latent stochastic processes. We present empirical Bayes methods that enable the efficient shrinkage-based estimation of the …

density of logreturns. Our proposed approach originates from the Bayesian approach to parameter estimation and time series … forecasting, however it is robust in the sense that it provides a more accurate estimation of the predictive density in the region …. This quasi-Bayesian approach yields more precise parameter estimation than a fully censored posterior for all parameters …

density of logreturns. Our proposed approach originates from the Bayesian approach to parameter estimation and time series … forecasting, however it is robust in the sense that it provides a more accurate estimation of the predictive density in the region …. This quasi-Bayesian approach yields more precise parameter estimation than a fully censored posterior for all parameters …

wide range of estimation procedures. A Monte Carlo study is conducted for time-varying parameter models such as generalized …

include stochastic volatility for the observation errors. Our estimation results are based on practical Bayesian state space …