Nonlinear Cointegration Analysis Based on Support Vector Machines and Its Application to the Connection between Financial Markets

摘要

With the purpose of analyzing non-stationary time series,this paper innovated nonlinear cointegration discriminant analysis by introducing support vector machines to overcome existing limitations of two methods,that is,the statistical approach and the neural network used by the nonlinear cointegration theory.Then,the application of the innovated method to the investigation of the connection between financial markets was explored.The empirical analysis demonstrates that the support vector machine is effective in analyzing the money demand function and its stability and has advantages in dealing with nonlinear cointegration relation and estimating nonlinear function over the two methods above.