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Climate risks and state-level stock market realized volatility

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

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.

Suggested Citation

  • Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and state-level stock market realized volatility," Journal of Financial Markets, Elsevier, vol. 66(C).
  • Handle: RePEc:eee:finmar:v:66:y:2023:i:c:s1386418123000526
    DOI: 10.1016/j.finmar.2023.100854
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    More about this item

    Keywords

    Finance; State-level data; Realized stock market volatility; Climate-related predictors; Prediction models;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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