This paper suggests a new technique to construct first order Markov processes using products of copula functions, in the spirit of Darsow et al. (1992). The approach requires the definition of: i) a sequence of distribution functions of the increments of the process; ii) a sequence of copula functions representing dependence between each increment of the process and the corresponding level of the process before the increment. The paper shows how to use the approach to build several kinds of processes (stable, elliptical, Farlie-Gumbel-Morgernstern, Archimedean), martingale processes, and how to extend the analysis to the multivariate setting. The technique turns out to be well suited to provide a discrete time representation of the dynamics of innovations to financial prices under the restrictions imposed by the Efficient Market Hypothesis.