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Geopolitical Risk and Forecastability of Tail Risk in the Oil Market: Evidence from Over a Century of Monthly Data

Author

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  • Afees A. Salisu

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

  • Christian Pierdzioch

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

  • Rangan Gupta

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

Abstract

Using monthly data for the period from 1916 to 2020, we report that geopolitical risk, when decomposed into threats and actual risk, has predictive value for tail risk in the oil market. When we study the full sample of data, we find that threats increase tail risk in the oil market, while actual acts related risk reduces tail risk at longer forecast horizons. While the findings of the full-sample analysis show that the effect of threats and acts on tail risk in the oil market is quantitatively small, results of an out-of-sample analysis show that, for several model configurations, geopolitical risks associated with threats are statistically significant predictors of tail risk in the oil market, even after controlling for a factor capturing global equity-market tail-risk spillovers. Our results have important investment implications.

Suggested Citation

  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta, 2021. "Geopolitical Risk and Forecastability of Tail Risk in the Oil Market: Evidence from Over a Century of Monthly Data," Working Papers 202122, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202122
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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. Faheem Aslam & Paulo Ferreira & Haider Ali & Ana Ercília José, 2022. "Application of Multifractal Analysis in Estimating the Reaction of Energy Markets to Geopolitical Acts and Threats," Sustainability, MDPI, vol. 14(10), pages 1-23, May.
    3. Wang, Zhe & Teng, Yin-Pei & Wu, Shuzhao & Liu, Yuxiang & Liu, Xianchang, 2023. "Geopolitical risk, financial system and natural resources extraction: Evidence from China," Resources Policy, Elsevier, vol. 82(C).
    4. 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.
    5. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2022. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Working Papers 202201, University of Pretoria, Department of Economics.
    6. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022. "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Energies, MDPI, vol. 15(22), pages 1-26, November.
    7. Matteo Foglia & Vasilios Plakandaras & Rangan Gupta & Elie Bouri, 2023. "Multi-Layer Spillovers between Volatility and Skewness in International Stock Markets Over a Century of Data: The Role of Disaster Risks," Working Papers 202337, University of Pretoria, Department of Economics.
    8. Xiao, Jihong & Wen, Fenghua & He, Zhifang, 2023. "Impact of geopolitical risks on investor attention and speculation in the oil market: Evidence from nonlinear and time-varying analysis," Energy, Elsevier, vol. 267(C).
    9. Xiao, Jihong & Liu, Hong, 2023. "The time-varying impact of uncertainty on oil market fear: Does climate policy uncertainty matter?," Resources Policy, Elsevier, vol. 82(C).
    10. Wu, Jie & Zhao, Ruizeng & Sun, Jiasen & Zhou, Xuewei, 2023. "Impact of geopolitical risks on oil price fluctuations: Based on GARCH-MIDAS model," Resources Policy, Elsevier, vol. 85(PB).
    11. Chatziantoniou, Ioannis & Gabauer, David & Gupta, Rangan, 2023. "Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach," Resources Policy, Elsevier, vol. 84(C).
    12. Ahmet Faruk Aysan & Ali Polat & Hasan Tekin & Ahmet Tunali, 2022. "The Ascent of Geopolitics: Scientometric Analysis and Ramifications of Geopolitical Risk," Working Papers hal-03638273, HAL.
    13. 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).
    14. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Forecasting Stock Market Returns in Advanced Economies over a Century," Mathematics, MDPI, vol. 11(9), pages 1-21, April.
    15. 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).
    16. Tin Hei Alpha Yuen & Wai Kee Thomas Yuen, 2022. "Relationship Between Geopolitical Risk In Major Oil Producing Countries and Oil Price," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 117-123, September.
    17. 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).
    18. 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).
    19. Zhang, Jialin & Shi, Shaodong, 2023. "Extraction of natural resources and geopolitical risk revisited: A novel perspective of research and development with financial development," Resources Policy, Elsevier, vol. 85(PA).
    20. 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 price; Tail risks; Geopolitical risks; 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
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • 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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