Open AccessForecasting the Financial Times Stock Exchange Bursa Malaysia Kuala Lumpur Composite Index Using Geometric Brownian Motion
Author(s) -
Teoh Yeong Kin,
Sharizal Hasan,
Nashni Hamdan
Publication year - 2018
Publication title -
journal of computing research and innovation
Language(s) - English
Resource type - Journals
ISSN - 2600-8793
DOI - 10.24191/jcrinn.v2i1.29
Subject(s) - kuala lumpur , stock exchange , composite index , econometrics , index (typography) , geometric brownian motion , brownian motion , stock market index , mathematics , statistics , economics , stock market , financial economics , business , geography , computer science , finance , economy , marketing , context (archaeology) , archaeology , diffusion process , world wide web , service (business)
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 tomake decisions involving their investments. Until now, there have been a lot of investors who faced losses due tomaking wrong investments at wrong times. The objective of this study is to forecast FBMKLCI for a one-monthperiod using differentperiods of data. Besides, this study finds the suitable length of period when the forecastedvalues are the most accurate for FBMKLCI. Geometric Brownian motion (GBM) of stochastic calculus is used topredict the future indices. The results showed that the forecasted FBMKLCI needed 1 to 20 weeks of input datato come out with the best values. The forecasted FBMKLCI will only be accurate within 4 weeks; after that thevalues will diverge. Since the average value of MAPE for eight different forecasted valuesis 1.54%, GBM can beused to predict the future FBMKLCI.