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Climate Risks and Realized Volatility of Major Commodity Currency Exchange Rates

Author

Listed:
  • Matteo Bonato

    (Department of Economics and Econometrics, University of Johannesburg, Auckland Park, South Africa; IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France)

  • Oguzhan Cepni

    (Copenhagen Business School, Department of Economics, Porcelaenshaven 16A, Frederiksberg DK-2000, Denmark)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany)

Abstract

We find that climate-related risks forecast the intraday-data-based realized volatility of exchange-rate returns of eight major fossil fuel-exporters (Australia, Brazil, Canada, Malaysia, Mexico, Norway, Russia, and South Africa). We study a wide array of metrics capturing risks associated with climate change, derived from data directly on variables such as, for example, abnormal patterns of temperature. We control for various other moments (realized skewness, realized kurtosis, realized good and variance, upside and downside tail risk, and jumps) and estimate our forecasting models using random forests, a machine-learning technique tailored to analyze models with many predictors.

Suggested Citation

  • Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Climate Risks and Realized Volatility of Major Commodity Currency Exchange Rates," Working Papers 202210, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202210
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    11. Carè, R. & Fatima, R. & Boitan, I.A., 2024. "Central banks and climate risks: Where we are and where we are going?," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 1200-1229.
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    More about this item

    Keywords

    Climate Risks; Commodity Currencies; Realized Variance; Forecasting;
    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
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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