Herd Behavior and Financial Crashes: An Interacting Particle System Approach

We provide an approach based on a modification of the Ising model to describe the dynamics of stock markets. Our modelincorporates three different factors: imitation, the impact of external news, and private information;moreover, it is characterized bycoupling coefficients, static in time, but not identical for each agent. By analogy with physical models, we consider the temperatureparameter of the system, assuming that it evolves with memory of the past, hence considering how former news influences realizedmarket returns.We show that a standard Ising potential assumption is not sufficient to reproduce the stylized facts characterizingfinancial markets; this is because it assigns low probabilities to rare events. Hence, we study a variation of the previous settingproviding, also by concrete computations, new insights and improvements.