Sains Malaysiana 41(3)(2012): 371–377

Markov Switching Models for Time Series Data with Dramatic Jumps

(Model Peralihan Markov untuk Data Siri Masa dengan Lompatan Drastik)  

Masoud Yarmohammadi*, Hamidreza Mostafaei & Maryam Safaei

Department of Statistics, Tehran North Branch, Islamic Azal University, Tehran Iran

Received: 10 June 2011 / Accepted: 19 September 2011

ABSTRACT

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.

Keywords: Fluctuations of exchange rate; Markov Switching Autoregressive model; nonlinear times series models

ABSTRAK

  Dalam penyelidikan ini model autoregresi Markov (MS-AR) dan enam pendekatan model siri masa dipertimbangkan.  Model-model ini dibandingkan mengikut  keupayaan mendapatkan siri kadar pertukaran wang  Iran. Siri ini mempunyai lompatan drastik pada awal 2002 yang berlaku serentak dengan perubahan polisi kadar regim pertukaran wang.  Kriteria yang telah kami gunakan adalah berasaskan kepada nilai AIC dan BIC.  Keputusan menujukkan bahawa model MS-AR boleh dikatakan berguna.

Kata kunci: Model autoregrasi peralihan Markov; model siri masa tak linear; naik-turun kadar pertukaran

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*Corresponding author; email: h_mostafaei@iau-tnb.ac.ir