We cite correspondences between dynamics in competitive markets and information theory in the objective of recovering signal from noisy information sequences. In financial markets, this objective has been examined as recovering signal on phase transitions between ordered and disordered states of agents in the market. These transitions have been indicated to denote critical points in time series of market price. Although there is a noteworthy background in information theory in the study of the dynamics of the Ising model in this manuscript, we pursue a different modeling approach. Whereas phase transitions in a multicomponent model of market states have previously been studied with numerical methods, we provide an analytical demonstration that a multicomponent model as an Ising analogue can evidence phase transitions.
Raseta et al. (Wed,) studied this question.