Firm-specific Climate Risk Estimated from Public News

Abstract

We estimate firm-specific exposures to climate risk from public news covering a period of 20 years by applying a novel topic modeling algorithm. We differentiate between regulatory (or transition) and physical climate risks and document that financial markets price both risks. Our study is the first to find a positive and statistically significant risk premium for physical climate risk. For regulatory climate risk we find a regime shift occurring around the year 2012 reconciling the conflicting evidence in the literature. While the risk premium is positive in the earlier period, it becomes significantly negative in the later one. A long-short portfolio that is long “green” firms and short “brown” firms, as identified by their topic exposures in public news, constitutes a priced risk factor and shows a surprisingly strong correlation with an ESG-sorted benchmark portfolio.

Keywords: Climate Change, Climate Risk, Text Analytics, Natural Language Processing, Factor Investing, Alternative Data, ESG

JEL Classification: G11, G12, G14, G18, G32, G38, Q51, Q54, Q55