estimator (SSV) and a simple re-weighting scheme to compute the optimal portfolio weights. Beside relying on a fast estimation …

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation.In order to simplify the … comprehension of these estimation methods, the main methods for estimating stochastic volatility are discussed, with focus on their …

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation. In order to simplify the … comprehension of these estimation methods, the main methods for estimating stochastic volatility are discussed, with focus on their …

This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches … conditional on the physical measure of the underlying asset. Via direct series type estimation of the pricing kernel we can derive …

representations using complex valued diffusions, and we also give Cram=E9r-Rao bounds for the estimation error …

We propose marginal integration estimation and testing methods for the coefficients of varying coefficient multivariate … regression model. Asymptotic distribution theory is developed for the estimation method which enjoys the same rate of convergence … as univariate function estimation. For the test statistic, asymptotic normal theory is established. These theoretical …

-Gaussian dependency structures with a small number of parameters. In this paper we develop a novel adaptive estimation technique of the …

Vector Autoregressive Moving Average (VARMA) models. We overcome the estimation issue that arises with this class of models …