Technical analysis testing in forecasting Socially Responsible Investment Index in Indonesia Stock Exchange

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This study aims to examine whether the Autoregressive Integrated Moving Average (ARIMA) model is appropriate to be applied in the Indonesia Stock Exchange, especially for the socially resposible investment stocks. For the ARIMA model combines the autoregressive and moving average method, so it is viewed as a useful tool to predict the stock prices. Those methods are frequently used methods to forecast the stock prices. The data used in this study were daily SRI-KEHATI Index during the period of June 8, 2009 to July 17, 2017. The results showed that the daily SRI-KEHATI Index data were not stationary data, thus this data needed to be transformed. The transformation was done by using the first seasonal differencing transformation process. After being transformed, those data became stationary. Furthermore, this study found that ARIMA (3,1,1) was a model, which might be appropriate and fit with the data condition. This method was also relevant to be applied in the Indonesia Stock Exchange in order to forecast the stock prices.

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    • Table 1. Stock transaction value in the Indonesia Stock Exchange during the period 2010–2017
    • Table 2. Result of Augmented Dickey-Fuller (ADF) test
    • Table 3. Result of PAC test
    • Table 4. Result of ARIMA (3,1,1)