Markov switching and long memory: a Monte Carlo analysis

This article finds the close relationship between long memory and some forms of Markov-switching models. The simulation results suggest: (1) when the transition probabilities are closer to unity, it is more likely to generate long memory process; (2) magnitude of regime-switching plays an important role in generating long memory; and (3) process with switching in variance (disturbance) is much less likely to explain long-memory process than switching in mean (intercept) and autoregressive coefficient. Therefore, given the observed high persistence in financial volatility data, volatility modelling by switching in mean and AR coefficient is preferred to that by switching in variance.