摘要
猪肉价格波动直接关系到物价水平,对居民生活产生显著影响。因此,研究生猪市场价格波动规律、找出可准确预测猪肉价格走势的工具,进而采取可行的应对措施十分重要。为更好地分析上海白条猪月均批发价格走势特征,增强对上海市场白条猪批发价格的预见性,采用走势特征分析和建模方法,对2010年1月至2020年3月上海市场白条猪月均批发价格走势进行预测分析。结果显示:上海白条猪月均批发价格走势波动较大,呈现出“W”型价格波动规律,表现出较明显的季节性;价格波动周期时长为48个月,价格高点多出现在每年的9月,价格低点多出现在4月。进一步分析发现,SARIMA (3,1,3)×(3,1,3) 12模型能较好地表示上海白条猪月均价格的波动特征,在分析预测上海白条猪市场月均批发价格时优于其他模型。SARIMA模型可用于分析预测上海市场白条猪批发价格的未来走势,模拟结果有效地预测了猪肉市场价格的显著波动。
The fluctuation of pork price is dlirectly related to the price level,which has a significant impact on residents'lives.Therefore,it is very important to study the fluctuation rules of pork market prices,find tools that can accurately predict pork prices,and take feasible countermeasures.In order to better analyze the trend characteristics of the monthly average wholesale price of pork in Shanghai,and enhance the predictability of the wholesale price of pork in Shanghai market,the trend characteristics analysis and modeling methods were adopted to analyze Shanghai market prices from January 2010 to March 2020,and the monthly average wholesale price trend of pork in the market was forecasted and analyzed.The results showed that:the monthly average wholesale price of pork in Shanghai fluctuates greatly,showing a W-shaped price fluctuation law,with a relatively obvious seasonality.The analysis found that the price fluctuation cycle is 48 months long,most of the high prices highs appear in September each year,and most of the low prices appear in April.The further analysis found that the SARIMA(3,1,3)×(3,1,3)12 model can better represent the fluctuation characteristics of the monthly average price ofShanghai pork,and is better than other models in analyzing and predicting the monthly average wholesaleprice of Shanghai pork.The SARIMA model can be used to analyze and predict the future trend of thewholesale price of pork in Shanghai market,the simulated results effectively prognose the significantfluctuations in market price of pork.
作者
许叶颖
杨娟
赵京音
马佳
钱婷婷
郑秀国
Xu Yeying;Yang Juan;Zhao Jingyin;Ma Jia;Qian Tingting;Zheng Xiuguo(Agricultural Information Institutes of Science and Technology,Shanghai Academy of A griculural Sciences,Shanghai Engineering Research Center of Information Technology in Agriculture,Shanghai 201403)
出处
《农业展望》
2023年第4期9-15,共7页
Agricultural Outlook
基金
上海市农业农村委农产品市场分析师“上海市农产品全产业链市场信息监测预警分析”任务资助。
