UK and US researchers analysed changes in the frequency with which 98 terms - including 'revenue', 'unemployment', 'credit' and 'nasdaq' - were Googled between 2004 and 2011.

The results show that spikes in searches tend to precede declines in the markets, suggesting that investors may be trawling the Web for information before selling off. Conversely, the researchers found that drops in interest in financial topics could be used as a signal for market rises.

Using the changes in search volume over the period studied as the basis of a trading strategy investing in the Dow Jones Industrial Average Index could have led to substantial profit for a trader.

In fact, in their paper the team of academics demonstrate that trading on the basis of the number of queries on Google using the keyword 'debt' could have brought in returns of up to 326%.

Susannah Moat, co-author, says: "Analysis of Google Trends data may offer a new perspective on the decision making processes of market participants during periods of large market movements. It's exciting to see that online search data may give us new insight into how humans gather information before making decisions - a process which was previously very difficult to measure."

Previous studies have shown that Twitter chatter can also be used to predict the ups and downs of the markets, with a $25 million hedge fund based on one sentiment algorithm launched in 2011, although it closed down within weeks.

And earlier this week the power of online data to not just predict but to affect the markets was demonstrated when traders were spooked by the Associated Press's Twitter account, which was hacked and used to spread a bogus claim that the White House had been hit by a terrorist attack

You can read the full paper from Moat, of University College London, Tobias Preis, of Warwick Business School, and H Eugene Stanley, of Boston University, here.