Tuning into Climate Risks: Extracting Innovation from Television News for Clean Energy Firms
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866910709762228224 |
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| author | Ahmad, Wasim Rahman, Mohammad Arshad Shrimali, Suruchi Roy, Preeti |
| author_facet | Ahmad, Wasim Rahman, Mohammad Arshad Shrimali, Suruchi Roy, Preeti |
| contents | 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. The measures are built on climate related keywords and cover the volume of coverage, type of coverage (climate crisis, renewable energy, and government & 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 physical risk of climate crises and transition risk from government & human initiatives, but no such impact is evident for idiosyncratic risk. Additionally, we observe an asymmetry in risk behavior: negative sentiments tend to decrease idiosyncratic risk and increase systematic risk, while positive sentiments have no significant impact. These findings remain robust to including print media and climate policy uncertainty variables, though some deviations are noted during the COVID-19 period. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_08701 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Tuning into Climate Risks: Extracting Innovation from Television News for Clean Energy Firms Ahmad, Wasim Rahman, Mohammad Arshad Shrimali, Suruchi Roy, Preeti Statistical Finance Computational Finance 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. The measures are built on climate related keywords and cover the volume of coverage, type of coverage (climate crisis, renewable energy, and government & 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 physical risk of climate crises and transition risk from government & human initiatives, but no such impact is evident for idiosyncratic risk. Additionally, we observe an asymmetry in risk behavior: negative sentiments tend to decrease idiosyncratic risk and increase systematic risk, while positive sentiments have no significant impact. These findings remain robust to including print media and climate policy uncertainty variables, though some deviations are noted during the COVID-19 period. |
| title | Tuning into Climate Risks: Extracting Innovation from Television News for Clean Energy Firms |
| topic | Statistical Finance Computational Finance |
| url | https://arxiv.org/abs/2409.08701 |