Hedging Climate Change News

• Tech Stack: Python, Web Scraping, Natural Language Processing, Finance Model
• Github URL: Project Link

This is a replication project of the research paper by Engle, R. F. et al.

The research purpose of this paper is to construct a portfolio that can hedge the climate change risk. To achieve this goal, first, the authors extract innovations of climate news series through textual analysis of newspapers and construct a Climate Change News Index. Second, they use this index to construct a proxy for climate change, called CCt, and use E-Score to construct a proxy for climate risk exposure. Finally, using all the variables calculated in the previous steps to select stocks and calculate their weights to form the hedge portfolios. Various approaches to construct such hedge portfolios have been proposed in the literature. The two main ones are cross-sectional regressions like Fama-MacBeth and mimicking portfolio approach.

In the result, the research purpose is to check if the return of the hedge portfolios we construct becomes higher as the Climate Change News Index gets higher. If so, investors can use it to hedge the climate change risk.