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We estimate linear functionals in the classical deconvolution problem by kernel estimators. We obtain a uniform central limit theorem with √ n–rate on the assumption that the smoothness of the functionals is larger than the ill–posedness of the problem, which is given by the polynomial decay rate of the characteristic function of the error. The limit(More)
Confidence intervals and joint confidence sets are constructed for the nonparametric calibration of exponential Lévy models based on prices of European options. This is done by showing joint asymptotic normality for the estimation of the volatility, the drift, the intensity and the Lévy density at finitely many points in the spectral calibration method.(More)
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