A parametric, information-theory model for predictions in time series

• Economic, chaotic time-series are analyzed with information theory methods.
• The maximum entropy principle is appealed to.
• Predictions concerning the Dow-Jones series are made.

In this work, a method based on information theory is developed to make predictions from a sample of nonlinear time series data. Numerical examples are given to illustrate the effectiveness of the proposed method.