On the stock market recurrence

We analyze the return of the S & P 500 index and characterize its evolution as being typical of a low-dimensional recurrent deterministic system. The first Poincaré return time of the chaotic logistic mapping trajectories is used to model the return evolution. The efficiency of the model is demonstrated by daily predictions over an interval of time since January, 1950 of this index, and long-term prediction for a period of 150 days.