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 …

relationship and the interactions on price and volatility, with special focus on the covolatility spillover effects for these two … volatility or covolatility in another asset, between the energy and agricultural industries is the primary emphasis of the paper … sought to find a relationship among commodity prices. Only a few published papers have been concerned with volatility …

's subsequent volatility in both spot and futures markets. Financial derivatives, which are not only highly representative of the … futures. The purpose of the paper is to investigate the co-volatility spillovers within and across the US energy and financial … sectors in both spot and futures markets, by using "generated regressors" and a multivariate conditional volatility model …

The primary purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility … spillovers between international crude oil and associated financial markets. The paper investigates co-volatility spillovers … (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility …

volatility of carbon emissions, it is not surprising that crude oil and coal have recently become a very important research topic … causality and volatility spillovers in spot and futures prices of carbon emissions, crude oil, and coal. A likelihood ratio test … is developed to test the multivariate conditional volatility Diagonal BEKK model, which has valid regularity conditions …

In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean …(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable … Stochastic Volatility (SV)model. However, efficient Monte Carlo simulationmethods for SV models have been developed to overcome …

improved volatility measurements but has also inspired research into their potential value as an information source for … volatility forecasting. In this paper we explore the forecasting value of historical volatility (extracted from daily return … series), of implied volatility (extracted from option pricing data) and of realised volatility (computed as the sum of …

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this … paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility …, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model …

improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source … for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … conjunction with a variety of volatility models for returns on the Standard & Poor's 100 stock index. We consider two so …