dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model … volatility forecasting of stock returns and exchange rates. …

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset … predictive performance relative to the standard volatility models. Furthermore, we construct volatility timing portfolios and …

volatility for estimating conditional variances and covariances; (2) alternative currencies; and (3) alternative maturities of … Chang et al. [17], we estimate four multivariate volatility models (namely CCC, VARMA-AGARCH, DCC and BEKK), and calculate …

volatility predictor, the results of an application to tactical asset allocation are presented. -- Multivariate GARCH ; forecast …

price volatility. To address this issue, we find a phenomenon, "momentum of jumps" (MoJ), that the predictive ability of the … jump component is persistent when forecasting the oil futures market volatility. Specifically, we propose a strategy that … according to their recent past forecasting performance. The volatility data are based on the intraday prices of West Texas …

formulate a volatility forecast of returns used as an input for determining some subjective views to be included in the Black …