In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and … indices and foreign exchange rates. -- Stochastic volatility ; Markov chain Monte Carlo ; Metropolis-Hastings algorithm Jump …

variance parameters, and for price inflation series we find strong evidence of changes in persistence. We find little evidence …

relative to a standard no-predictability benchmark, the optimal combination of predictors, stochastic volatility, and time …

volatility models. Overall, we find that our combination scheme produces markedly more accurate predictions than the existing …

We provide a formulation of stochastic volatility (SV) based on Gaussian process regression (GPR). Forecasting … volatility out-of-sample, both simulation and empirical analyses show that our GPR-based stochastic volatility (GPSV) model …

the volatility and persistence of inflation and interest rates occurring over a similar time frame as the volatility …Using Bayesian tests for a structural break at an unknown break date, we search for a volatility reduction within the … real GDP has been less volatile since the early 1980's, and that this volatility reduction is concentrated in the cyclical …

-memory stochastic volatility model. We develop a new Bayesian estimator based on the Markov chain Monte Carlo sampler and the wavelet … joint posterior distribution. Unlike short-memory stochastic volatility models, long-memory stochastic volatility models do … quickly and efficiently from the near independent multivariate distribution of the long-memory volatility's wavelet …

parametric approach utilizing a Stochastic-Volatility-Jump-Diffusion (SVJD) model, estimated with MCMC and extended with Particle … method may be biased in the case when large outlier jumps occur in the time series as well as when the stochastic volatility …