# T:A:L:K:S

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 title: Multilevel Monte Carlo for Levy driven SDEs: The Central Limit Theorem name: Li first name: Sangmeng location/conference: SPP-JT13 PRESENTATION-link: http://www.dfg-spp1324.de/nuhagtools/event_NEW/dateien/SPP-JT13/talks/Li_JT13.pdf abstract: In this talk, we consider multilevel Monte Carlo for the computation of expectations $E[f(Y)]$. Here $\{Y_{t}\}_{t\in[0,T]}$ denotes the solution to a L\'evy-driven stochastic differential equation and $f$ is at least Lipschitz continuous on path space. Approximate solutions are gained via the Euler method from an approximate simulation of the underlying L\'evy process. We establish convergence rates and show a central limit theorem (similar to recent work of Ben Alay \& Kebaier for diffusions). The central limit theorem is based on a proof of stable convergence for the error for two successive levels.