当代金融研究2026，Vol.9Issue(3)：1-15,15.DOI:10.20092/j.cnki.ddjryj.2026.03.001
机器学习在金融研究中的应用探究
Applications of Machine Learning in Financial Research
摘要
Abstract
As financial markets become increasingly complex and big data technolo-gies are applied more deeply,traditional financial econometric methods,which rely on linear assumptions and focus mainly on structured data,have gradually revealed limitations in supporting precise decision-making.Machine learning,with its ability to autonomously extract data patterns and handle massive amounts of both struc-tured and unstructured data,has emerged as a pivotal force breaking through these limitations.It has enabled transformative advancements across domains such as fi-nancial market forecasting,risk assessment and management,robo-advisory sys-tems,and text mining,evolving from technical applications to paradigm shifts.Building on a systematic review of machine learning applications in finance and alig-ning with fundamental research needs and technological trends,this paper outlines the core principles and innovative directions for integrating machine learning into financial research.It analyzes key challenges at the data,modeling,market,and reg-ulatory levels in current implementations and proposes actionable solutions with both theoretical rigor and practical feasibility.The study aims to provide a forward-looking yet practical framework for deepening financial technology integration,highlighting the inevitable evolution of financial research toward data-driven,preci-sion-oriented,and intelligent approaches powered by machine learning.关键词
机器学习/金融研究/市场预测/风险评估/文本挖掘Key words
Machine Learning/Financial Research/Market Forecasting/Risk As-sessment/Text Mining分类
管理科学引用本文复制引用
曹俊勇,周运弘,高颖琳..机器学习在金融研究中的应用探究[J].当代金融研究,2026,9(3):1-15,15.基金项目
广东省教育厅科技服务乡村振兴重点领域专项"数字普惠金融与乡村振兴:内在机理、动态影响与模式创新"(2022ZDZX4055)阶段性成果 （2022ZDZX4055）
教育部社科司高校思想政治理论课教师研究专项一般项目"知识图谱赋能'习近平新时代中国特色社会主义思想概论'课混合式教学创新与实践研究"(24JDSZK073)阶段性成果. （24JDSZK073）
