New technologies such as big data,artificial intelligence,mobile internet,cloud computing,Internet of Things,and blockchain have brought about significant changes and development in the financial industry.Predicting t...New technologies such as big data,artificial intelligence,mobile internet,cloud computing,Internet of Things,and blockchain have brought about significant changes and development in the financial industry.Predicting the financial situation of enterprises,reducing the probability of uncertainty risks,and reducing the likelihood of financial crises have become important issues in enterprise financial crisis warning.In view of the issues in enterprise financial early warning systems such as lag,low accuracy,and high warning costs in data analysis,a financial early warning system based on big data and deep learning technology has been established,taking into account the different situations of listed and non-listed companies.This carries significance in improving the accuracy of enterprise financial early warning and promoting timely and effective decision-making.展开更多
According to the index early warning method, a commercial bank loans risk early warning system based on BP neural networks is proposed. The warning signal is mainly involved with the financial situation signal of loan...According to the index early warning method, a commercial bank loans risk early warning system based on BP neural networks is proposed. The warning signal is mainly involved with the financial situation signal of loaning corporation. Except the structure description of the system structure the demonstration of attemptive designing is also elaborated.展开更多
The period economic fluctuation is vital for an enterprise to exist and further develop, it directly affect the enterprise financial health. So, it is significant to build up financial early-warning index and measure ...The period economic fluctuation is vital for an enterprise to exist and further develop, it directly affect the enterprise financial health. So, it is significant to build up financial early-warning index and measure the warning condition that the enterprise faces and take the effective measures to eliminate. We criticize Altman’sZ calculating model and build up some new indexes for enterprise financial early-warning condition measuring and making sound decision.展开更多
To establish a financial early-warning model with high accuracy of discrimination and achieve the aim of long-term prediction, principal component analysis (PCA), Fisher discriminant, together with grey forecasting mo...To establish a financial early-warning model with high accuracy of discrimination and achieve the aim of long-term prediction, principal component analysis (PCA), Fisher discriminant, together with grey forecasting models are used at the same time. 110 A-share companies listed on the Shanghai and Shenzhen stock exchange are selected as research samples. And 10 extractive factors with 89.746% of all the original information are determined by applying PCA, which obtains the goal of dimension reduction without information loss. Based on the index system, the early-warning model is constructed according to the Fisher rules. And then the GM(1,1) is adopted to predict financial ratios in 2004, according to 40 testing samples from 2000 to 2003. Finally, two different methods, a self-validated and a forecasting-validated, are used to test the validity of the financial crisis warning model. The empirical results show that the model has better predictability and feasibility, and GM(1,1) contributes to the ability to make long-term predictions.展开更多
With downward pressure of economy facing, monitoring boom index of employment continue to decline. This paper will research on how to cope with urban employment problem using fiscal and financial polices,through build...With downward pressure of economy facing, monitoring boom index of employment continue to decline. This paper will research on how to cope with urban employment problem using fiscal and financial polices,through building system of boom of urban employment, and identifying risk signal of Chinese urban employment.展开更多
文摘New technologies such as big data,artificial intelligence,mobile internet,cloud computing,Internet of Things,and blockchain have brought about significant changes and development in the financial industry.Predicting the financial situation of enterprises,reducing the probability of uncertainty risks,and reducing the likelihood of financial crises have become important issues in enterprise financial crisis warning.In view of the issues in enterprise financial early warning systems such as lag,low accuracy,and high warning costs in data analysis,a financial early warning system based on big data and deep learning technology has been established,taking into account the different situations of listed and non-listed companies.This carries significance in improving the accuracy of enterprise financial early warning and promoting timely and effective decision-making.
基金Supported by the National Science Foundation of China(Approved NO.79770086)
文摘According to the index early warning method, a commercial bank loans risk early warning system based on BP neural networks is proposed. The warning signal is mainly involved with the financial situation signal of loaning corporation. Except the structure description of the system structure the demonstration of attemptive designing is also elaborated.
文摘The period economic fluctuation is vital for an enterprise to exist and further develop, it directly affect the enterprise financial health. So, it is significant to build up financial early-warning index and measure the warning condition that the enterprise faces and take the effective measures to eliminate. We criticize Altman’sZ calculating model and build up some new indexes for enterprise financial early-warning condition measuring and making sound decision.
文摘To establish a financial early-warning model with high accuracy of discrimination and achieve the aim of long-term prediction, principal component analysis (PCA), Fisher discriminant, together with grey forecasting models are used at the same time. 110 A-share companies listed on the Shanghai and Shenzhen stock exchange are selected as research samples. And 10 extractive factors with 89.746% of all the original information are determined by applying PCA, which obtains the goal of dimension reduction without information loss. Based on the index system, the early-warning model is constructed according to the Fisher rules. And then the GM(1,1) is adopted to predict financial ratios in 2004, according to 40 testing samples from 2000 to 2003. Finally, two different methods, a self-validated and a forecasting-validated, are used to test the validity of the financial crisis warning model. The empirical results show that the model has better predictability and feasibility, and GM(1,1) contributes to the ability to make long-term predictions.
文摘With downward pressure of economy facing, monitoring boom index of employment continue to decline. This paper will research on how to cope with urban employment problem using fiscal and financial polices,through building system of boom of urban employment, and identifying risk signal of Chinese urban employment.
文摘随着中国金融市场的高水平开放,中国应对外部输入性风险的压力将进一步上升。探索中国金融市场所面临的输入性风险动态变化并构建预警体系具有重要意义。本文运用时变参数向量自回归模型(TVP-VAR)和深度神经网络模型SCInet(Sample Convolution and Interaction Network),对我国金融市场输入性风险进行测度和前瞻性预警。研究发现:(1)TVP-VAR模型能有效识别极端风险事件发生前的风险积累,极端风险事件时期输入性风险水平会显著提高;(2)通过与主要发达国家(或地区)和发展中国家的输入性风险对比,发现发达经济体的输入性风险波动幅度较小,通过研究各国(地区)对我国的输入性风险,发现香港地区对我国内地的风险输入水平最高,以美国为主的发达国家和以印度为主的发展中国家也向我国输送了大量风险;(3)相比于其他机器学习和神经网络模型,SCInet模型具有最优的预警性能,在输入性风险异常波动前能提前预警。本研究或可为个人规避风险、企业可持续发展、国家金融稳定提供参考和帮助。
