Do Politics-Themed Google Searches Predict Stock Activity?

By Daniel Akst 

Wondering if the market is in for a tumble? If you find yourself Googling a lot of political and financial terms, it may well be.

In the past, trends in Google searching have been shown to predict flu outbreaks, unemployment rates and the success of movies at the box office. There was even evidence that financially oriented searches--of Google and Wikipedia--could predict stock market movements.

The pattern was simple: Before stocks moved lower, there was an uptick in searches of finance-related terms. Now researchers from Boston University and the University of Warwick, in England, are reporting that stepped-up searching for terms relating to politics also points to a lower market.

Building on their previous work, the scientists used the techniques of computational linguistics to group all the words in Wikipedia into topics. Then, using Google Trends, a publicly available service, they determined how often salient keywords within each topic area were searched from 2004 to 2012. The result? Increased searching of finance or political terms predicted falling stocks.

The scientists used their keyword searches to make hypothetical trades based on historical data for the S&P 500 index. For each keyword topic, they bought or sold the index weekly depending on whether searches were rising or falling, comparing their results to a strategy of buying and selling randomly each week. The median return for trading based on a collection of politics keywords was 38% above the random strategy. For business-oriented keywords, it was 28%. "Crucially," the scientists write, "we find no robust link between stock-market moves and search-engine queries for a wide range of further semantic topics."

They also found that the power of Google searches to predict stock market movements has diminished in recent years.

"Quantifying the Semantics of Search Behavior Before Stock Market Moves, " Chester Curme, Tobias Preis, H. Eugene Stanley and Helen Susannah Moat, Proceedings of the National Academy of Sciences (July 28)

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