Summary
This paper investigates the soybean-oil "crush" spread, that is the profit margin gained by processing soybeans into soyoil. Soybeans form a large proportion (over 1/5th) of the agricultural output of US farmers and the profit margins gained will therefore have a wide impact on the US economy in general. The paper uses a number of techniques to forecast and trade the soybean crush spread. A traditional regression analysis is used as a benchmark against more sophisticated models such as a MultiLayer Perceptron (MLP), Recurrent Neural Networks and Higher Order Neural Networks. These are then used to trade the spread, the implementation of a number of filtering techniques as used in the literature are utilised to further refine the trading statistics of the models. The results show that the best model before transactions costs both in- and out-of-sample is the Recurrent Network generating a superior risk adjusted return to all other models investigated. However in the case of most of the models investigated the cost of trading the spread all but eliminates any profit potential.
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Extract
Modelling and Trading the Soybean-Oil Crush Spread with Recurrent and Higher Order Networks: A Comparative Analysis
1. Introduction
Motivation for this paper is taken from Dunis et al. (2005) who discover that trading the Gasoline Crack spread can lead to abnormal out- of- sample returns especially when traded using the neural network architectures described here. Further it is discovered that the application of a filter can further refine the trading statistics achieved. The Soybean Crush Spread can be interpreted as the profit margin gained by processing soybeans into soybean oil and soybean meal. It is simply the monetary difference between 1 bushel of soybeans on the one side and 1 bushel's worth of soybean oil and 1 bushel's worth of soybean meal on the other, all three of which have futures contracts that are traded on the Chicago Board of Trade (CBOT). The focus of this paper will be the spread between soybeans and soybean oil henceforth called "soybean-oil spread".Although large scale production of soybeans occurred only after the 2nd World War soybeans are now very important to US agriculture. In 2004 around 23% of all crops (by acre) planted in the US were soybeans. Approximately 400,000 farmers harvest 3.1 billion bushels of soybeans annually. Approximately 39 million tons of soymeal and about 18,800 million pounds of soybean oil was manufactured in the US1. It is easy to underestimate the impact soybean prices have on the US economy, and in particular the agricultural economy.Soybeans can be processed into two main products, soymeal and soy oil. Soymeal is used extensively in livestock feeds, mainly for poultry, swine a...See the full content of this document
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