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Early Warning Model of Business Group Financial Risks Based on SVM

机译:基于支持向量机的企业集团财务风险预警模型

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As the main subject of social economy activities, business groups faced with uncertain management environment. How to deal with environment risk, especially the financial risk has became the key factor that influence the existence and development of business groups. However, there are few specialized risk prediction model applied on business groups. So in our paper, we chose SVM method to classify and predict business groups' financial data and select right sample as detailed analysis for financial indicators. We chose 10 special treatment business groups and 10 normal state business groups as training samples. Six basic financial indicators and two unique financial indicators of business group are chosen as the input vectors. We trained the data and resulted better performance. Finally we built business group financial risk prediction model based on training result and conclude that SVM method can improve forecast accuracy.
机译:企业集团作为社会经济活动的主要课题,面临着不确定的经营环境。如何应对环境风险,尤其是财务风险,已成为影响企业集团生存和发展的关键因素。但是,很少有适用于业务组的专业风险预测模型。因此,在本文中,我们选择了SVM方法对业务组的财务数据进行分类和预测,并选择合适的样本作为财务指标的详细分析。我们选择了10个特殊待遇业务组和10个正常状态业务组作为培训样本。选择六个基本财务指标和两个业务组独特的财务指标作为输入向量。我们训练了数据并获得了更好的性能。最后,基于训练结果建立了企业财务风险预测模型,并得出结论:支持向量机方法可以提高预测的准确性。

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