Prediction of stock values changes using sentiment analysis of stock news headlines

IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
L. Nemes, A. Kiss
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引用次数: 31

Abstract

ABSTRACT The prediction and speculation about the values of the stock market especially the values of the worldwide companies are a really interesting and attractive topic. In this article, we cover the topic of the stock value changes and predictions of the stock values using fresh scraped economic news about the companies. We are focussing on the headlines of economic news. We use numerous different tools to the sentiment analysis of the headlines. We consider BERT as the baseline and compare the results with three other tools, VADER, TextBlob, and a Recurrent Neural Network, and compare the sentiment results to the stock changes of the same period. The BERT and RNN were much more accurate, these tools were able to determine the emotional values without neutral sections, in contrast to the other two tools. Comparing these results with the movement of stock market values in the same time periods, we can establish the moment of the change occurred in the stock values with sentiment analysis of economic news headlines. Also we discovered a significant difference between the different models in terms of the effect of emotional values on the change in the value of the stock market by the correlation matrices.
基于股票新闻标题情绪分析的股票价值变动预测
对股票市场价值的预测和猜测,特别是对跨国公司价值的预测和猜测,是一个非常有趣和有吸引力的话题。在这篇文章中,我们将讨论股票价值的变化,并使用有关这些公司的最新经济新闻来预测股票价值。我们关注的是经济新闻的头条。我们使用许多不同的工具来分析头条新闻的情绪。我们将BERT作为基准,并将结果与其他三种工具(VADER, TextBlob和递归神经网络)进行比较,并将情绪结果与同期的股票变化进行比较。BERT和RNN更加准确,与其他两种工具相比,这些工具能够在没有中性部分的情况下确定情绪值。将这些结果与同一时间段内股票市场价值的运动进行比较,我们可以通过对经济新闻标题的情绪分析来确定股票价值发生变化的时刻。通过相关矩阵分析,我们还发现不同模型在情绪价值观对股票市场价值变化的影响方面存在显著差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.50
自引率
0.00%
发文量
18
审稿时长
27 weeks
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