May 24, 2011 – You might have missed it: The day when an investment fund started following the crowd, before the crowd starts to move.

That was last Monday – May 16, 2011 – when a boutique investment firm in London started up a fund that will use real-time analysis of investor sentiment as expressed on social media to figure out where fear and greed – human emotion – is about to take capital markets.

Paul Hawtin, founder of the Derwent Capital Markets fund, called this the “fourth dimension” of investing.

And if he gets it right, he expects to be able to generate 15 percent to 20 percent annual returns on his investors’ capital. Because, if you can see the emotion coming, you can get a three or four days head start on trading stocks in its coming wake.

That’s the power of being able to aggregate and mathematically analyze 100 million tweets or other social communications every day.

But the advantage could be short-lived.

It took just one week for another set of mathematicians to release sentiment forecasting to the mass investor.

An Israeli firm, Sentigo, is taking a slightly different approach, but the sentiment, if you will, is the same.

Its Wall Street Scanner software will scans more than 7 million pages of information from news outlets, financial analysts and, yes, Twitter and Facebook, to figure out which way the top 2,000 stocks in America are headed. Tomorrow.

The app is headed onto the Apple iTunes digital file store. It can be downloaded to an iPhone, iPod Touch or iPad. Next: Blackberry and Android machines. The cost: Nothing.

For investors who think their opinion doesn’t matter and the only logical thing to do is follow the herd – before the herd moves – the aggregation of opinion and the mathematical analysis of the same now promises a new form of couch-potato investing.

Don’t worry about which way the market is headed. Just make sure you’ve got the app installed on your machine. And that it’s connected to your own personal execution management system.

Unless the crowd is wrong.

This column originally appeared on Securities Technology Monitor.

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