中文版 | English
Title

Firm-Level Climate Risks: Measurement and Asset Pricing Implications

Author
Name pinyin
YU Tingyu
School number
11851016
Degree
博士
Discipline
数学
Supervisor
杨招军
Mentor unit
金融系
Tutor of External Organizations
吴立昕
Tutor units of foreign institutions
香港科技大学
Publication Years
2022-06-23
Submission date
2022-07-15
University
香港科技大学
Place of Publication
香港
Abstract

We construct various measures of firm-level climate risk exposure by utilizing natural language processing techniques on firms' quarterly earnings conference call transcripts. The unsupervised learning method automatically generates five topics aligned with popular climate change concerns. Investors reward firms' efforts to fight against global warming and transition to a low-carbon economy by developing emission reduction technology and renewable investment. Such firms are less sensitive to the frontier green technology shock and less likely to be subject to penalties related to environmental issues. Therefore they have a lower cost of financing and expected return.
We conduct an empirical analysis on the topic that puts high weight on words about natural disasters. This disaster exposure measure has a significant negative association with firms' sales growth and profitability. Moreover, firms with higher disaster exposure tend to earn higher expected stock returns than their counterparts with lower exposure, suggesting that firms' disaster risk exposure significantly affects the cost of equity and market valuations. A long-short portfolio based on this exposure measure generates a positive return of 5% per annum, which cannot be explained by common risk factors and other firm characteristics.

Keywords
Language
English
Training classes
联合培养
Enrollment Year
2018
Year of Degree Awarded
2022-11
References List

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Data Source
人工提交
Document TypeThesis
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/355725
DepartmentDepartment of Mathematics
Recommended Citation
GB/T 7714
Yu TY. Firm-Level Climate Risks: Measurement and Asset Pricing Implications[D]. 香港. 香港科技大学,2022.
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