Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)

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Comparison Analysis of Stock Price Prediction Based on Different Machine Learning Methods

Authors
Zhiyuan Jiang1, *, Jiachen Liu2, *, Lixuan Yang3, *
1Statistics and Operations Research Department, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
2Computer Science and Mathematics, Wake Forest University, Winston-Salem, North Carolina, USA
3Asian Institute of Digital Finance, National University of Singapore, Singapore, Singapore
*Corresponding author. Email: Jamesjiang2323@icloud.com
*Corresponding author. Email: 15810144551@163.com
*Corresponding author. Email: e0809369@u.nus.edu
Corresponding Authors
Zhiyuan Jiang, Jiachen Liu, Lixuan Yang
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-198-2_7How to use a DOI?
Keywords
Stock Price Prediction; Machine Learning; Asset Portfolio
Abstract

This paper aims to compare the stock prices trend for industries affected by the pandemic in the post-Covid era. Specifically, the delivery and cardboard box industry are chosen as examples to project future growth in four different Machine Learning Methods. Furthermore, an optimized asset portfolio is constructed based on the asset Efficient Frontier Minimum Volatility Asset in order to provide a more precise projection of the stock prices. After the projection comparison, the Linear Regression Model fails to exhibit a logical trend. In contrast, the remaining three methods, Decision Tree, Random Forest, and Gradient Boosting Models, correspondingly, all show similar results and reasonably project the future growth.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
10 August 2023
ISBN
978-94-6463-198-2
ISSN
2589-4900
DOI
10.2991/978-94-6463-198-2_7How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Zhiyuan Jiang
AU  - Jiachen Liu
AU  - Lixuan Yang
PY  - 2023
DA  - 2023/08/10
TI  - Comparison Analysis of Stock Price Prediction Based on Different Machine Learning Methods
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 59
EP  - 67
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_7
DO  - 10.2991/978-94-6463-198-2_7
ID  - Jiang2023
ER  -