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关于股票市场预测近期趋势的系统文献综述。

A systematic literature survey on recent trends in stock market prediction.

作者信息

Balasubramanian Prakash, P Chinthan, Badarudeen Saleena, Sriraman Harini

机构信息

School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India.

School of Mechanical Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India.

出版信息

PeerJ Comput Sci. 2024 Jan 31;10:e1700. doi: 10.7717/peerj-cs.1700. eCollection 2024.

Abstract

Prediction of the stock market is a challenging and time-consuming process. In recent times, various research analysts and organizations have used different tools and techniques to analyze and predict stock price movements. During the early days, investors mainly depend on technical indicators and fundamental parameters for short-term and long-term predictions, whereas nowadays many researchers started adopting artificial intelligence-based methodologies to predict stock price movements. In this article, an exhaustive literature study has been carried out to understand multiple techniques employed for prediction in the field of the financial market. As part of this study, more than hundreds of research articles focused on global indices and stock prices were collected and analyzed from multiple sources. Further, this study helps the researchers and investors to make a collective decision and choose the appropriate model for better profit and investment based on local and global market conditions.

摘要

股票市场预测是一个具有挑战性且耗时的过程。近年来,各类研究分析师和组织运用了不同的工具和技术来分析和预测股价走势。在早期,投资者主要依靠技术指标和基本面参数进行短期和长期预测,而如今许多研究人员开始采用基于人工智能的方法来预测股价走势。在本文中,进行了详尽的文献研究,以了解金融市场领域用于预测的多种技术。作为这项研究的一部分,从多个来源收集并分析了数百篇专注于全球指数和股票价格的研究文章。此外,这项研究有助于研究人员和投资者做出集体决策,并根据本地和全球市场状况选择合适的模型以获取更好的利润和投资。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8834/10909160/7665620d8751/peerj-cs-10-1700-g001.jpg

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