摘要
对于股市是否能预测以及股市怎样预测的问题,学术界与金融业界一直有着极大的兴趣。近些年,大数据与人工智能技术开始兴起,机器学习作为人工智能领域的重要技术,在模拟对象的具体特征、处理复杂且大量的数据时有着优秀的表现,这一优点十分适合金融大数据领域的研究,因而受到了学者们的普遍关注。立足于机器学习技术在股市预测这一领域的应用,对已有的研究按照其使用的机器学习算法进行梳理分类,可以分析不同机器学习算法的贡献与局限性,也可以对其后续的发展方向提出展望。
There has been great interest in the academic circle and financial industry on whether and how the stock market could be predicted.In recent years with the emergence of big data and artificial intelligence(AI)technologies,machine learning,an important technology in the field of AI,has presented excellent performance in simulating specific characteristics of objects and handling complex and large amounts of data,an advantage that is very suitable for the research in the field of financial big data,and has thus aroused great interest of researchers.Based on the application of machine learning technology in the field of stock market prediction,this paper makes a study and classification of the existing researches according to the machine learning algorithms used,so as to analyze the advantages and limitations of different algorithms,which could be used to foresee the directions of their future development.
作者
张世杰
ZHANG Shi-jie(School of Finance,Shanghai University of International Business and Economics,Songjiang 201620,Shanghai,China)
出处
《贵阳学院学报（社会科学版）》
2021年第4期43-48,共6页
Journal of Guiyang University:Social Sciences
关键词
金融大数据
机器学习
股市预测
人工智能
financial big data
machine learning
stock market prediction
artificial intelligence
作者简介
张世杰,男,山西晋中人,硕士研究生。主要研究方向:金融工程、量化投资。
