Textual Sentiment in Finance: A Survey of Methods and Models

46 Pages Posted: 9 Feb 2013 Last revised: 5 Apr 2016

See all articles by Colm Kearney

Colm Kearney

Monash University - Monash Business School

Sha Liu

Southwestern University of Finance and Economics (SWUFE) - School of Finance

Date Written: April 27, 2013

Abstract

We survey the textual sentiment literature, comparing and contrasting the various information sources, content analysis methods, and empirical models that have been used to date. We summarize the important and influential findings about how textual sentiment impacts on individual, firm-level and market-level behavior and performance, and vice versa. We point to what is agreed and what remains controversial. Promising directions for future research are emerging from the availability of more accurate and efficient sentiment measures resulting from increasingly sophisticated textual content analysis coupled with more extensive field-specific dictionaries. This is enabling more wide-ranging studies that use increasingly sophisticated models to help us better understand behavioral finance patterns across individuals, institutions and markets.

Keywords: Behavioral finance, textual sentiment, internet messages, news, market efficiency

JEL Classification: D80, D82, G02, G10, G12, G14, G30, G34, G38, M41

Suggested Citation

Kearney, Colm and Liu, Sha, Textual Sentiment in Finance: A Survey of Methods and Models (April 27, 2013). International Review of Financial Analysis, Vol. 33, 2014, Available at SSRN: https://ssrn.com/abstract=2213801 or http://dx.doi.org/10.2139/ssrn.2213801

Colm Kearney (Contact Author)

Monash University - Monash Business School ( email )

Sir John Monash Drive
Caulfield
Melbourne, Victoria 3168
Australia
+353399031021 (Phone)

Sha Liu

Southwestern University of Finance and Economics (SWUFE) - School of Finance ( email )

Chengdu, 610074
China

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