Study on the risk assessment of real estate project based on BP neural network

Abstract

As known, real estate investment has many distinguish features: heavy invest, long recovery and high yield etc. So when facing the temptation of high yield, real estate enterprise has to assess risks scientifically. Especially since American subprime crisis broke out, trading volumes of real estate keep shrinking and house prices keep dropping. In this situation, risk management is particularly important. The risk assessment model based on BP neural network is more suitable for risk assessment of real estate project. It can also improve its accuracy and exclude subjective factors. Thus it can offer scientific basis for real estate investment decision, and help real estate enterprises avoid risks effectively. The paper uses the theory of BP neutral network to analyze the investment risk of real estate and its changing discipline, which have important practical meaning for the development of real estate enterprise.