Climate Risks and State-Level Stock-Market Realized Volatility

Matteo Bonato, Oguzhan Cepni, Rangan Gupta, Christian Pierdzioch

Research output: Working paperResearch

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.
Original languageEnglish
Place of PublicationPretoria
PublisherUniversity of Pretoria
Number of pages31
Publication statusPublished - Sept 2022
SeriesWorking Paper Series / Department of Economics. University of Pretoria
Number2022-46

Keywords

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

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