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A Professor Leverages Kensho NERD to Analyze Thousands of Textual Documents for Trading Strategy Development




Technology is transforming the way individuals can translate their insights into market-beating calls that can even outperform those devised by investment professionals.


A professor at this Asia-based university wanted to evaluate how media co-coverage (i.e., where multiple firms are simultaneously mentioned in the same news article) impacts market reactions and stock price movements. He realized that it would be a massive undertaking to identify co-mentioned firms across thousands of textual documents to establish causality, and wanted to see if there was an AI capability that would make this a much easier task.

Our Kensho NERD helped the professor expedite his analysis and uncovered the companies, subsidiaries and other financial organizations, and utilize an API that is research friendly to enable him to load a large volume of textual data and receive output in a speedy and structured manner.



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