Using LDA Model to Quantify and Visualize Textual Financial Stability Report

Abstract The financial system plays a crucial role in development of countries, which makes its stability be heated around the world. However, traditional indices which help measure financial stability such as quantile, leverage ratio and liquidity have instinctive shortcomings. For example, these digital indices are usually unavailable and one-sided. Therefore, finding a new approach to quantifying and visualizing financial stability is necessary and desirable. Different from digital data, textual data is more available and usually implies more abundant information and intuitional senses. Since textual data is not visualized, it is vital to find out what texts talk about. Latent Dirichlet Allocation (LDA) is one of the most effective approaches to achieve above goal. In order to apply LDA to measure financial stability, China Financial Stability Report is selected to make an empirical analysis. The results are as follows. Firstly, it is reasonable that LDA model can be applied to analyze China Financial Stability Report. Secondly, dividing core terms of every topic into basic terms and particular terms, we can draw pictures of every embranchment in finance. And we can analyze topics rank of 5 years or in every single year, so that a designing matrix comes into being and we can study financial stability tendencies. At last, the macro-environment in finance can be depicted easily using word cloud.