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 …

The volatility specification of the Markov-switching Multifractal (MSM) model is proposed as an alternative mechanism … for realized volatility (RV). We estimate the RV-MSM model via Generalized Method of Moments and perform forecasting by … volatility models of asset returns. An intra-day data set for five major international stock market indices is used to evaluate …

by estimating the intermittency parameter and forecasting of volatility for a sample of financial data from stock and … foreign exchange markets. -- Random Lognormal cascades ; GMM estimation ; best linear forecasting ; volatility of financial …

forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of volatility … which in principle is applicable for any continuous distribution with any number of volatility components. Monte Carlo … linear compared to optimal forecasts is small. Extending the number of volatility components beyond what is feasible with MLE …