Stock Chatter: Using Stock Sentiment to Predict Price Direction

29 Pages Posted: 18 Jan 2014  

Michael Rechenthin, PhD

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

Date Written: 2013

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.

Suggested Citation

Rechenthin, PhD, 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: https://ssrn.com/abstract=2380419

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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