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An Empirical Model Comparison for Valuing Crack Spread Options

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  • Steffen Mahringer

    (ICMA Centre, University of Reading)

  • Marcel Prokopczuk

    (ICMA Centre, University of Reading)

Abstract

In this paper, we investigate the pricing of crack spread options. The special focus is laid on the question, of whether univariate modeling of the crack spread or explicit modeling of the two underlyings is preferable. Therefore, we contrast the bivariate GARCH volatility model for co-integrated underlyings of Duan and Pliska (2004), with the alternative of modeling the crack spread directly. Conducting an extensive empirical analysis of crude oil/heating oil and crude oil/gasoline crack spread options traded on the New York Mercantile Exchange, the more simplistic univariate approach is found to be superior with respect to option pricing performance.

Suggested Citation

  • Steffen Mahringer & Marcel Prokopczuk, 2010. "An Empirical Model Comparison for Valuing Crack Spread Options," ICMA Centre Discussion Papers in Finance icma-dp2010-01, Henley Business School, University of Reading.
    • Handle: RePEc:rdg:icmadp:icma-dp2010-01
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    Cited by:

    1. Liu, Pan & Vedenov, Dmitry & Power, Gabriel J., 2017. "Is hedging the crack spread no longer all it's cracked up to be?," Energy Economics, Elsevier, vol. 63(C), pages 31-40.
    2. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    3. Rombouts, Jeroen & Stentoft, Lars & Violante, Franceso, 2014. "The value of multivariate model sophistication: An application to pricing Dow Jones Industrial Average options," International Journal of Forecasting, Elsevier, vol. 30(1), pages 78-98.
    4. Benth, Fred Espen & Koekebakker, Steen, 2015. "Pricing of forwards and other derivatives in cointegrated commodity markets," Energy Economics, Elsevier, vol. 52(PA), pages 104-117.
    5. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    6. Geng, Qianjie & Wang, Yudong, 2024. "Forecasting the volatility of crude oil basis: Univariate models versus multivariate models," Energy, Elsevier, vol. 295(C).
    7. Pierre J. Venter & Eben Maré, 2021. "Univariate and Multivariate GARCH Models Applied to Bitcoin Futures Option Pricing," JRFM, MDPI, vol. 14(6), pages 1-14, June.
    8. Spodniak, Petr & Bertsch, Valentin, 2017. "Determinants of power spreads in electricity futures markets: A multinational analysis," Papers WP580, Economic and Social Research Institute (ESRI).
    9. Song, Shiyu & Tang, Dan & Xu, Guangli & Yin, Xunbai, 2023. "An analytical GARCH valuation model for spread options with default risk," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 1-20.

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    More about this item

    Keywords

    Crack Spread Options; Option Valuation; Co-integrated Underlyings;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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