# Stochastic processes having Markov kernels

Let $(\Omega_1, \mathcal{F}_1, P_1)$ and $(\Omega_2, \mathcal{F}_2, P_2)$ be probability spaces and suppose $(X_t)$ and $(Y_t)$ are real-valued stochastic processes defined on the respective spaces. Furthermore, assume $(Y_t)$ is a Markov process. My question is the following:

Suppose $P_1\circ X_t^{-1}=P_2\circ Y_t^{-1}$ as measures on $\mathbb{R}$. Must $(X_t)$ be a Markov process?

-

No, that both processes have the same one-dimensional marginals is not sufficient. In contrary, when $X$ is an arbitrary elliptic Itô-process, you can always find a Markov process with the same marginals. Cf. I. Gyöngy, Mimicking the One-Dimensional Marginal Distributions of Processes Having an Itô Differential. Probab.Theory Relat.Fields 71(4), 501–516 (1986)
@Stozek: I do not know if I understand your question right, but if $X$ and $Y$ have the same finite dimensional marginals, the define by Kolmogorov's extension theorem the same process... –  Stephan Sturm May 22 '12 at 15:39