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Research On The Factors Of Credit Risk In Iron Trade Financing

Posted on:2020-01-24Degree:MasterType:Thesis
Country:ChinaCandidate:Y C WuFull Text:PDF
GTID:2481306536999599Subject:International business
Abstract/Summary:PDF Full Text Request
In recent years,China's major commercial banks have launched a business on iron ore trade financing,providing corresponding financing services to iron ore traders,which greatly eased the financial pressure of iron ore traders and contributed to iron ore.Stone traders make full use of resources to improve the overall utilization rate and turnover rate of iron ore.Of course,for commercial banks,iron ore trade financing as a loan business will inevitably face some risks,such as the collective trade of steel traders in the Yangtze River Delta region at the end of 2011,the Qingdao Port fraud incident in 2014,etc.Commercial banks bring a large credit risk.From the perspective of commercial banks,in the context of vigorously developing iron ore trade financing business,strengthen the credit risk control of iron ore trade financing,reduce the overall credit risk of commercial banks and the losses caused by credit risks,which is undoubtedly It is very important and important.Based on this,this paper hopes to take the credit risk perspective of iron ore trade financing as the research entry point,and through the combination of theoretical analysis and empirical research,grasp the key factors of iron ore trade financing credit risk,and then propose iron ore trade.Effective countermeasures and suggestions for financing credit risk prevention.This paper focuses on the research and discussion of iron ore trade financing credit risk,from the concept and theory of iron ore trade financing credit risk,introduces the theoretical model of iron ore trade financing credit risk,and analyzes China's commercial bank iron ore.The current status of trade finance,understanding the current status of iron ore trade financing.Then,from the four aspects of macroeconomic factors,industry fluctuation factors,loan characteristics and borrower characteristics,the impact of these four factors on the credit risk of iron ore trade financing is analyzed.At the same time,according to the analysis of influencing factors,establish a logistic model of iron ore trade financing credit risk,set research variables,select research sample data,and use logistic regression analysis to empirically study the influencing factors of iron ore trade financing credit risk,and obtain the following aspects.in conclusion:First,the macroeconomic factors that use the annual growth rate of GDP as a measure have a significant negative impact on the credit risk of iron ore trade financing,that is,the higher the annual GDP growth rate,the better the macroeconomic situation,the iron ore.The lower the trade finance credit risk.Second,the iron ore price index as a measure of industry fluctuations has a significant negative impact on the iron ore trade financing credit risk,that is,the higher the iron ore price index,the iron ore industry is in a boom cycle.The lower the credit risk of iron ore trade financing.Third,the margin ratio of loan characteristics has a significant negative impact on the iron ore trade financing credit risk,that is,the higher the margin ratio,the lower the iron ore trade financing credit risk.At the same time,the loan interest rate,loan term,and loan balance of the loan characteristics have a significant positive impact on the iron ore trade financing credit risk,that is,the higher the loan interest rate,the longer the loan term,and the more the loan balance,the iron ore.The higher the credit risk of trade finance.Fourth,the borrower's operating income,the borrower's operating time and the borrower's asset-liability ratio have a significant negative impact on the iron ore trade financing credit risk,ie the higher the borrower's operating income,the operating time The longer the asset-liability ratio,the lower the credit risk of iron ore trade financing.
Keywords/Search Tags:iron ore trade financing, credit risk, influencing factors, logistic model
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