@article{Kin_Abu Hasan_Hamdan_2017, place={Arau, Malaysia}, title={Forecasting the Financial Times Stock Exchange Bursa Malaysia Kuala Lumpur Composite Index Using Geometric Brownian Motion}, volume={2}, url={https://jcrinn.com/index.php/jcrinn/article/view/29}, abstractNote={<div><em>In Malaysia, Financial Times Stock Exchange (FTSE) of Bursa Malaysia Kuala Lumpur Composite Index</em></div> <div><em>(FBMKLCI) provides charts, companies’ profile and other market data to help the local and foreign i</em></div> <div><em>nvestors to</em></div> <div><em>make decisions involving their investments. Until now, there have been a lot of investors who faced losses due to</em></div> <div><em>making wrong investments at wrong times. The objective of this study is to forecast FBMKLCI for a one</em></div> <div><em>-</em></div> <div><em>month</em></div> <div><em>period using different</em></div> <div><em>periods of data. Besides, this study finds the suitable length of period when the forecasted</em></div> <div><em>values are the most accurate for FBMKLCI. Geometric Brownian motion (GBM) of stochastic calculus is used to</em></div> <div><em>predict the future indices. The results showed that th</em></div> <div><em>e forecasted FBMKLCI needed 1 to 20 weeks of input data</em></div> <div><em>to come out with the best values. The forecasted FBMKLCI will only be accurate within 4 weeks; after that the</em></div> <div><em>values will diverge. Since the average value of MAPE for eight different forecasted values</em></div> <div><em>is 1.54%, GBM can be</em></div> <div><em>used to predict the future FBMKLCI.</em></div>}, number={1}, journal={Journal of Computing Research and Innovation}, author={Kin, Teoh Yeong and Abu Hasan, Suzanawati and Hamdan, Nashni}, year={2017}, month={Mar.}, pages={45–49} }