Climate Risks and Predictability of Financial Risks in the US Banking Sector

Petre Caraiani (), Onur Polat (), Rangan Gupta and Elie Bouri ()
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Petre Caraiani: Bucharest University of Economic Studies and Institute for Economic Forecasting, Romanian Academy, Romania
Onur Polat: Department of Public Finance, Bilecik Seyh Edebali University, Bilecik, Turkiye
Elie Bouri: Corresponding author. School of Business, Lebanese American University, Lebanon

No 202507, Working Papers from University of Pretoria, Department of Economics

Abstract: In this paper, we relate physical and transition climate risks of the United States (US) to systemic risk of its banking sector. We start by estimating the systemic risk of 128 bank stock prices of the US over the period 26th May 2008 to 30th June 2023, taking the time-varying financial risk meter (FRM) approach, which relies on the Lasso quantile regression model. The FRM for the overall system of banks, as well as for large, medium, and small banks separately, exhibits notable peaks during COVID-19 in particular, and the global financial and European sovereign debt crises. Subsequently, using a nonparametric causality-in-quantiles test, which is robust to misspecification due to nonlinearity and structural breaks, we show that news-based metrics of physical and transition risks can significantly predict the entire conditional distribution of the FRMs over the full-sample and in a time-varying manner, with strongest causal impacts derived from news on international summits, compared to those on natural disasters, global warming, and US climate policies. Further analysis shows that all four climate risk factors consistently exert a positive impact on the conditional quantiles of the FRMs, supporting the premise that climate risks can damage assets and augment operating costs in the banking sector. Our findings have important policy implications which concern the stability of the banking sector.

Keywords: US bank stocks; financial risk meter (FRM); climate risks; nonparametric causality-in-quantiles test; predictability (search for similar items in EconPapers)
JEL-codes: C21 C22 G21 Q54 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2025-02
New Economics Papers: this item is included in nep-env and nep-fmk
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