This paper proposes a new class of multivariate volatility model that utilising high-frequency data. We call this model … realized correlations in the DCC-HEAVY model. The new model removes well known asymptotic bias in DCC-GARCH model estimation … and has more desirable asymptotic properties. We also derive a Quasi-maximum likelihood estimation and provide closed …

forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures … correlation MSV model, the conditional/stochastic Wishart autoregressive models, the matrix-exponential MSV model, and the … outperform existing dynamic conditional correlation models for forecasting future covariances. Among the new fMSV models, the …

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

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

the variance matrix. Monte Carlo evidence for parameter estimation based on different small sample sizes is provided. We …

allocation and risk management require estimates of the volatility of these factors. While realized volatility has become a … provide a statistical approach to estimate the volatility of these factors. The efficacy of this approach relative to the use … of models based on squared returns is demonstrated for forecasts of the market volatility and a portfolio allocation …