  Scaling analysis of the magnitude series (volatile series) has been proposed
recently to identify possible nonlinear/multifractal signatures in the given
data [1-3]. In this letter, correlations of volatile series generated from
stationary first-order linear feedback process with Gaussian and non-Gaussian
innovations are investigated. While volatile correlations corresponding to
Gaussian innovations exhibited uncorrelated behavior across all time scales,
those of non-Gaussian innovations showed significant deviation from
uncorrelated behavior even at large time scales. The results presented raise
the intriguing question whether non-Gaussian innovations can be sufficient to
realize long-range volatile correlations.
