Data Dump: World's First Hedge Fund Based on Twitter Trends Opens

Investment success has historically been based on what are sometimes called 'information asymmetries.' This is a polite way of referring to either knowledge gained legally through painstaking research and interpretation - or through illegally paying for insider information. The recent trial of billionaire New York hedge fund manager Raj Rajaratnam was about the latter. Stories about investors like Warren Buffett and George Soros are generally about the former. The business of risk arbitrage, in which securities are traded based on assumptions about market movements is a perfectly legal info asymmetry game.

Opening a hedge fund to invest on data that conveys knowledge which may be converted into wisdom about how financial markets may move is squarely within the legal investment tradition. However, it presumes a very significant - and questionable 'truth' - that Twitter data are, in fact, a leading indicator of market performance. One must assume that the academics retained to build the statistical model on which trading will be based have done extensive 'back casting' analysis using data several years old to see if their approach correctly predicted 'future' price swings (eg, price movements that occurred after the data they were using was generated but prior to the present day).

One might argue that the economy does not yet have enough experience to conduct this analysis with any reasonable expectation of validation. But hey, things are moving fast and if they get there first, there is a lot of money to be made.

Another way of looking at it is that this is a leading indicator of how much uninvested cash is sitting on the sidelines anxious to be put to work. Savvy investors might look at THAT and conclude that lots of dumb investments are going to be made so maybe they should either be selling them to the gullible or betting against them in the market. Either way, one may safely conclude that this has already occurred to Goldman Sachs...

Derek Thompson reports in The Atlantic:

"This week, Derwent Capital Markets, a London investment firm, launched a $40 million hedge fund that will use 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 email. With Twitter, he added, investors finally had a window to the world's fear.

Why would experienced investors cede their expertise to something as crude as Twitter for guiding tens of millions of dollars in bets? Hawtin won't share how his algorithm works. But a team of professors from both sides of the pond have already answered that question for usHOW TWITTER PREDICTS THE STOCK MARKET

If Twitter can predict the public's mood, and the public's mood can predict the stock market, can Twitter predict the stock market?

That's the question researchers at Indiana University and the University of Manchester asked when they set out to measure Twitter's forecast of stock fluctuations. The professors harvested tweets for key words and plugged them into an algorithm to determine the mood of the broader market. Using this mood index, the professors predicted the Dow's daily fluctuations in 2008 with an astounding 87 percent accuracy.

In particular, the professors found that changes in values of "calm" can predict stock market fluctuations, as you'll see in the graph below. In red, the authors produce the "score" of calm moods found in Tweets. In blue, they track Dow changes delayed by three days. Where the two graphs overlap, the calm index predicts the DJIA's closing value three days later.

The red and blue lines often trace each other, suggesting that Tweets can predict the stock market. But there are some alarming divergences. Around the "bank bailout" of October 13, 2008, Twitter calmness was at a year low, but the stock market soared. The authors explain that "the deviation between Calm values and the DJIA on that day illustrates that unexpected news [of a Federal Reserve bank bailout plan] not anticipated by the public mood."

In other words, Twitter can't predict future events. But it just might be able to predict how today's moods impact tomorrow's prices in the absence of shocking, disruptive events.

THE BANK OF TWEETS

Using Twitter to follow the stock is, self-evidently, more than an academic observation. Like following the needle of a barometer to predict rain and sun, investors could theoretically follow moods of the masses to take their portfolios long or short depending on the course they expect to see the markets take, Hawtin said.

"We made the decision to set-up a quantitative Hedge Fund before we came across the academic paper," Hawtin explained when I ask if his investment strategy was inspired by the paper excerpted above. "As soon as I read the academic paper it confirmed my thoughts so I arranged to meet up with Professor Johan Bollen, one of the co-authors."

The $40 million hedge fund's doors have been open for only a few days, but the firm is already targeting an annual return of 15% to 20% for its investors. "We have been testing the system for some time and the results have been outstanding," Hawtin said. If Twitter proves a trustworthy market guide, expect the firm to rake in more social media data from Facebook, Google trends and beyond.

"The greater the range and depth of social media data we can access the better," his email concluded.