IDEAS home Printed from https://ideas.repec.org/a/taf/apmtfi/v9y2002i1p21-43.html
   My bibliography  Save this article

Energy futures prices: term structure models with Kalman filter estimation

Author

Listed:
  • Mihaela Manoliu
  • Stathis Tompaidis

Abstract

We present a class of multi-factor stochastic models for energy futures prices, similar to the interest rate futures models recently formulated by Heath. We do not postulate directly the risk-neutral processes followed by futures prices, but define energy futures prices in terms of a spot price, not directly observable, driven by several stochastic factors. Our formulation leads to an expression for futures prices which is well suited to the application of Kalman filtering techniques together with maximum likelihood estimation methods. Based on these techniques, we perform an empirical study of a one- and a two-factor model for futures prices for natural gas.

Suggested Citation

  • Mihaela Manoliu & Stathis Tompaidis, 2002. "Energy futures prices: term structure models with Kalman filter estimation," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(1), pages 21-43.
    • Handle: RePEc:taf:apmtfi:v:9:y:2002:i:1:p:21-43
    DOI: 10.1080/13504860210126227
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/13504860210126227
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13504860210126227?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    2. David Heath & Robert Jarrow & Andrew Morton, 2008. "Bond Pricing And The Term Structure Of Interest Rates: A New Methodology For Contingent Claims Valuation," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 13, pages 277-305, World Scientific Publishing Co. Pte. Ltd..
    3. Miltersen, Kristian R. & Schwartz, Eduardo S., 1998. "Pricing of Options on Commodity Futures with Stochastic Term Structures of Convenience Yields and Interest Rates," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(1), pages 33-59, March.
    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. Max F. Schöne & Stefan Spinler, 2017. "A four-factor stochastic volatility model of commodity prices," Review of Derivatives Research, Springer, vol. 20(2), pages 135-165, July.
    2. Gonzalo Cortazar & Simon Gutierrez & Hector Ortega, 2016. "Empirical Performance of Commodity Pricing Models: When is it Worthwhile to Use a Stochastic Volatility Specification?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 457-487, May.
    3. Ke Du, 2013. "Commodity Derivative Pricing Under the Benchmark Approach," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2, July-Dece.
    4. Anh Ngoc Lai & Constantin Mellios, 2016. "Valuation of commodity derivatives with an unobservable convenience yield," Post-Print halshs-01183166, HAL.
    5. Leif Andersen, 2010. "Markov models for commodity futures: theory and practice," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 831-854.
    6. Cortazar, Gonzalo & Lopez, Matias & Naranjo, Lorenzo, 2017. "A multifactor stochastic volatility model of commodity prices," Energy Economics, Elsevier, vol. 67(C), pages 182-201.
    7. Iván Blanco, Juan Ignacio Peña, and Rosa Rodriguez, 2018. "Modelling Electricity Swaps with Stochastic Forward Premium Models," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    8. Ke Du, 2013. "Commodity Derivative Pricing Under the Benchmark Approach," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2013, January-A.
    9. 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.
    10. Secomandi, Nicola & Seppi, Duane J., 2014. "Real Options and Merchant Operations of Energy and Other Commodities," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 6(3-4), pages 161-331, July.
    11. Paschke, Raphael & Prokopczuk, Marcel, 2010. "Commodity derivatives valuation with autoregressive and moving average components in the price dynamics," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2742-2752, November.
    12. 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.
    13. 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.
    14. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    15. Fleten, Stein-Erik & Näsäkkälä, Erkka, 2003. "Gas fired power plants: Investment timing, operating flexibility and abandonment," MPRA Paper 217, University Library of Munich, Germany, revised Jun 2006.
    16. Richter, Martin & Sørensen, Carsten, 2002. "Stochastic Volatility and Seasonality in Commodity Futures and Options: The Case of Soybeans," Working Papers 2002-4, Copenhagen Business School, Department of Finance.
    17. Pieroni, Luca & Ricciarelli, Matteo, 2008. "Modelling dynamic storage function in commodity markets: Theory and evidence," Economic Modelling, Elsevier, vol. 25(5), pages 1080-1092, September.
    18. Gareth William Peters & Mark Briers & Pavel Shevchenko & Arnaud Doucet, 2013. "Calibration and Filtering for Multi Factor Commodity Models with Seasonality: Incorporating Panel Data from Futures Contracts," Methodology and Computing in Applied Probability, Springer, vol. 15(4), pages 841-874, December.
    19. Rajnish Kamat & Shmuel S. Oren, 2002. "Exotic Options for Interruptible Electricity Supply Contracts," Operations Research, INFORMS, vol. 50(5), pages 835-850, October.
    20. Paschke, Raphael & Prokopczuk, Marcel, 2007. "Integrating Multiple Commodities in a Model of Stochastic Price Dynamics," MPRA Paper 5412, University Library of Munich, Germany.

    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:taf:apmtfi:v:9:y:2002:i:1:p:21-43. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAMF20 .

    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.