Analysing And Forecasting Share Price Index In Malaysia - Nur Afiqah Mohamed Hafiz; Norizarina Ishak; Ahmad Fadly Nurullah Rasedee (American Scientific Publishers, 2024)
Wilkie investment model is a stochastic investment model that was built by Wilkie in 1984 and wasupdated in 1995. The model building objective is forecasting. Box-Jenkins method was the basicstructure of Wilkie model. It involves various type of forecasting model. Some model handle station-ary time series such as autoregressive moving average (ARMA) model while some of them handlenon-stationary time series such as autoregressiveintegrated moving average (ARIMA) model. Thereare four sub-models in the Wilkie model which is retail price index model, share dividend yieldmodel, share dividend index model and Consols yield model. In this paper, the Wilkie share pricemodel [4] was apply to Malaysia data in analysing and forecasting FTSE Bursa Malaysia KLCI shareprice index for 36 month ahead from November 2015 to October 2018. Monthly historical data fromJanuary 1996 to October 2015 are use as the base. We use ARIMA model to forecast the shareprice index in Malaysia. ARIMA(0,1,2) model was chosen as the best fit forecasting model. Throughforecasting, we are able to evaluate the performance of the share price index in Malaysia.