Bussiness ManagementMBAstrategyHuman ResourceMarketingHospitalityE-commerceInternational Tradingproject managementmedia managementLogisticsFinanceAccountingadvertisingLawBusiness LawEducationEconomicsBusiness Reportbusiness planresearch proposal
英语论文题目英语教学英语论文商务英语英语论文格式商务英语翻译广告英语商务英语商务英语教学英语翻译论文英美文学英语语言学文化交流中西方文化差异英语论文范文英语论文开题报告初中英语教学英语论文文献综述英语论文参考文献
ResumeRecommendation LetterMotivation LetterPSapplication letterMBA essayBusiness Letteradmission letter Offer letter
澳大利亚论文英国论文加拿大论文芬兰论文瑞典论文澳洲论文新西兰论文法国论文香港论文挪威论文美国论文泰国论文马来西亚论文台湾论文新加坡论文荷兰论文南非论文西班牙论文爱尔兰论文
小学英语教学初中英语教学英语语法高中英语教学大学英语教学听力口语英语阅读英语词汇学英语素质教育英语教育毕业英语教学法
英语论文开题报告英语毕业论文写作指导英语论文写作笔记handbook英语论文提纲英语论文参考文献英语论文文献综述Research Proposal代写留学论文代写留学作业代写Essay论文英语摘要英语论文任务书英语论文格式专业名词turnitin抄袭检查
temcet听力雅思考试托福考试GMATGRE职称英语理工卫生职称英语综合职称英语职称英语
经贸英语论文题目旅游英语论文题目大学英语论文题目中学英语论文题目小学英语论文题目英语文学论文题目英语教学论文题目英语语言学论文题目委婉语论文题目商务英语论文题目最新英语论文题目英语翻译论文题目英语跨文化论文题目
日本文学日本语言学商务日语日本历史日本经济怎样写日语论文日语论文写作格式日语教学日本社会文化日语开题报告日语论文选题
职称英语理工完形填空历年试题模拟试题补全短文概括大意词汇指导阅读理解例题习题卫生职称英语词汇指导完形填空概括大意历年试题阅读理解补全短文模拟试题例题习题综合职称英语完形填空历年试题模拟试题例题习题词汇指导阅读理解补全短文概括大意
论文作者:www.51lunwen.org论文属性:硕士毕业论文 dissertation登出时间:2014-09-27编辑:felicia点击率:29796
论文字数:16124论文编号:org201409251350209724语种:英语 English地区:美国价格:免费论文
关键词:非流动性资产资产证券化投资者Asset SecuritizationFinancial Crisis
摘要:资产证券化有什么作用?对金融风险和金融危机有什么影响?如何写好资产证券化留学论文?该从哪里入手?还在等什么,赶快看看这篇文章,这篇文章让你留学美国不再困难,让你申请宾夕法尼亚不再费力,让你留学不再苦恼。
According to (Moody`s Investors service, 2003), In the year 2003 moody's mortgage metrics published and it is as following.
In this model moody's incorporated up to date performance information which they got from loan performance Inc formerly known as mortgage Information Corporation. The loan performance information from loan performance Inc is used to calculate frequency of default, cause and effect relationship of macroeconomic variables and loan loss severity stress
Moody's believe that there is shift in origination practices which are using technology to access borrowers quality, loan risk and appraisal accuracy. So the whole process is streamlined with improved technology, tighter control of lending. However the strict the lending practices are there is huge impact on the loan performance beyond prediction to any statistical model.
There are many refinements to rating approach with stronger emphasis on evaluating the direct sensitivity of loan and pool performance to specific economic stress. Advanced time series analysis increases predictive power and enables meaningful conclusions from even moderately lived vintages.
The rating process starts with the review of an originators and servicers policies and practices. Next comes the analysis of the characteristics of loans in the pool. Then management will allocate corresponding rating accordingly depending up on credit support levels.
A new model has been developed and new parameters have been introduced as inputs. This model is called moody's mortgage metrics (MMM). Once pool is selected MMM run through each and every loan in the pool and simulates it over 1000 economies. MMM takes in to consideration interest rate and unemployment and real-estate movement to determine the probability of loan defaulting, prepaying in any quarter. Performance of the survivors is also simulated in future quarters. So loss analysis is time and history dependent.
Loan loss severity is the function of loan characteristics and local economy. And it is also known that market movement effects loan severity and the effect is complex.
The models result after simulation of loan performance is pool vector which is aggregate of individual loan results into pool losses for each economy. Now having pool loss distribution in hand moody's then analyzes the cash flow to the securitization structure and determines expected loss to any supported tranche
Moody's choose to analyze the likelihood of foreclosure status as a measure of default for loans. Analyzing only loans suffering a loss would have eliminated particularly for loans with deep mortgage insurance, which often generate no net loss to certificate holders even if the property is liquidated.
ne means of measuring the predictive power of the model is to graph power curve. Comparing the models prediction of default frequency to cumulative observations of default. 本论文由英语论文网提供整理,提供论文代写,英语论文代写,代写论文,代写英语论文,代写留学生论文,代写英文论文,留学生论文代写相关核心关键词搜索。