| While the dog-eat-dog market economy is pregnant with the opportunity for development, there are countless risk and crisis hided in it. As to listed company, the situation that it is titled with "ST" plate and even forced to quit listing because of financial crisis grows more and more seriously. It is not only the threat to existence and development of the company failing into the financial crisis, but also brings enormous loss to investors, creditors. So to establish a financial crisis early warning index system which is disrelated and covered amount of information, and build up a financial crisis early warning model, has become the important aspect of stabilifying the development of stockmarket, national economy, and society.In this paper, begin with agent technology, Genetic Algorithm and Neural Network have been applied to research on financial risk. There are five parts in this paper. Firstly, background of research of financial risk and research significance is introduced, and the statue of research over the world is further introduced. Secondly, related theory of financial crisis early-warning is expatiated, and qualitative and quantitative methods of financial crisis early-warning are respectively reviewed. Thirdly, research method is discussed. We introduced the empirical method to select the variables and samples, and the empirical methods and empirical models. The fourth part builds up the financial crisis early warning models by BP Neural Network and GA-BP Neural Network after extracting principal component factors. And the empirical results are compared to get a conclusion. At last, we summarize the research conclusion and the shortcomings of our study and suggestments for further study.The main characteristic and innovation of this paper lie in two aspects. Firstly, the index system is more integrate for including non-financial indexes. Secondly, we build up a financial crisis early warning model, which combines Genetic Algorithm and BP Neural Network. |
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