nonparametric predictor based on the canonical factorization of the spectral density function given in Whittle (1963) and known as … proposed method is semiparametric, in the sense that, in contrast to other methods, we do not need to assume any particular …

-to-construct non-parametric estimators and ii) parametric price duration estimators using autoregressive conditional duration … specifications. We derive the asymptotic properties of our non-parametric estimator with and without the presence of some of the … selecting a threshold parameter that defines a price duration event, or by averaging over a range of non-parametric duration …

We propose a hybrid penalized averaging for combining parametric and non-parametric quantile forecasts when faced with … context. The application offers three main findings. First, combining parametric and non-parametric approaches adds quantile …

This paper considers the estimation of a semi-parametric single-index regression model that allows for nonlinear … stationarity properties of asset returns but also avoids the curse of dimensionality associated with non-parametric regression …

calibration. The proposed Bayesian nonparametric approach takes advantage of the flexibility of Dirichlet process mixtures to …. The weak posterior consistency of the Bayesian nonparametric calibration is provided under suitable conditions for unknown …

calibration. The proposed Bayesian nonparametric approach takes advantage of the flexibility of Dirichlet process mixtures, to …. The weak posterior consistency of the Bayesian nonparametric. calibration is provided under suitable conditions for …