Credit Risk Measurement And Analysis Of Listed Nonferrous Metals Companies

Non-ferrous metal is base material which is indispensable in the development ofnational economy and improving people’s living standards and the maintenance nationalsecurity. With rapidly development of modern industry, agriculture, science andtechnology, the role of non-ferrous metal in social development is more and moreimportant. At present, China is already the world’s largest country in production andconsumption of non-ferrous metal. However, in recent years due to the deterioration of theglobal economy, the decrease of the non-ferrous metals market demand, the price sharplycut down, coupled with excess capacity problems, the industry credit risk is more andmore getting the attention of people. But the credit risk assessment of nonferrous metalindustry is still in qualitative analysis level, lack of effective quantitative analysis.This paper made qualitative analysis and quantitative analysis of credit riskevaluation of non-ferrous metals industry. First introduces the developing situation of thenon-ferrous metal industry, including the development environment and the industrycompetition structure. On this basis, from the angle of information asymmetry, this paperexplained the causes of the non-ferrous metal industry credit risk, sums up its credit riskfeature: cyclical fluctuations, lack of historical default data and infectiousness. And thispaper analyses the macro and micro influencing factors on credit risk of non-ferrousmetals enterprise.After the comparison of the measurement methods of traditional and modern creditrisk models, it is found that traditional methods are lack of forward-looking, poor abilityto predict. Although Credit Metrics, Credit Risk+and Credit Portfolio View have theirown advantages, there is lack of the basic application conditions in China. So this papertakes the KMV model that is relatively mature and most widely used as non-ferrous metalindustry credit risk measurement tools. This paper firstly adjusted equity value, expectedasset growth rate, risk-free interest rate, then set up five different default points, using thedata of2012sample companies from open market in order to verify the validity of theKMV model. The results showed that the original default distance DD under five differentdefault point are not good to distinguish the “default group” and normal group in creditrisk, but the improved new default distance NDD5can effectively check credit riskdifference between two groups of samples, and prediction effect is relatively best, setting default point as the sum of short-term liabilities plus long-term liabilities. The results showthat the eighty one point eight two percent samples whose improved new default distanceNDD5less than3.5are loss in the2013, and eighty eight point eight nine percent thatgreater than3.5in the year2013profit, so this paper take the early warning of newdefault distance NDD5as3.5. With2013data, then this paper estimates the defaultdistance NDD5of40listed companies in nonferrous metal industry. It is found that thereare18companies default distance NDD5less than3.5, expecting their credit risk in2014is still heavy. At the same time, it is also found polarization phenomenon in credit riskbetween different enterprises.Finally, this paper offers some proposal to improve the KMV model prediction ability,including improving the quality of information disclosure of listed companies and theeffectiveness of the securities market in China, establishing the credit database of listedcompanies and to deepen the study of KMV model. And this paper puts forward somecredit advice, for example grasping policy measure, tightening credit to smelting project,maintaining resource security, actively promoting the strategic restructuring, for yourreference.