Textual sentiment in finance: A survey of methods and models

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.

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Year of publication:	2014
Authors:	Kearney, Colm ; Liu, Sha
Published in:	International Review of Financial Analysis. - Elsevier, ISSN 1057-5219. - Vol. 33.2014, C, p. 171-185
Publisher:	Elsevier
Subject:	Behavioral finance \| Textual sentiment \| Internet messages \| News \| Market efficiency

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Type of publication:	Article
Classification:	D80 - Information and Uncertainty. General ; D82 - Asymmetric and Private Information ; g02 ; G10 - General Financial Markets. General ; G12 - Asset Pricing ; G14 - Information and Market Efficiency; Event Studies ; G30 - Corporate Finance and Governance. General ; G34 - Mergers; Acquisitions; Restructuring; Corporate Governance ; G38 - Government Policy and Regulation ; M41 - Accounting
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010786518