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随着经济的全球化和大数据时代的到来,企业的风险意识也进一步加强,上市公司都迫切需要时刻把握其财务状况。故从资产管理能力、盈利能力、营运能力、偿债能力和成长能力五个方面构建了上市公司财务危机预警指标体系,并基于PCA和数据挖掘技术构建了财务危机预警模型,来对企业的财务状况进行判别。通过利用C&R树、Logistic回归、C5、CHAID、SVM、决策列表、QUEST、神经网络、贝叶斯网络等方法分别建模。比较发现,基于C&R树的预警模型具有更好的精确度,并根据该模型的分析结果,给出了相应的预防对策及建议。
With the economic globalization and the arrival of big data era, the risk awareness of enterprises has been further strengthened, and listed companies urgently need to grasp their financial position at all times. Therefore, this paper constructs the early-warning index system of financial crisis of listed companies from the aspects of asset management ability, profitability, operational capability, solvency and growth ability. Based on PCA and data mining technology, it builds an early warning model of financial crisis, The situation is judged. By using C & R tree, Logistic regression, C5, CHAID, SVM, decision list, QUEST, neural networks, Bayesian networks and other methods were modeled. It is found that the C / R tree-based early warning model has better accuracy, and according to the analysis results of the model, the corresponding precautionary measures and suggestions are given.