  Asymptotic independence of the components of random vectors is a concept used
in many applications. The standard criteria for checking asymptotic
independence are given in terms of distribution functions (dfs). Dfs are rarely
available in an explicit form, especially in the multivariate case. Often we
are given the form of the density or, via the shape of the data clouds, one can
obtain a good geometric image of the asymptotic shape of the level sets of the
density. This paper establishes a simple sufficient condition for asymptotic
independence for light-tailed densities in terms of this asymptotic shape. This
condition extends Sibuya's classic result on asymptotic independence for
Gaussian densities.
