...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Industrial management & data systems >New tool for stock investment risk management Trend forecasting based on individual investor behavior
【24h】

New tool for stock investment risk management Trend forecasting based on individual investor behavior

机译：基于个人投资者行为的股票投资风险管理趋势预测新工具

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Purpose The purpose of this paper is to propose a new tool for stock investment risk management through studying stocks with what kind of characteristics can be predicted by individual investor behavior. Design/methodology/approach Based on comment data of individual stock from the Snowball, a thermal optimal path method is employed to analyze the lead-lag relationship between investor attention (IA) and the stock price. And machine learning algorithms, including SVM and BP neural network, are used to predict the prices of certain kind of stock. Findings It turns out that the lead-lag relationships between IA and the stock price change dynamically. Forecasting based on investor behavior is more accurate only when the IA of the stock is stably leading its price change most of the time.Originality/value This paper is one of the first few research works that introduce individual investor data into portfolio risk management. The new tool put forward in this study can capture the dynamic interplay between IA and stock price change, which help investors identify and control the risk of their portfolios.
机译：目的本文的目的是通过学习股票来提出股票投资风险管理的新工具，通过学习各种投资者行为可以预测有什么样的特征。设计/方法/方法基于来自雪球的个别股票数据的评论数据，采用热最佳路径方法来分析投资者关注（IA）与股价之间的引导滞后关系。和机器学习算法，包括SVM和BP神经网络，用于预测某种股票的价格。调查结果证明，IA之间的引导滞后关系和股票价格动态变化。仅根据投资者行为的预测只有当股票的IA大部分时间都稳定地引领其价格变化时更准确。更多的人，本文是将个人投资者数据引入投资组合风险管理的最初几个研究工作之一。本研究提出的新工具可以捕捉IA与股票价格变动之间的动态相互作用，帮助投资者识别和控制其投资组合的风险。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号