Study On Price Warning Of Turbot In China

With the development of economy and the improvement of people's income level,people pay more attention to the intake of dietary structure and protein.As one of the varieties of turbot aquatic products,aquaculture status in agriculture along with the economic development more and more important,plays an important role in food protein consumption,its price fluctuations not only brought the price risk to turbot farmers and consumers,but also not conducive to the healthy development of turbot industry.Therefore,it is necessary to study the fluctuation of China's turbot prices,this article discusses the main factors affecting China's turbot price fluctuations,finally to put forward relevant suggestions to individual farmers,industrial farming and fishery production,the consumer sector,in order to reduce the price fluctuation of turbot risks.This paper selects from January 2012 to turbot Moonrise pool prices and sunrise pool price related data in 2018 03 months,using the method of combining theoretical analysis and empirical analysis.In the second chapter,the related research literatures are reviewed,including the theory of economic early-warning,the construction of early warning index system,and the early warning model.In the third chapter,the thesis focuses on the analysis of price theory,price prediction theory and price warning theory.The price early-warning theory includes black early warning and yellow early-warning.The fourth chapter,based on my understanding of the turbot production status,cost income changes and changes in demand characteristics,this paper mainly from the three aspects of the policy of industrial production status,demand changes,state of risk warning sources in China turbot industry were analyzed,factors affecting the carding of turbot prices,construction of early warning index system.Combined with the actual situation of aquatic product production and consumption,and the availability and quantification of data,we set up 15 early warning index system of 3 level indicators for turbot price fluctuation.The calculation and warning indexes 2 years lag correlation coefficient by time difference correlation analysis,divided into first,synchronization and lag alarm index.On the basis of the 2013-2017 years of China's characteristics of turbot monthly data pool price,from negative to positive in the giant giant police police divided into seven districts,respectively,the red light district green zone,yellow light zone,white light district,orange light district,blue light district and purple light district,when the price of less than 44.87 yuan / kg or more than 51.87 yuan / kg for alarm zone.The fifth chapter,turbot Morrison price and price pool sunrise construct prediction model based on ARIMA model,the model of current and future sends the corresponding alarm.Based on the establishment of the fourth chapter leading indicators,the BP neural network early warning model is established.The results show that the model fitting effect is good,that is,using BP neural network to predict the price of turbot is a feasible and effective way,Finally,we compare and discuss different models of price prediction for turbot.The sixth chapter,thesis puts forward countermeasures and suggestions to establish and improve the price of our early warning mechanism of turbot,points out that the government departments should establish a price early warning information platform for professional,timely release of relevant information,the reasonable application of the result of early warning,timely release of relevant information,and take necessary measures to stabilize the price of China's turbot.This paper makes a deep research and Discussion on the price early-warning work of turbot in China from two aspects of theory and practice,hoping to play a certain reference value for promoting the healthy development of turbot market in China.