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Webinar Replays

Natural Language Processing - Stock Selection Insights from Corporate Earnings Calls

March 27, 2019
1 Hour

Natural Language Processing: Stock Selection Insights from Corporate Earnings Calls

Interest continues to grow in harnessing unstructured data to identify differentiated sources of alpha. During this webinar, our speakers will explore a number of sentiment- and behavioral-based signals that have historically demonstrated stock selection power.

Topics will include:

  • A review of natural language processing (NLP) fundamentals, including the importance of dictionary selection
  • Analysis of stock selection using sentiment- and behavioral-based signals from earnings call transcripts
  • The potential for faster analysis of historical data through the addition of metadata tagging to unstructured, textual data
  • How the integration of unstructured sources of data with traditional data sets can produce in-depth analysis
  • Examples of flexible delivery options to receive alternative data sources
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S&P Global Contributor
Frank is a key member of S&P Global Market Intelligence’s Quantamental Research group. Full Bio
S&P Global Contributor
Michael Patton is a senior director within Data Management Solutions global product management team at S&P Global Market Intelligence, overseeing various quantitative datasets, including its Global Earnings Estimates, Ownership, Transactions and Transcripts business.  Full Bio

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This webinar is now available on-demand. Access Now!