An effective approach for forecasting return volatility via threshold nonlinear heteroskedastic models of the daily … heteroskedasticity, which are commonly observed in financial markets. The focus is on parameter estimation, inference and volatility … supported by the data in terms of finding significant threshold nonlinearity, diagnostic checking and volatility forecast …

structure with GARCH-type dynamics, has been shown to offer a plausible decomposition of the contributions to volatility, as … unexpected return shocks on future volatility is obtained. An empirical out-of-sample study confirms the usefulness of the new …

volatility dynamics modeled as a HAR is augmented by a term involving quarticity in order to correct measurement errors in … accounts for a faster mean reversion when volatility is high. We argue that heteroskedasticity (volatility of volatility) and a …

This paper proposes a parsimonious threshold stochastic volatility (SV) model for financial asset returns. Instead of … imposing a threshold value on the dynamics of the latent volatility process of the SV model, we assume that the innovation of … time-varying volatility of returns, but also can accommodate the asymmetric shape of conditional distribution of the …

. Stochastic volatility models remain outside this review. -- ARCH ; conditional heteroskedasticity ; GARCH; nonlinear GARCH …; volatility modelling …