IDEAS home Printed from
   My bibliography  Save this article

Nonparametric estimation of market risk: an application to agricultural commodity futures


  • Abdoul G. Sam


Purpose - While the extant literature is replete with theoretical and empirical studies of value at risk (VaR) methods, only a few papers have applied the concept of VaR to quantify market risk in the context of agricultural finance. Furthermore, papers that have done so have largely relied on parametric methods to recover estimates of the VaR. The purpose of this paper is to assess extreme market risk on investment in three actively traded agricultural commodity futures. Design/methodology/approach - A nonparametric Kernel method was implemented which accommodates fat tails and asymmetry of the portfolio return density as well as serial correlation of the data, to estimate market risk for investments in three actively traded agricultural futures contracts: corn, soybeans, and wheat. As a futures contract is a zero-sum game, the VaR for both short and long sides of the market was computed. Findings - It was found that wheat futures are riskier than either corn or soybeans futures over both periods considered in the study (2000-2008 and 2006-2008) and that all three commodities have experienced a sharp increase in market risk over the 2006-2008 period, with VaR estimates 10-43 percent higher than the long-run estimates. Research limitations/implications - Research is based on cross-sectional data and does not allow for dynamic assessment of expenditure elasticities. Originality/value - This paper differs methodologically from previous applications of VaR in agricultural finance in that a nonparametric Kernel estimator was implemented which is exempt of misspecification risk, in the context of risk management of investment in agricultural futures contracts. The application is particularly relevant to grain elevator businesses which purchase grain from farmers on a forward contract basis and then turn to the futures markets to insure against falling prices.

Suggested Citation

  • Abdoul G. Sam, 2010. "Nonparametric estimation of market risk: an application to agricultural commodity futures," Agricultural Finance Review, Emerald Group Publishing, vol. 70(2), pages 285-297, August.
  • Handle: RePEc:eme:afrpps:v:70:y:2010:i:2:p:285-297

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers

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

    References listed on IDEAS

    1. Ait-Sahalia, Yacine, 1996. "Testing Continuous-Time Models of the Spot Interest Rate," Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 385-426.
    2. Brooks, C. & Clare, A.D. & Dalle Molle, J.W. & Persand, G., 2005. "A comparison of extreme value theory approaches for determining value at risk," Journal of Empirical Finance, Elsevier, vol. 12(2), pages 339-352, March.
    3. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, April.
    4. Gourieroux, C. & Laurent, J. P. & Scaillet, O., 2000. "Sensitivity analysis of Values at Risk," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 225-245, November.
    5. Song Xi Chen, 2005. "Nonparametric Inference of Value-at-Risk for Dependent Financial Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(2), pages 227-255.
    6. Sam, Abdoul G. & Jiang, George J., 2009. "Nonparametric Estimation of the Short Rate Diffusion Process from a Panel of Yields," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(05), pages 1197-1230, October.
    7. William W. Wilson & William E. Nganje & Cullen R. Hawes, 2007. "Value-at-Risk in Bakery Procurement," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 29(3), pages 581-595.
    8. Chu-Hsiung Lin & Shan-Shan Shen, 2006. "Can the student-t distribution provide accurate value at risk?," Journal of Risk Finance, Emerald Group Publishing, vol. 7(3), pages 292-300, May.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. repec:spr:chinre:v:10:y:2017:i:3:d:10.1007_s12187-016-9378-y is not listed on IDEAS
    2. Shuying Shen & Abdoul G. Sam & Eugene Jones, 2014. "Credit Card Indebtedness and Psychological Well-Being Over Time: Empirical Evidence from a Household Survey," Journal of Consumer Affairs, Wiley Blackwell, vol. 48(3), pages 431-456, October.


    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:eme:afrpps:v:70:y:2010:i:2:p:285-297. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Virginia Chapman). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.