IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1905.07546.html
   My bibliography  Save this paper

Hedging crop yields against weather uncertainties -- a weather derivative perspective

Author

Listed:
  • Samuel Asante Gyamerah
  • Philip Ngare
  • Dennis Ikpe

Abstract

The effects of weather on agriculture in recent years have become a major global concern. Hence, the need for an effective weather risk management tool (i.e., weather derivatives) that can hedge crop yields against weather uncertainties. However, most smallholder farmers and agricultural stakeholders are unwilling to pay for the price of weather derivatives (WD) because of the presence of basis risks (product-design and geographical) in the pricing models. To eliminate product-design basis risks, a machine learning ensemble technique was used to determine the relationship between maize yield and weather variables. The results revealed that the most significant weather variable that affected the yield of maize was average temperature. A mean-reverting model with a time-varying speed of mean reversion, seasonal mean, and local volatility that depended on the local average temperature was then proposed. The model was extended to a multi-dimensional model for different but correlated locations. Based on these average temperature models, pricing models for futures, options on futures, and basket futures for cumulative average temperature and growing degree-days are presented. Pricing futures on baskets reduces geographical basis risk, as buyers have the opportunity to select the most appropriate weather stations with their desired weight preference. With these pricing models, farmers and agricultural stakeholders can hedge their crops against the perils of extreme weather.

Suggested Citation

  • Samuel Asante Gyamerah & Philip Ngare & Dennis Ikpe, 2019. "Hedging crop yields against weather uncertainties -- a weather derivative perspective," Papers 1905.07546, arXiv.org, revised Aug 2019.
  • Handle: RePEc:arx:papers:1905.07546
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1905.07546
    File Function: Latest version
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Debopam Rakshit & Ranjit Kumar Paul & Md Yeasin & Walid Emam & Yusra Tashkandy & Christophe Chesneau, 2023. "Modeling Asymmetric Volatility: A News Impact Curve Approach," Mathematics, MDPI, vol. 11(13), pages 1-14, June.
    2. Mohammed Faez Hasan & Noor Salah Abdelnaby Al-Ramadan, 2022. "Using Options Futures Derivatives Weather in Hedging," Technium Social Sciences Journal, Technium Science, vol. 31(1), pages 430-436, May.
    3. Ke Wan & Alain Kornhauser, 2023. "Market Making and Pricing of Financial Derivatives based on Road Travel Times," Papers 2305.02523, arXiv.org, revised May 2023.
    4. Yuji Yamada & Takuji Matsumoto, 2023. "Construction of Mixed Derivatives Strategy for Wind Power Producers," Energies, MDPI, vol. 16(9), pages 1-26, April.
    5. Angelos Prentzas & Thomas Bournaris & Stefanos Nastis & Christina Moulogianni & George Vlontzos, 2024. "Enhancing Sustainability through Weather Derivative Option Contracts: A Risk Management Tool in Greek Agriculture," Sustainability, MDPI, vol. 16(17), pages 1-18, August.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:1905.07546. 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.

    We have no bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.