Abstract
Investing in stocks is a popular type of investment today. During the current COVID-19 pandemic, the shares of companies in the pharmaceutical sub-sector are becoming more attractive. Stock price movements determine whether investors will increase their investment in a company or withdraw their money. To minimize the risk of investor loss, forecasting is carried out on the daily closing of stock prices. Forecasting is the best method to predict future stock prices Geometric Brownian motion is a method used to predict time series data, where random variables follow Brownian motion. In this study, simulation and analysis of stock returns and fluctuations (volatility) of 5 companies from the basic industry and chemical sector (Basic Industry & Chemicals), pharmaceutical sub-sector on the IDX will be carried out. The five companies are PT Darya-Varia Laboratoria Tbk (DVLA), PT Indofarma (Persero) Tbk (INAF), PT Kimia Farma (Persero) Tbk (KAEF), PT Kalbe Farma Tbk (KLBF), and PT Industri Jamu and Pharmaceutical Sido. Muncul Tbk (SIDO). After the Kolmogorov-Smirnov normalization test, the stocks that meet the normal distribution are KLBF and SIDO. Then the predicted MAPE value of the two stocks is calculated. The MAPE values for KLBF at 100 iterations, 1000 iterations and 10000 iterations were 2.1073%, 1.4382% and 1.2847%.. MAPE values for SIDO at 100 iterations, 1000 iterations and 10000 iterations are 2.0136%, 2.2568%, and 2.0677%.