Abstract

http://ssrn.com/abstract=2380419
 


 



Stock Chatter: Using Stock Sentiment to Predict Price Direction


Michael Rechenthin


University of Iowa - Department of Management Sciences

W. Nick Street


University of Iowa - Department of Management Sciences

Padmini Srinivasan


University of Iowa - Department of Management Sciences

2013

Algorithmic Finance 2013, 2:3-4, 169-196

Abstract:     
This paper examines a popular stock message board and finds slight daily predictability using supervised learning algorithms when combining daily sentiment with historical price information. Additionally, with the profit potential in trading stocks, it is of no surprise that a number of popular financial websites are attempting to capture investor sentiment by providing an aggregate of this negative and positive online emotion. We question if the existence of dishonest posters are capitalizing on the popularity of the boards by writing sentiment in line with their trading goals as a means of influencing others, and therefore undermining the purpose of the boards. We exclude these posters to determine if predictability increases, but find no discernible difference.

Number of Pages in PDF File: 29

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Date posted: January 18, 2014  

Suggested Citation

Rechenthin, Michael and Street, W. Nick and Srinivasan, Padmini, Stock Chatter: Using Stock Sentiment to Predict Price Direction (2013). Algorithmic Finance 2013, 2:3-4, 169-196. Available at SSRN: http://ssrn.com/abstract=2380419

Contact Information

Michael Rechenthin (Contact Author)
University of Iowa - Department of Management Sciences ( email )
IA
United States
W. Nick Street
University of Iowa - Department of Management Sciences ( email )
IA
United States
Padmini Srinivasan
University of Iowa - Department of Management Sciences ( email )
IA
United States
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