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财务风险不仅严重危害企业的生存和发展,而且也会给投资者带来巨大的投资损失,因此上市公司财务风险的预测越来越受到实务界和学术界的重视。笔者基于中国资本市场的数据,选取了2014-2015两个时间窗口的27家首次被ST(特别处理的股票)的上市公司和54家各项财务指标符合上市规则的公司作为本文的研究数据来源,其中27家ST的公司以被ST前的第二个会计年度的数据为基数,运用CLementine工具,比较准确地实现了数据挖掘技术在上市公司财务困境预测中的运用。研究结果表明数据挖掘技术(Data mining)在财务困境预测模型具有较强预测能力,正确率较高。
Financial risks not only seriously jeopardize the survival and development of enterprises, but also bring huge investment losses to investors. Therefore, the forecast of financial risks of listed companies is paid more and more attention by practitioners and academics. Based on the data of China’s capital market, the author chooses 27 listed companies that are ST (special handling stock) for the first time in 2014-2015 two time windows and 54 companies whose financial indicators conform to the listing rules as the research data source of this article , Of which 27 ST companies based on the data of the second fiscal year prior to ST and using the CLementine tool accurately realized the application of data mining technology in the financial distress forecast of listed companies. The results show that Data Mining has strong predictive ability in the financial distress prediction model, and the correct rate is high.