  In this article, we consider a jump diffusion process (X_t), with drift
function b, diffusion coefficient sigma and jump coefficient xi^{2}. This
process is observed at discrete times t=0,Delta,...,nDelta. The sampling
interval Delta tends to 0 and nDelta tends to infinity. We assume that (X_t) is
ergodic, strictly stationary and exponentially beta-mixing. We use a penalized
least-square approach to compute adaptive estimators of the functions
sigma^2+xi^2 and sigma^2. We provide bounds for the risks of the two
estimators.
