Sains Malaysiana 35(2): 55-62 (2006)


Modelling Exchange Rates Using

Regime Switching Models

(Pemodelan Kadar Tukaran Wang Asing

Menggunakan Model Perubahan Rejim)



Mohd Tahir Ismail & Zaidi Isa

Program Sains Aktuari, Pusat Pengajian Sains Matematik

Fakulti Sains dan Teknologi

Universiti Kebangsaan Malaysia

43600 UKM Bangi, Selangor D.E.





Gelagat siri masa kewangan pada dasarnya tidak boleh dimodelkan hanya dengan menggunakan model siri masa linear sahaja. Fenomena seperti min berbalik, kemeruapan pasaran saham dan perubahan struktur siri masa  tidak boleh dimodelkan secara tersirat di dalam model linear mudah. Untuk itu, model siri masa tidak linear  dibangunkan untuk mengatasi masalah ketidaklinearan yang ditunjukkan oleh data tersebut. Kertas kajian ini telah  mengaplikasikan beberapa ujian “portmanteau” dan perubahan struktur  untuk mengenalpasti tabiat ketidaklinearan  di dalam kadar tukaran wang asing untuk tiga negara di ASEAN   iaitu Malaysia, Singapura dan Thailand.  Didapati bahawa hipotesis nol tentang kelinearan mampu ditolak dan wujudnya bukti bahawa perubahan struktur berlaku untuk ketiga-tiga siri yang dikaji. Untuk itu, penggunaan model perubahan rejim amatlah sesuai untuk kajian ini. Berdasarkan kriteria pemilihan model iaitu AIC, SBC dan HQC, pengkaji membandingkan kesuaian untuk dua bentuk model perubahan rejim iaitu model SETAR (Self-Exciting Threshold Autoregressive) dan model perubahan Markov (MS-AR).  Berdasarkan kepada nilai AIC, SBC dan HQC, didapati bahawa model MS-AR memberikan darjah kesuaian yang lebih baik untuk kesemua siri masa yang dikaji. Sebagai tambahan, mdoel perubahan rejim juga memberikan darjah kesuaian  yang lebih baik berbanding dengan model autoregresi mudah. Keputusan ini menunjukkan bahawa model tidak linear memberikan kesuaian dalam sampel yang lebih baik berbanding dengan model linear.


Kata kunci:  kadar tukaran wang asing; model perubahan rejim; ketidaklinearan; kriteria pemilihan model





The behaviour of many financial time series cannot be modeled  solely by linear time series model. Phenomena such as mean reversion, volatility of stock markets and structural breaks cannot be modelled implicitly using simple linear time series model. Thus, to overcome this problem, nonlinear time series models are typically designed to accommodate these nonlinear features in the data. In this paper, we use portmanteau test and structural change test to detect nonlinear feature in three ASEAN countries exchange rates (Malaysia, Singapore and Thailand). It is found that the null hypothesis of linearity is rejected and there is evidence of structural breaks in the exchange rates series. Therefore, the decision of using regime switching model in this study is justified. Using model selection criteria (AIC, SBC, HQC), we compare the in-sample fitting between two types of regime switching model. The two regime switching models we considered were the Self-Exciting Threshold Autoregressive (SETAR) model and the Markov switching Autoregressive (MS-AR) model where these models can explain the abrupt changes in a time series but differ as how they model the movement between regimes. From the AIC, SBC and HQC values, it is found that the MS -AR  model is the best fitted model for all the return series. In addition, the regime switching model also found to perform better than simple autoregressive model in in-sample fitting. This result justified that nonlinear model give better in-sample fitting than linear model.


Keywords: exchange rates; regime switching model; nonlinearity; model selection criteria





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