Further Evidence on Soybean Marketing Strategies: The Role of Options

Frank, Stuart D.; Irwin, Scott H.; Pfeiffer, George H.; Curtis, Charles E.

doi:10.2307/1349109

Cited by 6 publications

(5 citation statements)

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“…Kenyon and Shapiro (1976) and Frank et al (1989) demonstrate that processors could have enhanced returns and reduced risk by locking in above normal crush margins in the futures markets.…”

Section: Introductionmentioning

confidence: 99%

The soybean crush spread: Empirical evidence and trading strategies

Simon¹

1999

J. Fut. Mark.

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This article finds that deviations of the soybean crush spread from its long‐run equilibrium were transitory during the sample period from January 1985 through February 1995. This equilibrium is characterized by strong seasonality and by a persistent uptrend in soymeal and soyoil prices relative to soybean prices. A tendency also exists for the crush spread to revert toward its most recent 5‐day average. Simulations demonstrate that trading rules based on these results would have been profitable. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 271–289, 1999

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“…Kenyon and Shapiro (1976) and Frank et al (1989) demonstrate that processors could have enhanced returns and reduced risk by locking in above normal crush margins in the futures markets.…”

Section: Introductionmentioning

confidence: 99%

The soybean crush spread: Empirical evidence and trading strategies

Simon¹

1999

J. Fut. Mark.

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“…Foreign scholars such as Kenyon and Shapiro (1976) [5], Frank et al (1989) [6] proved oil squeezed the price on the high side through the purchase of soybean futures at the same time when selling soybean meal, soybean oil futures to lock the high press spreads to increase revenue and reduce risk. Mitchell (2010) [7] think soybean, soybean meal and soybean oil squeezing spread between short-term deviate from the long-term equilibrium after will not necessarily mean reversion, on the basis of volatile conditions by adjusting the storehouse to increase price earnings ratio, so as to realize the cross between and among commodity arbitrage.…”

Section: Soybean Futures Arbitrage Methodsmentioning

confidence: 99%

Soybean Futures Arbitrage: A Literature Review

Wang¹

2017

Proceedings of the 7th International Conference on Management, Education, Information and Control (MEICI 2017)

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Abstract. Soybean futures has been listed earlier in mainland China, while the cumulative volume of soybean futures is larger than other futures. This paper studies domestic and foreign achievements of soybean futures arbitrage from aspects of arbitrage methods and arbitrage strategies, and classifies these literatures. We should consider the price volatility of soybean futures and the long-term equilibrium relationship between soybean futures and other relative futures.

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“…Consequently, the choices between risky prospects are based on dispersion of the risky prospect without considering the level of wealth [31]. The CE for a discrete distribution of random MAMCs associated with a specific marketing strategy is calculated as follows, for the negative exponential utility function [22]:…”

Section: Choice Amongst Marketing Strategiesmentioning

confidence: 99%

“…However, it can be argued that the pricing strategies based on these sophisticated technical indicators are too complex for producers to understand, and therefore will not be adopted by producers. The moving average crossover (MAC) pricing strategy is a less complex strategy that is easily understood by decision-makers, since it uses the activity of two simple moving averages to inform buying or selling decisions during the marketing year [21][22][23][24][25]. Furthermore, several researchers have demonstrated the potential of the MAC pricing strategy to dominate other strategies [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

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

Monteiro¹,

Grové²,

Matthews³

2022

Agriculture

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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® 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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Further Evidence on Soybean Marketing Strategies: The Role of Options

Cited by 6 publications

References 0 publications

The soybean crush spread: Empirical evidence and trading strategies

The soybean crush spread: Empirical evidence and trading strategies

Soybean Futures Arbitrage: A Literature Review

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

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