New Academic Research: ECB predicts stock market using social data

The European Central Bank just released a research report that might be of some interest to readers of this blog. It turns out that Social Data can be useful in predicting the stock market (go figure!):

Quantifying the effects of online bullishness on international financial markets [ECB]

…In our work, we develop a simple, direct and unambiguous indicator of online investor sentiment, which is based on Twitter updates and Google search queries. We examine the predictive power of this new investor bullishness indicator for international stock markets. Our results indicate several striking regularities. First, changes in Twitter bullishness predict changes in Google bullishness, indicating that Twitter information precedes Google queries. Second, Twitter and Google bullishness are positively correlated to investor sentiment and lead established investor sentiment surveys. The former, in particular, is a more powerful predictor of changes in sentiment in the stock market than the latter. Third, we observe that high Twitter bullishness predicts increases in stock returns…

The paper contains lots of concepts that should be familiar to long-time readers, including the use of social data sources such as Twitter and Google Trends to trade the stock market, but the paper presents a fresh perspective on the subject, even testing that Twitter sentiment seems to lead Google Trends data using a causality test.

Yet more evidence from the community at large that there is still a great deal of edge to be had from including social datasets in your analysis of the market.

Want to learn how to mine social data sources like Google Trends, StockTwits, Twitter, and Estimize?

Make sure to download our book Intro to Social Data for Traders

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Screenshot from SliceMatrix

Screenshot from SliceMatrix

Lead image licensed from atbaker under CC BY-SA 2.0

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