Hadoop -- Enabling Expanded Financial Market Analysis Techniques while Improving Investment Performance
by Hadoop_Summit on Jul 10, 2013
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Financial market analysis has traditionally utilized structured data. Furthermore financial market participants have normally segregated themselves into two main camps; fundamental analysis (ie income ...
Financial market analysis has traditionally utilized structured data. Furthermore financial market participants have normally segregated themselves into two main camps; fundamental analysis (ie income statements, accounting information, business strategy, etc.) and technical analysis (ie asset prices, traded volume, market-related data, etc.). Unstructured data, meaning everything from news to press releases to interviews, was left to individual interpretation or ignored. Underperformance of hedge funds and the implosion of investment banks have accelerated the search for new innovative approaches. Big data and Hadoop will be at the core of financial market innovation going forward. Hadoop?s ability to consolidate multi-structured data in a scalable and easily accessible way will turn the advent of big data from a threat to an opportunity. The silo-ed analytical approaches are being replaced by a multi-factor approach based on multi-structured data. The focus of the session will be on big data as the catalyst for change within the financial market community, Hadoop as the enabler, and multiple successful applications of this form of analysis in the financial markets.
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