Fuzzy Support Vector Machines In The Early Warning Application Of Financial Risk

Along with the constant outburst of financial crisis throughout the world, thecorrelation and destructiveness of financial crisis are becoming more and moreobvious. Due to the practical relations between financial risks and financial crisis,financial risks tend to cause the prelusion, or beginning of financial crisis; whilefinancial crisis is the extreme consequence of dynamic accumulated financialrisks. Therefore, the research on early warnings of financial risks has causedwidespread governmental and public concern from all around the world, the results ofwhich will directly affect the proper understanding and judgment of financial marketstatus, thus bringing methods to prevent financial risks from taking place,withstanding the impacts of international financial crisis and regulating the financialrisks to be within the controllable range. It has great practical significance to thehealthy, stable development of economy and finance in our country.This article is based on the theories of financial risk early warnings and FuzzySupport Vector Machines. In accordance with research findings in the area offinancial risk early warning index system by experts from home and abroad, itchooses the index of financial risk early warnings appropriate for the practicalsituation in China after comparatively sufficient acknowledgements of the presentsituation and research findings in this field. Constantly constrained by theexperience of experts and simple mathematical models, traditional early warningmethods are not sufficient in coping with highly nonlinear models, thus notfulfilling the objective requirements macroscopic early-warning of finance. Thisarticle uses Fuzzy Support Vector Machines and its deformation algorithmic model totestify the feasibility and rationality of the selected early-warning index system andsuccessfully predicts the financial risks in upcoming years in China and provesthe feasibility of this approach.