Data clustering using Autoregressive Integrated Moving Average (ARIMA) model for Islamic country currency: an econometrics method for Islamic financial engineering

• Main Authors: Abu Bakar, Nashirah, Rosbi, Sofian
• Format: Article
• Language: English
• Published: 2017
• Subjects: HG Finance
• Online Access: http://repo.uum.edu.my/26302/1/IJES%206%206%202017%2022%2031.pdf; http://repo.uum.edu.my/26302/; http://doi.org/10.22161/ijaers.4.7.27
• Institution: Universiti Utara Malaysia

Exchange rate is price of a nation’s currency in terms of another currency. The value of exchange rate is important as one of the indicators to shows the strength of economic condition for particular country. This paper performed data clustering in analyzing the currency exchange rate which is 1 Malaysian Ringgit (MYR) to United States Dollar (USD). The method that is implemented in this study is Autoregressive Integrated Moving Average (ARIMA) model. This study performed stationary analysis, modeling analysis and diagnostics checking. In stationary evaluation process, the integration of order 1, I (1) is validated as stationary variable. The findings show ARIMA (1, 1, 1) is suitable for clustering the data between January 2010 until April 2017.The importance of this findings is to provide economists and researchers understand the dynamic behavior of currency movement. In addition, further study can be implement in evaluating the determinants factors that contributes to the dynamic behavior of currency exchange rate