Man v. Machine: Who Analyzes Information Faster?

Who do YOU think will win?

That information functions as currency is no surprise to anyone in this day and age.  What may be surprising are the lengths that people go to collect the raw data, turn it into actionable nuggets of information, and disseminate it.

Two recent articles in the New York Times call attention to the way that information has become meaningful and critical in both the business world and the political world.

Both articles, “Computers That Trade on the News” on December 22, 2010 and “Where News Is Power, a Fight to Be Well-Armed,” on January 16, 2011, detail the extent to which information is valued in politics and trading.

The subjects of these articles are also a study in contrasts.  As junior political aides parse the news and pull out the most useful and relevant insights and ammunition for the day’s politicking, the computers of Wall Street are humming away, using advanced algorithms and linguistic-based software to extract meaning from the wealth of unstructured data available online.

Politics has always been a bit old fashioned, but the divide between how Wall Street and Washington are utilizing information has never been starker.  In Washington, the day for junior aides and staffers begins early in the morning as they read the news, monitor blogs and social networks, and condense their findings into memos for their superiors.  These information gatherers put in a few hours of data collection and selection, then report to an office for the rest of their day that can stretch well into the evening.

The staffers are valued for their ability to ferret out tidbits of information online that have value.  Describing a media monitor under his supervision, Dan Pfeiffer, White House communications director, stated that, “For such a young guy, Andrew has a great ability to sniff out stories that need to be handled with dispatch. During our biggest fights, from health care to the Supreme Court confirmations, Andrew repeatedly spotted potential problems in the farthest reaches of the Internet before anyone else. That information was essential to our success.”

On Wall Street, a very different picture is playing out.  Traders are using software tools that analyze the massive amount of online unstructured data to extract sentiment around companies, analyze it, and then trade on it, often without human assistance.  The software analyzes words, sentence structure, and emoticons from blogs, company Web sites, editorials, news articles, and social software tools such as Twitter.  If the software detects anything that reflects positively or negatively on a company or a section of the market, then it can trigger automated trading.
According to Aite Groupa, a financial services consulting company, around 35% of quantitative trading firms are currently exploring the use of unstructured data in automated trading.  The trend is not likely to stop there, given the competitive advantage that even a few seconds can give a firm in high frequency trading.

Could Andrew Bates, our talented political aide, sniff out information faster and more accurately than the algorithms of Wall Street?  Short of a face-to-face showdown, it is hard to say.  One thing is for sure though; he would probably appreciate the extra hour of sleep.

Cody Burke is a senior analyst at Basex.

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