A Picture is Worth a Thousand Words : Measuring Investor Sentiment by Combining Machine Learning and Photos from News

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

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Year of publication:	2020
Authors:	Obaid, Khaled
Other Persons:	Kuntara Pukthuanthong (contributor)
Publisher:	[2020]: [S.l.] : SSRN
Subject:	Künstliche Intelligenz \| Artificial intelligence \| Anlageverhalten \| Behavioural finance

Extent:	1 Online-Ressource (74 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 29, 2020 erstellt
Other identifiers:	10.2139/ssrn.3297930 [DOI]
Classification:	C53 - Forecasting and Other Model Applications ; G10 - General Financial Markets. General ; G17 - Financial Forecasting
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012850689