Judging the mood of the market is one of the keys to investing in the stock market and while there are all manner of surveys to measure this, they usually involve surveys that are outdated quickly.

Now researchers are working on ways to use news photos to measure investor sentiment.

The idea was developed by University of Missouri researchers earlier this year and it has now been expanded upon by RMIT University in Australia.

The algorithm works by analysing the ‘top lists’ of editorial pictures on stock image website Getty.

Using machine learning, the algorithm produces a daily score based on the types of photos used in global news reports.

Lead author Dr Angel Zhong said investors could use this information to better predict daily stock market returns, based on the mood of investors worldwide.

“You can get a snapshot of global investment mood by looking at the 10 most popular photos, rather than reading hundreds of news articles,” she said.

“This technology could have a huge impact for those wanting to get the feel of the day quickly and accurately.”

Dr Zhong said when people are in a bad mood and facing higher uncertainty, they tend to buy and sell more impulsively and intensively.

“When the photo sentiment measure reflects a bad mood, it predicts a large increase in trading volume,” she said.

“Our study significantly broadens the scope of this tech by investigating how it applies in the international market, across developed and emerging economies.”

Would you be willing to base your investment decisions on what a computer told you was likely to be a good or bad trading day based on its analysis of news photos? Do you think this technique sounds any different to reading tea leaves to predict what the market will do?