The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized …. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions … from returns to volatility and co-volatility. …

prices, returns and volatility of related agricultural commodities. Analyzing the spillover effects on agricultural …. The purpose of this paper is to examine the volatility spillovers for spot and futures returns on bio-ethanol and related … agricultural commodities, specifically corn and sugarcane, using the multivariate diagonal BEKK conditional volatility model. The …

using volatility impulse response analysis. The data set features ten years of daily returns series for the New York Stock … independent shocks on volatility through time, while avoiding typical orthogonalization and ordering problems. Volatility impulse … response functions (VIRF) provide information about the impact of independent shocks on volatility. HHś VIRF extends a …

intra-day data. The paper analyses the relationships among the S&P 500 Index and futures prices, returns and volatility of … intra-day temporal aggregation in examining returns relationships and volatility spillovers across the equity and energy … futures markets, and the effects of overnight returns, volume, realized volatility, asymmetry, and spillovers across the four …

relationship between the S&P500 Composite Index and the Volatility Index (VIX), but few empirical studies have focused on the …

Hafner and Herwartz (2006) analysis of multivariate GARCH models using volatility impulse response analysis. We use two sets … of data, daily realized volatility estimates taken from the Oxford Man RV library, running from the beginning of 2000 to …) and the subsequent European Sovereign Debt Crisis (ESDC). The spillover index captures the transmission of volatility to …

relationship between the S&P500 Composite Index and the Volatility Index (VIX), but few empirical studies have focused on the …

One of the most widely-used multivariate conditional volatility models is the dynamic conditional correlation (or DCC … rather than a dynamic conditional correlation model; (ii) provides the motivation, which is presently missing, for … standardization of the conditional covariance model to obtain the conditional correlation model; and (iii) shows that the appropriate …

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 … the stochastic volatility model with asymmetry and long memory, using high frequency data for the underlying asset …