  The topic of this paper is testing exchangeability using e-values in the
batch mode, with the Markov model as alternative. The null hypothesis of
exchangeability is formalized as a Kolmogorov-type compression model, and the
Bayes mixture of the Markov model w.r. to the uniform prior is taken as simple
alternative hypothesis. Using e-values instead of p-values leads to a
computationally efficient testing procedure. In the appendixes I explain
connections with the algorithmic theory of randomness and with the traditional
theory of testing statistical hypotheses. In the standard statistical
terminology, this paper proposes a new permutation test. This test can also be
interpreted as a poor man's version of Kolmogorov's deficiency of randomness.
