Investigating the Influence of News Sources and Language Models on Climate Beta Estimates
使用五种语言模型和五家高质量报纸（包括《金融时报》）构建了25个意外气候新闻指数，并检验其对绿色、棕色及绿色减棕色股票组合收益的影响，发现综合指数与棕色组合收益在2012年7月至2021年11月间显著相关，但单一报纸指数不显著。
In this article, the authors seek to measure a news-based climate-change beta. Using five language models of increasing sophistication and five high-quality newspaper sources, including the <italic>Financial Times</italic>, they construct 25 unexpected climate news indices (UCNI). They measure the impact of these UCNI, plus UCNI aggregated over all the news sources, on a range of green, brown, and green-minus-brown (GMB) equity portfolios constructed by sorting S&P 500 Index firms based on their carbon intensity. The authors find that the relationship between the Aggregate UCNI and the brown and GMB portfolio returns is statistically significant over the period from July 2012 to November 2021. This result does not hold for UCNI built from a single newspaper. They find that green firms exhibit only a small, statistically nonsignificant degree of sensitivity to UCNI variations.