Mark Podolskij (Ruhr-Universitat Bochum)
	Inference for semimartingales in the presence of noise
		We present estimates for some characteristics of semimartingales, such as quadratic variation, in the presence of a general noise process. The core of our approach is the power variation applied to some moving average quantity. We present different "weak laws of large numbers" according to whether the underlying semimartingale is continuous or not. Furthermore, under very weak assumptions on the semimartingale, we prove the associated central limit theorems. All central limit theorems have the rate n^{-1/4} and the limiting variables/processes are mixed normal. The asymptotic results can be transformed into feasible (standard) central limit theorems. This theory can be applied to estimate the integrated volatility, squared jumps or for constructing tests for jumps in the presence of noise.