market, volatility and jump risks, and observation error of time changes. To operationalize the models, we use volume …

estimate complex latent state variable models with unknown parameters. The framework is applied to a stochastic volatility … model with independent jumps in returns and volatility. The implementation is based on a novel design of adapted proposal … algorithm to estimate stochastic volatility with jumps in returns and volatility model based on the Prague stock exchange …

Volatility has been one of the most active and successful areas of research in time series econometrics and economic … empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is … inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then …

This paper proposes a parsimonious threshold stochastic volatility (SV) model for financial asset returns. Instead of … imposing a threshold value on the dynamics of the latent volatility process of the SV model, we assume that the innovation of … time-varying volatility of returns, but also can accommodate the asymmetric shape of conditional distribution of the …