structural vector autoregression (TVP-VAR) with stochastic volatility, in both methodology and empirical applications. The TVP …-VAR model, combined with stochastic volatility, enables us to capture possible changes in underlying structure of the economy in … stochastic volatility to the TVP estimation significantly improves estimation performance. The Markov chain Monte Carlo (MCMC …

finite dimensional external factors, thus admitting a stochastic volatility structure. …

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation. In order to simplify the …

In practice, the choice of using a local volatility model or a stochastic volatility model is made according to their … dynamics, against the alternative of a stochastic volatility model. …

This paper proposes a new method for estimating continuous-time stochastic volatility (SV) models for the S&P 500 stock …

This paper proposes a new method for estimating continuous-time stochastic volatility (SV) models for the S&P 500 stock …

index by univariate and multivariate long-memory stochastic volatility models. …