SVM Prediction Method For Assessing The Financial Credit Rating Of The Listed Companies In Stock Market

A company that shares ownership of stocks is called listed company in the stock market. The listed companies are the foundation of the stock market, whether their behavior is normal and the financial situation is good or bad will directly influence securities of markets and the interests of investors. In recent years, The financial crisis of some listed companies in stock market have been sharp rising in a number of enterprises general weakened ability to resist risks. How objective evalution of the financial operation of a business is good or bad , so that an enterprise's financial situation has not developed to the deterioration of the time, we can reveal the potential risks, predict its crisis occurred earlier issued a warning to the operators so that they can do so as early as prepared or take timely measures to prevent a further deterioration of the financial situation to avoid serious financial crises actually happened, it is particularly important. This paper is based on the thinking of using statistical methods and Support Vector Machine method to create the credit evaluation model for china's listed company's financial condition feedback.Support Vector Machine (SVM) has developing rapidly in the decade of the 20th century . The statistical learning theory is the core content of it. Among the many kernel functions, Gaussian kernel is studied by the majority of researchers because of its special properties, as well as a wide range of applications,In this paper, using Gaussian kernel SVM ,we have established 42 financial risk assessment models from 13 major financial indicators of the selected indicators in the listed companies.Finally, the article compared the Support Vector Machine with statistical method, based on the numerical simulation with the Gaussian kernel ,The Support Vector Machine has much superiority in listed companies financial risk assessment forecast...