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Empirical Study On Financial Risk Warning In Chinese Listed Steel Companies Based On EVA

Posted on:2015-07-11Degree:MasterType:Thesis
Country:ChinaCandidate:X Q LiFull Text:PDF
GTID:2309330431491457Subject:Business management
Abstract/Summary:PDF Full Text Request
Iron and steel industry is the pillar industry of national economy,and occupies an important position in national economy. As a department of rawmaterial production and processing, steel industry is in the middle position industrialchain. Its development is closely related with China’s infrastructure and industrialdevelopment. But also the changes of related industries and policy at home andabroad, such as excess capacity, ore monopoly, financial constraints, lack of demand,personnel and environmental protection pressure, make China’s steel industry be inserious situation. In this background, it has important practical significance tointroduce EVA into listed steel companies financial risk warning. EVA evaluationsystem includes performance evaluation, budget management, operation management,incentive system etc. Especially the introduction of capital cost makes managers moreclose to environment of shareholders. So managers and general employees begin tothink like corporate shareholders. So this paper introduces EVA in financial riskwarning of listed steel companies. It increases the accuracy of warning model andpromotes healthy development of steel industry.This paper selects30listed steel companies as sample in2012and14traditionalfinancial indicators from solvency, operating capacity, cash flow, capacitydevelopment four aspects. In addition we use EVA to modify traditional profitability,select four fixed profitability indicators. These18financial indicators constitutefinancial risk warning index system of listed steel companies. Five common factorsare extracted by factor analysis. Secondly, cluster analysis divide sample companiesinto safe type and risk type. Then we use Logistic regression analysis to establishwarning model. EVA factor and growth factor are in the model. Through the result,EVA factor can better improve the prediction accuracy of model. Finally we use2011and2010data of sample companies to test model, and put forward opinions andmeasures for financial risk prevention of listed steel companies.
Keywords/Search Tags:Listed Steel Company, EVA, Financial Risk Warning, Cluster Analysis, Logistic Regression Analysis
PDF Full Text Request
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