We propose a mixed frequency stochastic volatility (MFSV) model for the dynamics of intraday asset return volatility …. In order to account for long-memory we separate stochastic daily and intraday volatility patterns by introducing a long …-run component that changes at daily frequency and a short-run component that captures the remaining intraday volatility dynamics. An …

model to be extended with stochastic volatility and heavy tailed disturbances. We develop a flexible estimation method for …

forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures …

This paper generalizes the basic Wishart multivariate stochastic volatility model of Philipov and Glickman (2006) and … process. The model allows for state-dependent (co)variance and correlation levels and state-dependent volatility spillover …-sample fit and the VaR forecasting performance relative to the basic model. -- Multivariate stochastic volatility ; Dynamic …

model to be extended with stochastic volatility and heavy tailed disturbances. We develop a flexible estimation method for …

We use a class of stochastic volatility models with multiple latent factors to investigate the joint dynamics of return …

In an efficient stock market, the returns and their time-dependent volatility are often jointly modeled by stochastic … volatility models (SVMs). Over the last few decades several SVMs have been proposed to adequately capture the defining features … of the relationship between the return and its volatility. Among one of the earliest SVM, Taylor (1982) proposed a …

different frequencies but also due to the preservation of high-frequency features such as time-varying volatility. Temporally … aggregated models misspecify the evolution frequency of the volatility dynamics, resulting in poor volatility timing and worse … mixed-frequency nature of predictors and volatility in predictive regressions …