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Using Twitter to Predict the Stock Market

Where is the Mood Effect?

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Abstract

Behavioral finance researchers have shown that the stock market can be driven by emotions of market participants. In a number of recent studies mood levels have been extracted from Social Media applications in order to predict stock returns. The paper tries to replicate these findings by measuring the mood states on Twitter. The sample consists of roughly 100 million tweets that were published in Germany between January, 2011 and November, 2013. In a first analysis, a significant relationship between aggregate Twitter mood states and the stock market is not found. However, further analyses also consider mood contagion by integrating the number of Twitter followers into the analysis. The results show that it is necessary to take into account the spread of mood states among Internet users. Based on the results in the training period, a trading strategy for the German stock market is created. The portfolio increases by up to 36 % within a six-month period after the consideration of transaction costs.

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Notes

  1. Daniel et al. (2002) provide an extensive literature review showing that investors’ psychology exerts an influence on security prices.

  2. https://dev.twitter.com.

  3. See also background mood (Loewenstein et al. 2001).

  4. See Germany Trade & Invest for more information on foreign investors: http://www.gtai.de/GTAI/Navigation/EN/Invest/Service/Publications/Markets-germany/Archive/Issues-2011/Volume-2/Fdi/foreign-investors-put-faith-germanys-stocks.html (accessed 22 June 2014).

  5. More information on VDAX-NEW can be found at the website of the exchange: http://www.dax-indices.com/EN/MediaLibrary/Document/VDAX_L_2_4_e.pdf (accessed 22 June 2014).

  6. Information on GfK index can be found on http://www.gfk.com.

  7. We also calculated SMI and WSMI values without the anger dimension and received qualitatively similar results.

  8. Among others, Antweiler and Frank (2004) report R² value of 0.049; Avery et al. (2009) report R² values between 0.0005 and 0.0151; Das and Chen (2007) report R² value of 0.0027 and 0.0041.

  9. There are several discount brokers who offer their clients cost-effective access to capital markets (e.g., Cortal Consors in Germany). We are aware that € 5 is at the low end of the range. However, these costs are very easy to realize for the individual investor. Nevertheless, the outperformance against the benchmark indices would persist even if we assume € 10 per trade.

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    Michael Nofer &  Oliver Hinz

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Nofer, M., Hinz, O. Using Twitter to Predict the Stock Market. Bus Inf Syst Eng 57, 229–242 (2015). https://doi.org/10.1007/s12599-015-0390-4

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