30 citations · 88 across the 10 of their papers we have counts for
10 papers
Inference via the Skewness-Kurtosis Set
Chris A. J. Klaassen, Bert van Es
Kurtosis minus squared skewness is bounded from below by 1, but for unimodal distributions this parameter is bounded by 189/125. In some applications it is natural to compare distr…
Deconvolution for an atomic distribution: rates of convergence
Shota Gugushvili, Bert van Es, Peter Spreij
Let be i.i.d.\ copies of a random variable where and and are independent and have the same distribution as and respecti…
Nonparametric methods for volatility density estimation
Bert van Es, Peter Spreij, Harry van Zanten
Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and re…
Multivariate Nonparametric Volatility Density Estimation
Bert van Es, Peter Spreij
We consider a continuous-time stochastic volatility model. The model contains a stationary volatility process, the multivariate density of the finite dimensional distributions of w…
Asymptotic normality of the deconvolution kernel density estimator under the vanishing error variance
Shota Gugushvili, Bert van Es
Let be i.i.d. observations, where and the 's and 's are independent. Assume that the 's are unobservable and that they have the density …
Weak convergence of the supremum distance for supersmooth kernel deconvolution
Bert van Es, Shota Gugushvili
We derive the asymptotic distribution of the supremum distance of the deconvolution kernel density estimator to its expectation for certain supersmooth deconvolution problems. It t…
Combining kernel estimators in the uniform deconvolution problem
Bert van Es
We construct a density estimator and an estimator of the distribution function in the uniform deconvolution model. The estimators are based on inversion formulas and kernel estimat…
Nonparametric volatility density estimation for discrete time models
Bert van Es, Peter Spreij, Harry van Zanten
We consider discrete time models for asset prices with a stationary volatility process. We aim at estimating the multivariate density of this process at a set of consecutive time i…
Estimating a structural distribution function by grouping
Bert van Es, Stamatis Kolios
By the method of Poissonization we confirm some existing results concerning consistent estimation of the structural distribution function in the situation of a large number of rare…
Nonparametric Volatility Density Estimation
Bert van Es, Peter Spreij, Harry van Zanten
We consider two kinds of stochastic volatility models. Both kinds of models contain a stationary volatility process, the density of which, at a fixed instant in time, we aim to est…