Strategies for Analyzing Financial Data of Listed Companies Based on Data Mining

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Abstract

INTRODUCTION: A company's net profit is a significant factor in measuring whether the company is performing well or not. How to improve the company's return on assets, strengthen the company's operations, improve the company's capital structure, enhance the company's marketing strength, and accelerate the company's financing speed is an inevitable choice for the company to avoid falling into a financial crisis. OBJECTIVES: Forecasting the financial crisis of listed companies based on the financial situation of selected listed companies. METHODS: The return on assets, shareholders' equity ratio, return on net worth and other company factors have been studied empirically using data mining techniques. A mathematical model for financial risk identification was developed and evaluated. RESULTS: The results show that the accuracy is above 90%. CONCLUSION: The study found that the lower the return on capital, the higher the financial risk the firm faces; the lower the financial debt ratio, the higher the chance of financial difficulties, and the two are positively correlated.

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APA

Xie, P., & Zheng, S. (2023). Strategies for Analyzing Financial Data of Listed Companies Based on Data Mining. EAI Endorsed Transactions on Scalable Information Systems, 10(6). https://doi.org/10.4108/eetsis.3827

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