Predicting Financial Markets with Google Trends and Not so Random Keywords
September 4, 2013 Leave a comment
Predicting Financial Markets with Google Trends and Not so Random Keywords
Damien Challet Ecole Centrale Paris – Laboratory of Mathematics Applied to Systems
Ahmed Bel Hadj Ayed Ecole Centrale Paris – Laboratory of Mathematics Applied to Systems
August 14, 2013
Abstract:
We check the claims that data from Google Trends contain enough data to predict future financial index returns. We first discuss the many subtle (and less subtle) biases that may affect the back-test of a trading strategy, particularly when based on such data. Expectedly, the choice of keywords is crucial: by using an industry-grade back-testing system, we verify that random finance-related keywords do not to contain more exploitable predictive information than random keywords related to illnesses, classic cars and arcade games. We however show that other keywords applied on suitable assets yield robustly profitable strategies, thereby confirming the intuition of Preis et al. (2013)
