of covariates as well as the smoothing parameters via cross-validation. We find that volatility forecastability is much …

forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures …

Recent literature has focuses on realized volatility models to predict financial risk. This paper studies the benefit … volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based … on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility …

forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

ARFIMAX models are applied in estimating the intra-day realized volatility of the CAC40 and DAX30 indices. Volatility … clustering and asymmetry characterize the logarithmic realized volatility of both indices. ARFIMAX model with time … superior next trading day's realized volatility forecasts …

This paper studies predictability of realized volatility of U.S. Treasury futures using high-frequency data for 2-year … to generate systemic under-predictions of future realized volatility. …

Two volatility forecasting evaluation measures are considered; the squared one-day ahead forecast error and its … standardized version. The mean squared forecast error is the widely accepted evaluation function for the realized volatility … standardized with its volatility. The statistical properties of the forecast errors point the standardized version as a more …

We propose exible models for multivariate realized volatility dynamics which involve generalizations of the Box …