analysis leads to exclude the presence of multifractality, we provide evidence supporting the conclusion that the …

components, stochastic shocks, Markov-switching and multifractality. Forecasts are evaluated by means of Mean Squared Errors (MSE …

In this study, the performance of the Multifractal Model of Asset Returns (MMAR) was examined for stock index returns … of four emerging markets. The MMAR, which takes into account stylized facts of financial time series, such as long memory … consists of two sections. In the first section, we estimated the parameters of GARCH, EGARCH, FIGARCH, MRS-GARCH and MMAR for …

In this study, the performance of the Multifractal Model of Asset Returns (MMAR) was examined for stock index returns … of four emerging markets. The MMAR, which takes into account stylized facts of financial time series, such as long memory … consists of two sections. In the first section, we estimated the parameters of GARCH, EGARCH, FIGARCH, MRS-GARCH and MMAR for …

long term rates are closer to the GBM's neutral persistence. The simulations of the identified MMAR are compared with the … wavelet scalograms, we demonstrate that the MMAR outperforms both the GBM and GARCH(1,1) in time-frequency comparisons, in … the empirical distributions in snapshot and over time-scale (frequency) analyses. The simulated MMAR can replicate all …

prices are compared. The former is the Multifractal Model of Asset Return (MMAR) introduced in 1997 by Mandelbrot, Calvet and …

the commonly used models, such as the Brownian motion, the Mutifractal Model of Asset Return (MMAR) takes into account … extension of multifractality towards stochastic processes, introducing the crucial concept of local H\"older exponent of a … Deviation Theory, suggesting possible ways in order to estimate the quantities involved. Finally in Section 6 the MMAR is …