Using Twitter to Predict The Market
Many expert traders claim to know how to predict whether the market will rise or fall at any particualr time. But there are few, if any, who can actually do it consistently better than simply tossing a coin.
For many economists that’s easy to explain. Conventional economic theory (ie, Efficient Market Theory) holds that the movement of prices in a perfect market should follow a random walk and should be impossible to predict with an accuracy greater than 50 per cent.
But the efficient market hypothesis no longer holds water because numerous studies have shown that stock market prices are not entirely random and may very well be tied to mass psychology and related factors. If so there may be a way to gauge the mass consciousness for predictive signs.
Researchers at Indiana University say they’ve found just such a predictor buried in the seemingly endless chatter that emanates from the Twitterverse. (Study results posted at bottom)
“One idea is that the stream of thought is representative of the mental state of humankind at any instant. Various groups have devised algorithms to analyse this datastream hoping to use it to take the temperature of various human states, ” reports MIT Technology Review.
From MIT Technology Review –
One algorithm, called the Google-Profile of Mood States (GPOMS), records the level of six states: happiness, kindness, alertness, sureness, vitality and calmness.
The question that John Bollen and his research team ask is whether any of these states correlates with stock market prices. After all, they say, it is not entirely beyond credence that the rise and fall of stock market prices is influenced by the public mood.
So these guys took 9.7 million tweets posted by 2.7 million tweeters between March and December 2008 and looked for correlations between the GPOMS indices and whether Dow Jones Industrial Average rose of fell each day.
Their extraordinary conclusion is that there really is a correlation between the Dow Jones Industrial Average and one of the GPOMS indices–calmness.
In fact, the calmness index appears to be a good predictor of whether the Dow Jones Industrial Average goes up or down between 2 and 6 days later. “We find an accuracy of 87.6% in predicting the daily up and down changes in the closing values of the Dow Jones Industrial Average,” say Bollen and company.
That’s an incredible result–that a Twitter mood can predict the stock market–but the figures appear to point that way.
