Forecasting stock price in Healthcare sector by using Geometric Brownian Motion model / Muhammad Afiq Mukhriz Shahruzain, Muhammad Nur Hazwan Zulfemi and Puteri Nurul Atiqah Muhamad Nor

• Main Authors: Shahruzain, Muhammad Afiq Mukhriz, Zulfemi, Muhammad Nur Hazwan, Muhamad Nor, Puteri Nurul Atiqah
• Format: Student Project
• Language: English
• Published: 2023
• Subjects: Mathematical statistics. Probabilities
• Online Access: https://ir.uitm.edu.my/id/eprint/83535/1/83535.pdf; https://ir.uitm.edu.my/id/eprint/83535/

This study suggests using Geometric Brownian Motion (GBM) model to forecast closing prices for 10 stocks in Healthcare sector in Bursa Malaysia. The forecasted close prices can be used as a reference for investors to make their investments. Investments is a process of investing money for profit. However, selecting the right stock to invest in can be challenging, and the lack of certainty surrounding stock prices can reduce investor trust. Thus, forecasting future stock prices is so crucial. Since all investors want to make profit quickly, the duration of this study are 2 weeks forecast and 4 weeks forecast only. In this study, GBM model which consists of rate of return, drift and volatility are used to forecast the future stock price. The result shows that GBM model able to forecast accurately as early as 2 weeks of investment by using Mean Absolute Percentage Error (MAPE) and percentage increment of stock price. Moreover, this study also shows that KOSSAN is the best stock by using relationship measurement, Sharpe’s and Treynor’s index. These methods are used to gauge the relationship and performance of the stock price with the FBMKLCI index.