Apama Partners with Dow Jones: CEP Applied to Elementized News in Financial Trading

from the Apama blog

What is “elementized news?” Dow Jones has added XML tags to their electronically distributed news stories that describe the semantics, or sentiment, of the news. The tags describe things like: is positive news? Negative? Earnings up? Earnings Down? Better than analysts estimates? Worse? And so on. Since trading began, news of economic and business trends have impacted behaviour; but, until now, it has been difficult to automate decisions based on news while it occurs because state of the art, until now, has been to publish news information in an “unstructured” way – that is, in a human-readable form.

This is important for algorithmic trading because elementized news feeds allow computers to:
* Trap each news item event, as it hits the wire

* Based on the tag elements, understand the semantics (e.g., positive earnings, negative analyst rating) of the news item

* Correlate the news to other news, or to trading activity

* Make automated decisions on this event, in the context other news and real-time trading activity

* Automate real-time advisory for human traders as a means to relate overall market sentiment in reaction to news, or to predict future market sentiment.

Complex event processing (CEP) engines are the underlying technology platform that enables effective elementized news feed processing. Announcement

Elementized News example, and a use case.

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