4.7 Article

Developing a Moving Average Crossover Strategy as an Alternative Hedging Strategy for the South Africa Maize Market

Journal

AGRICULTURE-BASEL
Volume 12, Issue 8, Pages -

Publisher

MDPI
DOI: 10.3390/agriculture12081227

Keywords

technical analysis; maize; South Africa; marketing strategies; agricultural derivatives market

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Grain marketing is complex, but tailor-made moving average crossover (MAC) strategies have been found to be adaptable and effective for grain producers with different risk levels. Moreover, selling grain early in the marketing season is more beneficial for risk-averse producers, while spreading marketing activities throughout the season is more advantageous for risk-neutral producers.
Grain marketing is complex because important decisions are made on the timing of sales and the quantities sold at every trading activity. The literature suggest various grain-hedging strategies, however these strategies are not adaptable to changing market conditions or are difficult for a producer to implement. To address these limitations, our study developed tailor-made moving average crossover (MAC) strategies that are adaptable to changing market conditions and can be easily followed by risk neutral and risk averse grain producers. The study used daily closing prices for the white maize May futures contract for the period 2009/2010 to 2019/2020. An optimization model was solved using the evolutionary algorithm embedded in Excel (R) to identify the optimal MAC strategy that maximizes the margin above marketing cost for a risk aversion level. The results showed that optimal MAC strategies differ amongst producers with different levels of risk aversion. Furthermore, it was found that the risk-averse producers perform best by marketing their grain early in the marketing season. Meanwhile, the risk-neutral producers perform better by spreading their marketing activities throughout the season. The results further showed that the optimal MAC strategies performed better than the previously proposed routine strategies. The conclusion is therefore that an optimal MAC strategy outperforms routine strategies because of its ability to adapt to changing market conditions, while still being easy to implement.

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