摘要
为科学分析与预测农产品市场日价格走势,研究农产品市场日价格波动的随机性特征,增强价格的预见性和市场的调控性,选择全国西红柿日批发价格为预测对象,基于价格序列数据的ADF检验和ARCH效应检验,结合2008-2009年间731天日价格数据分析,利用ARIMA、ARCH、GARCH等现代时间序列法,分别建立西红柿日批发价格预测模型,并选取2010年1月1-10日进行样本外区间的评估预测。研究表明,3个日价格预测模型的平均绝对百分比误差(MAPE)都在2%以内,其中GARCH模型在预测中具有更高的精度;农产品市场价格超短期预测中,在没有突发性因素干扰的情况下,所建立的3个模型预测结果的精度比较理想,但对于突发性事件等引起的价格急剧变化难以定量化模拟和预测。
Many factors may cause the fluctuation of agro-product market prices,so the agro-prod- uct price often experience ups and downs,whose fluctuations are similar to the random walk. In order to scientifically analyze and predict the trend of daily price of agro-product market, this paper selected the daily wholesale price of tomatoes in China as object to model, and the data used in the modeling are be- tween 2008 and 2009 with daily prices for 731 days. The ultimate goal is to provide technical support for price forecasting and market regulation. According to the random features of daily price fluctuation of ag- ro-product market as well as ADF test and ARCH effect test based on price series data,this paper em- ployed the modern time series methods of ARIMA, ARCH and GARCH to establish daily wholesale price forecasting models of tomatoes respectively, and applied the models to forecast the tomato price from January 1,2010 to January 10,2010 as evaluation. The result shows that mean absolute percentage error （MAPE） of the three daily price forecasting models is less than 2%,among which the highest ac- curacy in forecasting is GARCH model. Accuracy of the three models forecasting is ideal if unexpected incidents don^t occur in super short-term agro-product market price forecasting. But it is hard to simu- late and forecast quantitatively for emergencies causing dramatic changes.
出处
《华中农业大学学报（社会科学版）》
2010年第6期40-45,共6页
Journal of Huazhong Agricultural University(Social Sciences Edition)
基金
国家"十一五"科技支撑计划重点项目"农产品数量安全智能分析与预警的关键技术及平台研究"(2009BADA9B01)
中央公益性科研院所基本科研业务费专项(2010-J-11)
关键词
农产品
市场
日价格
短期预测
模型
agro-products
market
daily price
short-term forecasting
model
