IDEAS home Printed from
   My bibliography  Save this paper

Commodity derivatives pricing with inventory effects


  • Christian Bach

    () (Aarhus University and CREATES)

  • Matt P. Dziubinski

    () (Aarhus University and CREATES)


We introduce tractable models for commodity derivatives pricing with inventory and volatility effects, and illustrate with applications to the oil market. We contribute to the existing literature in several respects. First, whereas the previous literature uses futures data for investigating the relationship between inventory and volatility, we use the information available in options traded on futures. Second, performance assessment in the previous literature has primarily evolved around explaining moments of data or forecasting prices of futures. Instead, we assess the performance of our model by considering both the ability of explaining prices in-sample and out-of-sample - assessing both the pricing-performance and the hedging-performance of the models. Third, we model the futures surface rather than the spot price process, and from the no-arbitrage relationship between spot and futures prices we limit the number of parameters to calibrate. We introduce a new, maturity-wise calibration method compatible with this modeling methodology. Fourth, we use actual data on inventories rather than a proxy. Fifth, our model is very flexible and allows for testing several different types of relationships between inventory and volatility.

Suggested Citation

  • Christian Bach & Matt P. Dziubinski, 2012. "Commodity derivatives pricing with inventory effects," CREATES Research Papers 2012-06, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2012-06

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item


    Energy futures and options markets; energy price volatility; commodities; crude oil; stochastic volatility; stochastic inventories; inventories; option pricing; scarcity.;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:aah:create:2012-06. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.