IDEAS home Printed from https://ideas.repec.org/p/rdg/icmadp/icma-dp2010-01.html

An Empirical Model Comparison for Valuing Crack Spread Options

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.icmacentre.ac.uk/files/dp201001.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Turquet, Briac & Bajgrowicz, Pierre & Scaillet, Olivier, 2025. "Mean reversion trading on the naphtha crack," Energy Economics, Elsevier, vol. 148(C).
    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. Liu, Pan & Vedenov, Dmitry & Power, Gabriel J., 2016. "Hedging the Crack Spread during Periods of High Volatility in Oil Prices," 2016 Conference, April 18-19, 2016, St. Louis, Missouri 285860, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    10. 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.
    11. 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.

    More about this item

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rdg:icmadp:icma-dp2010-01. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Marie Pearson (email available below). General contact details of provider: https://edirc.repec.org/data/bsrdguk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.