The Random Forest Model for analyzing and Forecasting the US Stock Market under the background of smart finance

DOI

10.2991/978-94-6463-419-8_11How to use a DOI?

Keywords

Prediction of stock price trend; Random forest; Artificial intelligence; Smart finance

Abstract

As an important part of the financial market, The stock market plays a crucial role in wealth accumulation for investors, financing costs for listed companies, and the stable development of the national macroeconomy. Consequently, significant fluctuations in the stock market will not only damage the interests of stock investors, but also cause the imbalance of the industrial structure, which will interfere with the development of the national economy on the macro level. As a result, the prediction of stock price trend has become a hot research topic in the academic circles. Therefore, the prediction of three movement trends of stock price trend, namely, rising, sideways and falling, is more helpful for stock investors to make choices among all decision-making behaviors, namely, buying, holding and selling stocks. Given this context, establishing an effective forecasting model for these three stock price trends is of substantial practical importance to establish an effective forecasting model for the prediction of the three movement trends of stock prices. In this paper, the stock price trend of the financial market under the background of smart finance is predicted by model, and the stock price trend of the United States is predicted by random forest model through the combination of artificial intelligence, deep learning and other fields. [1]Moreover, the test set of three stocks is used to test the prediction effect of the model under the optimal parameters of the random forest models combined with artificial intelligence. Based on the modeling and forecasting process, the corresponding time consumption is recorded.Therefore, the prediction performance of the model is evaluated comprehensively by using the prediction effect and time consuming of the model.

Copyright

© 2024 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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TY  - CONF
AU  - Jiajian Zheng
AU  - Duan Xin
AU  - Qishuo Cheng
AU  - Miao Tian
AU  - Le Yang
PY  - 2024
DA  - 2024/05/07
TI  - The Random Forest Model for analyzing and Forecasting the US Stock Market under the background of smart finance
BT  - Proceedings of the 3rd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2024)
PB  - Atlantis Press
SP  - 82
EP  - 90
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-419-8_11
DO  - 10.2991/978-94-6463-419-8_11
ID  - Zheng2024
ER  -