  We define a new multivariate time series model by generalizing the ARMAX
process in a multivariate way. We give conditions on stationarity and analyze
local dependence and domains of attraction. As a consequence of the obtained
result, we derive a new method of construction of multivariate extreme value
copulas. We characterize the extremal dependence by computing the multivariate
extremal index and bivariate upper tail dependence coefficients. An estimation
procedure for the multivariate extremal index shall be presented. We also
address the marginal estimation and propose a new estimator for the ARMAX
autoregressive parameter.
