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Financial risk early warning model for quoted company using data mining technology

机译：运用数据挖掘技术的上市公司财务风险预警模型

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摘要

This paper aims to put forward a financial risk early warning model for quoted company, which is an important for modern company management. Firstly, the index system for financial risk early warning is given, which includes 1) Macro-economy, 2) Governmental capabilities, 3) Foreign trade, 4) Currency risk, 5) Financial institutions liquidity risk, and 6) Financial institutions operational risk. Secondly, financial risk early warning model based on radial basis function neural network is illustrated. For the radial basis function neural network, widths and centroids should be fixed, and then weights are obtained through solving a linear equation. Particularly, in our proposed model, nearest neighbor clustering algorithm is exploited to choose the centroids of clusters. Finally, experiments are conducted to make performance evaluation. Compared with other methods, we can see that the proposed is effective to tackle the problem of financial risk early warning for quoted company.
机译：本文旨在为上市公司提出财务风险预警模型，对现代公司管理具有重要意义。首先，给出了金融风险预警指标体系，包括：1）宏观经济; 2）政府能力; 3）对外贸易; 4）货币风险; 5）金融机构流动性风险; 6）金融机构操作风险。 。其次，阐述了基于径向基函数神经网络的金融风险预警模型。对于径向基函数神经网络，应固定宽度和质心，然后通过求解线性方程获得权重。特别是，在我们提出的模型中，利用最近邻聚类算法选择聚类的质心。最后，进行实验以进行性能评估。通过与其他方法的比较，可以看出该方法对于解决上市公司财务风险预警问题是有效的。

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