信用風(fēng)險(xiǎn)和資產(chǎn)證券化衍生品定價(jià)方法介紹_第一部分-信用風(fēng)險(xiǎn)理論介紹

1、金融工程案例分析課程， George Yuan， 2013-14第一部分第一部分: 信用風(fēng)險(xiǎn)理論介紹（信用風(fēng)險(xiǎn)理論介紹（2014年年7日上午日上午9:00am-11:30am）第1章信用風(fēng)險(xiǎn)介紹和信用評(píng)級(jí)第2章Merton 信用風(fēng)險(xiǎn)模型, KMV等模型應(yīng)用介紹第3章信用風(fēng)險(xiǎn)價(jià)值量調(diào)整(CVA)介紹第4章單因子結(jié)構(gòu)模型和信用風(fēng)險(xiǎn)價(jià)值量(Credit VaR) 介紹 第二部分第二部分: 信用和資產(chǎn)證券化衍生品定價(jià)信用和資產(chǎn)證券化衍生品定價(jià)( (2014年年7日下午日下午2:30pm-5:00pm) 第1章: 信用互換衍生品（CDS）定價(jià)介紹第2章: 資產(chǎn)證券化衍生品介紹第3章: 資產(chǎn)證券化衍生品定

2、價(jià)中南財(cái)大講學(xué)大綱中南財(cái)大講學(xué)大綱 信用風(fēng)險(xiǎn)和資產(chǎn)證券化衍生品定價(jià)方法介紹信用風(fēng)險(xiǎn)和資產(chǎn)證券化衍生品定價(jià)方法介紹袁先智（同濟(jì)大學(xué)風(fēng)險(xiǎn)管理研究所）第3頁(yè)2012-7-253一一信用風(fēng)險(xiǎn)管理的基本理論信用風(fēng)險(xiǎn)管理的基本理論目錄目錄金融工程案例分析課程， George Yuan， 2013-14第一部分第一部分: 信用風(fēng)險(xiǎn)理論介紹（信用風(fēng)險(xiǎn)理論介紹（2014年年7日上午日上午9:00am-11:30am）第第1章信用風(fēng)險(xiǎn)介紹和信用評(píng)級(jí)章信用風(fēng)險(xiǎn)介紹和信用評(píng)級(jí)第2章Merton 信用風(fēng)險(xiǎn)模型, KMV等模型應(yīng)用介紹第3章信用風(fēng)險(xiǎn)價(jià)值量調(diào)整(CVA)介紹第4章單因子結(jié)構(gòu)模型和信用風(fēng)險(xiǎn)價(jià)值量(Credit

3、 VaR) 介紹 中南財(cái)大講學(xué)大綱中南財(cái)大講學(xué)大綱 信用風(fēng)險(xiǎn)和資產(chǎn)證券化衍生品定價(jià)方法介紹信用風(fēng)險(xiǎn)和資產(chǎn)證券化衍生品定價(jià)方法介紹袁先智（同濟(jì)大學(xué)風(fēng)險(xiǎn)管理研究所）4第3頁(yè)2012-7-253一一Altman Score in Altman Score in 信用信用風(fēng)險(xiǎn)風(fēng)險(xiǎn)分析分析目錄目錄Altman Z-score IntroductionOriginal z-score component definitions variable definition weighting factorZ-score estimated for private firmsZ-score estimated f

4、or non-manufacturers & emerging markets金融工程案例分析課程， George Yuan， 2013-14目錄目錄- -Altman Score in Altman Score in 信用信用風(fēng)險(xiǎn)風(fēng)險(xiǎn)分析分析1. Altman Z-score Introduction1 Estimation of the formulaThe Z-score is a linear combination of four or five common business ratios, weighted by coefficients. The coefficients we

5、re estimated by identifying a set of firms which had declared bankruptcy and then collecting a matched sample of firms which had survived, with matching by industry and approximate size (assets).Altman applied the statistical method of discriminant analysis to a dataset of publicly held manufacturer

6、s. The estimation was originally based on data from publicly held manufacturers, but has since been re-estimated based on other datasets for private manufacturing, non-manufacturing and service companies.The original data sample consisted of 66 firms, half of which had filed for bankruptcy under Cha

7、pter 7. All businesses in the database were manufacturers, and small firms with assets of 2.99 -“Safe” Zones1.81 Z 2.99 -“Grey” ZonesZ 2.9 -“Safe” Zone1.23 Z 2.9 -“Grey” ZoneZ 3.75 -“Safe” Zone1.1 Z 3.75 -“Grey” ZoneZ化層化校正校正信用風(fēng)險(xiǎn)預(yù)期損失計(jì)量：客戶(hù)信用評(píng)級(jí)信用風(fēng)險(xiǎn)預(yù)期損失計(jì)量：客戶(hù)信用評(píng)級(jí)評(píng)級(jí)評(píng)級(jí)風(fēng)險(xiǎn)成本風(fēng)險(xiǎn)成本( (預(yù)期損失預(yù)期損失) )(EL

8、)(EL)=違約概率違約概率(PD)(PD)違約損失率違約損失率(LGD)(LGD)違約風(fēng)險(xiǎn)敞口違約風(fēng)險(xiǎn)敞口(EAD)(EAD)思想成就未來(lái)，專(zhuān)業(yè)創(chuàng)造價(jià)值第8頁(yè)50%50%75%75%100%100%有擔(dān)保有擔(dān)保清收清收損失損失無(wú)擔(dān)保收回?zé)o擔(dān)保收回比例比例擔(dān)保收回比擔(dān)保收回比例例債項(xiàng)評(píng)級(jí)對(duì)應(yīng)債項(xiàng)評(píng)級(jí)對(duì)應(yīng)LGDLGD0%0%25%25%信用風(fēng)險(xiǎn)預(yù)期損失計(jì)算：債項(xiàng)評(píng)級(jí)信用風(fēng)險(xiǎn)預(yù)期損失計(jì)算：債項(xiàng)評(píng)級(jí)客戶(hù)違約后不同業(yè)務(wù)的損失相同嗎？客戶(hù)違約后不同業(yè)務(wù)的損失相同嗎？風(fēng)險(xiǎn)暴露頭寸風(fēng)險(xiǎn)暴露頭寸無(wú)擔(dān)保無(wú)擔(dān)保風(fēng)險(xiǎn)成本風(fēng)險(xiǎn)成本( (預(yù)期損失預(yù)期損失) )(EL)(EL)=違約概率違約概率(PD)(PD)違約損失率

9、違約損失率(LGD)(LGD)違約風(fēng)險(xiǎn)敞口違約風(fēng)險(xiǎn)敞口(EAD)(EAD)違約損失率違約損失率(LGD)(LGD) 授信風(fēng)險(xiǎn)暴露授信風(fēng)險(xiǎn)暴露(EAD)(EAD)思想成就未來(lái)，專(zhuān)業(yè)創(chuàng)造價(jià)值第9頁(yè)信用風(fēng)險(xiǎn)預(yù)期損失計(jì)算示例信用風(fēng)險(xiǎn)預(yù)期損失計(jì)算示例舉例舉例1:1:評(píng)級(jí)為評(píng)級(jí)為A A的客戶(hù)、房產(chǎn)抵押的的客戶(hù)、房產(chǎn)抵押的1 1億元流動(dòng)資金貸款，風(fēng)險(xiǎn)成本是多少？?jī)|元流動(dòng)資金貸款，風(fēng)險(xiǎn)成本是多少？=客戶(hù)信用評(píng)級(jí)客戶(hù)信用評(píng)級(jí)0.30%0.30%違約概率違約概率(PD)(PD)債項(xiàng)評(píng)級(jí)債項(xiàng)評(píng)級(jí)貸款余額貸款余額50%50%1 1億元億元違約損失率違約損失率(LGD)(LGD) 授信風(fēng)險(xiǎn)暴露授信風(fēng)險(xiǎn)暴露(EAD)(E

10、AD)1515萬(wàn)萬(wàn)! !風(fēng)險(xiǎn)成本風(fēng)險(xiǎn)成本( (預(yù)期損失預(yù)期損失EL)EL)舉例舉例2:2:0.15%0.15%評(píng)級(jí)為評(píng)級(jí)為B B的客戶(hù)、房產(chǎn)抵押的的客戶(hù)、房產(chǎn)抵押的1 1億元流動(dòng)資金貸款，風(fēng)險(xiǎn)成本是多少？?jī)|元流動(dòng)資金貸款，風(fēng)險(xiǎn)成本是多少？=LGD)LGD) EAD)EAD)客戶(hù)信用評(píng)級(jí)客戶(hù)信用評(píng)級(jí)3.5%3.5%違約概率違約概率(PD)(PD)50%50%債項(xiàng)評(píng)級(jí)債項(xiàng)評(píng)級(jí)貸款余額貸款余額1 1億元億元175175萬(wàn)萬(wàn)! !風(fēng)險(xiǎn)成本風(fēng)險(xiǎn)成本( (預(yù)期損失預(yù)期損失EL)EL)1.75%!1.75%!第10頁(yè)信用風(fēng)險(xiǎn)的預(yù)期損失和非預(yù)期損失信用風(fēng)險(xiǎn)的預(yù)期損失和非預(yù)期損失預(yù)期損失預(yù)期損失nnnnn預(yù)期損

11、失(EL)是預(yù)計(jì)損失的平均值如果要獲得精確的預(yù)期損失，銀行必須對(duì)違約暴露、違約概率和違約損失率三項(xiàng)風(fēng)險(xiǎn)因素進(jìn)行準(zhǔn)確的計(jì)量可以被銀行所預(yù)見(jiàn)并成為需要考慮的經(jīng)營(yíng)成本，實(shí)質(zhì)上并不構(gòu)成真正的風(fēng)險(xiǎn)在銀行提供的產(chǎn)品價(jià)格（如貸款利率）中得到了補(bǔ)償通過(guò)提取壞賬準(zhǔn)備來(lái)抵補(bǔ)預(yù)期損失，影響銀行的當(dāng)期損益非預(yù)期損失非預(yù)期損失nnnn非預(yù)期損失是損失圍繞預(yù)期損失的波動(dòng)，它表現(xiàn)為風(fēng)險(xiǎn)損失標(biāo)準(zhǔn)差的若干倍違約事件可能存在相關(guān)性，當(dāng)違約同時(shí)發(fā)生時(shí)，資產(chǎn)的價(jià)值將發(fā)生劇烈的變化非預(yù)期損失不能被預(yù)見(jiàn)，是真正意義上的風(fēng)險(xiǎn)，需要使用資本金來(lái)抵補(bǔ)非預(yù)期損失。通常，穩(wěn)健的銀行都應(yīng)至少保證資本金足以抵御概率99.9%以上的非預(yù)期損失非預(yù)期損失

12、也是PD、LGD和EAD的函數(shù)，只不過(guò)更加復(fù)雜信用風(fēng)險(xiǎn)非預(yù)期損失與經(jīng)濟(jì)資本信用風(fēng)險(xiǎn)非預(yù)期損失與經(jīng)濟(jì)資本概率經(jīng)濟(jì)資本量是在一定置信水平下（用評(píng)級(jí)表示）應(yīng)對(duì)非預(yù)期損失的能力。第11頁(yè)損失非預(yù)期損失是在一定置信水平上的風(fēng)險(xiǎn)損失衡量。置信水平越高，損失越大，但概率越低。經(jīng)濟(jì)資本不是真正的銀行資本，它是一個(gè)虛擬的資本數(shù)字，在數(shù)額上與非預(yù)期損失相等。某國(guó)際活躍銀行信用評(píng)級(jí)目標(biāo)評(píng)級(jí)置信度A AA AAA99.9% 99.95% 99.99%第12頁(yè)信用風(fēng)險(xiǎn)的貸款定價(jià)信用風(fēng)險(xiǎn)的貸款定價(jià)貸款定價(jià)需要考慮的要素貸款定價(jià)需要考慮的要素目標(biāo)利潤(rùn)目標(biāo)利潤(rùn)總成本總成本根據(jù)盈利要求確定根據(jù)盈利要求確定考慮經(jīng)濟(jì)資本考慮經(jīng)濟(jì)資

13、本資金轉(zhuǎn)移價(jià)格資金轉(zhuǎn)移價(jià)格根據(jù)預(yù)期損失提根據(jù)預(yù)期損失提取減值準(zhǔn)備取減值準(zhǔn)備運(yùn)營(yíng)費(fèi)用運(yùn)營(yíng)費(fèi)用適用稅率適用稅率資本成本資本成本資金成本資金成本風(fēng)險(xiǎn)成本風(fēng)險(xiǎn)成本運(yùn)營(yíng)成本運(yùn)營(yíng)成本稅務(wù)成本稅務(wù)成本第3頁(yè)2012-7-253一一信用評(píng)級(jí)信用評(píng)級(jí)-Credit Ratings-Credit Ratings目錄目錄第13頁(yè)貸款收入貸款收入 - - 資金成本資金成本 - - 運(yùn)營(yíng)成本運(yùn)營(yíng)成本稅務(wù)成本稅務(wù)成本 - - 風(fēng)險(xiǎn)成本風(fēng)險(xiǎn)成本經(jīng)濟(jì)資本經(jīng)濟(jì)資本RAROCRAROC = =RAROCRAROC是考慮了風(fēng)險(xiǎn)的貸款盈利性指標(biāo)，即是考慮了風(fēng)險(xiǎn)的貸款盈利性指標(biāo)，即“風(fēng)險(xiǎn)調(diào)整后資本收益率風(fēng)險(xiǎn)調(diào)整后資本收益率”。風(fēng)險(xiǎn)調(diào)整

14、后資本收益率和經(jīng)濟(jì)增加值風(fēng)險(xiǎn)調(diào)整后資本收益率和經(jīng)濟(jì)增加值評(píng)價(jià)用評(píng)價(jià)用RAROCRAROC，兌現(xiàn)績(jī)效用，兌現(xiàn)績(jī)效用EVAEVA經(jīng)濟(jì)增加值經(jīng)濟(jì)增加值EVAEVA= = 貸款收入貸款收入 - - 資金成本資金成本 - - 運(yùn)營(yíng)成本運(yùn)營(yíng)成本 - - 稅務(wù)成本稅務(wù)成本 - - 風(fēng)險(xiǎn)成本風(fēng)險(xiǎn)成本資本成本資本成本即：即：EVAEVA = = 經(jīng)風(fēng)險(xiǎn)調(diào)整收益經(jīng)風(fēng)險(xiǎn)調(diào)整收益 資本成本資本成本第14頁(yè)信用風(fēng)險(xiǎn)限額管理信用風(fēng)險(xiǎn)限額管理復(fù)復(fù)雜雜程程度度風(fēng)風(fēng)險(xiǎn)險(xiǎn)反反映映程程度度基于風(fēng)險(xiǎn)等級(jí)限額基于風(fēng)險(xiǎn)等級(jí)限額基于經(jīng)濟(jì)資本的限額管理基于經(jīng)濟(jì)資本的限額管理低低高高高高基于貸款規(guī)?；谫J款規(guī)模經(jīng)濟(jì)資本配置管理是指以限額形式將

15、經(jīng)濟(jì)資本分解到各分支機(jī)構(gòu)、部門(mén)、產(chǎn)品、客戶(hù)等對(duì)象，并進(jìn)行動(dòng)態(tài)監(jiān)控和適時(shí)調(diào)整信用風(fēng)險(xiǎn)限額管理的發(fā)展：控制風(fēng)險(xiǎn) 風(fēng)險(xiǎn)收益的平衡第15頁(yè)信用風(fēng)險(xiǎn)集中度限額管理信用風(fēng)險(xiǎn)集中度限額管理信用集中度風(fēng)險(xiǎn)控制信用集中度風(fēng)險(xiǎn)限額管理信用集中度風(fēng)險(xiǎn)緩釋措施客戶(hù)集中度風(fēng)險(xiǎn)限額信用集中度風(fēng)險(xiǎn)組合限額監(jiān)管要求單一客戶(hù)單一集團(tuán)客戶(hù)最大十家單一客戶(hù)行業(yè)維度資產(chǎn)組合再平衡地區(qū)維度產(chǎn)品維度機(jī)構(gòu)維度信貸資產(chǎn)組合管理信貸資產(chǎn)組合管理n銀行要管理單筆信貸資產(chǎn)風(fēng)險(xiǎn)，更要管理信貸資產(chǎn)組合風(fēng)險(xiǎn)。貸款組合風(fēng)險(xiǎn)絕不是單筆貸款風(fēng)險(xiǎn)銀行要管理單筆信貸資產(chǎn)風(fēng)險(xiǎn)，更要管理信貸資產(chǎn)組合風(fēng)險(xiǎn)。貸款組合風(fēng)險(xiǎn)絕不是單筆貸款風(fēng)險(xiǎn)的算術(shù)加總，需要考慮單筆貸款之間

16、的相關(guān)性。的算術(shù)加總，需要考慮單筆貸款之間的相關(guān)性。 資產(chǎn)組合管理的核心是掌握不同資產(chǎn)之間的風(fēng)險(xiǎn)資產(chǎn)組合管理的核心是掌握不同資產(chǎn)之間的風(fēng)險(xiǎn)相關(guān)性（疊加、消減和對(duì)沖等），從而利用資產(chǎn)相關(guān)性實(shí)現(xiàn)風(fēng)險(xiǎn)的對(duì)沖和消減，通過(guò)風(fēng)險(xiǎn)相關(guān)性配相關(guān)性（疊加、消減和對(duì)沖等），從而利用資產(chǎn)相關(guān)性實(shí)現(xiàn)風(fēng)險(xiǎn)的對(duì)沖和消減，通過(guò)風(fēng)險(xiǎn)相關(guān)性配置實(shí)現(xiàn)風(fēng)險(xiǎn)的對(duì)沖和消減，降低資產(chǎn)同時(shí)損失的可能性。置實(shí)現(xiàn)風(fēng)險(xiǎn)的對(duì)沖和消減，降低資產(chǎn)同時(shí)損失的可能性。n銀行整個(gè)資產(chǎn)組合可以按照不同方式劃分成不同的細(xì)分組合，比如不同地區(qū)組合、不同客戶(hù)對(duì)象組銀行整個(gè)資產(chǎn)組合可以按照不同方式劃分成不同的細(xì)分組合，比如不同地區(qū)組合、不同客戶(hù)對(duì)象組合、不同行業(yè)組合

17、等，最低層次是單個(gè)客戶(hù)的信貸資產(chǎn)組合。不同層次組合之間不但有兩兩相關(guān)性，合、不同行業(yè)組合等，最低層次是單個(gè)客戶(hù)的信貸資產(chǎn)組合。不同層次組合之間不但有兩兩相關(guān)性，還有多重相關(guān)性；不但有一個(gè)層次上的相關(guān)，還有不同層次之間的相關(guān)性。因此，信貸資產(chǎn)組合的還有多重相關(guān)性；不但有一個(gè)層次上的相關(guān)，還有不同層次之間的相關(guān)性。因此，信貸資產(chǎn)組合的研研究是一個(gè)龐大的體系。究是一個(gè)龐大的體系。第16頁(yè)+1+1-1-10 0相關(guān)系數(shù)相關(guān)系數(shù)風(fēng)險(xiǎn)消減效應(yīng)風(fēng)險(xiǎn)消減效應(yīng)最小最小最大最大第17頁(yè)銀監(jiān)會(huì)對(duì)公司客戶(hù)內(nèi)部評(píng)級(jí)體系的要求銀監(jiān)會(huì)對(duì)公司客戶(hù)內(nèi)部評(píng)級(jí)體系的要求總體要求評(píng)級(jí)維度評(píng)級(jí)結(jié)構(gòu)債務(wù)人評(píng)級(jí)方法論和評(píng)級(jí)時(shí)間跨度評(píng)級(jí)標(biāo)準(zhǔn)

18、nnn至少包括債務(wù)人評(píng)級(jí)和債項(xiàng)評(píng)級(jí)兩個(gè)維度債務(wù)人不同債項(xiàng)的債務(wù)人評(píng)級(jí)一致初級(jí)法、高級(jí)法對(duì)債項(xiàng)評(píng)級(jí)要求不同nn使用IRB確定非零售債務(wù)人、債項(xiàng)評(píng)級(jí)，債務(wù)人包括所有債務(wù)人與保證人計(jì)量模型法、專(zhuān)家判斷法或綜合應(yīng)用nnn債務(wù)人評(píng)級(jí)至少7個(gè)非違約級(jí)別，1個(gè)違約級(jí)別有效區(qū)分風(fēng)險(xiǎn)，較高級(jí)別的風(fēng)險(xiǎn)小于較低級(jí)別的風(fēng)險(xiǎn)風(fēng)險(xiǎn)在不同級(jí)別合理分布nnnnnnnn可以采取時(shí)點(diǎn)評(píng)級(jí)法、跨周期評(píng)級(jí)法以及介于兩者之間評(píng)級(jí)方法估計(jì)債務(wù)人的PD同時(shí)考慮影響債務(wù)人違約風(fēng)險(xiǎn)的非系統(tǒng)性和系統(tǒng)性因素應(yīng)估計(jì)債務(wù)人未來(lái)一年違約概率。監(jiān)管部門(mén)鼓勵(lì)商業(yè)銀行采用長(zhǎng)于一年的時(shí)間跨度。模型使用計(jì)量模型應(yīng)在評(píng)估違約特征和損失特征中發(fā)揮重要作用。應(yīng)通過(guò)必要

19、的專(zhuān)家判斷保證內(nèi)部評(píng)級(jí)考慮了所有相關(guān)信息?？梢愿鶕?jù)業(yè)務(wù)的復(fù)雜程度以及風(fēng)險(xiǎn)管理水平建立多種評(píng)級(jí)體系監(jiān)測(cè)模型的預(yù)測(cè)能力，驗(yàn)證模型，持續(xù)改進(jìn)模型表現(xiàn)。對(duì)模型數(shù)據(jù)和假設(shè)的要求。nnnnn評(píng)級(jí)定義和標(biāo)準(zhǔn)應(yīng)合理、直觀，且能夠有意義地區(qū)分風(fēng)險(xiǎn)考慮與債務(wù)人和債項(xiàng)評(píng)級(jí)相關(guān)的所有重要信息。銀行擁有的信息越少，評(píng)級(jí)應(yīng)越保守。內(nèi)部評(píng)級(jí)可參考外部評(píng)級(jí)結(jié)果，但應(yīng)考慮其他信息。文檔化管理書(shū)面記錄非零售風(fēng)險(xiǎn)暴露內(nèi)部評(píng)級(jí)的設(shè)計(jì)。書(shū)面記錄內(nèi)部評(píng)級(jí)的重要過(guò)程、評(píng)級(jí)標(biāo)準(zhǔn)及各級(jí)別定義就模型的方法論、使用范圍等建立完整文檔技術(shù)要求第18頁(yè)內(nèi)部評(píng)級(jí)和五級(jí)分類(lèi)內(nèi)部評(píng)級(jí)和五級(jí)分類(lèi)nnnn內(nèi)部評(píng)級(jí)法是以歷史數(shù)據(jù)為基礎(chǔ)，通過(guò)數(shù)理統(tǒng)計(jì)分析方法，計(jì)算

20、借款人和債項(xiàng)的數(shù)據(jù)指標(biāo)，并籍此開(kāi)展信用風(fēng)險(xiǎn)管理。而五級(jí)分類(lèi)則以主觀判斷為特征，缺乏必要的定量分析，而且沒(méi)有反映出貸款的實(shí)際損失。內(nèi)部評(píng)級(jí)法體現(xiàn)了對(duì)貸款發(fā)放的事先管理，強(qiáng)調(diào)通過(guò)分析既有的數(shù)據(jù)來(lái)預(yù)測(cè)和防范未來(lái)的風(fēng)險(xiǎn)，因而能有效地決定貸款發(fā)放與否、貸款發(fā)放額度、貸款利息水平以及抵押擔(dān)保的要求等。而五級(jí)分類(lèi)則只能在事后的檢查或補(bǔ)救中發(fā)揮作用。內(nèi)部評(píng)級(jí)是二維評(píng)級(jí)系統(tǒng)。一維是針對(duì)借款人；另一維是針對(duì)債項(xiàng)的評(píng)級(jí)。五級(jí)分類(lèi)則是一維評(píng)級(jí)系統(tǒng)，不區(qū)分借款人與債項(xiàng)這兩類(lèi)不同性質(zhì)的風(fēng)險(xiǎn)以及影響這兩類(lèi)風(fēng)險(xiǎn)的重要因素，因此，它并不能準(zhǔn)確地反映風(fēng)險(xiǎn)，更不利于有效地防范風(fēng)險(xiǎn)。借助內(nèi)部評(píng)級(jí)，可以把五級(jí)分類(lèi)細(xì)化為十二級(jí)分類(lèi)。第1

21、9頁(yè)信用風(fēng)險(xiǎn)內(nèi)部評(píng)級(jí)法的風(fēng)險(xiǎn)暴露分類(lèi)信用風(fēng)險(xiǎn)內(nèi)部評(píng)級(jí)法的風(fēng)險(xiǎn)暴露分類(lèi)銀行賬戶(hù)的風(fēng)險(xiǎn)暴露分類(lèi)金融機(jī)構(gòu)銀行類(lèi)機(jī)構(gòu)風(fēng)險(xiǎn)暴露非銀行類(lèi)機(jī)構(gòu)風(fēng)險(xiǎn)暴露兩類(lèi)公司一般公司風(fēng)險(xiǎn)暴露專(zhuān)業(yè)貸款項(xiàng)目融資物品融資商品融資產(chǎn)生收入的房地產(chǎn)中小企業(yè)風(fēng)險(xiǎn)暴露零售個(gè)人住房抵押貸款風(fēng)險(xiǎn)暴露合格循環(huán)零售貸款風(fēng)險(xiǎn)暴露其它零售風(fēng)險(xiǎn)暴露股權(quán)銀行直接或間接持有的股東權(quán)益主權(quán)主權(quán)國(guó)家或經(jīng)濟(jì)實(shí)體區(qū)域及其中央銀行非中央政府公共部門(mén)實(shí)體適用零風(fēng)險(xiǎn)權(quán)重的多邊開(kāi)發(fā)銀行、國(guó)際清算銀行、國(guó)際貨幣基金組織等的債權(quán)第20頁(yè)nnn信用風(fēng)險(xiǎn)管理應(yīng)與業(yè)務(wù)發(fā)展相協(xié)調(diào)，并滿(mǎn)足監(jiān)管要求。信用風(fēng)險(xiǎn)管理工具應(yīng)支持信貸業(yè)務(wù)人員，而不是取代或影響他們的權(quán)威。信用風(fēng)險(xiǎn)管理工具只有在

22、被理解的情況下，才能充分發(fā)揮作用。信用風(fēng)險(xiǎn)管理的基本理念信用風(fēng)險(xiǎn)管理的基本理念信用風(fēng)險(xiǎn)管理是銀行的核心能力信用風(fēng)險(xiǎn)管理是銀行的核心能力nn雖然定量工具對(duì)于信用風(fēng)險(xiǎn)管理的科學(xué)性具有重要作用，但是信用風(fēng)險(xiǎn)管理不是一門(mén)工程學(xué)科。對(duì)于歷史數(shù)據(jù)的分析相當(dāng)有用，但其在信用風(fēng)險(xiǎn)管理中并不起決定性作用。業(yè)務(wù)專(zhuān)家的主觀判斷對(duì)于信用風(fēng)險(xiǎn)管理非常重要。n西方國(guó)家的模型開(kāi)發(fā)技術(shù)，需要根據(jù)國(guó)內(nèi)中小銀行的數(shù)據(jù)質(zhì)量狀況和市場(chǎng)背景，有選擇地采用。信用風(fēng)險(xiǎn)管理是一門(mén)實(shí)用藝術(shù)信用風(fēng)險(xiǎn)管理是一門(mén)實(shí)用藝術(shù)nn為了達(dá)到風(fēng)險(xiǎn)管理的最佳效果，需要風(fēng)險(xiǎn)管理體系的各方面協(xié)調(diào)統(tǒng)一，包括：治理架構(gòu)、政策制度、工具方法、人員培訓(xùn)和信息科技等。只有在

23、一個(gè)完善的風(fēng)險(xiǎn)管理體系中，復(fù)雜的信用風(fēng)險(xiǎn)管理工具和方法，才能充分發(fā)揮其作用。風(fēng)險(xiǎn)管理是一個(gè)復(fù)雜的體系風(fēng)險(xiǎn)管理是一個(gè)復(fù)雜的體系金融工程案例分析課程， George Yuan， 2013-14Historical Data Historical data provided by rating agencies are also used to estimate the probability of default金融工程案例分析課程， George Yuan， 2013-14Cumulative Ave Default Rates (%) (1970-2009, Moodys, Table 23.

24、1, page 522) 1 2 3 4 5 7 10 Aaa 0.000 0.012 0.012 0.037 0.105 0.245 0.497 Aa 0.022 0.059 0.091 0.159 0.234 0.384 0.542 A 0.051 0.165 0.341 0.520 0.717 1.179 2.046 Baa 0.176 0.494 0.912 1.404 1.926 2.996 4.851 Ba 1.166 3.186 5.583 8.123 10.397 14.318 19.964 B 4.546 10.426 16.188 21.256 25.895 34.473

25、44.377 Caa-C 17.723 29.384 38.682 46.094 52.286 59.771 71.376 金融工程案例分析課程， George Yuan， 2013-14Interpretation The table shows the probability of default for companies starting with a particular credit rating A company with an initial credit rating of Baa has a probability of 0.176% of defaulting by t

26、he end of the first year, 0.494% by the end of the second year, and so on金融工程案例分析課程， George Yuan， 2013-14Do Default Probabilities Increase with Time? For a company that starts with a good credit rating default probabilities tend to increase with time For a company that starts with a poor credit rati

27、ng default probabilities tend to decrease with time 金融工程案例分析課程， George Yuan， 2013-14Hazard Rates vs Unconditional Default Probabilities (page 522-523) The hazard rate (also called default intensity) is the probability of default for a certain time period conditional on no earlier default The uncondi

28、tional default probability is the probability of default for a certain time period as seen at time zero What are the default intensities and unconditional default probabilities for a Caa rated company in the third year?金融工程案例分析課程， George Yuan， 2013-14Hazard Rate The hazard rate that is usually quote

29、d is an instantaneous rate If V(t) is the probability of a company surviving to time tttdttetQtetVtVttVttVt)()(1)()()()()()(0is timeby default ofy probabilit cumulative Theto leads This金融工程案例分析課程， George Yuan， 2013-1437Recovery Rate The recovery rate for a bond is usually defined as the price of the

30、 bond immediately after default as a percent of its face value Recovery rates tend to decrease as default rates increase金融工程案例分析課程， George Yuan， 2013-14Recovery Rates; Moodys: 1982 to 2009Class Mean(%) 1st lien bank loan 65.6 2nd lien bank loan 32.8 Sen Unsec. bank loan 48.7 Senior Secured 49.8 Seni

31、or Unsecured 36.6 Senior Subordinated 30.7 Subordinated 31.3 Junior Subordinated 24.7 金融工程案例分析課程， George Yuan， 2013-14Estimating Default Probabilities Alternatives:Use Bond PricesUse CDS spreadsUse Historical DataUse Mertons Model金融工程案例分析課程， George Yuan， 2013-14Using Bond Prices (Equation 23.2, page

32、 524)Average default intensity over life of bond is approximatelywhere s is the spread of the bonds yield over the risk-free rate and R is the recovery rateRs1金融工程案例分析課程， George Yuan， 2013-14More Exact Calculation Assume that a five year corporate bond pays a coupon of 6% per annum (semiannually). T

33、he yield is 7% with continuous compounding and the yield on a similar risk-free bond is 5% (with continuous compounding) Price of risk-free bond is 104.09; price of corporate bond is 95.34; expected loss from defaults is 8.75 Suppose that the probability of default is Q per year and that defaults al

34、ways happen half way through a year (immediately before a coupon payment. 金融工程案例分析課程， George Yuan， 2013-14Calculations (Table 23.3, page 525)金融工程案例分析課程， George Yuan， 2013-14Calculations continued We set 288.48Q = 8.75 to get Q = 3.03% This analysis can be extended to allow defaults to take place mor

35、e frequently With several bonds we can use more parameters to describe the default probability distribution金融工程案例分析課程， George Yuan， 2013-14The Risk-Free Rate The risk-free rate when default probabilities are estimated is usually assumed to be the LIBOR/swap zero rate (or sometimes 10 bps below the L

36、IBOR/swap rate) Asset swaps provide a direct estimates of the spread of bond yields over swap rates金融工程案例分析課程， George Yuan， 2013-14Real World vs Risk-Neutral Default Probabilities The default probabilities backed out of bond prices or credit default swap spreads are risk-neutral default probabilitie

37、s The default probabilities backed out of historical data are real-world default probabilities金融工程案例分析課程， George Yuan， 2013-14A Comparison Calculate 7-year default intensities from the Moodys data, 1970-2009, (These are real world default probabilities) Use Merrill Lynch data to estimate average 7-y

38、ear default intensities from bond prices, 1996 to 2007 (these are risk-neutral default intensities) Assume a risk-free rate equal to the 7-year swap rate minus 10 basis points金融工程案例分析課程， George Yuan， 2013-14Data from Moodys and Merrill Lynch Cumulative 7-year default probability (Moodys: 1970-2009)

39、Average bond yield spread in bps* (Merrill Lynch: 1996 to June 2007) Aaa 0.245% 35.74 Aa 0.384% 43.67 A 1.179% 58.68 Baa 2.996% 127.53 Ba 14.318% 280.28 B 34.473% 481.04 Caa 59.771% 1103.70 *The benchmark risk-free rate for calculating spreads is assumed to be the swap rate minus 10 basis points. Bo

40、nds are corporate bonds with a life of approximately 7 years. 金融工程案例分析課程， George Yuan， 2013-1448Real World vs Risk Neutral Hazard Rates (Table 23.4, page 527) 1 Calculated asln(1-d)/7 where d is the Moodys 7 yr default rate. For example, in the case of Aaa companies, d=0.00245 and -ln(0.99755)/7=0.0

41、004 or 4bps. For investment grade companies the historical hazard rate is approximately d/7. 2 Calculated as s/(1-R) where s is the bond yield spread and R is the recovery rate (assumed to be 40%). 金融工程案例分析課程， George Yuan， 2013-1449Average Risk Premiums Earned By Bond Traders 1 Equals average spread

42、 of our benchmark risk-free rate over Treasuries.2 Equals historical hazard rate times (1-R) where R is the recovery rate. For example, in the case of Baa, 26bps is 0.6 times 43bps.金融工程案例分析課程， George Yuan， 2013-1450Possible Reasons for These Results (The third reason is the most important) Corporate

43、 bonds are relatively illiquid The subjective default probabilities of bond traders may be much higher than the estimates from Moodys historical data Bonds do not default independently of each other. This leads to systematic risk that cannot be diversified away. Bond returns are highly skewed with l

44、imited upside. The non-systematic risk is difficult to diversify away and may be priced by the market金融工程案例分析課程， George Yuan， 2013-14Which World Should We Use? We should use risk-neutral estimates for valuing credit derivatives and estimating the present value of the cost of default We should use re

45、al world estimates for calculating credit VaR and scenario analysis金融工程案例分析課程， George Yuan， 2013-14第一部分第一部分: 信用風(fēng)險(xiǎn)理論介紹（信用風(fēng)險(xiǎn)理論介紹（2014年年7日上午日上午9:00am-11:30am）第1章信用風(fēng)險(xiǎn)介紹和信用評(píng)級(jí)第第2 2章章Merton Merton 信用風(fēng)險(xiǎn)模型信用風(fēng)險(xiǎn)模型, KMV, KMV等模型應(yīng)用介紹等模型應(yīng)用介紹第3章信用風(fēng)險(xiǎn)價(jià)值量調(diào)整(CVA)介紹第4章單因子結(jié)構(gòu)模型和信用風(fēng)險(xiǎn)價(jià)值量(Credit VaR) 介紹 中南財(cái)大講學(xué)大綱中南財(cái)大講學(xué)大綱 信用風(fēng)險(xiǎn)

46、和資產(chǎn)證券化衍生品定價(jià)方法介紹信用風(fēng)險(xiǎn)和資產(chǎn)證券化衍生品定價(jià)方法介紹袁先智（同濟(jì)大學(xué)風(fēng)險(xiǎn)管理研究所）金融工程案例分析課程， George Yuan， 2013-14Using Equity Prices: Mertons Model (page 530-531) Mertons model regards the equity as an option on the assets of the firm In a simple situation the equity value ismax(VT D, 0)where VT is the value of the firm and D is

47、the debt repayment required金融工程案例分析課程， George Yuan， 2013-14Equity vs. Assets The Black-Scholes-Merton option pricing model enables the value of the firms equity today, E0, to be related to the value of its assets today, V0, and the volatility of its assets, sVEV N dDeN ddVDrTTddTrTVVV0012102212()()l

48、n()();wheresss金融工程案例分析課程， George Yuan， 2013-14Volatilities sssEVVEEVVN dV0010()This equation together with the option pricing relationship enables V0 and sV to be determined from E0 and sE金融工程案例分析課程， George Yuan， 2013-14Example A companys equity is $3 million and the volatility of the equity is 80%

49、The risk-free rate is 5%, the debt is $10 million and time to debt maturity is 1 year Solving the two equations yields V0=12.40 and sv=21.23% The probability of default is N(d2) or 12.7%金融工程案例分析課程， George Yuan， 2013-14The Implementation of Mertons Model Choose time horizon Calculate cumulative oblig

50、ations to time horizon. This is termed by KMV the “default point”. We denote it by D Use Mertons model to calculate a theoretical probability of default Use historical data or bond data to develop a one-to-one mapping of theoretical probability into either real-world or risk-neutral probability of d

51、efault.金融工程案例分析課程， George Yuan， 2013-14The Implementation of Mertons Model KMV 模型介紹模型介紹Asset (A(t) = Debt (D(t) + Equity (E(t)Three main approaches to modeling credit risk in the finance literatureStructural approach: Assumptions are made about the dynamics of a firms assets, its capital structure,

52、and its debt and share holders. A firm defaults if the assets are insufficient according to some measure. A liability is characterized as an option on the firms assets.Reduced form approach: No assumptions are made concerning why a default occurs. Rather, the dynamics of default are exogenously give

53、n by the default rate (or intensity). Prices of credit sensitive securities can be calculated as if they were default free using the risk free rate adjusted by the level of intensity. Incomplete information approach: Combines the structural and reduced form approaches.Structural approach: default in

54、 the classical Merton model (1974).1. We want to use the structural approach to incorporate bond default risk in bond valuationThe value of the firms assets are assumed to follow the process, where is the instantaneous expected rate of return on assets, and is the standard deviation of the return on

55、 assets.Let D(t,T) be the date t market value of debt with promised payment B at date t. The second line in (18.2) says that the payoff to the creditors equals the promised payment (B) minus the payoff on a European put option written on the firms assets with exercise price B.Market value of firm de

56、bt, D(t)Let P(t,T) represent the current date t price of a default-free, zero-coupon bond that pays $1 at date T, where the bond conforms with the Vasicek model in Ch. 9. Pennacchi asserts that using results for pricing options (Ch. 9.3) when interest rates are random (as in 9.58), we can write Mark

57、et value of firm equity, E(t)Shareholder equity is similar to a call option on the firms assets, since at maturity the payoff to equity holders is max A(t) B, 0. However, shareholder equity is different from a European option if the firm pay dividends to shareholders prior to maturity as reflected i

58、n the first term of the last line in (18.4) where denotes the dividend rate.Critique of the Merton modelThe Merton model assumption is that the firm has a single issue of zero-coupon debt. That is unrealistic. Modeling multiple issues with different maturities and seniorities complicates default. In

59、 response some models have suggested that default occurs when the firms assets hit a lower boundary. That boundary has a monotonic relation to the firms total outstanding debt. The first passage time is when the value of the firms assets crosses through the lower boundary. First passage model - - bo

60、nd indenture provisions often include safety covenants that give bond holders the right to reorganize the firm if the value falls below a given barrier.The first passage model defines the survival probability as p(t,T) that the distance to default does not reach zero at any date between t and T. The