RT Journal Article SR Electronic T1 Big Data, Small Pickings: Predicting the Stock Market with Google Trends JF The Journal of Index Investing FD Institutional Investor Journals SP 75 OP 82 DO 10.3905/jii.2017.7.4.075 VO 7 IS 4 A1 Wai Mun Fong YR 2017 UL https://pm-research.com/content/7/4/75.abstract AB Big data such as Google Trends has stimulated much interest in the use of search query volumes for predicting social, business, and financial market trends. A recent paper by Preis, Moat, and Stanley [2013] claimed that a simple trading strategy using the Google Trends keyword debt powerfully predicts the Dow Jones Industrial Average stock index one week ahead and outperforms the buy-and-hold strategy by a factor of 20. Using the same sample period used by Preis, Moat, and Stanley, we show that debt completely loses its predictive power once look-ahead bias is eliminated. We find a similar result with a more recent sample period, from 2011 to 2016. Search terms that do outperform the buy-and-hold strategy generally have no economic meaning and are most likely spurious.TOPICS: Big data/machine learning, performance measurement