Donsker-type functional limit theorems are proved for empirical processes arising from discretely sampled increments of a univariate L\évy process. In the asymptotic regime the sampling frequencies increase to infinity and the limiting object is a Gaussian process that can be obtained from the composition of a Brownian motion with a covariance operator determined by the L\évy measure. The results are applied to derive the asymptotic distribution of natural estimators for the distribution function of the L\évy jump measure. As an application we deduce Kolmogorov-Smirnov type tests and confidence bands.
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