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Understanding recent oil price dynamics: A novel empirical approach

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  • D'Ecclesia, Rita L.
  • Magrini, Emiliano
  • Montalbano, Pierluigi
  • Triulzi, Umberto

Abstract

Crude oil is a major driver of the global economy and its price dynamics are a key indicator for producers, consumers and investors. The increasing volatility of crude oil prices in the last decade has encouraged many researchers to model its dynamics. Recent studies have tried to explain this dynamics by taking into account the role of various market participants many of whom have increasingly used crude oil for portfolio diversification. We propose a modified supply–demand framework which assumes that the real price of crude oil is affected not only by fundamental shocks but also by financial shocks. We assess the role of what we define as the financial shock component when describing the dynamics of the real crude oil price and endeavor to measure a possible equilibrium relationship between standard supply/demand variables and our financial shock component. Using a Dynamic Ordinary Least Squares (DOLS) approach and an ECM framework we are able to empirically assess the significant role of “hedging pressure” on the real price of oil and find evidence that the impact of the “hedging pressure” is not only affecting quick reverting short-term deviations but also the structural long-run equilibrium of the oil price.

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  • D'Ecclesia, Rita L. & Magrini, Emiliano & Montalbano, Pierluigi & Triulzi, Umberto, 2014. "Understanding recent oil price dynamics: A novel empirical approach," Energy Economics, Elsevier, vol. 46(S1), pages 11-17.
  • Handle: RePEc:eee:eneeco:v:46:y:2014:i:s1:p:s11-s17
    DOI: 10.1016/j.eneco.2014.10.005
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    3. Benjamin Cheng & Christina Sklibosios Nikitopoulos & Erik Schlögl, 2019. "Interest rate risk in long‐dated commodity options positions: To hedge or not to hedge?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 109-127, January.
    4. Qingqing Hu & Tinghui Li & Xue Li & Hao Dong, 2021. "Dynamic Characteristics of Oil Attributes and Their Market Effects," Energies, MDPI, vol. 14(13), pages 1-22, June.
    5. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    6. Baur, Dirk G. & Dimpfl, Thomas, 2018. "The asymmetric return-volatility relationship of commodity prices," Energy Economics, Elsevier, vol. 76(C), pages 378-387.
    7. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2017. "Can stock market investors hedge energy risk? Evidence from Asia," Energy Economics, Elsevier, vol. 66(C), pages 559-570.
    8. Jing Ao & Jihui Chen, 2020. "Price Volatility, the Maturity Effect, and Global Oil Prices: Evidence from Chinese Commodity Futures Markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(4), pages 627-654, October.
    9. Figuerola-Ferretti, Isabel & McCrorie, J. Roderick & Paraskevopoulos, Ioannis, 2020. "Mild explosivity in recent crude oil prices," Energy Economics, Elsevier, vol. 87(C).
    10. Salles, Andre Assis de & Maria Eduarda, Silva & Paulo, Teles, 2022. "Empirical Evidence of Associations and Similarities between the National Equity Markets Indexes and Crude Oil Prices in the International Market," MPRA Paper 113589, University Library of Munich, Germany.
    11. Yanqiong Liu & Zhenghui Li & Yanyan Yao & Hao Dong, 2021. "Asymmetry of Risk Evolution in Crude Oil Market: From the Perspective of Dual Attributes of Oil," Energies, MDPI, vol. 14(13), pages 1-22, July.
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    13. Theodosios Perifanis, 2019. "Detecting West Texas Intermediate (WTI) Prices’ Bubble Periods," Energies, MDPI, vol. 12(14), pages 1-16, July.

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    More about this item

    Keywords

    Oil price; Hedging; Financialization; Futures; DOLS; ECM;
    All these keywords.

    JEL classification:

    • 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
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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