This article proposes a simple and intuitive framework to combine a discrete volatility forecast series produced by a …-combining binomial trees that capture the distributional properties of the volatility forecasts. Finally, the framework is employed to …

Correlation models, such as Constant Conditional Correlation (CCC) GARCH model or Dynamic Conditional Correlation (DCC … constant correlation tests into correlation models has been proven to be helpful in terms of the improvement of the accuracy of … VaR or ES forecasts. Galeano & Wied (2017) suggested an algorithms for detecting structural breaks in the correlation …

leverage effect and the volatility feedback effect. We stress the importance of distinguishing between realized volatility and … implied volatility, and find that implied volatilities are essential for assessing the volatility feedback effect. The … leverage hypothesis asserts that return shocks lead to changes in conditional volatility, while the volatility feedback effect …

frequency volatilities and correlations ; Dynamic conditional correlation ; Spline-GARCH ; Idiosyncratic volatility ; Long … that characterize long-term correlation patterns. We associate such term behavior with low frequency economic variables … improves the empirical fit of equity correlations in the US and correlation forecasts at long horizons. -- Factor models ; Low …

We propose exible models for multivariate realized volatility dynamics which involve generalizations of the Box … covariance matrix eigenvalues, while for the Box-Cox dynamic correlation (BC-DC) specification the variances are transformed …

This paper analyzes the forecast accuracy of the multivariate realized volatility model introduced by Chiriac and Voev …

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