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This paper provides conditions under which a non-stationary copula-basedMarkov process is $\beta$-mixing. We introduce, as a particular case, aconvolution-based gaussian Markov process which generalizes the standard randomwalk allowing the increments to be dependent.

$\beta$-mixing and moments properties of a non-stationary copula-based Markov process