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Climate Risks and State-Level Stock-Market Realized Volatility

Matteo Bonato (), Oguzhan Cepni, Rangan Gupta and Christian Pierdzioch
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Matteo Bonato: Department of Economics and Econometrics, University of Johannesburg, Auckland Park, South Africa; IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France

No 202246, Working Papers from University of Pretoria, Department of Economics

Abstract: We analyze the predictive value of climate risks for state-level realized stock-market volatility, computed, along with other realized moments, based on high-frequency intra-day U.S. data (September, 2011 to October, 2021). A model-based bagging algorithm recovers that climate risks have predictive value for realized volatility at intermediate and long (one and two months) forecast horizons. This finding also holds for upside (``good") and downside (``bad") realized volatility. The benefits of using climate risks for predicting state-level realized stock-market volatility depend on the shape and (as-)symmetry of a forecaster's loss function.

Keywords: Finance; State-level data; Realized stock-market volatility; Climate-related predictors; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 G10 G17 Q54 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2022-09
New Economics Papers: this item is included in nep-env, nep-fmk and nep-rmg
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