Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 26, 20 December 2023
Open
Access | Article
Research of future Uber stocks trend using ARIMA model
* Author to whom correspondence should be addressed.
Abstract
The primary focus of this article is on Uber Technologies Inc (Uber) and aims to provide an in-depth forecast of Uber's future stock price. The article introduces Uber company from various dimensions, including Uber's unique business model, leveraging on the sharing economy, enable individuals to use personal vehicles as a means of generating income. This article will be built around the ARIMA model, which is employs this robust model to generate forecasts that offer insights into Uber's stock performance. Before the forecasting process the article will comprehensively describe the data selection process and offer a clear explanation of how the ARIMA model works including the equations. To enhance the effectiveness and reliability of the prediction results, In this article, data visualization is used to present different data representations. The predicted results are presented in the form of graphs and charts, to make a more visual representation of the data and to present and interpret the prediction results effectively.
Keywords
Uber, stock prices, forecasting, ARIMA model.
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-235-0
- ISBN (Online)
- 978-1-83558-236-7
- Published Date
- 20 December 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/26/20241025
- Copyright
- 20 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited