Forecasting Tesla’s Stock Price Using the ARIMA Model

Qiangwei Weng; Ruohan Liu; Zheng Tao

doi:10.26689/pbes.v5i5.4331

Qiangwei Weng College of Science and Technology, Wenzhou-Kean University, Wenzhou325000, Zhejiang Province, China
Ruohan Liu College of Science and Technology, Wenzhou-Kean University, Wenzhou325000, Zhejiang Province, China
Zheng Tao Department of Statistics and Data Science, National University of Singapore, 10 Kent Ridge Crescent 119077, Singapore

DOI: https://doi.org/10.26689/pbes.v5i5.4331

Keywords: Stock price forecast, ARIMA model, Naïve method, Tesla

Abstract

The stock market is an important economic information center. The economic benefits generated by stock price prediction have attracted much attention. Although the stock market cannot be predicted accurately, the stock market’s prediction of the trend of stock prices helps in grasping the operation law of the stock market and the influence mechanism on the economy. The autoregressive integrated moving average (ARIMA) model is one of the most widely accepted and used time series forecasting models. Therefore, this paper first compares the return on investment (ROI) of Apple and Tesla, revealing that the ROI of Tesla is much greater than that of Apple, and subsequently focuses on ARIMA model’s prediction on the available time series data, thus concluding that the ARIMA model is better than the Naïve method in predicting the change in Tesla’s stock price trend.