Year: 2024
Type: article
Abstract: Stock prices often experience unpredictable changes, leading to the uncertainty of stock return values. This paper aims to find a mathematical model to predict future stock prices based on past stock price data. One of the models used to predict stock prices is the Brownian Motion Model, which is based on the concept of random movement. The research method used to solve the stock forecasting problem is by using Geometric Brownian Motion by calculating the return value of closing stock prices using Ms. Excel, testing the normality of return value data, modeling stock prices using Geometric Brownian Motion, and calculating the model’s accuracy level using MAPE. Based on the model, the accuracy level using MAPE from the calculation results is obtained with a MAPE value of less than 10%, which is 4,93%. Therefore, it can be concluded that the average error deviation generated indicates a high level of forecasting accuracy.
Authors: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jenderal Soedirman, Jl. Profesor DR. HR Boenyamin No.708, Dukuhbandong, Grendeng, Kec. Purwokerto Utara, Kabupaten Banyumas, Jawa Tengah 53122, Indonesia, Zidni Ilma Nafi’a, Aliffia Yasya Nuraliya, Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jenderal Soedirman, Jl. Profesor DR. HR Boenyamin No.708, Dukuhbandong, Grendeng, Kec. Purwokerto Utara, Kabupaten Banyumas, Jawa Tengah 53122, Indonesia, Gilang Axtria Mukti, Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jenderal Soedirman, Jl. Profesor DR. HR Boenyamin No.708, Dukuhbandong, Grendeng, Kec. Purwokerto Utara, Kabupaten Banyumas, Jawa Tengah 53122, Indonesia, Iqbal Ramadhanu Trenggono, Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jenderal Soedirman, Jl. Profesor DR. HR Boenyamin No.708, Dukuhbandong, Grendeng, Kec. Purwokerto Utara, Kabupaten Banyumas, Jawa Tengah 53122, Indonesia
Institution: Jenderal Soedirman University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4409775999