The transition to a low-carbon economy seems to gain urgency with each headline about the latest climate extreme. In this literature review, we summarise a study that investigates the relationship between unexpected climate news and equity performance, aiming to quantify climate beta.

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The paper aims to measure climate change beta by deriving climate news indices from multiple sources with various natural-language processing (NLP) methodologies. It quantitatively assesses unexpected climate change news and evaluates the effect on asset returns.

Climate beta is used to assess investors’ climate change exposure based on a portfolio’s sensitivity to the transition to a low-carbon economy.

• The authors create 25 unexpected climate news indices (UCNI), one for each underlying news source and model. They also create an aggregated UCNI across all news sources.
• Constituents of the S&P 500 were ranked based on carbon intensity to create “green”, “brown” and “green-minus-brown” (GMB) portfolios.
• The findings show a negative relationship between brown portfolio returns and the aggregated UCNI of all five sources. No significant relationships were found for green portfolios.