Research On The Influencing Factors Of Financing Ratio Of Crowd-Funding In China

The number of chips is a kind of fund-raising model that is based on the Internet for the public to raise funds.Since the establishment of the "Kickstarter" in the world since the establishment of the Internet,the Internet has been developed for nearly eight years.The entire platform "named time" in 2011,the official operation,has also been developed for nearly six years.Internet crowd-funding to innovate the financing,with "low threshold,convenient,not subject to geographical restrictions," the characteristics of effective mitigation of small and medium enterprises financing problems,but also the financing of entrepreneurs to choose the best choice.This paper mainly studies the influencing factors of the financing ratio of China’s product type,expounds the theory of herding,social capital theory and information asymmetry theory in the financing market,and analyzes the three theories,The three factors of financing ratio-herd behavior factors,social capital factors,information transfer factors,and extract nine independent variables,put forward the corresponding assumptions.In this paper,descriptive statistical analysis,correlation analysis,regression analysis of the product type of factors affecting the empirical analysis,test hypothesis is established.The number of topics in the social capital factors and the number of project sponsors initiated a positive correlation with the financing ratio,and the impact of the project sponsor support project on the financing ratio is not significant;the number of project sponsors has a positive impact on the financing ratio;In theinformation transmission factor,the target amount has a negative impact on the financing ratio,and the impact of the video and the number of the project progress on the financing ratio is not significant.In addition,based on the BP neural network to establish the prediction model,which is conducive to Matlab software,80% of the sample data by training,10% of the test,10% of the way to predict the adjustment parameters,and finally found that three layers of hidden layer of BP Neural network can effectively predict the forecast of product type financing ratio.