Forecasting stock prices and evaluating portfolio of oil and gas companies in Malaysia: a Geometric Brownian Motion mode

Forecasting stock prices is crucial in guiding investors, especially in volatile industries such as oil and gas. This study employs the Geometric Brownian Motion (GBM) model to simulate short-term stock price movements of 30 oil and gas companies listed on Bursa Malaysia. The companies were categorised into five portfolios using Altman Z-scores to reflect financial stability. Historical daily closing prices over two months were analysed and forecast accuracy was validated using Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Mean Absolute Deviation (MAD). The results show that Portfolio 5 achieved the highest projected return of 18.01%, making it the most suitable for investment, while Portfolio 1 recorded a negative return of –7.38%. Forecast accuracy validation further revealed that Portfolio 2 produced the most reliable results with the lowest error values, while Portfolio 5, despite its profitability, exhibited weaker accuracy due to the volatility of certain stocks. These findings demonstrate that the GBM model is an effective tool for short-term forecasting and portfolio evaluation, supporting better riskinformed decision-making in Malaysia’s oil and gas sector.