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Seasonal volatility in agricultural markets : modelling and empirical investigations

Author

Listed:
  • Lorenz Schneider

    (EM - EMLyon Business School)

  • Bertrand Tavin

    (EM - EMLyon Business School)

Abstract

This paper deals with the issue of modelling the volatility of futures prices in agricultural markets. We develop a multi-factor model in which the stochastic volatility dynamics incorporate a seasonal component. In addition, we employ a maturity-dependent damping term to account for the Samuelson effect. We give the conditions under which the volatility dynamics are well defined and obtain the joint characteristic function of a pair of futures prices. We then derive the state-space representation of our model in order to use the Kalman filter algorithm for estimation and prediction. The empirical analysis is carried out using daily futures data from 2007 to 2019 for corn, cotton, soybeans, sugar and wheat. In-sample, the seasonal models clearly outperform the nested non-seasonal models in all five markets. Out-of-sample, we predict volatility peaks with high accuracy for four of these five commodities.

Suggested Citation

  • Lorenz Schneider & Bertrand Tavin, 2024. "Seasonal volatility in agricultural markets : modelling and empirical investigations," Post-Print hal-04514341, HAL.
    • Handle: RePEc:hal:journl:hal-04514341
    as

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    Cited by:

    1. Richard Wamalwa Wanzala & Lawrence Ogechukwu Obokoh, 2024. "Sustainability Implications of Commodity Price Shocks and Commodity Dependence in Selected Sub-Saharan Countries," Sustainability, MDPI, vol. 16(20), pages 1-26, October.
    2. Tang, Wenjin & Bu, Hui & Ji, Yuqiong & Li, Zhongfei, 2024. "Market uncertainty and information content in complex seasonality of prices," Pacific-Basin Finance Journal, Elsevier, vol. 86(C).

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