This paper introduces the class of stationary prediction strategies and constructs a prediction algorithm that asymptotically
performs as well as the best continuous stationary strategy. We make mild compactness assumptions but no stochastic assumptions
about the environment. In particular, no assumption of stationarity is made about the environment, and the stationarity of
the considered strategies only means that they do not depend explicitly on time;
it is natural to consider only stationary strategies for many non-stationary environments.