IDEAS home Printed from https://ideas.repec.org/p/rdg/icmadp/icma-dp2009-10.html
   My bibliography  Save this paper

Commodity Derivatives Valuation with Autoregression and Moving Average in the Price Dynamics

Author

Listed:
  • Raphael Paschke

    (University of Mannheim)

  • Marcel ProkopczukÂ

    (ICMA Centre, University of Reading)

Abstract

In this paper we develop a continuous time factor model of commodity prices that allows for higher order autoregression and moving average components. The need for these components is documented by analyzing the convenience yield's time series dynamics. Making use of the affine model structure, closed-form pricing formulas for futures and options are derived. Empirically, a parsimonious version of the general model is estimated for the crude oil market using futures data. We demonstrate the model's superior performance in pricing nearby futures contracts in- and out-of-sample. Most notably, the model improves the pricing of long horizon contracts with information from the short end of the futures curve substantially.

Suggested Citation

  • Raphael Paschke & Marcel ProkopczukÂ, 2009. "Commodity Derivatives Valuation with Autoregression and Moving Average in the Price Dynamics," ICMA Centre Discussion Papers in Finance icma-dp2009-10, Henley Business School, University of Reading, revised Sep 2009.
    • Handle: RePEc:rdg:icmadp:icma-dp2009-10
    as

    Download full text from publisher

    File URL: http://www.icmacentre.ac.uk/files/icma_dp200910marcel.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gibson, Rajna & Schwartz, Eduardo S, 1990. "Stochastic Convenience Yield and the Pricing of Oil Contingent Claims," Journal of Finance, American Finance Association, vol. 45(3), pages 959-976, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Unterschultz, James R., 2000. "New Instruments For Co-Ordination And Risk Sharing Within The Canadian Beef Industry," Project Report Series 24046, University of Alberta, Department of Resource Economics and Environmental Sociology.
    2. 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.
    3. Tomas Björk & Magnus Blix & Camilla Landén, 2006. "On Finite Dimensional Realizations For The Term Structure Of Futures Prices," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 281-314.
    4. Guedes, José & Santos, Pedro, 2016. "Valuing an offshore oil exploration and production project through real options analysis," Energy Economics, Elsevier, vol. 60(C), pages 377-386.
    5. Czudaj Robert L., 2020. "The role of uncertainty on agricultural futures markets momentum trading and volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-39, June.
    6. Jilong Chen & Christian Ewald & Ruolan Ouyang & Sjur Westgaard & Xiaoxia Xiao, 2022. "Pricing commodity futures and determining risk premia in a three factor model with stochastic volatility: the case of Brent crude oil," Annals of Operations Research, Springer, vol. 313(1), pages 29-46, June.
    7. Moreno, Manuel & Novales, Alfonso & Platania, Federico, 2019. "Long-term swings and seasonality in energy markets," European Journal of Operational Research, Elsevier, vol. 279(3), pages 1011-1023.
    8. Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2019. "Jumps in commodity markets," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 55-70.
    9. Joëts, Marc & Mignon, Valérie & Razafindrabe, Tovonony, 2017. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 313-326.
    10. Ames, Matthew & Bagnarosa, Guillaume & Matsui, Tomoko & Peters, Gareth W. & Shevchenko, Pavel V., 2020. "Which risk factors drive oil futures price curves?," Energy Economics, Elsevier, vol. 87(C).
    11. Carlos Andres Zapata Quimbayo & Carlos Armando Mej¨ªa Vega, 2019. "Real Options Valuation in Gold Mining Projects under Multinomial Tree Approach," Business and Economic Research, Macrothink Institute, vol. 9(3), pages 204-218, September.
    12. Steffen Volkenand & Günther Filler & Martin Odening, 2020. "Price Discovery and Market Reflexivity in Agricultural Futures Contracts with Different Maturities," Risks, MDPI, vol. 8(3), pages 1-17, July.
    13. Back, Janis & Prokopczuk, Marcel & Rudolf, Markus, 2013. "Seasonality and the valuation of commodity options," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 273-290.
    14. Möst, Dominik & Keles, Dogan, 2010. "A survey of stochastic modelling approaches for liberalised electricity markets," European Journal of Operational Research, Elsevier, vol. 207(2), pages 543-556, December.
    15. Björn Lutz, 2010. "Pricing of Derivatives on Mean-Reverting Assets," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-02909-7, October.
    16. Constantino Hevia & Ivan Petrella & Martin Sola, 2018. "Risk premia and seasonality in commodity futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 853-873, September.
    17. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    18. Aur'elien Alfonsi & Nerea Vadillo, 2023. "Risk valuation of quanto derivatives on temperature and electricity," Papers 2310.07692, arXiv.org.
    19. Ian Davidson & Yoshikatsu Shinozawa & Mark Tippett, 2009. "Capital Project Analysis When Cash Flows Evolve as a Continuous Time Branching Process," Abacus, Accounting Foundation, University of Sydney, vol. 45(1), pages 44-65, March.
    20. Wurm, Laura, 2021. "Strangling speculation: The effect of the 1903 Viennese futures trading ban," QUCEH Working Paper Series 21-09, Queen's University Belfast, Queen's University Centre for Economic History.

    More about this item

    Keywords

    Commodity Pricing; CARMA; Futures; Crude Oil;
    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

    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-dp2009-10. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.