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.
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