Title: Quantifying macroeconomic expectations in stock markets using Google Trends,
Abstract: Among other macroeconomic indicators, the monthly release of U.S.
unemployment rate figures in the Employment Situation report by the U.S. Bureau
of Labour Statistics gets a lot of media attention and strongly affects the
stock markets. I investigate whether a profitable investment strategy can be
constructed by predicting the likely changes in U.S. unemployment before the
official news release using Google query volumes for related search terms. I
find that massive new data sources of human interaction with the Internet not
only improves U.S. unemployment rate predictability, but can also enhance
market timing of trading strategies when considered jointly with macroeconomic
data. My results illustrate the potential of combining extensive behavioural
data sets with economic data to anticipate investor expectations and stock
market moves.