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Corn and Soybean Futures Price Intelligent Forecasting Based on Deep Learning
XU Yulin, KANG Mengzhen, WANG Xiujuan, HUA Jing, WANG Haoyu, SHEN Zhen
Corn and Soybean Futures Price Intelligent Forecasting Based on Deep Learning
Corn and soybean are upland grain in the same season, and the contradiction of scrambling for land between corn and soybean is prominent in China, so it is necessary to explore the price relations between corn and soybean. In addition, agricultural futures have the function of price discovery compared with the spot. Therefore, the analysis and prediction of corn and soybean futures prices are of great significance for the management department to adjust the planting structure and for farmers to select the crop varieties. In this study, the correlation between corn and soybean futures prices was analyzed, and it was found that the corn and soybean futures prices have a strong correlation by correlation test, and soybean futures price is the Granger reason of corn futures price by Granger causality test. Then, the corn and soybean futures prices were predicted using a long short-term memory (LSTM) model. To optimize the futures price prediction model performance, Attention mechanism was introduced as Attention-LSTM to assign weights to the outputs of the LSTM model at different times. Specifically, LSTM model was used to process the input sequence of futures prices, the Attention layer assign different weights to the outputs, and then the model output the prediction results after a layer of linearity. The experimental results showed that Attention-LSTM model could significantly improve the prediction performance of both corn and soybean futures prices compared to autoregressive integrated moving average model (ARIMA), support vector regression model (SVR), and LSTM. For example, mean absolute error (MAE) was improved by 3.8% and 3.3%, root mean square error (RMSE) was improved by 0.6% and 1.8% and mean absolute error percentage (MAPE) was improved by 4.8% and 2.9% compared with a single LSTM, respectively. Finally, the corn futures prices were forecasted using historical corn and soybean futures prices together. Specifically, two LSTM models were used to process the input sequences of corn futures prices and soybean futures prices respectively, two parameters were trained to perform a weighted summation of the output of two LSTM models, and the prediction results were output by the model after a layer of linearity. The experimental results showed that MAE was improved by 6.9%, RMSE was improved by 1.1% and MAPE was improved by 5.3% compared with the LSTM model using only corn futures prices. The results verify the strong correlation between corn and soybean futures prices at the same time. In conclusion, the results verify the Attention-LSTM model can improve the performances of soybean and corn futures price forecasting compared with the general prediction model, and the combination of related agricultural futures price data can improve the prediction performances of agricultural product futures forecasting model.
corn and soybean futures / futures price forecast / LSTM model / Attention / deep learning / support vector regression {{custom_keyword}} /
Table 1 Correlation coefficient matrix of corn and soybean futures prices表 1 玉米和大豆期货价格相关系数矩阵 |
玉米期货价格 | 大豆期货价格 | |
---|---|---|
玉米期货价格 | 1 | 0.841042 |
大豆期货价格 | 0.841042 | 1 |
Table 2 Granger test results of corn and soybean futures prices表 2 大豆和与玉米期货价格的格兰杰检验结果 |
原假设 | | 结论 |
---|---|---|
大豆 | 0.0000 | 拒绝 |
玉米 | 0.2247 | 接受 |
Table 3 Forecast results of corn futures表 3 玉米期货的预测结果 |
模型 | MAE | RMSE | MAPE |
---|---|---|---|
ARIMA | 401.3278 | 539.2874 | 15.6619 |
SVR | 105.2223 | 124.7325 | 2.2771 |
LSTM | 14.3700 | 22.0111 | 0.6251 |
Attention-LSTM | 13.8260 | 21.8842 | 0.5949 |
Table 4 Forecast results of soybean futures表 4 大豆期货的预测结果 |
模型 | MAE | RMSE | MAPE |
---|---|---|---|
ARIMA | 1096.0313 | 1424.5800 | 20.6672 |
SVR | 82.5733 | 112.1443 | 1.7724 |
LSTM | 43.5901 | 65.2569 | 0.9093 |
Attention-LSTM | 42.1634 | 64.0829 | 0.8831 |
Table 5 Results of soybean futures forecasting with historical data of corn and soybean futures price表5 玉米和大豆期货历史数据预测大豆期货性能结果 |
数据 | 评价指标 | ||
---|---|---|---|
MAE | RMSE | MAPE | |
玉米期货历史数据 | 14.3700 | 22.0111 | 0.6251 |
玉米+大豆期货历史数据 | 13.3817 | 21.7791 | 0.5917 |
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