Research and Forecast Analysis of Financial Stability for Policy Uncertainty.

Abstract

The instability of financial market will have a great impact on money, bonds, and stocks and affect the economic development of society and people's lives. Therefore, it is very necessary for us to study and predict the financial stability. According to the forecast results, we will analyze and make a series of preparatory measures. First, we make a series of analyses on the structure and significance of policy uncertainty and financial stability. This paper introduces the advantages and disadvantages of the P/L model, the KLS signal method, and the BP neural network model for financial stability early warning, It is clearly pointed out that the BP neural network is more reliable and accurate, Then, the BP neural network, the ant colony algorithm, and the genetic algorithm are used to predict the opening price, closing price, highest price, and lowest price of KDJ index of Cathay Pacific Group's 5-day data. Compared with the real value, we find that the BP neural network is almost the smallest in forecasting the opening price and closing price, or the lowest price and the highest price, and has good stability, which once again proves the feasibility of applying the BP neural network to the research and prediction of financial stability.