Behavioral absorption of Black Swans: simulation with an artificial neural network

Abstract This article attempts to formalize the Black Swan theory as a phenomenon of collective Behavioral change. A mathematical model of collectively intelligent social structure, which absorbs random external disturbances, has been built, with a component borrowed from quantum physics, i.e. that of transitory, impossible states, represented by negative probabilities. The model served as basis for building an artificial neural network, to simulate the behaviour of a collectively intelligent social structure optimizing a real sequence of observations in selected variables of Penn Tables 9.1. The simulation led to defining three different paths of collective learning: cyclical adjustment of structural proportions, long-term optimization of size, and long-term destabilization in markets. Capital markets seem to be the most likely to develop adverse long-term volatility in response to Black Swan events, as compared to other socio-economic variables. JEL: E01, E17, J01, J11