Textual sentiment in finance: A survey of methods and models

Colm Kearney and Sha Liu

International Review of Financial Analysis, 2014, vol. 33, issue C, 171-185

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 (search for similar items in EconPapers)
JEL-codes: D80 D82 G02 G10 G12 G14 G30 G34 G38 M41 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (125)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:33:y:2014:i:c:p:171-185

DOI: 10.1016/j.irfa.2014.02.006

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