This study used the discrete-time method to construct the Geometric Brownian motion,
and use the technique to simulate the path of the stock price. The study sample was
based on the most weighted Chinese companies in the CSI 300 index. 50 Companies
were chosen. Daily data were obtained from March 12th, 2022 to March 13th, 2023.The
result shows that the Discrete-Time Geometric Brownian motion can predict the actual
stock price accurately in the short term. As the period of simulation become longer, the
prediction result becomes increasingly inaccurate. Simulations provide support to the validity of the GBM
models after dividing companies into portfolios.