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 …

allow these to differ from the correlation processes (namely, DCC-type models) are more beneficial than the models that …

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

while adjusting for the volatility risk premium. Relative model performance does not change during the global financial …

This paper proposes a range-based dynamic conditional correlation (DCC) model combined by the return-based DCC model … and the conditional autoregressive range (CARR) model. The substantial gain in efficiency of volatility estimation can …

their occurrence raises correlation and persistence among assets. Our application to 20 Dow Jones stocks, shows that common …

Heteroskedasticity (GARCH) models and neural networks to deliver better volatility predictions than purely econometric models. Despite … matrices of asset returns. To do so, we propose a new model, based on multivariate GARCHs that decompose volatility and … correlation predictions. The volatilities are here forecast using hybrid neural networks while correlations follow a traditional …