For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between … futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers … that the new method based on stochastic volatility models with the asymmetry and long memory outperforms the forecasting …

of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting …

forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …

using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear …

forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …

using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear …

Modeling and forecasting realized volatility is of paramount importance. Previous studies have examined the role of … both the continuous and jump components of volatility in forecasting. This paper considers how to use index level jumps and … cojumps across index constituents for forecasting index level volatility. In combination with the magnitude of past index …

forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation …

forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …

account of them in estimating and forecasting IV. This paper investigates through Monte Carlo simulations the effects of RV … errors on estimating and forecasting IV with RV data. It is found that: (i) neglecting RV errors can lead to serious bias in …