Economic And Financial Risk Assessment Of Countries Along The “Belt And Road”

Since the president Xi Jinping put forward the initiative of OBOR,the initiative results have been remarkable.However,some countries have higher economical and financial risks.The national economical and financial risks vary from country to country.Therefore,it is necessary to analyze and evaluate the risks of OBOR countries.The OBOR national economical and financial risk assessment is based on the identification and analysis of possible risk factors.Then,we should judge the possibility of risk in the OBOR countries,as well as the level of national economical and financial risks.National economical and financial risk assessment can provide reference and scientific basis of risk prevention and risk management for investor when they invest in various countries.This paper establishes' an economical and financial risk evaluation index system which is fit for the OBOR countries.We selected data of the OBOR countries from 1998 to 2017.We also established the Bayesian network model which is based on K-means clustering algorithm to evaluate the national economical and financial risks of the "One Belt and One Road" countries.This paper first analyzes the theoretical basis of the economical and financial risk assessment of the OBOR countries.We analyzed the reasons for the formation of economical and financial risks in the OBOR countries,the principles to be followed when selecting indicators,and the methods to establish an indicator system,the purpose,basis,process and method of economical and financial risk assessment of OBOR countries.This paper analyzes the particularity of the economical and financial risks of the OBOR countries.Hereby,we proposed the method of this paper of Bayesian network model based on K-means clustering algorithm.Next,we analyzed the general situation of economical and financial risks of the OBOR countries from the four aspects of economical and financial development,economic stability,national debt status and financial market stability of the OBOR countries.Finally,we made empirical analysis from five aspects of economic and financial development,economic stability,national debt status,financial market stability and the factors between the host country and the home country.In the system,all data is complemented by interpolation.Then discretize the continuous data by the isometric binning method.The K-means clustering algorithm is used to classify the risk levels of the OBOR countries,and the risk is divided into six levels.The Bayesian network is constructed according to the results of the risk level divided by the K-means clustering algorithm.The training set and the test set are selected according to the ratio of 7:3.The Bayesian network is established on the training set,and the test set is used to predict the accuracy of Bayesian network.According to the results of parameter learning,reverse reasoning and strength analysis of Bayesian network,we found that most of OBOR countries economical and financial risks have a decreasing trend which indicated that the investment environment is get better.First of all,the economical and financial risks of most OBOR countries are declining or fluctuating.Secondly,the economical and financial risks of some OBOR countries are still high.Thirdly,some countries economical and financial risks fluctuate at medium and high levels which we should to be vigilant.Last,the impact of political and cultural risks behind economical and financial risks cannot be ignored.According to the results of Bayesian network strength analysis,some corresponding policy recommendations are proposed.First,improve the level of financial development and enhance the stability of the financial market.Secondly,maintain the appropriate scale of external debt and enhance the solvency of external debts.Thirdly,we should be alert of the economical and financial risks brought about by the opening of the economy.Finally,the bilateral tax cooperation mechanism should be improved.