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Extreme price moves: an INGARCH approach to model coexceedances in commodity markets
[The market response to government crop news under different release regimes]

Author

Listed:
  • Bernardina Algieri
  • Arturo Leccadito

Abstract

This study presents a set of integer-valued generalised autoregressive conditional heteroskedastic models to identify possible transmission channels of joint extreme price moves (coexceedances) across a group of agricultural commodities. These models are very useful to identify factors affecting joint tail events and they are superior in terms of goodness of fit to models without autoregressive components. Emerging market demand, crude oil, exchange rate, stock market conditions and credit spread explain extreme joint returns. Psychological factors and the Monday effect play a role in affecting extreme events, while weather anomalies (El Niño and La Niña episodes) do not have explanatory power.

Suggested Citation

  • Bernardina Algieri & Arturo Leccadito, 2021. "Extreme price moves: an INGARCH approach to model coexceedances in commodity markets [The market response to government crop news under different release regimes]," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 48(4), pages 878-914.
    • Handle: RePEc:oup:erevae:v:48:y:2021:i:4:p:878-914.
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    File URL: http://hdl.handle.net/10.1093/erae/jbaa030
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    Cited by:

    1. Sun, Yiqun & Ji, Hao & Cai, Xiurong & Li, Jiangchen, 2023. "Joint extreme risk of energy prices-evidence from European energy markets," Finance Research Letters, Elsevier, vol. 56(C).
    2. Yang, Yao & Karali, Berna, 2022. "The Role of USDA Reports on Extreme Volatility Coexceedances: An Application to the Soybean Complex," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322104, Agricultural and Applied Economics Association.

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