Research On The Relationship Between Network Retrieval Data And Price Fluctuations

The prices problem is always an important issue affecting the national economic development,and the economy is the main driving force to promote the country to move forward,so the price problem has a very important influence for social environment stability and country economic prosperity.Although China has accumulated many years of experience in price management,the current trend of price fluctuation is full of uncertain factors and is difficult to grasp.With the rapid development and wide application of the Internet,we change the traditional way of "economic data" + "economic model" = "economic conclusions" into the new way of "noneconomic data" + "economic model" = "economic conclusions".The new idea is based on the social subject's behavior information in the process of Internet data generation can describe and explain the current socio economic phenomenon.The main contents of this paper are divided into two parts:The first part takes the core theory of information theory as a fulcrum,combined with the specific price fluctuation problem,analyzes the complete influence process of the relationship between web search data and price fluctuation from the perspective of information theory.The second part has completed the analysis of the correlation between web search data and price fluctuation information,and mainly discusses the relationship between web search data and price fluctuation.In the analysis of influence relations,the improved multivariate linear regression model based on the inertia factor of inflation is constructed and compared with the neural network model.The analysis results of linear models show that price fluctuation is also influenced by both inertia factors and search data,and the influence of inertia factors is more obvious;The neural network model is better to the linear model in the fitting and prediction effect,Therefore,it is considered that the NN model is more suitable for the analysis of the influence between the network retrieval data and the price fluctuation.