Sains Malaysiana 43(10)(2014): 1609–1622


Application of the Threshold Model for Modelling and Forecasting of

Exchange Rate in Selected ASEAN Countries

(Aplikasi Model Ambang untuk Permodelan dan Peramalan Kadar Pertukaran di Negara ASEAN Terpilih)



Faculty of Economics and Management, Universiti Kebangsaan Malaysia,

43600 Bangi, Selangor, Malaysia


Received: 27 February 2013/Accepted: 13 February 2014



Linear time series models are not able to capture the behaviour of many financial time series, as in the cases of exchange rates and stock market data. Some phenomena, such as volatility and structural breaks in time series data, cannot be modelled implicitly using linear time series models. Therefore, nonlinear time series models are typically designed to accommodate for such nonlinear features. In the present study, a nonlinearity test and a structural change test are used to detect the nonlinearity and the break date in three ASEAN currencies, namely the Indonesian Rupiah (IDR), the Malaysian Ringgit (MYR) and the Thai Baht (THB). The study finds that the null hypothesis of linearity is rejected and evidence of structural breaks exist in the exchange rates series. Therefore, the decision to use the self-exciting threshold autoregressive (SETAR) model in the present study is justified. The results showed that the SETAR model, as a regime switching model, can explain abrupt changes in a time series. To evaluate the prediction performance of SETAR model, an Autoregressive Integrated Moving Average (ARIMA) model used as a benchmark. In order to increase the accuracy of prediction, both models are combined with an exponential generalised autoregressive conditional heteroscedasticity (EGARCH) model. The prediction results showed that the construct model of SETAR-EGARCH performs better than that of the ARIMA model and the combined ARIMA and EGARCH model. The results indicated that nonlinear models give better fitting than linear models.


Keywords: EGARCH; exchange rate; nonlinearity; SETAR




Model siri masa linear tidak mampu menghuraikan tingkah laku kebanyakan data siri masa pasaran tukaran asing dan pasaran saham. Fenomena seperti kemeruapan dan perubahan struktur dalam data kadar pertukaran tidak dapat dipadankan dengan baik menggunakan model siri masa linear. Justeru, model tak linear diperlukan bagi mengambil kira ciri-ciri ketaklinearan. Dalam kajian ini, ujian ketaklinearan dan perubahan struktur digunakan bagi mengesan kewujudan kedua-dua ciri tersebut menggunakan data kadar pertukaran bagi tiga negara ASEAN terpilih, iaitu Indonesia Rupiah, Ringgit Malaysia dan Baht Thailand. Kajian ini mendapati bahawa hipotesis nol kelinearan ditolak dan bukti pecah struktur wujud dalam siri kadar pertukaran. Oleh itu, keputusan untuk menggunakan model sendiri-rangsang ambang autoregresi (SETAR) dalam kajian ini adalah dibenarkan. Kajian menunjukkan bahawa model SETAR, sebagai model pensuisan rejim, dapat menjelaskan perubahan mendadak dalam siri masa. Untuk menilai prestasi ramalan model SETAR, satu model autoregresi bersepadu purata bergerak (ARIMA) digunakan sebagai penanda aras. Dalam usaha untuk meningkatkan ketepatan ramalan, kedua-dua model digabungkan dengan eksponen model am autoregresi heteroskedastisiti bersyarat (EGARCH). Keputusan ramalan menunjukkan bahawa model konstruk daripada SETAR-EGARCH adalah lebih baik daripada model ARIMA serta gabungan model ARIMA dan EGARCH. Keputusan menunjukkan bahawa model tak linear memberi pemasangan lebih baik daripada model linear.


Kata kunci: EGARCH; kadar pertukaran; ketaklinearan; SETAR



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