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 …

stochastic volatility. Estimation of the model delivers measures of daily variation outperforming their non …When analysing the volatility related to high frequency financial data, mostly non-parametric approaches based on …

variable selection, LASSO estimation of threshold autoregressive models, high dimensional stochastic regression with latent …-memory stochastic volatility models, testing for independence between functional time series, statistical inference for panel dynamic … of conditional quantiles in nonlinear time series models, quasi-likelihood estimation of a threshold diffusion process …

1989-2003. We identify the currency components of the mean and the volatility processes of exchange rates using the recent …

An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear log … index by univariate and multivariate long-memory stochastic volatility models.<P> Forthcoming in <I>Econometric Reviews</I>. …

In this paper we compare the predictive abilility of Stochastic Volatility (SV)models to that of volatility forecasts … implied by option prices. We develop anSV model with implied volatility as an exogeneous var able in the varianceequation … stochastic shocks incorporated in the SVXmodels. The out-of-sample volatility forecasts are evaluated against dailysquared …

estimation for models with high-dimensional state vectors, and overcomes a bias-variance trade-off encountered by other sampling …

process, at present this is not the case for the Heston stochastic volatility model, where the variance is modelled as a …

considered for themodelling of economic time series. The focus of this paper is on thesimultaneous estimation of parameters …