IDEAS home Printed from https://ideas.repec.org/p/ags/aawewp/37298.html
   My bibliography  Save this paper

Identification of stochastic processes for an estimated icewine temperature hedging variable

Author

Listed:
  • Cyr, Don
  • Kusy, Martin

Abstract

Weather derivatives are a relatively new form of financial security that can provide firms with the ability to hedge against the impact of weather related risks to their activities. Participants in the energy industry have employed standardized weather contracts trading on organized exchanges since 1999 and the interest in non-standardized contracts for specialized weather related risks is growing at an increasing rate. The purpose of this paper is to examine the potential use of weather derivatives to hedge against temperature related risks in Canadian ice wine production. Specifically we examine historical data for the Niagara region of the province of Ontario, Canada, the largest icewine producing region of the world, to determine an appropriate underlying variable for the design of an option contact that could be employed by icewine producers. Employing monte carlo simulation we derive a range of benchmark option values based upon varying assumptions regarding the stochastic process for an underlying temperature variable. The results show that such option contracts can provide valuable hedging opportunities for producers, given the historical seasonal temperature variations in the region.

Suggested Citation

  • Cyr, Don & Kusy, Martin, 2007. "Identification of stochastic processes for an estimated icewine temperature hedging variable," Working Papers 37298, American Association of Wine Economists.
    • Handle: RePEc:ags:aawewp:37298
    DOI: 10.22004/ag.econ.37298
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/37298/files/AAWE_WP05.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.37298?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
    ---><---

    References listed on IDEAS

    as
    1. Sean D. Campbell & Francis X. Diebold, 2005. "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 6-16, March.
    2. Richards, Timothy J. & Manfredo, Mark R. & Sanders, Dwight R., 2004. "Pricing Weather Derivatives," Working Papers 28536, Arizona State University, Morrison School of Agribusiness and Resource Management.
    3. Jewson,Stephen & Brix,Anders With contributions by-Name:Ziehmann,Christine, 2005. "Weather Derivative Valuation," Cambridge Books, Cambridge University Press, number 9780521843713, October.
    4. M. Davis, 2001. "Pricing weather derivatives by marginal value," Quantitative Finance, Taylor & Francis Journals, vol. 1(3), pages 305-308, March.
    5. Dwight R. Sanders, 2004. "Pricing Weather Derivatives," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1005-1017.
    6. Ait-Sahalia, Yacine, 2004. "Disentangling diffusion from jumps," Journal of Financial Economics, Elsevier, vol. 74(3), pages 487-528, December.
    7. Helyette Geman & M. Leonardi, 2005. "Alternative Approaches to Weather Derivatives Pricing," Post-Print halshs-00144304, HAL.
    8. repec:dau:papers:123456789/1386 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Ben Salk, Sana & Blondel, Serge & Daniel, Christophe & Deffains-Crapsky, Catherine & Jutard, Catherine & Sejourne, Bruno, 2007. "Management of climate risks in the wine sector: a field study on risky behaviour," 101st Seminar, July 5-6, 2007, Berlin Germany 9251, European Association of Agricultural Economists.
    2. Holemans, N. & Van Vuuren, G. & Styger, P., 2011. "Pricing weather derivatives for the Chardonnay cultivar in Wellington using a credit default swap methodology," International Journal of Agricultural Sciences and Technology (IJAGST), SvedbergOpen, vol. 50(4), December.

    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. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    2. Heng Xiong & Rogemar Mamon, 2018. "Putting a price tag on temperature," Computational Management Science, Springer, vol. 15(2), pages 259-296, June.
    3. repec:hum:wpaper:sfb649dp2009-046 is not listed on IDEAS
    4. Benth, Fred & Härdle, Wolfgang Karl & López Cabrera, Brenda, 2009. "Pricing of Asian temperature risk," SFB 649 Discussion Papers 2009-046, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Bertrand, Jean-Louis & Brusset, Xavier & Fortin, Maxime, 2015. "Assessing and hedging the cost of unseasonal weather: Case of the apparel sector," European Journal of Operational Research, Elsevier, vol. 244(1), pages 261-276.
    6. Turvey, Calum G. & Norton, Michael, 2008. "An Internet-Based Tool for Weather Risk Management," Agricultural and Resource Economics Review, Cambridge University Press, vol. 37(1), pages 63-78, April.
    7. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    8. Wolfgang Karl Härdle & Brenda López Cabrera, 2012. "The Implied Market Price of Weather Risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 19(1), pages 59-95, February.
    9. Birgit Lemmerer & Stephan Unger, 2019. "Modeling and pricing of space weather derivatives," Risk Management, Palgrave Macmillan, vol. 21(4), pages 265-291, December.
    10. repec:hum:wpaper:sfb649dp2014-006 is not listed on IDEAS
    11. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    12. Zhang, Li, 2008. "Three essays on agricultural risk and insurance," ISU General Staff Papers 2008010108000016857, Iowa State University, Department of Economics.
    13. Eirini Konstantinidi & Gkaren Papazian & George Skiadopoulos, 2015. "Modeling the Dynamics of Temperature with a View to Weather Derivatives," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 17, pages 511-544, World Scientific Publishing Co. Pte. Ltd..
    14. 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, August.
    15. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, August.
    16. Ahmet Göncü, 2013. "Comparison of temperature models using heating and cooling degree days futures," Journal of Risk Finance, Emerald Group Publishing, vol. 14(2), pages 159-178, February.
    17. Musshoff, Oliver & Hirschauer, Norbert, 2008. "Hedging von Mengenrisiken in der Landwirtschaft – Wie teuer dürfen „ineffektive“ Wetterderivate sein?," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 57(05), pages 1-12.
    18. 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.
    19. Jr‐Wei Huang & Sharon S. Yang & Chuang‐Chang Chang, 2018. "Modeling temperature behaviors: Application to weather derivative valuation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1152-1175, September.
    20. L. Kermiche & N. Vuillermet, 2016. "Weather derivatives structuring and pricing: a sustainable agricultural approach in Africa," Applied Economics, Taylor & Francis Journals, vol. 48(2), pages 165-177, January.
    21. Helene Hamisultane, 2010. "Utility-based pricing of weather derivatives," The European Journal of Finance, Taylor & Francis Journals, vol. 16(6), pages 503-525.
    22. Markus Stowasser, 2011. "Modelling rain risk: a multi-order Markov chain model approach," Journal of Risk Finance, Emerald Group Publishing, vol. 13(1), pages 45-60, December.

    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:ags:aawewp:37298. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaweeea.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.