Font Size: a A A

Research On Financial Risk Early Warning Mechanism Of Kunming Based On Financial Ecological Environment

Posted on:2014-02-18Degree:MasterType:Thesis
Country:ChinaCandidate:P JingFull Text:PDF
GTID:2279330422459237Subject:Finance
Abstract/Summary:PDF Full Text Request
The superiority of financial ecological environment directly affects the size offinancial risk. Guard against financial risk, not only to strengthen the internalsupervision and perfect the market mechanism of the financial system, but moresynthetically considering all kinds of external environment of their survival anddevelopment. It is the important guarantee to guard against and defuse financial risksby good financial ecological environment and establishment and improvement offinancial risk early warning mechanism. Kunming is constructing to become Chineseregional international financial center by facing Southeast Asia and South Asia, andtakes it as the goal. Meanwhile, Kunming is promoting the construction of pan-Asianfinancial industrial park and regional cross-border RMB financial services center asthe focus. In order to achieve the development goals, Kunming municipalgovernment highly pays attention to construction of the financial ecologicalenvironment and financial risk management. How to guard against and defusefinancial risks to minimize the possibility of a crisis level, guide the safe and stabledevelopment of financial industry, is a big problem in front of Kunming.Establishing a scientific and reasonable financial risk early warning mechanism caneffectively solve this problem.Based on this, this article sets up a financial risk early warning mechanism fromthe perspective of the financial ecological environment. Firstly, building Kunmingfinancial risk early warning research framework; and then choose a quantity andappropriate financial risk index system which is maximum features economycondition, financial development, good faith and the rule of law under thegovernment behavior; thirdly, using the analytic hierarchy process (AHP), entropyvalue method, BP artificial neural network to build, train and test the Kunmingfinancial risk early warning model; meanwhile, combining the secondary exponentialsmoothing method to forecast the future financial risks over the next two years;finally puts forward countermeasures and suggestions to establish and perfectfinancial risk early warning mechanism. In this paper, the study predicted results showing that, Kunming financial risk degree are0.1039and0.0877in2012and2013respectively, predicting a blue light and indicating that over the next two yearsKunming’s financial operation in a safe range.
Keywords/Search Tags:financial ecological environment, financial risk early warningmechanism, BP artificial neural network
PDF Full Text Request
Related items