Forecasting the financial times stock exchange Bursa Malaysia Kuala Lumpur Composite Index using Geometric Brownian Motion / Teoh Yeong Kin, Suzanawati Abu Hasan and Nashni Hamdan - Teoh, Yeong Kin; Abu Hasan, Suzanawati; Hamdan, Nashni (UiTM Cawangan Perlis, 2017)
In Malaysia, Financial Times Stock Exchange (FTSE) of Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) provides charts, companies' profile and other market data to help the local and foreign investors to make decisions involving their investments. Until now, there have been a lot of investors who faced losses due to making wrong investments at wrong times. The objective of this study is to forecast FBMKLCI for a one - month period using different periods of data. Besides, this study finds the suitable length of period when the forecasted values are the most accurate for FBMKLCI. Geometric Brownian motion (GBM) of stochastic calculus is used to predict the future indices. The results showed that the forecasted FBMKLCI needed 1 to 20 weeks of input data to come out with the best values. The forecasted FBMKLCI will only be accurate within 4 weeks; after that the values will diverge. Since the average value of MAPE for eight different forecasted values is 1.54%, GBM can be used to predict the future FBMKLCI.