Investment risk model based on intelligent fuzzy neural network and VaR

Abstract

Credit risk of government financing platform loans is a hot topic in economic circles. This paper briefly summarizes the literature research on government financing platforms, analyzes its risk characteristics, and tries to establish an appropriate early warning evaluation index system of credit risk. In the selection of risk assessment methods, it departs from the traditional logistic evaluation model of regression analysis based on historical data starting from the fuzzy neural network (FNN) model of artificial intelligence method. This paper quantitatively estimates the early warning indicators of credit risk of sample enterprises from the financial perspective, draws conclusions through empirical comparative analysis, and puts forward corresponding policy recommendations.