economic collapse by positive loops. In this work, I outline the fundamental idea of a floating taxation system as a feedback system to prevent market collapse by asymmetrical company overgrowth and extreme reduction of system complexity. The paradigm would promote the long-term stability of the economic system. I’ve implemented a generic computational neural network with 5000 virtual companies whose initial states (i.e. capital) and connective weights (trading network) were normally distributed. A negative feedback loop was implemented with different weights. The market complexity was measured in terms of joint entropy in an algorithm to calc neural complexity in networks. Without feedback, some companies had explosive growth annihilating all collateral ones until all system collapses. With feedback loops, the complexity was stable while many companies disappeared (negative selection) and the capital variance substantially increased (from 10 units in initial conditions to 2000 times) as well complexity (increment on order to 104). This data supports a theory about feedback dynamic mechanisms for market self-regulation based on floating taxes, maintaining homeostasis with complexity, capital growth, and competitive balance.