Resum:
We present a simple randomized procedure for the prediction of a binary
sequence. The algorithm uses ideas from recent developments of the
theory of the prediction of individual sequences. We show that if the
sequence is a realization of a stationary and ergodic random process
then the average number of mistakes converges, almost surely, to that
of the optimum, given by the Bayes predictor.