李干琼农产品市场价格短期预测方法与模型研究_基于时间序列模型的预测_李干琼.pdfVIP

　2011, 16(2):172-178 Journal of China A g ricultur al U nive rsity ——— ＊ 李干琼　许世卫 　李哲敏　董晓霞 ( / , 100081) 　　为提高农产品市场价格的预见性, 及早采取措施减缓价格波动, 以全国西红柿月 批发市场价格为预测 目标,综合利用季节虚拟变量法、Census X 12 法、移动平均比率法、Ho lt-W inters 季节指数平滑法、SA R M A 法等建 立短期预测模型, 并根据模型预测误差大小赋予不同的权重值, 从而建立组合预测方法。 实证分析结果表明:单 一 模型预测误差波动较大, 总体上随着预测周期变长精 下降。在 2009 年的评估预测中,所建立的5 个单 一短期预 测模型平均绝对误差百分比(M A P E)为10 %左右, 其中H olt-Winter s 季节指数平滑法建立的短期预测模型精 最 高, M A P E 为 6.81%。如果预测提前期为3 个月, SA R M A 模型的预测精 更高, 准确率达到95%以上。在实证 分析的基础上, 采用组合预测方法对2010 年西红柿价格进行了预测。 　农产品;市场价格;预测模型 　F 323.7　　　　1007-4333(20 11)02-0172-07 　　　　A Study onshort-termforecasting methods and modeling of agro-product market price: Forecasting based onthe time series models ＊ LIGan-qiong, XUShi-wei , LIZhe-min, D NGXiao-xia (Agricultural Information Institute, Chinese Academy of Agricultural Sciences/Key Lab of Digital Agricultural Early Warning Technology, Ministry of Agriculture, Beijing 0008 , China) Abstract　In order to improve the predictability of agro-product market price and to take measures to reduce price fluctuation, this study selected the wholesale price of tomatoes as an object and employed the five methods, the seasonal dummy variables, the Census X 2 method, the moving average method,the Holt-Winters seasonal exponential smoothing method and the SARIMA, to establish short-term forecasting models.A combination forecasting model was establishedand the weights used in the model were calculated according to the single model prediction error.The results showed that the error of single model fluctuated greatly and