电力行业上市公司财务危机预警研究--基于Logistic回归模型

Research on Financial Crisis Early Warning of Listed Companies in Power Industry-Based on Logistic Regression Model

通过对电力行业进行财务预警研究,选取2021年电力行业57家上市公司为研究对象,以2019年度财务数据为样本,选取能够反映上市企业多方面能力的28个财务指标,使用K-S的方法进行正态性检验并作独立样本T检验和非参数指标Mann-Whitney U检验,筛选出预警模型需要的9个财务指标,用企业连续两年的经营活动现金流量净额与流动负债比值作为判定企业财务状况的标志,结合主成分分析法和Logistic回归方法建立了属于电力行业的财务预警模型。最后,用72家电力企业2018年财务数据进行模型检测,整体预测准确率为84.72%,对电力行业财务状况起到了预警作用。

Through the research on financial early warning of the power industry,57 listed companies in the power industry in 2021 are selected as the research object,and the financial data of 2019 are taken as the sample,28 financial indicators that can reflect the various capabilities of listed enterprises are selected.K-S method is used to conduct a normality test,and independent sample T test and non-parametric indicator Mann Whitney U test are conducted to screen out 9 financial indicators required for the early warning model,With the ratio of net cash flow from operating activities to current liabilities for two consecutive years as the indicator to determine the financial status of enterprises,combined with the principal component analysis and logistic regression method,a financial early warning model belonging to the power industry is established.Finally,the financial data of 72 power enterprises in 2018 were used for model testing,and the overall prediction accuracy rate was 84.72%,which played an early warning role in the financial situation of the power industry.