  We present a new approach to the bootstrap for chains of infinite order
taking values on a finite alphabet. It is based on a sequential Bootstrap
Central Limit Theorem for the sequence of canonical Markov approximations of
the chain of infinite order. Combined with previous results on the rate of
approximation this leads to a Central Limit Theorem for the bootstrapped
estimator of the sample mean which is the main result of this paper.
