A Study on Estimation of Financial Liquidity Risk Prediction Model Using Financial Analysis

摘要

In this study we conducted a static financial analysis of the financial ratios of the manufacturing, information service, and financial and insurance industries to propose a model for predicting the financial liquidity risk, and performed ANOVA to select the significant variables affecting the healthy liquidity firms and the poor liquidity firms. Using the results of ANOVA, the linear discriminant model, the secondary discriminant model, the probit model, and the logit discriminant model were estimated and tested to propose a predictive model. The results of the test are as follows. The variables selected by ANOVA were all significant in the significance test of all models. And the fitness and the explanatory power of the estimated model were evaluated by the Apparent Error Rate (APER) which is the misclassification rate of the confusion matrix which is the classification matrix of the observation result and the prediction result. As the result, the misclassification rate of the logit discriminant model was the lowest, and the next lowest model was the probit model. Therefore, in order to compare the predictive power of the probit and logit discriminant models, the association analysis between the prediction probability and the observation response was analyzed and the predictive power was compared using rank correlation coefficients. As the result, the predictive power of the logit discriminant model is higher than that of the probit model. Therefore, the logit discrimination model, which has the lowest misclassification rate of all data and has the highest forecasting power, is proposed as the final model for predicting the financial liquidity risk.