We examine the performance of volatility models that incorporate features such as long (short) memory, regime …-t). Second, we perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models … over the alternative volatility models in terms of mean absolute forecast errors and that (iii) forecast combinations …

) with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the … sufficiently many volatility components. In comparison with a Binomial MSM specification [7], results are almost identical. This … distribution is very limited. -- Markov-switching multifractal ; scaling ; return volatility …

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 …

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 …

) with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the … sufficiently many volatility components. In comparison with a Binomial MSM specification [7], results are almost identical. This …

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 …