Markov switching models for time series data with dramatic jumps - Masoud Yarmohammadi; Hamidreza Mostafaei; Maryam Safaei (Universiti Kebangsaan Malaysia, 2012)
In this research, the Markov switching autoregressive (MS-AR) model and six different time series modeling approaches are considered. These models are compared according to their performance for capturing the Iranian exchange rate series. The series has dramatic jump in early 2002 which coincides with the change in policy of the exchange rate regime. Our criteria are based on the AIC and BIC values. The results indicate that the MS-AR model can be considered as useful model, with the best fit, to evaluate the behaviors of Iran’s exchange rate