雷振华, 邹果①.现金流量预警指标视角下的BP神经网络模型实证检验研究——来自2007—2012年沪深两市ST公司的数据分析[J].,2014,15(3):62-66 |
现金流量预警指标视角下的BP神经网络模型实证检验研究——来自2007—2012年沪深两市ST公司的数据分析 |
Empirical Test Research on BP Neural Network Model Under the Cash Flow Early Warning Indicators Perspective——Statistics based on ST companies of Shanghai and Shenzhen stock markets from 2007 to 2012 |
投稿时间:2014-04-21 |
DOI: |
中文关键词: 现金流量预警指标 BP神经网络模型 实证检验 |
English Keywords:cash flow early warning indicators BP neural network model empirical test |
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中文摘要: |
文章针对现金流量指标的国内外研究动态,从财务危机预警角度构建现金流量预警指标体系;并选取2007年—2012年沪、深两市A股79家ST公司及79家非ST公司作为训练样本,用样本公司被ST前1年、2年、3年的数据对指标进行筛选,将BP神经网络模型预警结果与样本的实际结果进行比较。研究结果表明:BP神经网络模型t-1年、t-2年、t-3年的预测精度依次下降,但t-3年财务预警模型对训练样本的预测精度仍能达到79.22%,对检验样本的预测精度也能达到78%。 |
English Summary: |
The cash flow early warning indicators system is established according to the current research dynamic at home and abroad and the financial crisis early warning perspective.79 ST and 79 non-ST companies of Shanghai and Shenzhen stock markets from 2007 to 2012 are selected as the training example.The 3-year statistics of the training example before they are ST are used to select indicators.The prediction result of BP neural network model is compared to the truth according to the selected indicators and BP neural network model.The research concludes :the prediction accuracy of BP neural network model declines in turn from t-1 year to t-3 year.The accuracy of training example of the financial warning model of the t-3 year still reaches to 77.85%.The accuracy of test example also reaches to 78%. |
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