重大突发公共事件的形象情绪会影响股市表现吗?来自深度学习技术的新见解

Yun Liu, Dengshi Huang, Jianan Zhou, Sirui Wang
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摘要

本研究利用深度学习分析 COVID-19 图像情感,揭示了其对股市动态的重大影响。它强调了生动的图像如何引发明显的情绪反应,从而改变市场表现,以及新闻情绪如何调节这种影响。此外,研究还强调了论坛投资者情绪的关键作用,尤其是在股市低迷和交易周开始时对小盘股和大盘股的影响。这项研究不仅促进了对行为金融学的理解,还为管理和监管策略提供了参考。
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Does image sentiment of major public emergency affect the stock market performance? New insight from deep learning techniques
Leveraging deep learning to analyse COVID‐19 image sentiment, this study reveals its significant impact on stock market dynamics. It highlights how vivid imagery prompts marked emotional responses, altering market performance and how news sentiment can modulate this effect. Further, it underscores the pivotal role of forum‐based investor sentiment, particularly affecting small‐minus‐big stocks during downturns and trading week commencements. This research not only advances behavioural finance understanding but also informs management and regulatory strategies.
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