Climate Risks and State-level Stock Market Realized Volatility

Matteo Bonato, Oguzhan Cepni, Rangan Gupta, Christian Pierdzioch*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


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.
Original languageEnglish
Article number100854
JournalJournal of Financial Markets
Number of pages18
Publication statusPublished - Nov 2023

Bibliographical note

Published online: 10 July 2023.


  • Finance
  • State-level data
  • Realized stock market volatility
  • Climate-related predictors
  • Prediction models

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