• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE International Conference on Big Data Analytics >Predicting Financial Markets Using The Wisdom of Crowds
【24h】

Predicting Financial Markets Using The Wisdom of Crowds

机译：使用人群智智慧预测金融市场

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In the world of finance, one key lesson is the importance of psychology in the behavior of financial markets. Many investors are irrationally exuberant when making financial decisions, but predictive analytics can generate insights that are free of investors' emotions, and hence human irrational exuberance in decision-making can be mitigated. Data sources that investors adopt in their investment decision-making are, in most cases, traditional - including quarterly earnings reports and financial statements. In this work, we propose a predictive analytics framework that aims at mining insights from two alternative data sources: news articles and micro-blogs. We investigate the predictive correlation and causation between (1) collective opinion mining in news articles fused with Twitter mood and (2) movements in financial markets. Experimental results indicate a relationship between stock market prices and collective opinion mining variations on news articles combined with Twitter's sentiment variations. The framework introduced in this work could potentially be adopted as a supplement to the conventional analyses being used in major investment banks. This research was partially funded by the Australian government under the Awards-Endeavour research grant.
机译：在金融世界中，一个关键课程是心理在金融市场的行为中的重要性。许多投资者在进行财务决策时是不合理的，但预测分析可以产生没有投资者情绪的见解，因此可以减轻人类的非理性令人生意的决策。在大多数情况下，投资者在其投资决策中采取的数据来源是传统的 - 包括季度盈利报告和财务报表。在这项工作中，我们提出了一种预测的分析框架，旨在从两个替代数据来源采矿洞察：新闻文章和微博。我们调查（1）在与Twitter情绪融合的新闻文章中的预测相关性和因果关系与金融市场的动态和（2）流动融合在一起。实验结果表明股票市场价格与集体意见采矿的关系，新闻文章与Twitter的情感变化相结合。本作工作中介绍的框架可能被采用作为主要投资银行所使用的常规分析的补充。该研究部分由澳大利亚政府根据奖项 - 努力研究申请部分资助。

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