Corporate Climate Risk: Measurements and Responses

ArXiv ID: ssrn-3508497 “View on arXiv”

Authors: Unknown

Abstract

This paper conducts a textual analysis of earnings call transcripts to quantify climate risk exposure at the firm level. We construct dictionaries that measure

Keywords: Climate Risk, Textual Analysis, Earnings Calls, Environmental Exposure, Corporate Equities

Complexity vs Empirical Score

• Math Complexity: 4.0/10
• Empirical Rigor: 6.0/10
• Quadrant: Street Traders
• Why: The research focuses on textual analysis and dictionary construction with relatively basic statistical measures, placing it in low-to-moderate math complexity. However, the use of earnings call transcripts, firm-level quantification, and likely implementation of text mining tools suggests a data-heavy, backtest-ready approach suited for practical trading or risk management.

  flowchart TD
    A["Research Goal<br>Quantify firm-level climate risk"] --> B["Data Source<br>Earnings Call Transcripts"]
    B --> C["Methodology<br>Textual Analysis & Dictionary Construction"]
    C --> D["Computational Process<br>Measure Risk Exposure Scores"]
    D --> E{"Key Outcomes"}
    E --> F["Climate Risk Quantified<br>at Firm Level"]
    E --> G["Discriminates between<br>Physical & Transition Risks"]