Loss given default(LGD)is a key parameter in credit risk management to calculate the required regulatory minimum capital.The internal ratings-based(IRB)approach under the Basel II allows institutions to determine the ...Loss given default(LGD)is a key parameter in credit risk management to calculate the required regulatory minimum capital.The internal ratings-based(IRB)approach under the Basel II allows institutions to determine the loss given default(LGD)on their own.In this study,we have estimated LGD for a credit portfolio data by using beta regression with precision parameter(∅)and mean parameter(μ).The credit portfolio data was obtained from a banking institution in Jordan;for the period of January 2010 untilDecember 2014.In the first stage,we have used the“outstandingamount”and“amount of borrowing”to find LGD of each default borrower(494 out of 4393 borrower).In the second stage,we fit univariate parametric distributions to the LGD data to obtain the beta distribution.After that,we have estimated the values of∅based on microeconomic variables(SPP,OE and LR).Moreover,we have estimated the values ofμbased on macroeconomic variables(GDP and Inflation rate).Finally,we have compared between six different link functions(Logit,loglog,probit,cloglog,cauchit,and log),which have used with∅andμ.The results show that Beta regression with probit link function has the highest R-squared with accepted measurements for logL,AIC and BIC.展开更多
In this research,an econometric with panel data using Ordinary least squares OLS model is constructed following the guidelines recommended by the EBA stress test methodology for 2016.The findings indicate that macroec...In this research,an econometric with panel data using Ordinary least squares OLS model is constructed following the guidelines recommended by the EBA stress test methodology for 2016.The findings indicate that macroeconomic factors affecting defaults are the expected ones in the Spanish credit institutions.However,loan impairments do not follow the patterns that a priori would be normal.Divergent is outcomes in defaults and impairments:the Non-Performing Loans(NPL)is pro-cyclical and impairment losses are counter-cyclical.展开更多
基于智能电网融合大数据分析技术,探索海量数据的潜在价值,以实现反窃查违。文中采用高速电力线载波(High-speed Power Line Carrier,HPLC)数据传输技术,对采集到的智能电表的96个时刻电参量进行数据处理,通过引入户表间电压降提出表间...基于智能电网融合大数据分析技术,探索海量数据的潜在价值,以实现反窃查违。文中采用高速电力线载波(High-speed Power Line Carrier,HPLC)数据传输技术,对采集到的智能电表的96个时刻电参量进行数据处理,通过引入户表间电压降提出表间关系距离矩阵、户表标签和户表相似度的概念,以户表相似度计算传输阻抗,确定台区合理线损。结合实际情况下的户表聚类处理和线损识别,验证了构建基于聚类分析的台区传输阻抗特性及线损模型的可靠性,能够精准判别每个台区线损是否正常,正确率达到99%,为反窃查违提供了重要线索。展开更多
基金the Fundamental Research Grant Scheme/Ministry of Education Malaysia[Research No.:FRGS/1/2019/STG06/UKM/01/5]and the Research University Grant/Universiti Kebangsaan Malaysia [Research No.: GUP-2019-031]. Initials ofauthors who received the grant: N. Ismail.
文摘Loss given default(LGD)is a key parameter in credit risk management to calculate the required regulatory minimum capital.The internal ratings-based(IRB)approach under the Basel II allows institutions to determine the loss given default(LGD)on their own.In this study,we have estimated LGD for a credit portfolio data by using beta regression with precision parameter(∅)and mean parameter(μ).The credit portfolio data was obtained from a banking institution in Jordan;for the period of January 2010 untilDecember 2014.In the first stage,we have used the“outstandingamount”and“amount of borrowing”to find LGD of each default borrower(494 out of 4393 borrower).In the second stage,we fit univariate parametric distributions to the LGD data to obtain the beta distribution.After that,we have estimated the values of∅based on microeconomic variables(SPP,OE and LR).Moreover,we have estimated the values ofμbased on macroeconomic variables(GDP and Inflation rate).Finally,we have compared between six different link functions(Logit,loglog,probit,cloglog,cauchit,and log),which have used with∅andμ.The results show that Beta regression with probit link function has the highest R-squared with accepted measurements for logL,AIC and BIC.
文摘In this research,an econometric with panel data using Ordinary least squares OLS model is constructed following the guidelines recommended by the EBA stress test methodology for 2016.The findings indicate that macroeconomic factors affecting defaults are the expected ones in the Spanish credit institutions.However,loan impairments do not follow the patterns that a priori would be normal.Divergent is outcomes in defaults and impairments:the Non-Performing Loans(NPL)is pro-cyclical and impairment losses are counter-cyclical.
文摘基于智能电网融合大数据分析技术,探索海量数据的潜在价值,以实现反窃查违。文中采用高速电力线载波(High-speed Power Line Carrier,HPLC)数据传输技术,对采集到的智能电表的96个时刻电参量进行数据处理,通过引入户表间电压降提出表间关系距离矩阵、户表标签和户表相似度的概念,以户表相似度计算传输阻抗,确定台区合理线损。结合实际情况下的户表聚类处理和线损识别,验证了构建基于聚类分析的台区传输阻抗特性及线损模型的可靠性,能够精准判别每个台区线损是否正常,正确率达到99%,为反窃查违提供了重要线索。
