We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse … variances, allows for unbiased convergence diagnostics and for a simple implementation of the estimation on parallel computers …. Finally, we provide all algorithms in the open source software JBendge for the solution and estimation of a general class of …

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 …

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

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 …

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors …