An Empirical Research on Financial Crisis Forecasting Based on BP Neural Network
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摘要: 财务危机预警具有重要的经济研究价值。在考虑中国现行会计信息供给状况基础上,构建了包含偿债能力、资产管理能力、盈利能力、成长性、现金流量以及会计信息披露质量的六大类预警指标体系。以沪、深两市上市公司为样本,比较了经秩和检验前后,BP神经网络模型的预警效果。结果显示:BP神经网络模型在中国上市公司财务危机预警中具有良好的应用价值,特别是经秩和检验以后,模型判别准确率显著提高,具有很强的优越性。Abstract: The research on financial distress prediction is significant to the economy. Tak ing into full account the status quo of the accounting information supply in Chi na, this paper constructs a six-category warning index system in cluding solvency, assets and liabilities management, profitability, growth, cash flow and the disclosure quality of accounting information. It compares the effe cts of early warning using BP Neural Network before and after the rank sum test, sampling the listed companies in Shenzhen and Shanghai Security Markets. The re sults show that BP neural network model has good application value to the warnin g for financial distress of China's listed companies. Especially, the accurac y of obtained classifying model is improved obviously after the rank sum test.
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