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)
BEHROOZ GHARLEGHI*, ABU HASSAN SHAARI MD NOR
& TAMAT SARMIDI
Faculty of Economics and Management, Universiti
Kebangsaan Malaysia,
43600 Bangi, Selangor, Malaysia
Diserahkan: 27 Februari 2013/Diterima: 13 Februari 2014
ABSTRACT
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
ABSTRAK
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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*Pengarang untuk surat-menyurat; email: gharleghi.bn@gmail.com
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