A Picture is Worth a Thousand Words: Measuring Investor Sentiment by Combining Machine Learning and Photos from News
74 Pages Posted: 10 Dec 2018 Last revised: 2 Jul 2020
Date Written: June 29, 2020
By applying machine learning to accurately and cost effectively classify photos based on sentiment, we introduce a daily market-level investor sentiment index (Photo Pessimism) from a large sample of news photos. Between 1926 and 2018, Photo Pessimism predicts market return reversal and increase in trading volume. The predictability pattern is concentrated among stocks with high limits to arbitrage and during high uncertainty periods. Photo Pessimism enhances pessimism embedded in text, but subsumes it during days with traumas and influential photos. Photo Pessimism from business news has over six times stronger predictive power than Photo Pessimism from general news.
Keywords: Investor Sentiment, Behavioral Finance, Return Predictability, Machine Learning, Big Data
JEL Classification: C53, G10, G17
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