TY - UNPB

T1 - Mining User-Generated Financial Content to Predict Stock Price Movements

AU - Mastel, Andreas

AU - Jacobs, Jürgen

PY - 2012/12

Y1 - 2012/12

N2 - Sentiment extraction from user-generated online content to predict stock price movements has become an active research field. This paper gives an overview of common approaches to this topic and analyzes the content generated by the financial social network Seekingalpha.com. The first finding is that a large proportion of users’ attention is focused on only a few stocks. Regarding these stocks it can be shown that sentiment is significantly driven by past abnormal performance. Only the sentiment of premium users contains some degree of predictivepower. Generally, the users’ sentiment is consistent with a naïvemomentum mentality.

AB - Sentiment extraction from user-generated online content to predict stock price movements has become an active research field. This paper gives an overview of common approaches to this topic and analyzes the content generated by the financial social network Seekingalpha.com. The first finding is that a large proportion of users’ attention is focused on only a few stocks. Regarding these stocks it can be shown that sentiment is significantly driven by past abnormal performance. Only the sentiment of premium users contains some degree of predictivepower. Generally, the users’ sentiment is consistent with a naïvemomentum mentality.

KW - Informatics

KW - Stock price prediction

KW - event study

KW - sentiment analysis

M3 - Working papers

VL - 22

T3 - FInAL

BT - Mining User-Generated Financial Content to Predict Stock Price Movements

PB - Universität Lüneburg

CY - Lüneburg

ER -