The Application Of Two Kinds Of Optimization Algorithms In Financial Market Risk Management Model

In the field of modern finance,the problem of portfolio has always been the hot issue for investors and scholars.The modern portfolio theory began in 1952,and then it is widely used in the financial market.The Markowitz model is still an important part of modern portfolio theories until now,but the assumed conditions of classical mean-variance model are harsh and hence the low fitting degree for real capital markets.Concerning the shortcomings of the classical-mean variance theory,the objective function of the management fee is added in this paper for the modification of the original model,and the mathematical optimization method is used for the sake of improvement of original model.Finally,the weed invasion algorithm is used to find the solution and then it is analyzed with the stock data of China and Shanghai.Credit risk,the risk of economic loss caused by the breach of contract of counter party,is one of the most ancient forms of risk still existing now in the whole financial market.With the advancement of the integration of world financial market,China is further involved in the fierce international competition,and the management of credit risk of domestic financial industry faces the challenge both from home and abroad.This paper studies the classical credit risk measurement model-KMV credit risk measurement model,and analyzes the basic ideas,main assumptions,basic parameters and parameter solving of KMV credit risk model.And it also proposes the method of improving the descending direction of the Levenberg-Marquardt method,gives the algorithm steps of the improved method,proves the convergence of the improved method and gives the reasoning of convergence times.In view of the actual case of China's securities market,this paper uses the improved algorithm to solve the KMV model and calculate the probability of default,and proves the effectiveness of the algorithm.