COVID-19 impact on NASDAQ earnings through an AI lens

COVID-19 impact on NASDAQ earnings through an AI lens

This article studies COVID-19 impact by looking at how company earnings changed in the wake of COVID-19. This article uses concepts from financial statement analysis and machine learning to derive insights. I first present my methodology and findings followed by a deep-dive into modelling.

“The lens we chose transforms the way we look at things” — Dewitt Jones

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Increased availability of data, higher computing power, and availability of easily implementable AI frameworks ushered in an era of AI resurgence between the Great Recession and now. This gives us the ability to analyze the recession post COVID-19 in ways we could not in 2008.

This article studies COVID-19 impact by looking at how company earnings changed in the wake of COVID-19. Specifically it uses machine learning to predict the key factors behind a NASDAQ-listed company’s earnings declining by more than 10% YoY in Q2FY20.

This article uses concepts from financial statement analysis and machine learning to derive insights. I first present my methodology and findings followed by a deep-dive into modelling. This is intended to be used more as a framework for analysis than as a piece of research deriving specific insights. Grab a coffee, sit-back and enjoy!

Contents

  1. Summary
  2. Key drivers + Select deep-dives
  3. Company modelling example: Salesforce
  4. Modelling deep-dive
  5. Further background reading
  6. Concluding thoughts

machine-learning covid19 financial-statements data-science ai

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