| 摘要: |
| 根据价格风险体系的一般组成结构,文章以大菱鲆为例分析了我国海水鱼价格风险预警体系的组成。从产业的供给与需求及国家宏观政策等影响我国海水鱼市场价格的因素出发,以大菱鲆出池价格为例,作为海水鱼产业市场风险预警的警情指标,构建了我国大菱鲆产业价格风险预警的指标体系。运用BP神经网络对2012—2017年的季度调研样本作为原始数据对我国大菱鲆价格风险预警进行实证研究,研究表明，成鱼养殖面积、幼苗存量和牙鲆出池价格是大菱鲆价格变动的主要先行指标。验证了BP神经网络构建的风险预警模型对我国大菱鲆价格风险研究,具有实用性和可行性,并对针海水鱼产业提出了加强政府监管、提升方案有效性和加强技术创新等建议。 |
| 关键词: 价格风险预警 实证研究 海水鱼 预警 BP神经网络 |
| DOI： |
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| 基金项目:现代农业产业技术体系专项资金资助（CARS-49-G29）. |
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| The Early Warning of Sea Fish Price Risk in China:Taking Turbot as an Example |
| HUANG Minghong,YANG Zhengyong |
| College of Economics and Managements,Shanghai Ocean University;China Aquaculture Research Center;Research Center for the Development Strategy of Marine Industry |
| Abstract: |
| Based on the general structure of the price risk system,the composition of the early warning system of price risk of turbot in China was analyzed.From the industry supply and demand and the national macro policy factors affecting the price of China sea fish market of the turbot out warning index pool price as example as seawater fish industry market risk warning system,the index system of turbot industry price risk warning of China was constructed.An empirical study on price risk early warning of turbot in China was taken by using BP neural network for 2012—2017 years’ quarterly survey samples.The study showed that the main indexes of price changes in turbot are the area of adult fish,the stock of seedlings and the price of flounder.It is proved that the risk early warning model constructed by BP neural network is practical and feasible for the study of price risk of turbot in China,and some suggestions on strengthening government supervision,improving the effectiveness of the scheme and strengthening technological innovation were put forward. |
| Key words: Price risk early-warning,Empirical research,Sea fish,Early warning,BP neural network |
