Doe the publicly available news allow to refine ESG ratings in order to create better hedged portfolios against climate change news?

  • Grégoire de SAUVAGE VERCOUR

Student thesis: Master typesMaster in Business Engineering Professional focus in Data Science


Engle et al. (2019) developed an approach to construct portfolios hedged against the climate change news. Their approach is based on ESG ratings, but these scores are criticised among other things for their lack of transparency. In this paper, we therefore decide to use Data Science through techniques such as word embedding or Sentiment Analysis in order to refine these ratings on the basis of scraped ESG related news. We then adapt the methodology of Engle et al. (2019) by integrating our refined score in attempt to improve the portfolio hedging against climate risk. The hedging of the two approaches are similar, so our methodology does not allow for better results, but this work lays the foundation for further research.
Date of Award26 Aug 2022
Original languageEnglish
Awarding Institution
  • University of Namur
SupervisorSophie Bereau (Supervisor)

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