Stock Price Analysis of Atlassian Corporation Based on Linear Regression

Conference: ICMLCA 2021 - 2nd International Conference on Machine Learning and Computer Application
12/17/2021 - 12/19/2021 at Shenyang, China

Proceedings: ICMLCA 2021

Pages: 5Language: englishTyp: PDF

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Authors:
Wang, Ziheng (School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China)
Yu, Zonghong (School of Engineering, Rensselaer Polytechnic Institute, Troy, USA)
Zhu, Yipeng (Harbin No. 3 High School, Harbin, China)

Abstract:
The rudimental stock price prediction method involves the evaluation of a basic corporation financial level. However, fundamental analysis utilizes simple factors, such as current financial performance and competitive environment, to evaluate the stock value, which excludes considering the true value of a corporation’s stock that needs to be tested through experiments. This paper proposed different simulation models to tackle this issue, which can be utilized to analyze the correlation between the current financial performance and potential future prediction. By obtaining the company's financial performance and conducting linear regression methods along with other statistical tests such as data visualization, auto regression, and two-headed hypothesis test through RStudio, the team generated figures and a regression line to predict the corporation's future stock value. The experimental results demonstrated that the regression line generated a correct and consistent trend with the corporation’s performance. Furthermore, the team note that the stock price predictions run higher than the actual performance due to other external factors that cannot be controlled, such as global and social factors.