Information‐Theoretic Approach to Financial Market Modeling

ABSTRACT

The paper treats the financial market as a communication system, using four information‐theoretic assumptions to derive an idealized model with only one parameter. State variables are scalar stationary diffusions. The model maximizes the surprisal of the market and minimizes the Kullback–Leibler divergence between the benchmark‐neutral pricing measure and the real‐world probability measure. The state variables, their sums, and the growth optimal portfolio of the stocks evolve as squared radial Ornstein‐Uhlenbeck processes in respective activity times.