Abstract
We present empirical evidence that collective investor behavior can be inferred from large-scale Wikipedia search data for individual-level stocks. Using Shannon transfer entropy, a model-free measure that considers any kind of statistical dependence between time series, we investigate the statistical information transfer between daily Wikipedia searches and stock returns for a sample of 447 stocks and all trading days from 2008 to 2017. We entertain a hypothetical trading strategy based on Wikipedia search momentum that maps our findings to average portfolio returns. Results are in line with the notion of investor sentiment and the trading patterns of retail investors.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
