In this paper we consider an ergodic diffusion process with jumps whose drift coefficient depends on $\mu$ and volatility coefficient depends on $\sigma$, two unknown parameters. We suppose that the process is discretely observed at the instants (t n i)i=0,...,n with $\Delta$n = sup i=0,...,n--1 (t n i+1 -- t n i) $\rightarrow$ 0. We introduce an estimator of $\theta$ := ($\mu$, $\sigma$), based on a contrast function, which is asymptotically gaussian without requiring any conditions on the rate at which $\Delta$n $\rightarrow$ 0, assuming a finite jump activity. This extends earlier results where a condition on the step discretization was needed (see [13],[28]) or where only the estimation of the drift parameter was considered (see [2]). In general situations, our contrast function is not explicit and in practise one has to resort to some approximation. We propose explicit approximations of the contrast function, such that the estimation of $\theta$ is feasible under the condition that n$\Delta$ k n $\rightarrow$ 0 where k > 0 can be arbitrarily large. This extends the results obtained by Kessler [17] in the case of continuous processes. Efficient drift estimation, efficient volatility estimation,ergodic properties, high frequency data, L{\'e}vy-driven SDE, thresholding methods.

翻译：在本文中,我们考虑的是以跳跃为转移扩散过程,其漂移系数取决于$mu美元,波动系数取决于2个未知参数。我们假设该过程在瞬时(tn i)i=0,...,以$delta$n=sup i=0,...,n-1(tn i+1 -- t n i) rightrow $.我们采用一个估计值$(tta$):=$mu,美元,波动系数取决于美元,两个未知参数。我们假设该过程在瞬时(tn n i) i=0,以美元=0,美元= i) =0,xn,xn,xn,n+1,n+1,n+1,或仅考虑漂移参数的估算值(见[2]。一般情况下,我们的对比函数并不明确,而实际上不得不采用某种近似值。我们建议,在直径的直径直的直径值值值值值值值值值下,xxxxxxxxxxxxxxxxxxxxalalalalalalalalalalalalal 。