In a sample of U.S. firms, we find strong evidence that firms' implied cost of equity is decreasing in a novel proxy of firm-level climate change sentiments of earnings call participants, supporting prior literature that shows investors demand higher returns from their investments in brown firms and lower returns from that in green firms. This effect, however, is particularly pronounced for the firm-years headquartered in the states experiencing higher than median per-capita energy related CO2 emissions, those headquartered in climate related disaster intensive counties and those headquartered in RED and SWING states, supporting “boomerang hypothesis” that green firms are hedged against potential changes in local climate standards and thus enjoy considerably cheaper financing in the localities marred with greenhouse gas emission concerns, climate related physical disasters, and climate unfriendly political environment. We utilize the variation in regionwide and statewide public beliefs about scientists' beliefs regarding the occurrence of global warming as an instrument to address endogeneity issues, among other tests.

Using a sample of 30,270 forecasts by 2,280 analysts under a stacked difference‐in‐differences framework involving 22 major climatic disasters in the United States, we examine the effect of climatic disasters on information production by security analysts, who play a crucial role in the financial market as information intermediaries. We find that earnings forecasts by analysts who experienced a major climatic disaster become less accurate than those by unaffected analysts within 3 months after the disaster, due to distracted attention. Disaster‐zone analysts are more likely to allocate their attention to firms of greater importance or salience, and they tend to reiterate their previous forecasts to maintain the quantity and timeliness of their forecasts. Overall, we document the real impact of cognitive bias on financial professionals' performance.

I review the economic characteristics of the climate problem, focusing on the choice of discount rates in the presence of a stock externality, risk and uncertainty/ambiguity, and the role of integrated assessment models (IAMs) in analyzing policy choices. I suggest that IAMs can play a role in providing qualitative understanding of how complex systems behave, but are not accurate enough to provide quantitative insights. Arguments in favor of action on climate issues have to be based on aversion to risk and ambiguity and the need to avoid a small but positive risk of a disastrous outcome.

Global warming is the defining challenge of our times. An emerging literature is investigating the interactions between climate change and financial markets. Climate finance is studying the pricing of climate risks across asset classes and the ways to channel public and private capital towards climate mitigation and adaptation investments. In 2019, the Journal of Corporate Finance launched a call for papers on the finance of climate change with the goal of publishing a special volume. In this context, we discuss how finance can help to address climate challenges, the contribution of the papers selected for the Special Issue and what we view as a broader climate finance research program.

The first Global Climate Strike on March 15, 2019, represented a historical turning point in climate activism. We investigate the cross-section of stock price reactions to this event for a large sample of European firms. The strike's unanticipated success caused a decrease in the stock prices of carbon-intensive firms. The effect appears to be driven by the increased public attention to climate activism. Furthermore, after the first Global Climate Strike financial analysts downgraded their longer-term earnings forecasts on carbon-intensive firms.

Quantitative estimates of the impacts of climate change on economic outcomes are important for public policy. We show that the vast majority of estimates fail to account for well-established uncertainty in future temperature and rainfall changes, leading to potentially misleading projections. We reexamine seven well-cited studies and show that accounting for climate uncertainty leads to a much larger range of projected climate impacts and a greater likelihood of worst-case outcomes, an important policy parameter. Incorporating climate uncertainty into future economic impact assessments will be critical for providing the best possible information on potential impacts.

We propose and implement a procedure to dynamically hedge climate change risk. We extract innovations from climate news series that we construct through textual analysis of newspapers. We then use a mimicking portfolio approach to build climate change hedge portfolios. We discipline the exercise by using third-party ESG scores of firms to model their climate risk exposures. We show that this approach yields parsimonious and industry-balanced portfolios that perform well in hedging innovations in climate news both in sample and out of sample. We discuss multiple directions for future research on financial approaches to managing climate risk.