BibTex Citation Data :
@article{J.Gauss8155, author = {Ulfah Sulistyowati and Tarno Tarno and Abdul Hoyyi}, title = {PEMODELAN KURS MATA UANG RUPIAH TERHADAP DOLLAR AMERIKA MENGGUNAKAN METODE GARCH ASIMETRIS}, journal = {Jurnal Gaussian}, volume = {4}, number = {1}, year = {2015}, keywords = {Exchange rate, ARIMA, GARCH, Asymmetric GARCH, volatilty}, abstract = { One factor causing to slowing economic growth in Indonesia is the currency exchange rate. In Indonesia,the exchange rate of the rupiah against the dollar is always become an attention of society. To monitor the movement needed a mathematical model that can be used to forecast the rupiah exchange rate to the dollar. Data rupiah exchange rate against the dollar is a financial time series data has a non-constant volatility. One model that is often used for the prediction of these data is ARIMA-GARCH. In this study discussed about modeling the data rate of the rupiah against the dollar using asymmetric GARCH, such as exponential GARCH (EGARCH), Threshold GARCH (TGARCH) and Autoregressive Power ARCH (APARCH). Modeling the exchange rate against the dollar using all three types of the Asymmetric GARCH models produce the best models, the ARIMA ([4.5], 1, [4,5]) - APARCH (2,1). With the results obtained using the model for volatility forecasting that volatility decreased from the previous forecast but still be at its high volatility. Keywords : Exchange rate, ARIMA, GARCH, Asymmetric GARCH, volatilty }, issn = {2339-2541}, pages = {151--160} doi = {10.14710/j.gauss.4.1.151-160}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/8155} }
Refworks Citation Data :
One factor causing to slowing economic growth in Indonesia is the currency exchange rate. In Indonesia,the exchange rate of the rupiah against the dollar is always become an attention of society. To monitor the movement needed a mathematical model that can be used to forecast the rupiah exchange rate to the dollar. Data rupiah exchange rate against the dollar is a financial time series data has a non-constant volatility. One model that is often used for the prediction of these data is ARIMA-GARCH. In this study discussed about modeling the data rate of the rupiah against the dollar using asymmetric GARCH, such as exponential GARCH (EGARCH), Threshold GARCH (TGARCH) and Autoregressive Power ARCH (APARCH). Modeling the exchange rate against the dollar using all three types of the Asymmetric GARCH models produce the best models, the ARIMA ([4.5], 1, [4,5]) - APARCH (2,1). With the results obtained using the model for volatility forecasting that volatility decreased from the previous forecast but still be at its high volatility.
Keywords : Exchange rate, ARIMA, GARCH, Asymmetric GARCH, volatilty
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