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Twitter and stock returns

Forbergskog, Jens-Otto; Blom, Christer Ryland
Master thesis
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http://hdl.handle.net/11250/94935
Issue date
2014-02-19
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  • Master of Science [835]
Abstract
In this thesis, we investigate whether the sentiment of tweets mentioning stock

tickers can be used to predict stock performance. In particular we test for leading

and lagged relationships between the percentage of positive and/or negative

tweets and the returns of the S&P 500 index. We obtain a longitudinal data set of

all tweets mentioning stock tickers over a four-month period amounting to

2,599,277 tweets distributed over 84 trading days. We use daily measures for

positive and negative sentiment to generate our explanatory variables. Our results

indicate that an increase in the percentage of positive tweets predicts increased

stock performance the following day whereas an increase in the percentage of

emotional tweets predicts a reduction in stock returns after two and three days. An

increase in the percentage of negative tweets may predict a reduction in stock

returns.
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Masteroppgave(MSc) in Master of Science in Business, Finance - Handelshøyskolen BI, 2014

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