Wasim Ahmad, Mohammad Arshad Rahman, Suruchi Shrimali, Preeti Roy
{"title":"Tuning into Climate Risks: Extracting Innovation from TV News for Clean Energy Firms","authors":"Wasim Ahmad, Mohammad Arshad Rahman, Suruchi Shrimali, Preeti Roy","doi":"arxiv-2409.08701","DOIUrl":null,"url":null,"abstract":"This article develops multiple novel climate risk measures (or variables)\nbased on the television news coverage by Bloomberg, CNBC, and Fox Business, and\nexamines how they affect the systematic and idiosyncratic risks of clean energy\nfirms in the United States (US). The measures are built on climate related\nkeywords and cover the volume of coverage, type of coverage (climate crisis,\nrenewable energy, and government and human initiatives), and media sentiments.\nWe show that an increase in the aggregate measure of climate risk, as indicated\nby coverage volume, reduces idiosyncratic risk while increasing systematic\nrisk. When climate risk is segregated, we find that systematic risk is\npositively affected by the \\textit{physical risk} of climate crises and\n\\textit{transition risk} from government and human initiatives, but no such\nimpact is evident for idiosyncratic risk. Additionally, we observe an asymmetry\nin risk behavior: negative sentiments tend to increase idiosyncratic risk and\ndecrease systematic risk, while positive sentiments have no significant impact.\nThis asymmetry persists even when considering print media variables, climate\npolicy uncertainty, and analysis based on the COVID-19 period.","PeriodicalId":501139,"journal":{"name":"arXiv - QuantFin - Statistical Finance","volume":"46 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Statistical Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08701","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article develops multiple novel climate risk measures (or variables)
based on the television news coverage by Bloomberg, CNBC, and Fox Business, and
examines how they affect the systematic and idiosyncratic risks of clean energy
firms in the United States (US). The measures are built on climate related
keywords and cover the volume of coverage, type of coverage (climate crisis,
renewable energy, and government and human initiatives), and media sentiments.
We show that an increase in the aggregate measure of climate risk, as indicated
by coverage volume, reduces idiosyncratic risk while increasing systematic
risk. When climate risk is segregated, we find that systematic risk is
positively affected by the \textit{physical risk} of climate crises and
\textit{transition risk} from government and human initiatives, but no such
impact is evident for idiosyncratic risk. Additionally, we observe an asymmetry
in risk behavior: negative sentiments tend to increase idiosyncratic risk and
decrease systematic risk, while positive sentiments have no significant impact.
This asymmetry persists even when considering print media variables, climate
policy uncertainty, and analysis based on the COVID-19 period.