  We propose to examine the predictability and the complexity characteristics
of the Standard&Poor500 dynamics behaviors in a coarse-grained way using the
symbolic dynamics method and under the prism of the Information theory through
the concept of entropy and uncertainty. We believe that experimental
measurement of entropy as a way of examining the complexity of a system is more
relevant than more common tests of universality in the transition to chaos
because it does not make any prior prejudices on the underlying causes
associated with the system dynamics, whether deterministic or stochastic. We
regard the studied economic time series as being complex and propose to express
it in terms of the amount of information this last is producing on different
time scales and according to various scaling parameters.
