A recent study in the Journal of Finance by Zhi Da
and Paul Gao
of the University of Notre Dame shows that data from public Google searches can be used to beat the stock market by up to ten percentage points per year. Similar findings were released last month by researchers at the University of Kansas.
The Notre Dame authors argue that the frequency of Google searches received by a stock (its SVI number) is a better, more direct method of measuring investor attention (a precursor to buying the stock) than traditional, indirect methods of measurement, such as news and advertising expense.
To read the entire article visit: Can Google Searches Predict Stock Price Performance?