We provide a formulation of stochastic volatility (SV) based on Gaussian process regression (GPR). Forecasting … clearly outperforms SV and GARCH benchmarks, especially at long horizons. Most importantly, our approach enables the … reduces the error rate on one-year out-of-sample forecasting during the 2007-09 recession by 26% relative to a benchmark range …

COVID-19 observations and discusses their impact on prior calibration for inference and forecasting purposes. It shows that … volatility. For forecasting, the choice among outlier-robust error structures is less important, however, when a large cross …

for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … the intraday volatility measure. For forecasting horizons ranging from one day to one week the most accurate out …

forecasting volatility model with the most appropriate error distribution. The results suggest the presence of leverage effect … validate this result. The last twenty eight days out-of-sample forecast adjudged Power-GARCH (1, 1, 1) in student's t error … forecasting model that could guarantee a sound policy decisions. …

estimates lead in turn to substantial gains for forecasting various risk measures at horizons ranging from a few days to a few …

Using well-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is …

In this paper, we present a brief description of multivariate GARCH models. Usually, their parameter estimates are …

In this paper, we present a brief description of multivariate GARCH models. Usually, their parameter estimates are …

Efficient posterior simulators for two GARCH models with generalized hyperbolic disturbances are presented. The first … model, GHt-GARCH, is a threshold GARCH with a skewed and heavy-tailed error distribution; in this model, the latent … variables that account for skewness and heavy tails are identically and independently distributed. The second model, ODLV-GARCH …