Research on stock prediction method based on random forest

Yixin Zhong

doi:10.47297/wspceWSP2516-251913.20250901

PDF
Export
Share
Collection
Album

Research on stock prediction method based on random forest

Volume 9, Issue 1

Views: 0 Downloads: 0

Research on stock prediction method based on random forest
Research on stock prediction method based on random forest
College of Mathematics and Information Technology, South China Agricultural University, Guangzhou, Guangdong, 510640
Vol. 9, Issue 1, Pages: 62-67(2025)
Published：27 February 2025
DOI：10.47297/wspceWSP2516-251913.20250901
Accepted：

Scan QR Code

Zhong Yixin.Research on stock prediction method based on random forest[J].Creative Economy,2025,09(01):62-67.
DOI：

Zhong Yixin.Research on stock prediction method based on random forest[J].Creative Economy,2025,09(01):62-67. DOI： 10.47297/wspceWSP2516-251913.20250901.

摘要

Abstract

The complexity and nonlinearity of stock prices have made the study of stock price prediction techniques a significant area of concern in the finance industry. This paper approaches the stock price prediction issue as a categorization challenge

considering the stock's opening

minimum

maximum

trading volume

and daily fluctuation amplitude as key factors. The stock's closing price on the same day is forecasted using logistic regression

support vector machine

decision tree

and random forest algorithms

followed by a comparative analysis of the predictive outcomes from these models. The lattice search is then used to optimize the random forest model. According to the experimental results

the random forest model outperforms the other methods in terms of stock price prediction ability. Following grid search optimization

the model's stability and prediction accuracy are further enhanced.

关键词

Keywords

references

Gao Ziyi . ( 2021 ). Research on Stock Price Trend Prediction Based on Random Forest . Master's Thesis of China University of Political Science and Law .

Daori H , Alharthi M , Alanazi A , et al . ( 2022 ). Predicting Stock Prices Using the Random Forest Classifier . https://www.researchgate.net/publication/365386418_Predicting_Stock_Prices_Using_the_Random_Forest_Classifier https://www.researchgate.net/publication/365386418_Predicting_Stock_Prices_Using_the_Random_Forest_Classifier

Khaidem L , Saha S , Dey S R . ( 2016 ). Predicting the direction of stock market prices using random forest . https://arxiv.org/abs/1605.00003 https://arxiv.org/abs/1605.00003

Wang H , Hao Y . ( 2021 ) Stock Price Trend Prediction Algorithm Based on Technical Index and Random Forest . Modern Computer , 27 ( 27 ): 43 - 47,52 .

Zheng J , Xin D , Cheng Q , et al . ( 2024 ). The Random Forest Model for Analyzing and Forecasting the US Stock Market in the Context of Smart Finance . https://arxiv.org/abs/2402.17194 https://arxiv.org/abs/2402.17194

Zhang H . ( 2022 ) Scenario Analysis for Linear and Logistic Regression . Automation & Instrumentation , 10 : 1 - 4,8 .

Zhang L . ( 2020 ). Stock Market Trend Analysis and Forecasting Based on Support Vector Machine . Master's Thesis of Nanjing University of Posts and Telecommunications .

Liu X , Cui W . ( 2023 ) A decision tree-based classifier for building quantitative strategies . Journal fur die Reine and Angewandte Mathematik , 39 ( 3 ): 339 - 349 .

AI Yu . ( 2020 ). Research on CSI 300 Index Trend Prediction Based on Random Forest Optimization . Master's Thesis of Shandong University .

Alert me when the article has been cited

Submit

No data

Related Author

No data

Related Institution

No data

⁰