Letting F be a Levy measure whose "tail" $F ([-x, x])$ admits an expansion $\sigma_{i\ge 1} a_i/x^\beta$ as $x \rightarrow 0$, we call $\beta_1 > \beta_2 >...$ the successive Blumenthal-Getoor indices, since $\beta_1$ is in this case the usual Blumenthal-Getoor index. This notion may be extended to more general semimartingale. We propose here a method to estimate the $\beta_i$'s and the coefficients $a_i$'s, or rather their extension for semimartingales, when the underlying semimartingale $X$ is observed at discrete times, on fixed time interval. The asymptotic is when the time-lag goes to $0$. It is then possible to construct consistent estimators for $\beta_i$ and $a_i$ for those $i$'s such that $\beta_i > \beta_1 /2$, whereas it is impossible to do so (even when $X$ is a Levy process) for those $i$'s such that $\beta_i < \beta_1 /2$. On the other hand, a central limit theorem for $\beta_1$ is available only when $\beta_i < \beta_1 /2$: consequently, when we can actually consistently estimate some $\beta_i$'s besides $\beta_1$ , then no central limit theorem can hold, and correlatively the rates of convergence become quite slow (although one know them explicitly): so the results have some theoretical interest in the sense that they set up bounds on what is actually possible to achieve, but the practical applications are probably quite thin.
(joint with Yacine Ait-Sahalia)