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Empirical Hedging Performance on Long-Dated Crude Oil Derivatives

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Abstract

This paper presents an empirical study on hedging long-dated crude oil futures options with forward price models incorporating stochastic interest rates and stochastic volatility. Several hedging schemes are considered including delta, gamma, vega and interest rate hedge. Factor hedging is applied to the proposed multi-dimensional models and the corresponding hedge ratios are estimated by using historical crude oil futures prices, crude oil option prices and Treasury yields. Hedge ratios from stochastic interest rate models consistently improve hedging performance over hedge ratios from deterministic interest rate models, an improvement that becomes more pronounced over periods with high interest rate volatility, such as during the GFC. An interest rate hedge consistently improves hedging beyond delta, gamma and vega hedging, especially when shorter maturity contracts are used to roll the hedge forward. Furthermore, when the market experiences high interest rate volatility and the hedge is subject to high basis risk, adding interest rate hedge to delta hedge provides an improvement, while adding gamma and/or vega to the delta hedge worsens performance.

Suggested Citation

  • Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2016. "Empirical Hedging Performance on Long-Dated Crude Oil Derivatives," Research Paper Series 376, Quantitative Finance Research Centre, University of Technology, Sydney.
  • Handle: RePEc:uts:rpaper:376
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    File URL: https://www.uts.edu.au/sites/default/files/QFR-rp376.pdf
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    References listed on IDEAS

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    1. James D. Hamilton, 2009. "Causes and Consequences of the Oil Shock of 2007-08," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 40(1 (Spring), pages 215-283.
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    4. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2016. "Hedging Futures Options with Stochastic Interest Rates," Research Paper Series 375, Quantitative Finance Research Centre, University of Technology, Sydney.
    5. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2016. "Empirical Pricing Performance in Long-Dated Crude Oil Derivatives: Do Models with Stochastic Interest Rates Matter?," Research Paper Series 367, Quantitative Finance Research Centre, University of Technology, Sydney.
    6. James D. Hamilton, 2009. "Understanding Crude Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 179-206.
    7. Chiarella, Carl & Kang, Boda & Nikitopoulos, Christina Sklibosios & Tô, Thuy-Duong, 2013. "Humps in the volatility structure of the crude oil futures market: New evidence," Energy Economics, Elsevier, vol. 40(C), pages 989-1000.
    8. Franklin R. Edwards & Michael S. Canter, 1995. "The Collapse Of Metallgesellschaft: Unhedgeable Risks, Poor Hedging Strategy, Or Just Bad Luck?," Journal of Applied Corporate Finance, Morgan Stanley, vol. 8(1), pages 86-105, March.
    9. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2015. "Pricing of Long-dated Commodity Derivatives with Stochastic Volatility and Stochastic Interest Rates," Research Paper Series 366, Quantitative Finance Research Centre, University of Technology, Sydney.
    10. Dempster, M.A.H. & Medova, Elena & Tang, Ke, 2008. "Long term spread option valuation and hedging," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2530-2540, December.
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    Cited by:

    1. Benjamin Tin Chun Cheng, 2017. "Pricing and Hedging of Long-Dated Commodity Derivatives," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2017.
    2. repec:uts:finphd:37 is not listed on IDEAS
    3. James S. Doran & Ehud I. Ronn, 2021. "Hedging Long-Dated Oil Futures and Options Using Short-Dated Securities—Revisiting Metallgesellschaft," JRFM, MDPI, vol. 14(8), pages 1-10, August.
    4. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2016. "Hedging Futures Options with Stochastic Interest Rates," Research Paper Series 375, Quantitative Finance Research Centre, University of Technology, Sydney.
    5. P. Karlsson & K. F. Pilz & E. Schlögl, 2017. "Calibrating a market model with stochastic volatility to commodity and interest rate risk," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 907-925, June.

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    More about this item

    Keywords

    Stochastic interest rates; Delta hedge; Interest rate hedge; Long-dated crude oil options;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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