Stock price prediction using geometric Brownian motion

W. Farida Agustini, Ika Restu Affianti, Endah R.M. Putri

Research output: Contribution to journalConference articlepeer-review

32 Citations (Scopus)

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%.

Original languageEnglish
Article number012047
JournalJournal of Physics: Conference Series
Volume974
Issue number1
DOIs
Publication statusPublished - 22 Mar 2018
Event3rd International Conference on Mathematics: Pure, Applied and Computation, ICoMPAC 2017 - Surabaya, Indonesia
Duration: 1 Nov 20171 Nov 2017

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