计算机工程与应用2025，Vol.61Issue(19)：1-11,11.DOI:10.3778/j.issn.1002-8331.2501-0157
基于模型和算法的量化投资方法股票预测研究综述
Review on Stock Prediction Based on Models and Algorithms Within Quantitative Investment Methods
摘要
Abstract
Stock price prediction remains a critical topic in financial research.In recent years,quantitative investment methods have gained prominence for their objectivity,systematic structure,and efficiency.The proliferation of large-scale,multi-source,and heterogeneous data in the era of big data provides a rich foundation for market modeling and decision-making.Effectively integrating multimodal data has become essential for improving prediction accuracy.This paper reviews the theoretical evolution of quantitative investment methods and examines the development of machine learning applica-tions in stock prediction.From the perspectives of data,models,and algorithms,it surveys recent research outcomes,ana-lyzing and comparing differences in methodological innovations and technical implementations.Challenges and limita-tions in current research are discussed,along with a summary of practical insights.Future directions such as multimodal data integration,weak signal mining,transfer learning,and portfolio weight optimization are also explored.关键词
量化投资/股票预测/机器学习/自然语言处理Key words
quantitative investment/stock forecast/machine learning/natural language processing分类
信息技术与安全科学引用本文复制引用
李子煜,张金珠,高青山..基于模型和算法的量化投资方法股票预测研究综述[J].计算机工程与应用,2025,61(19):1-11,11.基金项目
国家重点研发计划项目(2023YFB4503002). （2023YFB4503002）
