Should you fire your stock broker and sign up for Twitter instead? According to some new research, you may be in luck.

The Journal of Computational Sciences is giving more fuel for the fire after revealing a “Twitter Hedge Fund” that used algorithms to track mood changes and trends in messages broadcasted via the social networking service. The findings showed that the algorithm predicted an insanely high rate of accuracy in pegging stocks’ price changes across the day.

“We find an accuracy of 87.6 percent in predicting the daily up and down changes in the closing values of the DJIA and a reduction of the Mean Average Percentage Error by more than 6 percent,” the study says, published by Indiana University (News - Alert) informatics Professor Johan Bollen.

87.6 percent is nothing to joke about. But how does it work?

“Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time. We analyze the text content of daily Twitter feeds by two mood tracking tools, namely OpinionFinder that measures positive vs. negative mood and Google (News - Alert)-Profile of Mood States (GPOMS) that measures mood in terms of 6 dimensions (Calm, Alert, Sure, Vital, Kind, and Happy). We cross-validate the resulting mood time series by comparing their ability to detect the public’s response to the presidential election and Thanksgiving day in 2008. A Granger causality analysis and a Self-Organizing Fuzzy Neural Network are then used to investigate the hypothesis that public mood states, as measured by the OpinionFinder and GPOMS mood time series, are predictive of changes in DJIA closing values,” according to the study.

Basically, societies experience moods which affect their decision making which is then tracked on a larger scale (Twitter) and that data is then compiled and voila! The answer is presented.

However, this is not exact science.

“Correlation does not imply causation” is a phrase used in science and statistics to emphasize that correlation between two variables does not automatically imply that one causes the other. Correlation is, however, necessary for linear causation in the absence of any third and countervailing causative variable. 

In basic terms, correlation can be a hint towards the cause, but not to be-all-end-all.

Regardless, that didn’t stop Paul Hawtin from launching a Twitter-based hedge fund that relies on Twitter to guide its investments.

The world’s first social media-based hedge fund will monitor a selection of tweets in real-time to feel out market sentiment before placing its bets.

“For years, investors have widely accepted that financial markets are driven by fear and greed but we’ve never before had the technology or data to be able to quantify human emotion,” Paul Hawtin, the founder of Derwent Capital Markets, wrote The Atlantic in an e-mail. With Twitter, he added, investors finally had a window to the world’s fear.

The fund stems from the recent research from The Journal of Computational Sciences Sciences.

“If we can predict the market three or four days out, that’s going to be huge,” Bollen told CNBC’s Kate Kelly.

“Everybody was telling me, ‘this is huge, you’re going to be rich,’ and of course I’m not rich,” he said. A moment later, he added, “well, who knows.”

The results are nothing short of “astounding,” according to Hawtin. “From a financial point of view, it’s pretty momentous.”

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