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Humps in the Volatility Structure of the Crude Oil Futures Market

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Abstract

This paper analyzes the volatility structure of commodity derivatives markets. The model encompasses stochastic volatility that may be unspanned by futures contracts. A generalized hump-shaped volatility specification is assumed that entails a finite-dimensional affine model for the commodity futures curve and quasi-analytical prices for options on commodity futures. An empirical study of the crude oil futures volatility structure is carried out using an extensive database of futures prices as well as futures option prices spanning 21 years. The study supports a hump-shaped, partially spanned stochastic volatility specification. Factor hedging, which takes into account shocks to both the volatility processes and the futures curve, depicts the presence of unspanned components in the volatility of commodity futures and the outperformance of the hump-shaped volatility in comparison to the more popular exponential decaying volatility. This hump shaped feature is more pronounced when the market is volatile.

Suggested Citation

  • Carl Chiarella & Boda Kang & Christina Nikitopoulos-Sklibosios & Thuy-Duong To, 2012. "Humps in the Volatility Structure of the Crude Oil Futures Market," Research Paper Series 308, Quantitative Finance Research Centre, University of Technology, Sydney.
  • Handle: RePEc:uts:rpaper:308
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    Cited by:

    1. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2016. "Empirical Hedging Performance on Long-dDted Crude Oil Derivatives," Research Paper Series 376, Quantitative Finance Research Centre, University of Technology, Sydney.
    2. Kang, Wensheng & Ratti, Ronald. A. & Vespignani, Joaquin, 2017. "Global commodity prices and global stock volatility shocks: effects across countries," Working Papers 2017-05, University of Tasmania, Tasmanian School of Business and Economics.
    3. 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.
    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. Lorenz Schneider & Bertrand Tavin, 2018. "The Samuelson Effect and Seasonal Stochastic Volatility in Agricultural Futures Markets," Papers 1802.01393, arXiv.org.
    6. 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.
    7. repec:uts:finphd:37 is not listed on IDEAS
    8. Carl Chiarella & Boda Kang & Christina Sklibosios Nikitopoulos & Thuy‐Duong Tô, 2016. "The Return–Volatility Relation in Commodity Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(2), pages 127-152, February.

    More about this item

    Keywords

    commodity derivatives; crude oil derivatives; Unspanned stochastic volatility; hump-shaped volatility; pricing; hedging;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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