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El Niño, La Niña, and the Forecastability of the Realized Variance of Heating Oil Price Movements

Author

Listed:
  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Famagusta 99268, Turkey)

  • Elie Bouri

    (Adnan Kassar School of Business, Lebanese American University, Beirut P.O. Box 13-5053, Lebanon)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria 0002, South Africa)

  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University, 22008 Hamburg, Germany)

Abstract

We use the heterogenous autoregressive (HAR) model to compute out-of-sample forecasts of the monthly realized variance (RV) of movements of the spot and futures price of heating oil. We extend the HAR–RV model to include the role of El Niño and La Niña episodes, as captured by the Equatorial Southern Oscillation Index (EQSOI). Using data from June 1986 to April 2021, we show evidence for several model configurations that both El Niño and La Niña phases contain information useful for forecasting subsequent to the realized variance of price movements beyond the predictive value already captured by the HAR–RV model. The predictive value of La Niña phases, however, seems to be somewhat stronger than the predictive value of El Niño phases. Our results have important implications for investors, as well as from the perspective of sustainable decisions involving the environment.

Suggested Citation

  • Mehmet Balcilar & Elie Bouri & Rangan Gupta & Christian Pierdzioch, 2021. "El Niño, La Niña, and the Forecastability of the Realized Variance of Heating Oil Price Movements," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7987-:d:596011
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    Cited by:

    1. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    2. Pham, Linh & Kamal, Javed Bin, 2024. "Blessings or curse: How do media climate change concerns affect commodity tail risk spillovers?," Journal of Commodity Markets, Elsevier, vol. 34(C).
    3. Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment," Energies, MDPI, vol. 14(23), pages 1-18, December.
    4. Wei, Yu & Zhang, Jiahao & Chen, Yongfei & Wang, Yizhi, 2022. "The impacts of El Niño-southern oscillation on renewable energy stock markets: Evidence from quantile perspective," Energy, Elsevier, vol. 260(C).
    5. Wei, Yu & Zhang, Jiahao & Bai, Lan & Wang, Yizhi, 2023. "Connectedness among El Niño-Southern Oscillation, carbon emission allowance, crude oil and renewable energy stock markets: Time- and frequency-domain evidence based on TVP-VAR model," Renewable Energy, Elsevier, vol. 202(C), pages 289-309.

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    More about this item

    Keywords

    El Niño-Southern Oscillation; realized heating oil price volatility; heterogenous autoregression; 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
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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