Publication

This publication examines the performance of volatility models that incorporate features such as long (short) memory, regime-switching and multifractality along with two competing distributional assumptions of the error component, i.e. Normal vs Student-t. The authors introduce a new model to the family of Markov-Switching Multifractal models of asset returns (MSM), namely, the Markov-Switching Multifractal model of asset returns with Student-t innovations (MSM-t). Then, they perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) legacy.