ASEAN-5 Stock Indexes Predictions using Geometric Brownian Motion

Norizarina   Ishak; Norazman  Nordin; Ahmad Nurullah  Rasedee

doi:10.37934/araset.49.2.264277

Authors

Norizarina Ishak Faculty of science and Technology, Universiti Sains Islam Malaysia, 71800 Bandar Baru Nilai, Negeri Sembilan Malaysia
Norazman Nordin Faculty of science and Technology, Universiti Sains Islam Malaysia, 71800 Bandar Baru Nilai, Negeri Sembilan Malaysia
Ahmad Nurullah Rasedee Faculty of Economy and Muamalat, Universiti Sains Islam Malaysia

DOI:

https://doi.org/10.37934/araset.49.2.264277

Keywords:

ASEAN-5, Geometric Brownian motion, mean, volatility, stock market indexes, MAPE, forecasting

Abstract

Even though the ASEAN-5 region has recently experienced enormous economic growth and advancement, this expansion has been associated with increased market volatility. Analysing historical data to assess stock market performance is crucial to comprehending these markets' dynamics and spotting potential hazards and opportunities. This study seeks to determine the mean and volatility parameters of the Geometric Brownian Motion (GBM) model for stock indexes to see trends and patterns in the ASEAN-5 stock market from 2017 to 2022. Once these parameters are determined, they are used in the GBM model to forecast the stock market indexes. Consequently, this research intends to highlight the value of incorporating GBM into stock indexes and assist investors in making short-term price predictions. The geometric Brownian motion involving randomness, volatility, and drift that might aid investors in making sensible investment decisions will be elaborated on in this research.