Volatility transmission in the South African white maize futures market

Abstract

Research in the United States’ agricultural futures markets have found maize (what they refer to as corn) to be the commodity that most broadly received and transmitted volatility transmissions. South Africa is the main emerging market for price discovery of maize in Africa, with white maize being the largest and most liquid agricultural commodity futures contract traded on the South African Futures Exchange (SAFEX). This paper examines volatility spillover effects in white maize futures against several other domestic grain and external market futures listed on SAFEX. Using daily return data, a multivariate GARCH approach is employed to study spillover effects between grain futures (white maize, yellow maize, wheat and sunflower seed), currency futures (Dollar/Rand and Euro/Rand), equity futures (JSE Top 40 Index) and interest rate futures (JIBA). A Dynamic Conditional Correlation (DCC) model is used to evaluate the degree of interdependence between futures markets which is measured through a time-variant conditional correlation matrix. The results indicate that the South African futures markets analyzed are highly interrelated, with significant dependence and volatility transmissions being observed. Furthermore, the results also highlight that these interrelations are changing over time. The findings have important implications for portfolio allocations, hedging strategies and policy and regulatory initiatives.

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Fig. 1

Source: Bloomberg and authors’ own calculation

Fig. 2

Source: Bloomberg and authors’ own calculation

Fig. 3
Fig. 4

Notes

  1. 1.

    The International Maize and Wheat Improvement Center (CIMMYT) is a global leader in publicly funded maize and wheat research and related farming systems.

  2. 2.

    Source: Authors’ own calculation using data from the JSE—available on request.

  3. 3.

    Price limits are a regulatory tool intended to control volatility in a financial market.

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Sayed, A., Auret, C. Volatility transmission in the South African white maize futures market. Eurasian Econ Rev 10, 71–88 (2020). https://doi.org/10.1007/s40822-019-00128-y

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Keywords

  • Volatility spillover
  • Volatility transmission
  • Multivariate GARCH
  • Dynamic conditional correlations
  • White maize futures
  • Grain price volatility

JEL classification

  • C32
  • G13
  • G14
  • G32
  • Q13