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A Bimodal Model for Oil Prices

Author

Listed:
  • Joanna Goard

    (School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW 2522, Australia)

  • Mohammed AbaOud

    (Department of Mathematics and Statistics, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11564, Saudi Arabia)

Abstract

Oil price behaviour over the last 10 years has shown to be bimodal in character, displaying a strong tendency to congregate around one range of high oil prices and one range of low prices, indicating two distinct peaks in its frequency distribution. In this paper, we propose a new, single nonlinear stochastic process to model the bimodal behaviour, namely, d p = α ( p 1 − p ) ( p 2 − p ( p 3 − p ) d t + σ p γ d Z , γ = 0 , 0.5 . Further, we find analytic approximations of oil price futures under this model in the cases where the stable fixed points of the corresponding deterministic model are (a) evenly spaced about the unstable fixed point and (b) are spaced in the ratio 1:2 about the unstable fixed point. The solutions are shown to produce accurate prices when compared to numerical solutions.

Suggested Citation

  • Joanna Goard & Mohammed AbaOud, 2023. "A Bimodal Model for Oil Prices," Mathematics, MDPI, vol. 11(10), pages 1-26, May.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:10:p:2222-:d:1142538
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Raj, Mahendra & Sim, Ah Boon & Thurston, David C., 1997. "A generalized method of moments comparison of the cox-ingersoll-ross and heath-jarrow-morton models," Journal of Economics and Business, Elsevier, vol. 49(2), pages 169-192.
    3. Stein, Elias M & Stein, Jeremy C, 1991. "Stock Price Distributions with Stochastic Volatility: An Analytic Approach," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 727-752.
    4. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    5. Grunbichler, Andreas & Longstaff, Francis A., 1996. "Valuing futures and options on volatility," Journal of Banking & Finance, Elsevier, vol. 20(6), pages 985-1001, July.
    6. Black, Fischer & Scholes, Myron S, 1972. "The Valuation of Option Contracts and a Test of Market Efficiency," Journal of Finance, American Finance Association, vol. 27(2), pages 399-417, May.
    7. Robert S. Pindyck, 1999. "The Long-Run Evolutions of Energy Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-27.
    8. Brennan, Michael J & Schwartz, Eduardo S, 1985. "Evaluating Natural Resource Investments," The Journal of Business, University of Chicago Press, vol. 58(2), pages 135-157, April.
    9. Egloff, Daniel & Leippold, Markus & Wu, Liuren, 2010. "The Term Structure of Variance Swap Rates and Optimal Variance Swap Investments," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(5), pages 1279-1310, October.
    10. Luis Mª Abadie & José M. Chamorro, 2017. "Valuation of Real Options in Crude Oil Production," Energies, MDPI, vol. 10(8), pages 1-21, August.
    11. Ferson, Wayne E. & Foerster, Stephen R., 1994. "Finite sample properties of the generalized method of moments in tests of conditional asset pricing models," Journal of Financial Economics, Elsevier, vol. 36(1), pages 29-55, August.
    12. Joanna Goard & Noel Hansen, 2004. "Comparison of the performance of a time-dependent short-interest rate model with time-independent models," Applied Mathematical Finance, Taylor & Francis Journals, vol. 11(2), pages 147-164.
    13. Joanna Goard, 2011. "A Time-Dependent Variance Model for Pricing Variance and Volatility Swaps," Applied Mathematical Finance, Taylor & Francis Journals, vol. 18(1), pages 51-70.
    14. Gonzalo Cortazar & Lorenzo Naranjo, 2006. "An N‐factor Gaussian model of oil futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(3), pages 243-268, March.
    15. MacKinlay, A Craig & Richardson, Matthew P, 1991. "Using Generalized Method of Moments to Test Mean-Variance Efficiency," Journal of Finance, American Finance Association, vol. 46(2), pages 511-527, June.
    16. Hilliard, Jimmy E. & Reis, Jorge, 1998. "Valuation of Commodity Futures and Options under Stochastic Convenience Yields, Interest Rates, and Jump Diffusions in the Spot," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(1), pages 61-86, March.
    17. McDonald, Robert L & Siegel, Daniel R, 1985. "Investment and the Valuation of Firms When There Is an Option to Shut Down," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(2), pages 331-349, June.
    18. Mohammed A. Aba Oud & Joanna Goard, 2015. "Stochastic Models for Oil Prices and the Pricing of Futures on Oil," Applied Mathematical Finance, Taylor & Francis Journals, vol. 22(2), pages 189-206, April.
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    Cited by:

    1. Fehaid Salem Alshammari, 2024. "Novel Numerical Investigation of Reaction Diffusion Equation Arising in Oil Price Modeling," Mathematics, MDPI, vol. 12(8), pages 1-17, April.

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