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Predicting the Conditional Distribution of US Stock Market Systemic Stress: The Role of Climate Risks

Massimiliano Caporin, Petre Caraiani, Oguzhan Cepni () and Rangan Gupta
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Oguzhan Cepni: Copenhagen Business School, Department of Economics, Porcelaenshaven 16A, Frederiksberg DK-2000, Denmark; Ostim Technical University, Ankara, Turkiye

No 202407, Working Papers from University of Pretoria, Department of Economics

Abstract: This paper explores how climate risks impact the overall systemic stress levels in the United States (US). We initially apply the TrAffic Light System for Systemic Stress (TALIS) approach that classifies the stock markets across all 50 states based on their stress levels, to create an aggregate stress measure called ATALIS. Then, we utilize a nonparametric causality-in-quantiles approach to thoroughly assess the predictive power of climate risks across the entire conditional distribution of ATALIS, accounting for any data nonlinearity and structural changes. Our analysis covers daily data from July 1996 to March 2023, revealing that various climate risk indicators can predict the entire conditional distribution of ATALIS3, particularly around its median. The full-sample result also carries over time, when the nonparametric causality-in-quantiles test is conducted based on a rolling-window. Our findings, showing that climate risks are positively associated with ATALIS over its entire conditional distribution, provide crucial insights for investors and policymakers regarding the economic impact of environmental changes.

Keywords: State stock markets; Systemic stress; Climate risks; Quantile predictions (search for similar items in EconPapers)
JEL-codes: C21 C32 C53 G10 Q54 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2024-03
New Economics Papers: this item is included in nep-ene, nep-env, nep-fmk and nep-res
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