New research by Zhi Da and Pengjie (Paul) Gao, both assistant professors of finance at the University of Notre Dame, has found that Google's public search data can be used to beat the stock market by as much as 10 percentage points per year. Their award-winning research appears as the lead article in this month’s Journal of Finance.
They measured abnormal search volume - the number of searches for a share's ticker symbol in one week, relative to the number in the previous eight weeks. They found that lots of searches led to share prices rising. A one standard deviation rise in search volume led to shares outperforming by an average of 0.3 percentage points in the following two weeks.
The reason for this is simple. Many searches for a stock is a sign that investors are paying attention to it, which is often a precursor to them buying it. This is consistent with other evidence that Google search data has predictive power.
Zhi Da can be reached at 574-631-0354 or firstname.lastname@example.org
Paul Gao can be reached at 574-631-8048 or email@example.com