This study develops and estimates mixture models of crop price comovements using copula functions, which allow for departures from normality during extreme market circumstances. The models also account for unique time-series patterns inherent in crop price data. The results point to two main conclusions. First, mixture models appear to provide an easy-to-estimate approach for capturing real-life crop price movements. Second, mixture models find that, during extreme market downswings, correlations in price movements strengthen by several orders of magnitude. These results suggest that structured securities assembled from different crops tend to lose diversified protection during extreme market downswings, the exact times when such protection is needed most."> This study develops and estimates mixture models of crop price comovements using copula functions, which allow for departures from normality during extreme market circumstances. The models also account for unique time-series patterns inherent in crop price data. The results point to two main conclusions. First, mixture models appear to provide an easy-to-estimate approach for capturing real-life crop price movements. Second, mixture models find that, during extreme market downswings, correlations in price movements strengthen by several orders of magnitude. These results suggest that structured securities assembled from different crops tend to lose diversified protection during extreme market downswings, the exact times when such protection is needed most."> This study develops and estimates mixture models of crop price comovements using copula functions, which allow for departures from normali">
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Crop price comovements during extreme market downturns

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  • David M. Zimmer
Abstract
type="main" xml:id="ajar12119-abs-0001"> This study develops and estimates mixture models of crop price comovements using copula functions, which allow for departures from normality during extreme market circumstances. The models also account for unique time-series patterns inherent in crop price data. The results point to two main conclusions. First, mixture models appear to provide an easy-to-estimate approach for capturing real-life crop price movements. Second, mixture models find that, during extreme market downswings, correlations in price movements strengthen by several orders of magnitude. These results suggest that structured securities assembled from different crops tend to lose diversified protection during extreme market downswings, the exact times when such protection is needed most.

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  • David M. Zimmer, 2016. "Crop price comovements during extreme market downturns," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 60(2), pages 265-283, April.
    • Handle: RePEc:bla:ajarec:v:60:y:2016:i:2:p:265-283
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    File URL: http://hdl.handle.net/10.1111/ajar.2016.60.issue-2
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    Cited by:

    1. Liu, Qi & Niu, Jun & Wood, Jeffrey D. & Kang, Shaozhong, 2022. "Spatial optimization of cropping pattern in the upper-middle reaches of the Heihe River basin, Northwest China," Agricultural Water Management, Elsevier, vol. 264(C).
    2. Carlson, Mari K. & Rezitis, Anthony N., 2018. "Integration of the EU broiler meat markets – Application of Regular Vine Copulas," 2018 Annual Meeting, August 5-7, Washington, D.C. 273864, Agricultural and Applied Economics Association.

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