volatility, since this is precisely the variable that is negotiated. We present then a statistical methodology for the estimation … of the volatility parameter for an asset using methods of the Bayesian approach to statistics. As prior distributions for … volatility parameter, models of the Gamma family and the Standard Levy are assumed. The results obtained using the proposed …

Traditionally volatility is viewed as a measure of variability, or risk, of an underlying asset. However recently … investors began to look at volatility from a different angle. It happened due to emergence of a market for new derivative … instruments - variance swaps. In this paper first we introduse the general idea of the volatility trading using variance swaps …

price volatility in agricultural markets to rise. Rather, fundamental factors are made responsible for this. Therefore, most …

volatility in agricultural markets to rise. Rather, fundamental factors are responsible for this. Therefore, most papers are not …

The paper proposes a general asymmetric multifactor Wishart stochastic volatility (AMWSV) diffusion process which …

volatility models. We propose a continuous timefractionally integrated Wishart stochastic volatility (FIWSV) process. We derive …

Bayesian forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of … volatility components. From a practical point of view, ML also becomes computationally unfeasible for large numbers of components … forecasts which in principle is applicable for any continuous distribution with any number of volatility components. Monte Carlo …