An intriguing new paper published in Nature suggests Google Search data can in some cases be correlated to major stock market movements:
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.
The big question is whether this data reflects the market, or predicts it. The authors conclude that within certain limits, collective search behavior predicts collective market movement.
The results of our investigation suggest that combining large behavioral data sets such as financial trading data with data on search query volumes may open up new insights into different stages of large-scale collective decision making. We conclude that these results further illustrate the exciting possibilities offered by new big data sets to advance our understanding of complex collective behavior in our society.
Big Data is jargon, but it stands for new capabilities available not just to sophisticated traders, but forward leaning marketers as well. In businesses where the difference between first place and tenth place can be measured in small points of difference, can you afford not to be the one on the leading edge?