Financial Risk Analysis and Early Warning Research Based on Data Mining and Statistical Analysis Technology

Abstract Using the advantage of decision tree algorithm in the screening work, the traditional ID3 algorithm is improved and optimized, and a new and simplified financial index system is constructed. At the same time, combined with the unique value of artificial neural network in early warning model and data analysis, B-P model is used to build a mixed financial early warning model. In the model study, the HFPM model and Z-score model were compared and analyzed by using test samples and training samples, and the superior warning ability of the former was effectively verified.

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Study on Simulation of Rural Financial Risk Early Warning Model Based on MATLAB

2020 International Conference on Computer Engineering and Application (ICCEA) ◽

10.1109/iccea50009.2020.00088 ◽

2020 ◽

Author(s):

Handan Zhang

Keyword(s):

Early Warning ◽

Financial Risk ◽

Early Warning Model ◽

Model Based ◽

Warning Model

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Application of Artificial Neural Network in Corporate Financial Risk Early-Warning

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.336-338.2476 ◽

2013 ◽

Vol 336-338 ◽

pp. 2476-2479 ◽

Cited By ~ 2

Author(s):

Hong Xiao Zhou ◽

Sai Hua Xu

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Early Warning ◽

Bp Neural Network ◽

Financial Risk ◽

Financial Data ◽

Early Warning Model ◽

Risk Warning ◽

Artificial Neural ◽

Warning Model

The traditional financial risk warning model are all based on probability theory and statistical analysis, but the precisions of the results are usually not satisfied in practice. This paper studies the application of artificial neural network in corporate financial risk early-warning. It designs an early warning model of financial risk based on BP neural network. And then selects financial data from 30 enterprises as samples to train and test the network. The result indicates that the risk early warning model is very effective. It can solve some problems of the traditional early warning methods such as difficult to deal with highly non-linear and lack of adaptive capacity.

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New Energy Enterprises Financial Risk Early Warning Model Based on the Comparison of Principal Component and Logistic Regression Model Analysis

10.1145/3470716.3470737 ◽

2021 ◽

Author(s):

Xinyan He

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Early Warning ◽

Financial Risk ◽

Logistic Regression Model ◽

Principal Component ◽

Model Analysis ◽

Early Warning Model ◽

New Energy ◽

Warning Model

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One belt, one road, the early warning model of financial risk analysis for small and medium sized enterprises based on big data analysis

10.1109/icicta51737.2020.00037 ◽

2020 ◽

Author(s):

Boyi Xiao ◽

Yuping Zhang

Keyword(s):

Big Data ◽

Data Analysis ◽

Risk Analysis ◽

Early Warning ◽

Financial Risk ◽

Big Data Analysis ◽

Early Warning Model ◽

One Belt One Road ◽

Warning Model

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Research on the Analysis and Application of Financial Risk Early Warning Model

Proceedings of the 2019 2nd International Conference on Information Management and Management Sciences - IMMS 2019 ◽

10.1145/3357292.3357301 ◽

2019 ◽

Author(s):

Di Lu ◽

Guanhua Wang

Keyword(s):

Early Warning ◽

Financial Risk ◽

Early Warning Model ◽

Warning Model

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The Regional Financial Risk Early-Warning Model Integrating the Regression of Lagging Factors

Applied Mathematics & Information Sciences ◽

10.12785/amis/070322 ◽

2013 ◽

Vol 7 (3) ◽

pp. 1035-1041 ◽

Cited By ~ 1

Author(s):

DongSheng Liu ◽

GuangLan Zhou ◽

KeNa Zhu ◽

Chonghuan Xu

Keyword(s):

Early Warning ◽

Financial Risk ◽

Early Warning Model ◽

Warning Model

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Financial Risk Early Warning Model

Lecture Notes in Electrical Engineering - Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012 ◽

10.1007/978-1-4471-4847-0_63 ◽

2013 ◽

pp. 507-515 ◽

Cited By ~ 1

Author(s):

Hong Wang ◽

Jun Zheng ◽

Lu Yang Gao ◽

Hui Wang

Keyword(s):

Early Warning ◽

Financial Risk ◽

Early Warning Model ◽

Warning Model

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Research on Financial Risk Early Warning of Listed Companies Based on Stochastic Effect Mode

Applied Mathematics and Nonlinear Sciences ◽

10.2478/amns.2021.2.00027 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Liduo Zhang ◽

Lina Zhang ◽

Mohammed Basheri ◽

Hafnida Hasan

Keyword(s):

Early Warning ◽

Financial Risk ◽

Market Competition ◽

Random Effect ◽

Random Effect Model ◽

Listed Companies ◽

Financial Risks ◽

Early Warning Model ◽

Effect Model ◽

Warning Model

Abstract In the current era, the market competition is becoming increasingly fierce, complicated and unpredictable. Based on the interaction of various factors, the probability of financial risks of listed companies is significantly improved. Because of its unique characteristics, the listed companies’ operating status affects the overall operation of China’s market economy and occupies a fundamental position in the national economic system. If listed companies have financial risks, it will cause great trauma to our economy. Based on the financial risk evaluation theory of listed companies, this paper analyzes the financial indicators of listed companies through random effect model, and puts forward the risk analysis and prediction index system of listed companies from theoretical and empirical angles, thus constructing a financial risk early warning model based on linear random effect model, and studying the financial risk early warning of listed companies with practical cases. The research results show that the financial risk early warning model of random effect model is feasible and effective, which can help listed companies to carry out financial risk early warning management and improve financial management level.

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