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El Nino and Forecastability of Oil-Price Realized Volatility

Author

Listed:
  • Elie Bouri

    (Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon)

  • Rangan Gupta

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

  • Christian Pierdzioch

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

  • Afees A. Salisu

    (Centre for Econometric & Allied Research, University of Ibadan, Ibadan, Nigeria)

Abstract
In this paper, we forecast monthly realized volatility (RV) of the oil price based on an extended heterogenous autoregressive (HAR)-RV model that incorporates the role of the El Nino Southern Oscillation (ENSO), as captured by the Equatorial Southern Oscillation Index (EQSOI). Based on the period covering 1986:01 to 2020:12 and studying various rolling-estimation windows and forecast horizons, we find that the EQSOI has predictive value for oil-price RV particularly at forecast horizons from two to four years, and for rolling-estimation windows of length four to six years. We show that this result holds not only based on standard tests of out-of-sample predictability, but also under an asymmetric loss function.

Suggested Citation

  • Elie Bouri & Rangan Gupta & Christian Pierdzioch & Afees A. Salisu, 2021. "El Nino and Forecastability of Oil-Price Realized Volatility," Working Papers 202105, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202105
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    Citations

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    Cited by:

    1. Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2022. "Oil tail risks and the forecastability of the realized variance of oil-price: Evidence from over 150 years of data," Finance Research Letters, Elsevier, vol. 46(PB).
    2. Gupta, Rangan & Nielsen, Joshua & Pierdzioch, Christian, 2024. "Stock market bubbles and the realized volatility of oil price returns," Energy Economics, Elsevier, vol. 132(C).
    3. Khan, Nasir & Saleem, Asima & Ozkan, Oktay, 2023. "Do geopolitical oil price risk influence stock market returns and volatility of Pakistan: Evidence from novel non-parametric quantile causality approach," Resources Policy, Elsevier, vol. 81(C).
    4. Zhu, Jiaji & Han, Wei & Zhang, Junchao, 2023. "Does climate risk matter for gold price volatility?," Finance Research Letters, Elsevier, vol. 58(PC).
    5. Elie Bouri & Afees A. Salisu & Rangan Gupta, 2023. "The predictive power of Bitcoin prices for the realized volatility of US stock sector returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    6. Hong, Yanran & Yu, Jize & Su, Yuquan & Wang, Lu, 2023. "Southern oscillation: Great value of its trends for forecasting crude oil spot price volatility," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 358-368.
    7. 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).
    8. Salisu, Afees A. & Gupta, Rangan & Nel, Jacobus & Bouri, Elie, 2022. "The (Asymmetric) effect of El Niño and La Niña on gold and silver prices in a GVAR model," Resources Policy, Elsevier, vol. 78(C).
    9. 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).
    10. Zhang, Li & Li, Yan & Yu, Sixin & Wang, Lu, 2023. "Risk transmission of El Niño-induced climate change to regional Green Economy Index," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 860-872.
    11. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Forecasting realized volatility of international REITs: The role of realized skewness and realized kurtosis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 303-315, March.
    12. Çepni, Oğuzhan & Gupta, Rangan & Pienaar, Daniel & Pierdzioch, Christian, 2022. "Forecasting the realized variance of oil-price returns using machine learning: Is there a role for U.S. state-level uncertainty?," Energy Economics, Elsevier, vol. 114(C).
    13. Zhang, Xiheng & Liu, Jiayu & Zhang, Kaiqi & Robert, James, 2023. "Analysis of firm performance in presence of oil price shocks: Importance of skilled management," Resources Policy, Elsevier, vol. 86(PA).
    14. Gupta, Rangan & Ji, Qiang & Pierdzioch, Christian & Plakandaras, Vasilios, 2023. "Forecasting the conditional distribution of realized volatility of oil price returns: The role of skewness over 1859 to 2023," Finance Research Letters, Elsevier, vol. 58(PC).
    15. 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.
    16. Salisu, Afees A. & Ndako, Umar B. & Vo, Xuan Vinh, 2023. "Transition risk, physical risk, and the realized volatility of oil and natural gas prices," Resources Policy, Elsevier, vol. 81(C).

    More about this item

    Keywords

    El Nino-Southern Oscillation; Realized Oil 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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