The Early Warning Research Of Financial Distress Of Listed Company Of Our Country

The purport of this text studies is to improve the practicability and accuracy of enterprise's financial distress prewarning. The former's setting-up related to early warning index system of the distress but the latter associates with result of the early warning model. In order to reach the first goal, this text sets about from the reason for influencing enterprise's financial distress, construct the comprehensive early warning index system including capital operation of material resources and capital accumulation of the manpower, and through determining the nature and the quantitative method carries on the index preconditioning, construct the index preconditioning system of suiting enterprise's financial distress prewarning. In order to realize the second goal, this text, through carrying on in-depth analysis to the early warning models of statistics and artificial intelligence, develop the combined early warning model; carry on the development of the enterprise financial distress early warning administrative decision tool and move forward and study.While analyzing the cause of the financial distress of listed company of our country, define category and time of the financial distress of this text and pass and count the cause of the listed company of our country of the data analysis at first, and establish the system of index based on this. In index preconditioning links, the article adopts the single preconditioning method and preconditioning method made up. The single preconditioning method includes quantitative statistical check preconditioning and quantitative financial data level preconditioning; Make the preconditioning method up in order to guarantee the structural integrality prerequisite of financial data, carry on ration and qualitative association preconditioning, and carry on the comparative study to the single and preconditioning method made up, obtain the relatively superior index on the basis that this selected works originally take a sample and make the preconditioning method up.The research links in the prewarning algorithm, the article regards making the preconditioning up as the foundation, construct the early warning model of association that is headquartered in counting algorithms and artificial intelligent algorithm, count algorithms including linear Fisher differentiates models and non-linear Logit regression model, adopt ANN model by artificial intelligent algorithm. Through analyzing to application to study sample, obtain it while doing the prewarning of financial distress, the non-linear model should be superior to the linear model, it is superior to the single early warning model to make the result of the early warning model up.