用AI分析中国分析师报告，预测股票涨跌和波动
Analyst Reports and Stock Performance: Evidence from the Chinese Market
- 用定制BERT模型分析中文报告情绪，分正/中/负三类
- 正面情绪报告使超额收益和日内波动上升，负面则推高交易量但降低未来收益
- 正面情绪的影响比负面更显著，适合关注市场情绪的投资者
本文采用自然语言处理技术，从大量中国分析师报告中提取并量化文本信息以预测股票表现。基于包含中文文本的广泛数据集，使用定制化的BERT深度学习模型对报告情绪进行分类（正向、中性、负向）。研究发现，该情绪指标对股票波动率、超额收益和交易量具有预测能力：强烈正向情绪报告会提升超额收益与日内波动率；强烈负向情绪报告虽增加波动率和交易量，但降低未来超额收益。正面情绪的影响幅度大于负面情绪。本研究为中文股市情绪分析及新闻反应的实证文献提供了新证据。
原文摘要 · Abstract (English)
This article applies natural language processing (NLP) to extract and quantify textual information to predict stock performance. Using an extensive dataset of Chinese analyst reports and employing a customized BERT deep learning model for Chinese text, this study categorizes the sentiment of the reports as positive, neutral, or negative. The findings underscore the predictive capacity of this sentiment indicator for stock volatility, excess returns, and trading volume. Specifically, analyst reports with strong positive sentiment will increase excess return and intraday volatility, and vice versa, reports with strong negative sentiment also increase volatility and trading volume, but decrease future excess return. The magnitude of this effect is greater for positive sentiment reports than for negative sentiment reports. This article contributes to the empirical literature on sentiment analysis and the response of the stock market to news in the Chinese stock market.
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