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The Search for Alpha: Analyzing Unstructured Data

Researchers and Wall Street firms are analyzing the avalanche of Internet content -- including news feeds, blogs and Twitter posts -- to help improve trading performance.

Finding an edge on Wall Street can be worth millions of dollars. And lately, converting text-based information -- such as news feeds, blogs and Twitter posts -- into machine-readable data is a hot topic in trading circles.

With the exponential increase in Web-based content -- including RSS-based news feeds and social networking sites such as Twitter -- as well as SEC filings, there is an avalanche of unstructured textual data to analyze. "The question is, how can you use it; should you use it?" said Mani Chandy, Simon Ramo Professor of Computer Science at the California Institute of Technology (Caltech) in Pasadena, Calif. Chandy spoke on the topic of "Analyzing Unstructured Real-Time Information for Algorithmic Trading" as part of a panel discussion at the Accelerating Wall Street virtual event in late November sponsored by Wall Street & Technology. [Ed. note: The complete event, which focused on low-latency technology and managing growing data volumes, can be accessed at www.techweb.com/wallstreet-virtual.]

"The challenge is being able to produce some alpha from the news," added panelist David Leinweber, a well-known quant and author of "Nerds on Wall Street: Math, Machines and Wired Markets," as well as the founding director of the Center for Innovative Financial Technology at U.C. Berkeley. "This can be done by filtering and categorizing news and combining it with other quantitative analytics."

It's not clear to what extent hedge funds' and quants' black-box strategies currently trade based on news feeds. According to a 2008 Aite Group report, only 2 percent of firms that employed electronic trading strategies leveraged unstructured data in a machine-readable format. But there have been advances in the past five years in services for analyzing news, blogs and other text-based reports, Caltech's Chandy noted. For example, major news providers Dow Jones and Thomson Reuters offer news products that archive the news and provide machine-readable feeds for use in algorithms.

While Chandy indicated that there are news services that provide structured data that firms can try for free, according to the Aite report, depending on the content required, pricing for a firm can range from $4,000 per month to $60,000 per month for low-latency premium content. Despite the hefty price tag, however, the market for unstructured real-time information is growing.

Aite estimated that global spending on unstructured data for electronic trading will jump from $75 million in 2009 to $115 million in 2010 and to more than $141 million by 2011. As a sign of the demand for integratable unstructured data, German exchange Deutsche Borse in November acquired Need to Know News, a Washington D.C.-based provider of machine-readable news for automated trading engines.

Ivy is Editor-at-Large for Advanced Trading and Wall Street & Technology. Ivy is responsible for writing in-depth feature articles, daily blogs and news articles with a focus on automated trading in the capital markets. As an industry expert, Ivy has reported on a myriad ... View Full Bio

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