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The ability to extract insights from market, economic and news-based data depend substantially on the underlying metadata that enables models and analytics to leverage information out of the data stream. Asset managers and hedge funds typically spend USD 1M or more on these data sources, and as such, comprise a relatively large component of their operational expenses.


Notably, the usability of these data sources in the aggregate is typically poor. They cannot efficiently deliver the necessary contexts for portfolio managers to quickly uncover insights into specific situations. As a result, the information vacuum typically spurs the need to acquire yet more data sources, eventually leading to an unusable glut of underutilized and oftentimes, marginal data sources.


ContextStreams™ automatically parses information out of your existing data sources, creates the necessary metadata, and expresses the resulting elements into XML and database-ready structures. The models and analytics in use by portfolio managers, analysts and traders can then access this enriched context-aware information targetted specifically to their unique systems and implied workflows.


We have found that technologies developed for the Semantic Web are better suited to evaluating and handling securities transactions since many of these electronic messages are in practice complex documents. For example, a corporate actions notice for a ReOrg event still contains a significant amount of free-form information (despite the heroic efforts expended by ISO, SWIFT and various industry working groups in promoting messaging standards, rigorous transaction structures, and industry-wide best practices).


The data management framework that enables context-aware usage is driven by an investment management ontology developed by forward look, inc.

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