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Forecasting Oil Price over 150 Years: The Role of Tail Risks

Author

Listed:
  • Afees A. Salisu

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

  • Rangan Gupta

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

  • Qiang Ji

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, China)

Abstract

In this study, we examine the predictive value of tail risks for oil returns using the longest possible data available for the modern oil industry, i.e., 1859-2020. The Conditional Autoregressive Value at Risk (CAViaR) of Engle & Manganelli (2004) is employed to generate the tail risks for both 1% and 5% VaRs across four variants (Adaptive, Symmetric absolute value, Asymmetric slope and Indirect GARCH) of the CAViaR with the best variant obtained using the Dynamic Quantile test (DQ) test and %Hits. Overall, our proposed predictive model for oil returns that jointly accommodates tail risks associated with the oil market and US financial market improves the out-of-sample forecast accuracy of oil returns in contrast with a benchmark (random walk) model as well as a one-predictor model with own tail risk only. Our results have important implications for academicians, investors and policymakers.

Suggested Citation

  • Afees A. Salisu & Rangan Gupta & Qiang Ji, 2021. "Forecasting Oil Price over 150 Years: The Role of Tail Risks," Working Papers 202120, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202120
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    Cited by:

    1. Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Reneé van Eyden, 2023. "Climate risks and U.S. stock‐market tail risks: A forecasting experiment using over a century of data," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 228-244, June.
    2. Ahamuefula E. Ogbonna & Olusanya E. Olubusoye, 2021. "Tail Risks and Stock Return Predictability - Evidence From Asia-Pacific," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(3), pages 1-6.
    3. Qian, Lihua & Zeng, Qing & Lu, Xinjie & Ma, Feng, 2022. "Global tail risk and oil return predictability," Finance Research Letters, Elsevier, vol. 47(PB).
    4. Idris A. Adediran, 2021. "Can Tail Risk Predict Asia-Pacific Exchange Rates Out of Sample?," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(3), pages 1-6.
    5. Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan & Gabauer, David, 2022. "Forecasting stock-market tail risk and connectedness in advanced economies over a century: The role of gold-to-silver and gold-to-platinum price ratios," International Review of Financial Analysis, Elsevier, vol. 83(C).
    6. Adediran, Idris A. & Swaray, Raymond, 2023. "Carbon trading amidst global uncertainty: The role of policy and geopolitical uncertainty," Economic Modelling, Elsevier, vol. 123(C).
    7. Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.
    8. Salisu, Afees A. & Olaniran, Abeeb & Tchankam, Jean Paul, 2022. "Oil tail risk and the tail risk of the US Dollar exchange rates," Energy Economics, Elsevier, vol. 109(C).
    9. Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2021. "Geopolitical risk and forecastability of tail risk in the oil market: Evidence from over a century of monthly data," Energy, Elsevier, vol. 235(C).
    10. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Vo, Xuan Vinh, 2023. "Oil tail risks and the realized variance of consumer prices in advanced economies," Resources Policy, Elsevier, vol. 83(C).
    11. Vicknair, David & Tansey, Michael & O'Brien, Thomas E., 2022. "Measuring fossil fuel reserves: A simulation and review of the U.S. Securities and Exchange Commission approach," Resources Policy, Elsevier, vol. 79(C).
    12. Salisu, Afees A. & Gupta, Rangan & Pierdzioch, Christian, 2022. "Predictability of tail risks of Canada and the U.S. Over a Century: The role of spillovers and oil tail Risks☆," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    13. 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).
    14. Zhao, Lu-Tao & Wang, Dai-Song & Ren, Zhong-Yuan, 2024. "The impact of joint events on oil price volatility: Evidence from a dynamic graphical news analysis model," Economic Modelling, Elsevier, vol. 130(C).
    15. Afees A. Salisu & Rangan Gupta & Christian Pierdzioch, 2021. "Predictability of Tail Risks of Canada and the U.S. Over a Century: The Role of Spillovers and Oil Tail Risks," Working Papers 202127, University of Pretoria, Department of Economics.

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    More about this item

    Keywords

    Oil returns; Tail risks; Forecasting; Advanced equity markets;
    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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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