Abstract: For a symmetric -stable random vector with
and spectral measure we find a necessary and sufficient condition in
terms of for the conditional variance to be finite.
We express the conditional variance in terms of and we develop an additivity
property when are independent. These results are then applied to stable
processes: scale mixtures of Gaussian processes, harmonizable and moving averages.