  We study stochastic differential games of jump diffusions, where the players
have access to inside information. Our approach is based on anticipative
stochastic calculus, white noise, Hida-Malliavin calculus, forward integrals
and the Donsker delta functional. We obtain a characterization of Nash
equilibria of such games in terms of the corresponding Hamiltonians. This is
used to study applications to insider games in finance, specifically optimal
insider consumption and optimal insider portfolio under model uncertainty.
