Investigating the Effect of Climate-Related Financial Disclosures on Investment Risk and Corporate Valuation

Posted: Aug 23, 2023

• Olivia Gonzalez
• Sophia White
• Liam Gonzalez

Abstract

This research presents a novel computational framework for analyzing the relationship between climate-related financial disclosures and corporate financial metrics, employing natural language processing techniques to quantify disclosure quality and machine learning models to assess their impact on investment risk and firm valuation. Unlike previous studies that rely on binary disclosure indicators or manual coding, our approach develops a multi-dimensional disclosure quality index derived from textual analysis of corporate sustainability reports and financial filings. We introduce a transformer-based architecture specifically fine-tuned for climate finance terminology that extracts and scores disclosure components across five dimensions: physical risk assessment, transition risk evaluation, scenario analysis depth, adaptation strategy specificity, and governance integration. Our dataset comprises 3,200 publicly traded companies across 12 sectors from 2015 to 2023, representing the most comprehensive analysis of climate disclosures to date. The methodology integrates these disclosure metrics with traditional financial indicators, market data, and proprietary climate risk scores to construct predictive models of firm valuation multiples and equity risk premiums. Our findings reveal a non-linear relationship between disclosure quality and financial outcomes, with diminishing returns beyond certain thresholds and significant sectoral variations. The results demonstrate that high-quality climate disclosures are associated with 15-25