悲观
套利
索引(排版)
经济
库存(枪支)
计算机科学
行为经济学
情绪分析
金融经济学
计量经济学
样品(材料)
股票市场
人工智能
微观经济学
历史
哲学
万维网
考古
化学
认识论
背景(考古学)
色谱法
作者
Khaled Obaid,Kuntara Pukthuanthong
标识
DOI:10.1016/j.jfineco.2021.06.002
摘要
By applying machine learning to the accurate and cost-effective classification of photos based on sentiment, we introduce a daily market-level investor sentiment index (Photo Pessimism) obtained from a large sample of news photos. Consistent with behavioral models, Photo Pessimism predicts market return reversals and trading volume. The relation is strongest among stocks with high limits to arbitrage and during periods of elevated fear. We examine whether Photo Pessimism and pessimism embedded in news text act as complements or substitutes for each other in predicting stock returns and find evidence that the two are substitutes.
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