Data modeling diagnostics for share price performance of Islamic Bank in Malaysia using Computational Islamic Finance approach

Bank Islam Malaysia Berhad is an institution that offers financing activity that complies with shariah (Islamic law) and its practical application through the development of Islamic economics. The objective of this study is to forecast the performance of share price for Islamic Bank in Malaysia. The method implemented in this study is autoregressive integrated moving average (ARIMA). From the analysis, there are two model of ARIMA that developed which are ARIMA (3,1,3) and ARIMA(3,1,4). The model of ARIMA (3,1,4) show larger value of R-squared and lower absolute value of Akaike info criterion (AIC). In addition, the mean absolute percentage error (MAPE) is 0.85% in ex-post data range. This results indicates ARIMA (3,1,4) is a reliable forecasting model . The findings from this study will help investors to select a better portfolio for their investment decision in order to gain better profits. In addition, the findings of this study also will help economists to understand the future condition of economic scenario in Malaysi