Date of Award

4-2025

Degree Name

Master of Science

Department

Mathematics

First Advisor

Qiji Jim Zhu, Ph.D.

Second Advisor

Jay Treiman, Ph.D.

Third Advisor

Yuri Ledyaev, Ph.D.

Access Setting

Masters Thesis-Open Access

Abstract

The growing impact of climate change on financial markets necessitates a rigorous approach to climate risk assessment. This thesis examines methods for quantifying climate-related financial risks, with a focus on distinguishing climate risk from broader market movements (represented by S&P 500). Using a factor model, we isolate climate risk factors to better understand sector-specific volatility. The insurance sector is used as a proxy for climate risk exposure, given its sensitivity to climate-related losses and regulatory changes. We apply Extreme Value Theory (EVT); the Block Maxima Method and the Peaks Over Threshold Method, to identify excess risk patterns in financial portfolios. Through empirical analysis of the energy sector (XLE) and coal industry (KOL), we demonstrate how climate risk manifests in market behavior. Our findings show that EVT can effectively estimate Value at Risk (VaR), and Conditional VaR (CVaR), in financial market return series, providing a robust framework for climate risk assessment.

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