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W Farida Agustini1, Ika Restu Affianti1 and Endah RM Putri1
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Journal of Physics: Conference Series,Volume 974,International Conference on Mathematics: Pure, Applied and Computation 1 November 2017, Surabaya, Indonesia Citation W Farida Agustini et al 2018 J. Phys.: Conf. Ser. 974 012047 DOI 10.1088/1742-6596/974/1/012047
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Author e-mails
agustini.farida54@gmail.com
Author affiliations
1 Department of Mathematics, Faculty of Mathematics and Science, Institut Teknologi Sepuluh Nopember (ITS), Jl. Arief Rahman Hakim, Surabaya 60111 Indonesia
1742-6596/974/1/012047
Abstract
Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.
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