Research On Financial Early-Warning In Listed Companies Based On EVA

With the rapid development of China’s capital market, the macro and micro- economic environment that listed companies face is complexed and diversity in daily business activities, listed companies will face a variety of financial risk factors. these risks have a process, if we can not find the problems in time, the company and stakeholders will have serious loss. Therefore, for listed company, the introduction of a early financial warning system is essential.At present, many listed companies are based on the traditional accounting earnings indicators to forecast the risk of bankruptcy. but the traditional accounting earnings indicators can be manipulated easily, it bases on the accrual basis,and without considering the cost of equity, as a result, accounting information is unaccuracy, the accuracy of prediction is not very high. EVA warning model considers the cost of equity and have a process of adjustment of income indicators, it effectively reduce the distortion of accounting information. In this paper, by introducing model EVA, the traditional early-warning model is improved, thereby a more efficient early warning models is created.The main contents are as follows:The first part focuses on the prediction accuracy of early warning of listed companies, the problems is that prediction accuracy is not high. compared to traditional accounting earnings indicators, EVA indicators consider the cost of equity of the company. By introducing literature review, the paper describes the background of EVA, the EVA model intends to improve the prediction accuracy of the financial early warning; the second part focuses on the meaning of a listed company financial crisis, the financial crisis is dynamic、 preventable、double-sided characteristics, the role of the financial early warning system for listed companies, basic concepts of EVA and analyzes the feasibility of EVA, compared to traditional indicators, EVA has the advantages of forward-looking and sensitivity; the third part focuses on construction of the model, this paper uses logistic regression method to construct the model, including financial and non-financial indicators, the method of calculation of EVA, EVA financial indicators specific adjustments principles, such as excluding non-operating income; the fouth part focuses on empirical analysis, the paper selects for 2013 ST’s32 listed companies as samples, and selects the same number、same industry and similar size companies as a pair of non- ST study sample, the selected indicators t-3 years of financial data, through significant test, correlation analysis, and the logistic regression testing, the paper also carried out tests on the sample group. in this paper, not only considering the financial indicators, but also the non-financial indicators, The non-financial indicators used to further refine EVA financial indicators for early warning models; finally, there is a conlusion that EVA index has higher prediction accuracy.