IDEAS home Printed from https://ideas.repec.org/a/eee/jocoma/v21y2021ics240585131930087x.html

Analysis of the risk premium in the forward market for salmon

Author

Listed:
  • Benth, Fred Espen
  • Eikeset, Anne Maria
  • Levin, Simon Asher
  • Ren, Wanjuan

Abstract

We analyse forward prices observed at the Fishpool market, and propose a two-factor continuous-time stochastic process for modelling the time dynamics. The data analysis reveals that the two factors can be assumed to be a non-stationary compound Poisson process and a stationary continuous-time autoregressive dynamics, describing the bumps observed in the forward curves. We use the model to analyse the risk premium in the forward markets, and find a negative premium in the long end of the market which is in line with the theory of normal backwardation. However, contracts with short time to maturity have a risk premium with randomly changing sign, pointing towards a hedging pressure also induced by the demand-side of the market.

Suggested Citation

  • Benth, Fred Espen & Eikeset, Anne Maria & Levin, Simon Asher & Ren, Wanjuan, 2021. "Analysis of the risk premium in the forward market for salmon," Journal of Commodity Markets, Elsevier, vol. 21(C).
    • Handle: RePEc:eee:jocoma:v:21:y:2021:i:c:s240585131930087x
    DOI: 10.1016/j.jcomm.2019.100122
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S240585131930087X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jcomm.2019.100122?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

    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. P. Brockwell, 2001. "Lévy-Driven Carma Processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 113-124, March.
    3. Dietz, Simon & Bowen, Alex & Dixon, Charlie & Gradwell, Philip, 2016. "Climate value at risk of global financial assets," LSE Research Online Documents on Economics 66226, London School of Economics and Political Science, LSE Library.
    4. Asche, Frank & Misund, Bård & Oglend, Atle, 2016. "Determinants of the Atlantic salmon futures risk premium," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 6-17.
    5. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2008. "Stochastic Modeling of Electricity and Related Markets," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6811.
    6. Hendrik Bessembinder & Michael L. Lemmon, 2002. "Equilibrium Pricing and Optimal Hedging in Electricity Forward Markets," Journal of Finance, American Finance Association, vol. 57(3), pages 1347-1382, June.
    7. 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.
    8. Eugene F. Fama & Kenneth R. French, 2015. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 4, pages 79-102, World Scientific Publishing Co. Pte. Ltd..
    9. Schütz, Peter & Westgaard, Sjur, 2018. "Optimal hedging strategies for salmon producers," Journal of Commodity Markets, Elsevier, vol. 12(C), pages 60-70.
    10. Martin Reeves & Knut Haanaes & Claire Love & Simon Levin, 2012. "Sustainability as Adaptability," Journal of Applied Corporate Finance, Morgan Stanley, vol. 24(2), pages 14-22, June.
    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. Stefan Trück & Rafał Weron, 2016. "Convenience Yields and Risk Premiums in the EU‐ETS—Evidence from the Kyoto Commitment Period," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(6), pages 587-611, June.
    2. Andrés Mirantes & Javier Población & Gregorio Serna, 2015. "Commodity derivative valuation under a factor model with time-varying market prices of risk," Review of Derivatives Research, Springer, vol. 18(1), pages 75-93, April.
    3. Prilly Oktoviany & Robert Knobloch & Ralf Korn, 2021. "A machine learning-based price state prediction model for agricultural commodities using external factors," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1063-1085, December.
    4. 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.
    5. 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.
    6. Björn Lutz, 2010. "Pricing of Derivatives on Mean-Reverting Assets," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-02909-7, September.
    7. Mirantes, Andrés García & Población, Javier & Serna, Gregorio, 2013. "The stochastic seasonal behavior of energy commodity convenience yields," Energy Economics, Elsevier, vol. 40(C), pages 155-166.
    8. repec:aen:journl:ej39-2-pena is not listed on IDEAS
    9. Nikolay Gospodinov & Ibrahim Jamali, 2018. "Monetary policy uncertainty, positions of traders and changes in commodity futures prices," European Financial Management, European Financial Management Association, vol. 24(2), pages 239-260, March.
    10. 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.
    11. Shao, Chengwu & Bhar, Ramaprasad & Colwell, David B., 2015. "A multi-factor model with time-varying and seasonal risk premiums for the natural gas market," Energy Economics, Elsevier, vol. 50(C), pages 207-214.
    12. Longstaff, Francis & Wang, Ashley, 2002. "Electricity Forward Prices: A High-Frequency Empirical Analysis," University of California at Los Angeles, Anderson Graduate School of Management qt7mh2m2bt, Anderson Graduate School of Management, UCLA.
    13. Fred Espen Benth & Claudia Kluppelberg & Gernot Muller & Linda Vos, 2012. "Futures pricing in electricity markets based on stable CARMA spot models," Papers 1201.1151, arXiv.org.
    14. Cortazar, Gonzalo & Kovacevic, Ivo & Schwartz, Eduardo S., 2015. "Expected commodity returns and pricing models," Energy Economics, Elsevier, vol. 49(C), pages 60-71.
    15. Davidson Heath, 2019. "Macroeconomic Factors in Oil Futures Markets," Management Science, INFORMS, vol. 65(9), pages 4407-4421, September.
    16. Farshid Mehrdoust & Idin Noorani, 2023. "Valuation of Spark-Spread Option Written on Electricity and Gas Forward Contracts Under Two-Factor Models with Non-Gaussian Lévy Processes," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 807-853, February.
    17. Ernstsen, Rune Ramsdal & Boomsma, Trine Krogh, 2018. "Valuation of power plants," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1153-1174.
    18. Bégin, Jean-François & Gómez, Fabio & Ignatieva, Katja & Li, Han, 2025. "The stochastic behavior of electricity prices under scrutiny: Evidence from spot and futures markets," Energy Economics, Elsevier, vol. 144(C).
    19. Ewald, Christian & Zou, Yihan, 2021. "Analytic formulas for futures and options for a linear quadratic jump diffusion model with seasonal stochastic volatility and convenience yield: Do fish jump?," European Journal of Operational Research, Elsevier, vol. 294(2), pages 801-815.
    20. Markus Burger & Bernhard Klar & Alfred Muller & Gero Schindlmayr, 2004. "A spot market model for pricing derivatives in electricity markets," Quantitative Finance, Taylor & Francis Journals, vol. 4(1), pages 109-122.
    21. Bredin, Don & O'Sullivan, Conall & Spencer, Simon, 2021. "Forecasting WTI crude oil futures returns: Does the term structure help?," Energy Economics, Elsevier, vol. 100(C).

    More about this item

    Keywords

    ;
    ;
    ;

    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:eee:jocoma:v:21:y:2021:i:c:s240585131930087x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jcomm .

    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.