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For the sake of a better cross-commodity arbitrage in the futures market, WNN (wavelet neural network) is adopted to analyze the previous spread and predict the future in this paper. Firstly, the correlation coefficient of previous prices between the two goods is calculated in order to examine whether there is arbitrage opportunity. Considered that the spread could be affected by many nonlinearity factors and BP neural network has slow convergence rat, BP neural network is combined with wavelet analysis which has excellent partial analysis ability.In this way, the prediction model about soya oil and soybean meal spreads is built based on WNN Compared the result calculated through that method with only BP neural network’s: WNN is superior to neural network in predicting rapid fluctuation and secular trend.

The Empirical Analysis for the Spread of Soya Oil and Soybean Meal Based on Wavelet Neural Network