Seasonal Volatility in Agricultural Markets: Modelling and Empirical Investigations

40 Pages Posted: 20 Jun 2015 Last revised: 11 Mar 2021

See all articles by Lorenz Schneider

Lorenz Schneider

EMLYON Business School

Bertrand Tavin

emlyon business school

Date Written: January 7, 2021

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.

Keywords: Stochastic Volatility, Model Selection, Agricultural Commodities, Seasonal Volatility

JEL Classification: C51, C52, D81

Suggested Citation

Schneider, Lorenz and Tavin, Bertrand, Seasonal Volatility in Agricultural Markets: Modelling and Empirical Investigations (January 7, 2021). Available at SSRN: https://ssrn.com/abstract=2620584 or http://dx.doi.org/10.2139/ssrn.2620584

Lorenz Schneider

EMLYON Business School ( email )

23 Avenue Guy de Collongue
Ecully, 69132
France

Bertrand Tavin (Contact Author)

emlyon business school ( email )

23 Avenue Guy de Collongue
Ecully, 69132
France

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