Study On Main Board Initial Public Offerings Pricing In Chinese Security Market

With the deepening of the reform of China's securities market,the IPO pricing accuracy in Chinese security market is also increasingly important.Each country's market cannot completely copy othes,therefore,on the basis of the exploration and learning from others,finding the right pricing method of the main board market in our country,seeking a reasonable stock price become the core issue of this article.This paper studies the traditional pricing method,and compares the advantages and disadvantages between them.We think the traditional method is not suitable for the main board security market in China,but the introduction of options,risk,neural network,game make ipo pricing an improvement.For main market pricing,the BP neural network method is the most applicable,it can make the error rate of around 15%,but,in our view,risk assessment and the factors of consideration can raise the accuracy of pricing,so we introduce the risk assessment.At the same time,the environment of different countries is the main reason on pricing method cannot directly in use,so we select United States,Singapore,Japan and Germany,all of them compared with our country.In this paper,we combined the BP neural network model with VaR risk pricing method for stock pricing.and it is concluded that CVaR is better than the VaR method for accurately measure risk,because the former error rate is low,with an average of only 12.69%,that is In addition to the methodological innovation,on the factors of BP neural network model,I considered the risk factors and the government system unprecedentedly:one is the error rate of risk factors method is lower than market environment factors,that is reduce more than 2%in previous method.At the same time,quantify the system of government as a listed cost factors and unified with normalization method of different dimensions.In the further study of China,the United States,Singapore,Japan,Germany government system on the basis of the five countries,using the improved BP neural network model with the government institutional factors can reduce the error rate to 11.96%,the pricing model is more effective,which is the shortest time,the least funds,the strongest government supervisory system of pricing model in Germany,and the supervisory system is the most important factors in issue time,issue funds and supervision.Our government have a lot of benefit to reform the IPO system.