Crises in financial markets affect humans worldwide. Detailed market data on trading decisions reflect some of the complex human behavior that has led to these crises. We suggest that massive new data sources resulting from human interaction with the Internet may offer a new perspective on the behavior of market participants in periods of large market movements. By analyzing changes in Google query volumes for search terms related to finance, we find patterns that may be interpreted as “early warning signs” of stock market moves. Our results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior.
The increasing volumes of ‘big data’ reflecting various aspects of our everyday activities represent a vital new opportunity for scientists to address fundamental questions about the complex world we inhabit1, 2, 3, 4, 5, 6, 7. Financial markets are a prime target for such quantitative investigations8, 9. Movements in the markets exert immense impacts on personal fortunes and geopolitical events, generating considerable scientific attention to this subject10, 11, 12, 13, 14, 15, 16, 17, 18, 19. For example, a range of recent studies have focused on modeling financial markets20, 21, 22, 23, 24, 25and on performing network analyses26, 27, 28, 29.
At their core, financial trading data sets reflect the myriad of decisions taken by market participants. According to Herbert Simon, actors begin their decision making processes by attempting to gather information30. In today's world, information gathering often consists of searching online sources. Recently, the search engine Google has begun to provide access to aggregated information on the volume of queries for different search terms and how these volumes change over time, via the publicly available service Google Trends. In the present study, we investigate the intriguing possibility of analyzing search query data from Google Trends to provide new insights into the information gathering process that precedes the trading decisions recorded in the stock market data.
A recent investigation has shown that the number of clicks on search results stemming from a given country correlates with the amount of investment in that country31. Further studies exploiting the temporal dimension of Google Trends data have demonstrated that changes in query volumes for selected search terms mirror changes in current numbers of influenza cases32 and current volumes of stock market transactions33. This demonstration of a link between stock market transaction volume and search volume has also been replicated using Yahoo! data34. Choi and Varian35 have shown that data from Google Trends can be linked to current values of various economic indicators, including automobile sales, unemployment claims, travel destination planning and consumer confidence. A very recent study has shown that Internet users from countries with a higher per capita GDP are more likely to search for information about years in the future than years in the past36.
Here, we suggest that within the time period we investigate, Google Trends data did not only reflect the current state of the stock markets33 but may have also been able to anticipate certain future trends. Our findings are consistent with the intriguing proposal that notable drops in the financial market are preceded by periods of investor concern. In such periods, investors may search for more information about the market, before eventually deciding to buy or sell. Our results suggest that, following this logic, during the period 2004 to 2011 Google Trends search query volumes for certain terms could have been used in the construction of profitable trading strategies.