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Solving the COVID Challenge with Natural Language Processing

Wednesday, February 24, 2021
1 hour

The COVID-19 pandemic and subsequent economic lockdown have impacted firms around the world. Many executives of publicly traded firms have dedicated time on earnings calls to discuss the impact and strategies that firms are employing to address COVID-19 challenges. Some firms have chosen to amend the ‘Risk Disclosures’ and ‘Management Discussions & Analysis (MD&A)’ sections of their regulatory filings. Join us for a webinar as Victor Li from team QES (Quant, Economics & Strategy) at Wolfe Research, the winner of the S&P Global Marketplace Hackathon, discusses how they categorized S&P 500 stocks by their response to the pandemic and further identified the most opportunistic and riskiest companies and sectors associated with COVID-19.

During this webinar, you will learn how Wolfe Research:

  • Leveraged S&P Global’s leading alternative textual and financial data, coupled with state-of-the-art Natural Language Processing algorithms (e.g. large-scale pretrained language model FinBERT), to conduct an extensive study to identify companies’ response to the impact of the COVID-19 pandemic including a two-phase approach utilizing dimension shortlisting and cluster recognition.
  • Identified and shortlisted 11 metrics incorporating data from the MD&A, risk disclosure, earnings calls’ question/answers sections, as well as fundamental metrics such as changes in credit, profitability, liquidity, leverage, and analyst sentiment, to provide a 360-degree company perspective of COVID-19 response.
  • Utilized 11 of these features to identify clusters of companies that thrived or succumbed during the COVID-19 crisis through the implementation of a robust DBSCAN algorithm to categorize the behavior pattern of firms pre and post COVID-19.
  • Accessed data via Snowflake at fast speed, along with using pre-built queries from the S&P Global Marketplace, to conduct the analysis and develop interactive data visualization charts.


S&P Global Contributor
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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