This paper proposes a new class of multivariate volatility model that utilising high-frequency data. We call this model …

The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized …. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions … from returns to volatility and co-volatility. …

market volatility …

models. We show that HF-based predictions yield a significantly lower portfolio volatility than methods employing daily …

components and the mixed-sign component load differently on economic information concerning stochastic correlation and jumps. The …

) multivariate volatility models, both in-sample and out-of-sample. We also comment on the possibility to use composite likelihood …

We present a new model to decompose total daily return volatility into a filtered (high-frequency based) open …-to-close volatility and a time-varying scaling factor. We use score-driven dynamics based on fat-tailed distributions to limit the impact …-to-close volatility changes substantially through time, especially for financial stocks. …

Several novel large volatility matrix estimation methods have been developed based on the high-frequency financial data …. They often employ the approximate factor model that leads to a low-rank plus sparse structure for the integrated volatility … matrix and facilitates estimation of large volatility matrices. However, for predicting future volatility matrices, these …