A Picture Is Worth a Thousand Words: Market Sentiment From Photos

59 Pages Posted: 10 Dec 2018 Last revised: 15 Dec 2018

See all articles by Khaled Obaid

Khaled Obaid

University of Missouri at Columbia - Department of Finance

Kuntara Pukthuanthong

University of Missouri, Columbia

Date Written: November 18, 2018

Abstract

This paper proposes a new market-level investor sentiment index (Photo Sentiment) constructed from photos in the financial press. We apply a machine learning technique to classify a large sample of photos in The Economist based on perceived sentiment. Photo Sentiment is measured as the average probability the photos have negative sentiment minus the average probability the photos have positive sentiment. Between 1997 and 2017, Photo Sentiment is found to predict short-term return reversal, trading volume and market volatility, and explains flows between equity and money market funds. A trading strategy based on Photo Sentiment outperforms the market index by 2.6% on an annual basis while assuming less risk.

Keywords: Investor Sentiment, Behavioral Finance, Return Predictability, Machine Learning, Big Data

JEL Classification: C53, G10, G17

Suggested Citation

Obaid, Khaled and Pukthuanthong, Kuntara, A Picture Is Worth a Thousand Words: Market Sentiment From Photos (November 18, 2018). Available at SSRN: https://ssrn.com/abstract=3297930 or http://dx.doi.org/10.2139/ssrn.3297930

Khaled Obaid

University of Missouri at Columbia - Department of Finance ( email )

Columbia, MO 65211
United States

Kuntara Pukthuanthong (Contact Author)

University of Missouri, Columbia ( email )

Robert J. Trulaske, Sr. College of Business
403 Cornell Hall
Columbia, MO 65211
United States
6198076124 (Phone)

HOME PAGE: http://https://kuntara.weebly.com

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