挖掘COVID-19情绪和市场表现之间的关系
Ziyuan Xia1, Jeffrey Chen2, Anchen Sun3
1Antai College of Economics & Management, Shanghai Jiao Tong University, Shanghai, China.
PloS one
|July 5, 2024
概括
社交媒体上的公众情绪,特别是关于股票的情绪,与COVID-19大流行期间的股票市场波动有很强的相关性. 我们的情感S) -LSTM模型有效地跟踪了这些不断变化的动态,从流行病到流行病阶段.
科学领域:
- 金融市场是金融市场.
- 计算社会科学 计算社会科学
- 流行病学 流行病学
背景情况:
- 从2020年3月开始,COVID-19大流行导致了前所未有的股票市场波动.
- 了解市场波动的驱动因素对于投资者和政策制定者来说至关重要.
- 通过社交媒体放大公众情绪,可能会影响金融市场.
研究的目的:
- 调查关于COVID-19和股票市场波动的公众情绪之间的关系.
- 为了确定社交媒体情绪是否可以预测大流行阶段的股票市场趋势.
- 为了验证一种新的情绪-LSTM模型来分析情绪-市场动态.
主要方法:
- 使用与流行病相关的关键词对Twitter数据进行自然语言处理和情绪分析.
- 整合专家注释的金融情绪数据.
- 从流行病到流行病阶段的长期社交媒体情绪分析.
- 在时间序列分析中应用情绪 (Sentiment) -LSTM模型.
主要成果:
- 在社交媒体情绪和股票市场波动之间发现了显著的相关性.
- 与股票直接相关的情绪显示出特别强大的预测关系.
- 情绪 (S) -LSTM模型在捕捉不断变化的情绪市场动态方面表现出有效性.
- 流行病,流行病和新常态阶段出现了不同的情绪模式.
结论:
- 特别是社交媒体上的公众情绪是影响股票市场波动的重要因素.
- 情绪 (S) -LSTM模型为公众情绪和金融市场之间的复杂相互作用提供了有价值的见解.
- 监测社交媒体情绪可以为了解健康危机期间和之后的市场行为提供预测能力.
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