穆迪的政府相关发行人评级方法论

Rating Methodology

The Application of Joint Default Analysis to Government Related Issuers

Introduction

This Rating Methodology describes the extension of joint-default analysis (JDA), as announced in a February 2005Special Comment, to government-related issuers (GRIs).1 That Special Comment followed a Request for Comment,issued in December 2004, in which Moody’s proposed incorporation of joint-default analysis to rated, non-structured finance entities.

We define a GRI as an entity with full or partial government ownership or control, a special charter, or a public-policy mandate from the national or local government. An issuer fully or partially owned (or controlled) by a GRI may also be included in the new approach.

The joint-default methodology represents an elaboration and systematization of Moody’s prior approach to rating issuers and obligations with full or partial support. It explicitly accounts for a) the GRI’s baseline, or stand-alone, risk assessment (detailed below); b) the supporting government’s rating; c) an estimate of default correlation between the two entities; and d) the degree of government support.

The first section of this special comment reviews the methodology underlying joint-default analysis. The second section characterizes GRIs and provides guidance on implementing JDA for GRIs. The final section offers examples in which JDA is applied to hypothetical situations.

Overview of Joint-Default Analysis

JDA formally incorporates the following principle: The risk that two obligors will both default should be less than or equal to the default risk of the stronger obligor. It allows us to approach the problem of rating obligations subject to the credit strength of two obligors. The most straightforward situation is where one party (the supporter) uncondi-tionally guarantees the obligations of another. But it is not difficult to extend the analysis to situations in which the strength of the guarantee, or “support,” is less than full.2

1. Please see Moody’s Special Comment “The Incorporation of Joint-Default Analysis into Moody's Corporate, Financial and Government Rating Methodologies,” Feb-ruary 2005.

2. The Appendix to this document provides a technical summary of the joint-default methodology .New York

Jerome S. Fons 1.212.553.1653

Vincent J. Truglia Christopher T. Mahoney Contact Phone

April 2005

The methodology, as described in the appendix, relies on conditional default analysis to characterize the credit dependence between two obligors. We propose a weighting parameter W to represent the degree of dependence between two obligors’ baseline, or stand-alone, default risk. The more highly dependent – or correlated – the two obligors’ baseline default risk, the lower the benefits achieved from joint support.

As applied to GRIs, the dependence parameter W is a function of any intrinsic economic relationship between the GRI and its sponsoring government. It captures shared sources of business or credit risk, but it is independent of the two parties’ vulnerability to default. That is, while the baseline credit profiles of the GRI and the sponsoring gov-ernment may change over time, their default dependence need not change.

Extending the analysis to incorporate partial support is accomplished by considering two extremes: no support and full support. Where support is non-existent, the default risk faced by an investor is simply the baseline default risk of the GRI. On the other hand, full support reduces default risk to that of the joint-default (i.e., guarantee) situation, in turn a function of credit dependence, as described above. We therefore model support as a second weighting parameter S which places the final credit risk somewhere between these two outcomes.

In order to successfully apply JDA, one must have estimates of baseline default risk for each party to a transaction. In most situations, this is not difficult. But an estimate of the baseline risk of, say, a state-owned railway, becomes somewhat more complicated, as described below.

At least initially, Moody’s intends to publicly release only ranges for the model inputs (aside from the published rating of the supporting government). The dependence ratio and support probability will be expressed as being low, medium or high. Likewise, the baseline risk assessment for the GRI will be expressed as falling within a risk scale ranging between 1 and 6, with 1 representing the lowest risk. The next section provides an overview of each of these inputs.

Implementation Guidelines for GRIs

Definition of GRI

In order to apply joint default analysis to a government related issuer, one must first estimate the baseline credit risk of the underlying obligor. T o be considered a GRI, an issuer should meet the following criteria:3?The issuer should have full or partial (national or local) government ownership or have a charter from the (national or local) government.4 An issuer fully or partially owned or controlled by a GRI may be consid-ered a GRI.

?The issuer does not have taxing authority.5

Examples of GRIs are state-owned electric utilities, railroads, government-sponsored enterprises (GSEs), devel-opment banks and highway authorities.

Baseline Default Risk

In many instances, the continuing operation of a GRI depends on some form of subsidy, tariff or capital support scheme. Its charter may require the GRI to provide a public service which otherwise would not be met through pri-vate enterprise, or if offered privately, might entail unacceptable private costs or pose national security concerns. In many countries, natural monopolies are prime candidates for GRI status.

In most other applications, an assessment of baseline default risk simply means that the analysis excludes parent, state or third party support. When applied to a government-related institution that requires a subsidy to survive, the concept of baseline default risk becomes more complex. Because such institutions would fail absent financial ties to a supporting government, we have chosen to refine our criteria for baseline risk. In particular:

The baseline risk assessment for a government-related institution measures the likelihood that the issuer will

require an extraordinary bailout. It takes into account all aspects of the entity's existing (or anticipated) business

model, including benefits (such as regular subsidies or credit extension) and/or drags associated with the govern-

ment relationship.

In other words, the baseline risk assessment for a GRI can incorporate normal operating subsidies and therefore contemplates the risk that it would need an extraordinary bailout from the government.6 By including maintenance, a GRI’s financial attributes may be compared to global peers (fully private firms as well as other GRIs) in determining its baseline default risk.7

3. We exclude from this analysis US Public Finance state and local governments.

4. Here, partial government ownership is generally considered be 20% or greater.

5. Sub-national government ratings will be evaluated under joint-default analysis at a later date.

2Moody’s Rating Methodology

Moody’s Rating Methodology 3

Separating bailout risk from on-going

financial assistance is one of the challenges

in applying this methodology to GRIs. The

question arises: At what point do subsidies

become a de facto bailout? The guiding prin-

ciple is that any normal maintenance fac-

tored into the baseline risk assessment must

not be viewed as extraordinary “support”

when determining the degree of govern-

ment support (as discussed below) so as to

avoid double-counting government support

benefits.Default Dependence/Correlation

T o calculate the joint-default risk between a GRI and its sponsoring government, one needs an estimate of their default dependence.8 Maximum possible dependence holds if, given a default by the supporting government, the GRI will default with certainty. In other words, the baseline credit profiles of the government and the GRI are inextricably linked. In such a situation, the joint-default risk will equal the sovereign’s default risk. Any ratings on such fully sup-ported obligations would therefore be capped at the sovereign’s rating.

Minimum possible dependence holds if, given a default by the supporting government, the GRI’s default risk (absent extraordinary support) remains consistent with its baseline default risk assessment. In other words, their default risks are independent of one another and the joint-default risk is therefore equal to the product of their respec-tive default probabilities.9

One can imagine situations in which the credit profile of a GRI could be independent of the supporting govern-ment. A commercially run commodity exporter located in a low-rated developing country would be one example. A rating committee might assign a dependence factor W of just 20% in such a case.

On the other hand, an electric utility operating in the same country would likely experience high default depen-dence with the sovereign. Here, a committee might assign a dependence factor W as high as 70% or higher. For situ-ations where there is no compelling guidance in either direction, a dependence factor W of 50% – meaning that the joint-default risk between the GRI and the sovereign lies halfway between the product of their default risks and the default risk of the sovereign – is an acceptable choice.

Degree of Support

The final input to the rating process is an assessment of the degree of government support for a GRI. This is the like-lihood that the government will step in and bail out a GRI if it were to experience a catastrophic loss. An explicit guar-antee would be an example of full support (S=100%). In this case, the default risk faced by a GRI’s bondholders is simply the joint-default risk of the GRI and the supporting government – in turn, a function of their respective base-line ratings and the dependence factor.

At the other extreme, where support is non-existent, the default risk faced by an investor is simply the baseline default risk of the GRI. In most cases, however, support for a GRI can not be characterized as a guarantee, in which case judgment is required to place support along a continuum. We rarely assume that government support for a GRI is non-existent (S=0%), but is instead a positive value that is itself a function of several factors. Among these are the percentage of state ownership, national importance of the GRI, privatization status and political tolerance towards government intervention. The table below provides guidance as to how these and other factors might map to a sup-port assessment.

6.

The sovereign’s baseline default risk is typically represented by its government bond rating. However, a sovereign’s ability to bail out an entity may , under certain cir-cumstances, be stronger than that suggested by the published government bond rating – which focuses on the ability and willingness of the sovereign to make debt payments as promised. The willingness to support an entity is captured in the analysis by the parameter S, as discussed below.7.

This holds for GRIs with a well-defined, commercial function. Please refer to Moody’s Industry Rating Methodology for the sector in question.8.

The term “dependence” as used here is synonymous with, but not exactly the same as, “default correlation.”9. In accordance with prevailing practice, we exclude the possibility of negative default correlation. If it were allowed, the minimum possible joint-default probability would instead be zero.Baseline Risk Assessments A baseline risk assessment is an opinion of the likelihood that an issuer will require an extraordinary bailout.Moody's Baseline Risk Assessment Definitions:1Entities with baseline risk assessments of 1 are judged to exhibit minimal credit risk.2Entities with baseline risk assessments of 2 are judged to be of very low credit risk.3Entities with baseline risk assessments of 3 are judged to be of low credit risk.4Entities with baseline risk assessments of 4 are judged to be of moderate credit risk.5Entities with baseline risk assessments of 5 are judged to exhibit substantial credit risk.6Entities with baseline risk assessments of 6 are judged to be of high credit risk.

4Moody’s Rating Methodology TYPICAL ATTRIBUTES OF STATE SUPPORT FOR GOVERNMENT-RELATED ISSUERS

Application and Examples

We now illustrate how the joint-default methodology would be applied to GRIs. The case studies below use hypothet-ical issuers and do not necessarily reflect real-world firms or countries.

State-Owned Electric Utility

Consider a 50% state-owned electric utility which is located in a developed country rated Aaa. A rating committee has determined that, based on its intrinsic financial profile, the baseline default risk for the utility is a Baa2 risk. This rat-ing incorporates a statutory tariff enjoyed by the firm, but it excludes the likelihood of an extraordinary bailout.

The default dependence between the utility and the state is estimated to be medium at W=50%, reflecting the fact that the linkage between electricity demand and the country’s overall economic performance is thought to be moder-ate, as well as the moderate risk that the government would implement price controls coincident with a sovereign default on local currency instruments.

Finally, it is estimated that the probability that the government would bailout bondholders in the event of a failure by the utility is moderate, and the committee therefore votes on a value of S=60%. For this combination of inputs, the resulting, supported rating is A3.

State-owned Oil Refinery

We now consider an oil refiner, 100% owned by the government. Assume that the government itself is rated A3. A rating committee determines that the baseline default risk of the refiner is equivalent to Baa3. Dependence is consid-ered low at W=25% and support is considered relatively high at S=75%. Here the GRI’s supported rating would equal Baa1, one notch below the supporting government.

State Railway

Many railway systems throughout the world operate at a loss, with government subsidies required to maintain opera-tions and debt service. Consider a state-owned railway system located within a country rated A2. A rating committee has estimated that the railway’s baseline default risk is equivalent to a Ba1 risk. This risk assessment incorporates nor-mal subsidies, but excludes any support likely to be extended in the event of a catastrophe.

The default dependence between the railway and the sovereign is considered to be moderate and a rating commit-tee has agreed on a value for W of 50%. State support is thought to be relatively strong, resulting in an estimate for S of 85%. The resulting, supported rating for the GRI would therefore be Baa1.LOW SUPPORT 0-30%

MEDIUM SUPPORT 31-70%HIGH SUPPORT 71-100%1 - State ownership

- Less than 51%- Between 51 and 100%100%2 - Privatisation status - In the process of being privatised - Legal minimum stake to be maintained is below 50%

- No immediate prospects, but possible over medium-term (5 years)- Legal minimum stake is 50%- Will not be privatised within 5 years, or full guarantee required if stake is reduced 3 - Governance and business model - Government is an arm's length shareholder - Company is managed and funded on a fully stand-alone basis - No differentiating legal status - History of fund flows between entity and state (e.g., dividends and capital injections), but not mandatory or budgeted - Management is mostly state-appointed, beyond proportional representation - No differentiating legal status

- Legal status at or close to EPIC/Ente Publico, or Authority - Stable legal status, or assets/liabilities may be transferred to State in future - If no specific legal status, entity budget relies substantially on government funding - Business model is not viable 4 - Political tolerance for government intervention and support - No government economic intervention allowed - No evidence of direct support, or statements from government that direct support is likely - Legislative/regulatory body (e.g. EU) is very likely to object and prevail - Moderately interventionist government - Indirect State support likely (e.g., willing to act as "deep-pocket" shareholder)- Legislative/regulatory body (e.g., EU) likely to raise objections to additional future support

- Highly interventionist government - Documented support intentions (e.g., letters of comfort, consolidation on government books)- Entity is key to country's economic health - Legislative/regulatory body (e.g., EU) not very likely to object 5 - National importance of issuer - Low - Financial health of entity is not strategic to government - Entity is likely "flagship" national company

- Avoidance of default deemed critical to financial reputation of State 6 - Possible sources of delays in providing support

- If willing to support, there may be very significant internal impediments to timely support (e.g., bureaucratic processes, unclear or very politicised mechanisms, etc.)- Internal processes are well defined, but support process can be exposed to complexity of mechanism (e.g., multiple municipalities) or external interference (e.g., legislation)- Support deemed to be timely in all cases

Appendix – A Review of Joint-Default Analysis

CONDITIONAL DEFAULT PROBABILITIES

The probability that two parties will jointly default depends on a) the probability that one of them defaults, and b) the

probability that the second will default, given that the first has already defaulted. Expressed algebraically, one can write this for events A and B as:10

P(A and B) = P(A | B) x P(B) (1) Or equivalently,

P(A and B) = P(B | A) x P(A) (2) We define A as the event “obligor A defaults on its obligations” and B as the event “obligor B defaults on its obliga-tions.” Likewise, “A and B” is the joint-default event “obligors A and B both default on their obligations.”11 The oper-ator P(?) represents the probability that event “?” will occur and P(? | *) is defined as the conditional probability of event “?” occurring, given that event “*” has occurred.

Moody’s ratings can be used to infer directly the probability that a particular issuer will default (P(A) and P(B)).12 But in order to estimate the conditional default probabilities P(A | B) and P(B | A), one must take into account the relationship between the drivers of default for both obligors. Each of these four probabilities – P(A), P(B), P(A | B) and P(B | A) – are intended to represent unsupported risk measures. That is, they represent the likelihood of an obli-gor default in the absence of any joint support or interference. We present in the Applications and Examples section below a framework for modeling both support and interference.

Although in theory, one can tackle this problem directly by estimating either one of the conditional default proba-bilities described in equations (1) and (2), it may be more intuitive to focus on the product of the conditional probabil-ity of default for the lower-rated, or supported, firm and the unconditional probability of default for the higher-rated, or supporting, firm. Using L to denote the event “lower-rated obligor L defaults on its obligations” and H to denote “higher-rated obligor H defaults on its obligations,” we can rewrite equation (1) as:

P(L and H) = P(L | H) x P(H) (3) It is not difficult to imagine situations where the conditional probability P(L | H) might be at its theoretical max-

imum (i.e., 1) or at its minimum (i.e., P(L)).13 Let us consider these extreme outcomes in turn by way of example.

?P(L | H) = 1. Suppose that the financial health of an issuer is crucially linked to the operations of another, higher-rated entity. For example, the default risk of a distributor in a competitive distribution market dom-inated by a single supplier may be highly dependent on the financial health of that supplier. In other words, the conditional probability of the distributor’s default given a default by the higher-rated supplier, P(L | H), is equal to one. In this case, events L and H are maximally correlated.14 Under such a scenario, the joint-default probability P(L and H) in equation (3) above is simply P(H). That is, the rating applied to such jointly supported obligations would equal the supplier’s rating, without any ratings lift, regardless of issuer L’s standalone rating.

10. Statisticians will recognize these equations as axioms of probability theory that underlie Bayes’ Theorem.

11. The implication here is that the default events occur simultaneously, but we require only that the timing be such that a holder of the supported obligation suffers credit

loss within a specified horizon.

12. Moody’s ratings are defined as ordinal (or relative) measures of default risk and not in terms of cardinal (or absolute) default rates. However, as long as ratings can

provide a constant measure of relative default risk, with actual default probabilities rising and falling proportionately by rating category over a credit cycle, the methods proposed here will produce logically consistent measures of jointly supported ratings.

13. T echnically, the conditional default probability P(L | H) could be as low as zero, a situation which would occur if the default correlation between the two obligors was at

its theoretically maximum negative value. However, throughout this discussion, we follow the standard practice of ignoring the highly unlikely possibility that the default experience of the two obligors will be negatively correlated.

14. This use of the term “correlation” applies to default events that follow a binomial distribution and should not be confused with potential correlation in rating transitions

(or default intensities). When the default profiles of two obligors are maximally correlated, P(L | H) = 1 and P(H | L) = P(H)/P(L). That is, the weaker entity always defaults when the stronger entity defaults, and the stronger entity will only default if the weaker entity also defaults. This leads to the result P(H | L) = P(H)/P(L). Note that maximum correlation will be less than 1 in cases where obligors have different ratings.

Moody’s Rating Methodology5

?P(L | H) = P(L). Suppose a highly rated European bank provides a letter of credit to a lower-rated agribusi-ness in the US. While there may be circumstances in which the agribusiness might face financial difficulties on its own, its intrinsic operational health is generally unrelated to the circumstances that might lead the European bank to default on its obligations. Under this scenario, the conditional probability of a default by the agribusiness, given a default by the bank – i.e., P(L | H) – is simply the standalone default risk P(L) of the agribusiness. That is, events L and H are uncorrelated and independent of one another. In this case, their joint-default probability is the product of their standalone default probabilities, P(L)*P(H). The jointly supported obligation rating implied by such a relationship is generally higher than the rating of the supporting entity H.

In practice, the conditional default risk of the lower-rated entity, given a default by the stronger entity, will vary somewhere between these two extremes, maximum correlation (i.e., where P(L | H) = 1) and independence, (i.e., where P(L | H) = P(L))

INTERMEDIATE LEVELS OF CORRELATION

We propose here a simple tool for modeling intermediate cases of default risk linkage. Let us denote the variable W as a correlation weighting factor, where W = 1 corresponds to a maximum theoretical correlation between the default of the lower-rated entity and that of the higher-rated entity; and W = 0 corresponds to a complete independence (i.e., zero correlation) between default events. Fractional values of W indicate intermediate levels of correlation between the two default events.

Using the correlation weighting concept, we can express the joint-default probability between obligors L and H as: P (L and H) =W* P(L and H | W=1) + (1-W)* P(L and H | W=0) (4) Or more compactly,

P(L and H) = W*P(H) + (1 - W)*P(L)* P(H) (5) In other words, once we have determined standalone ratings for the two obligors, the task of assigning a rating to a jointly supported obligation may be reduced to the assignment of a correlation weight.15

PARTIAL SUPPORT

In many cases, an obligation benefits from external support, but that support falls short of an iron-clad guarantee. Examples include bonds issued by a weak subsidiary of a relatively strong parent firm, or bonds issued by an issuer with partial government ownership. In the latter case, the government's incentive to bail the issuer out, should it run into difficulties, may be a function of the share of government ownership or of the importance of that issuer to the national economy.

It is helpful to think of the two extreme situations in which an investor faces losses. The first is where the issuer of the obligation defaults and there is no external support. The probability of this event occurring is simply P(L), the probability that issuer L will default on its own. The second is where there is full support, but both the issuer and the support provider default on their obligations. As above, this is given by P(L and H). The degree of support can also be thought of as a probability and can therefore vary between 0 and 1. We model the risk to the investor as a shifting probability between the two risk outcomes P(L) and P(L and H):

P(L and H | S) = (1-S)*P(L)+S*P(L and H) (6) Here, the weighting parameter S represents the likelihood of support. Full support (i.e., S = 1) leads to the joint-default outcome and no support (i.e., S = 0) yields the standalone default risk of the obligor, P(L).

15. While this derivation focused on P(L | H), it could also be approached through a focus on P(H | L). (See footnote 15.) An alternative methodology is described in a

paper published by Douglas Lucas, “Default Correlation and Credit Analysis,” The Journal of Fixed Income, Vol. 4, No. 4, March 1995.

6Moody’s Rating Methodology

Related Research

Special Comment:

The Incorporation of Joint-Default Analysis into Moody's Corporate, Financial and Government Rating Methodologies, February 2005 (91617)

T o access any of these reports, click on the entry above. Note that these references are current as of the date of publication of this report and that more recent reports may be available. All research may not be available to all clients.

Moody’s Rating Methodology7

? Copyright 2005, Moody’s Investors Service, Inc. and/or its licensors including Moody’s Assurance Company, Inc. (together, “MOODY’S”). All rights reserved. ALL INFORMATION CONTAINED HEREIN IS PROTECTED BY COPYRIGHT LAW AND NONE OF SUCH INFORMATION MAY BE COPIED OR OTHERWISE REPRODUCED, REPACKAGED, FURTHER TRANSMITTED, TRANSFERRED, DISSEMINATED, REDISTRIBUTED OR RESOLD, OR STORED FOR SUBSEQUENT USE FOR ANY SUCH PURPOSE, IN WHOLE OR IN PART, IN ANY FORM OR MANNER OR BY ANY MEANS WHATSOEVER, BY ANY PERSON WITHOUT MOODY’S PRIOR WRITTEN CONSENT . All information contained herein is obtained by MOODY’S from sources believed by it to be accurate and reliable. Because of the possibility of human or mechanical error as well as other factors, however, such information is provided “as is” without warranty of any kind and MOODY’S , in particular, makes no representation or warranty, express or implied, as to the accuracy, timeliness, completeness, merchantability or fitness for any particular purpose of any such information. Under no circumstances shall MOODY’S have any liability to any person or entity for (a) any loss or damage in whole or in part caused by,resulting from, or relating to, any error (negligent or otherwise) or other circumstance or contingency within or outside the control of MOODY’S or any of its directors, officers, employees or agents in connection with the procurement, collection, compilation, analysis, interpretation, communication, publication or delivery of any such information, or (b) any direct, indirect,special, consequential, compensatory or incidental damages whatsoever (including without limitation, lost profits), even if MOODY’S is advised in advance of the possibility of such damages, resulting from the use of or inability to use, any such information. The credit ratings and financial reporting analysis observations, if any, constituting part of the information contained herein are, and must be construed solely as, statements of opinion and not statements of fact or recommendations to purchase, sell or hold any securities. NO WARRANTY,EXPRESS OR IMPLIED, AS TO THE ACCURACY, TIMELINESS, COMPLETENESS, MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OF ANY SUCH RATING OR OTHER OPINION OR INFORMATION IS GIVEN OR MADE BY MOODY’S IN ANY FORM OR MANNER WHATSOEVER. Each rating or other opinion must be weighed solely as one factor in any investment decision made by or on behalf of any user of the information contained herein, and each such user must accordingly make its own study and evaluation of each security and of each issuer and guarantor of, and each provider of credit support for, each security that it may consider purchasing, holding or selling.

MOODY’S

hereby discloses that most issuers of debt securities (including corporate and municipal bonds, debentures, notes and commercial paper) and preferred stock rated by MOODY’S have, prior to assignment of any rating, agreed to pay to MOODY’S for appraisal and rating services rendered by it fees ranging from $1,500 to $2,400,000. Moody’s Corporation (MCO) and its wholly-owned credit rating agency subsidiary, Moody’s Investors Service (MIS), also maintain policies and procedures to address the independence of MIS’s ratings and rating processes. Information regarding certain affiliations that may exist between directors of MCO and rated entities, and between entities who hold ratings from MIS and have also publicly reported to the SEC an ownership interest in MCO of more than 5%, is posted annually on Moody’s website at https://www.wendangku.net/doc/0d4919104.html, under the heading “Shareholder Relations — Corporate Governance — Director and Shareholder Affiliation Policy.”

8

Moody’s Rating Methodology T o order reprints of this report (100 copies minimum), please call 1.212.553.1658.Report Number: 92432Author Production Manager

Jerome Fons William L. Thompson

穆迪 评级方法

Rating Methodology Request for Comment Bank Financial Strength Ratings: Revised Methodology Summary This report details Moody’s proposal to revise our rating methodology for assigning Bank Financial Strength Ratings (BFSRs) globally.1 This revision does not change the main factors that Moody’s considers in rating banks. However,the revised approach provides a single, global methodology instead of separate methodologies for mature and develop-ing markets. It also establishes specific ranges for each factor that relate to different rating categories. The updated methodology is intended to provide investors and issuers with a transparent set of guidelines allowing them to better understand our rating process and how we reach our decisions. T o this end, we have developed a rating scorecard that uses a common set of globally available financial metrics together with key qualitative factors that Moody’s analysts consider critical in evaluating a bank’s intrinsic financial strength and specific weights for each factor. This scorecard will be used by Moody’s analysts as the first step in deter-mining BFSRs. It should also enable investors and issuers to independently estimate a BFSR for most banks within two notches. This report describes the scorecard and discusses some of its limitations as well as some of the further adjust-ments that Moody’s analysts may employ in assigning BFSRs. The revised methodology is also intended to improve the consistency of Moody’s BFSRs. As previously announced, Moody’s intends to incorporate joint-default analysis (JDA) into our assessment of external support for banks later this year.2 We believe the updated BFSR methodology will help ensure that existing BFSRs are indeed “pure” measures of stand-alone financial strength and do not include external support. This is important in order to avoid double counting external support when we implement JDA for banks. We are requesting comments because we believe that the implementation of this methodology could lead to changes in the BFSRs for a significant number of banks, although we do not expect most of those to exceed 2 notches. Readers should note that this methodology is not an exhaustive treatment of every factor considered by Moody’s in assigning bank financial strength ratings, but it should enable our constituents to better understand how and why we arrive at a BFSR. Moody’s welcomes comments or suggestions on this proposal from market participants. Comments should be sent to cpc@https://www.wendangku.net/doc/0d4919104.html, by September 29, 2006. 1.Moody's current approach is outlined in the following Rating Methodology reports: "Bank Credit Risk -- An Analytical Framework for Banks in Developed Markets," April 1999 and "Bank Credit Risk in Emerging Markets -- An Analytical Framework," July 1999. 2.Please see "Request for Comment: Incorporation of Joint-Default Analysis for Systemic Support into Moody's Bank Rating Methodology ," October 2005; "Update to Proposal to Incorporate Joint-Default Analysis into Moody's Bank Rating Methodology ," April 2006; and "Bank Joint Default Analysis: Rating Methodology Update," August 2006.New York David Fanger 1.212.553.1653 Rosemarie Conforte Jeanne Del Casino Greg Bauer Laura Levenstein London Lynn Exton 44.20.7772.5454 Adel Satel Antonio Carballo Madrid Maria Cabanyes 34.91.310.14.54Tokyo Mutsuo Suzuki 81.3.5408.4000 Yasunobu Doi Singapore Deborah Schuler 65.6398.8300Hong Kong Jerry Chien 852.2916.1121 Contact Phone September 2006

标准普尔、穆迪评级分类表

标准普尔、穆迪评级分类表 (2007-03-25 18:02:22) 转载 分类：学术研究 穆迪从A至B的分类评级都缀以数字(1.2和3)。如缀以l即表示该银行信用属于该级别的高档次级别，如缀以2即表示属于该级别的中档次级别，如缀以3即表示属于该级别的低档次级别。标准普尔使用加号(十)或减号(一)表示评级类别的相对档次。 评级符号后标有‘pi’表示该等评级是利用已公开的财务资料或其它公开信息作分析的依据，即标准普尔并未与该等机构的管理层进行深入的讨论或全面考虑其重要的非公开资料，所以这类评级所依据的资料不及全面的评级全面。

标普评级 标普的长期评级分为投资级和投机级两大类，投资级的评级具有信誉高和投资价值高的特点，投机级的评级则信用程度较低。投资级包括AAA、AA、A和BBB，投机级则分为BB、B、CCC、CC、C和D。AA A级为最高信用等级；D级最低，视为对条款的违约。 从AA至CC C级，每个级别都可通过添加“+”或“-”来显示信用高低程度。例如，在AA序列中，信用级别由高到低依次为AA+、AA、AA-。 标普的短期评级共设6个级别，依次为A-1、A-2、A-3、B、C和D。其中A-1表示发债方偿债能力较强，此评级可另加“+”号表示偿债能力极强。 标普目前对126个国家和地区进行了主权信用评级。美国失去AAA评级后，目前拥有AAA评级的国家和地区还有澳大利亚、奥地利、加拿大、丹麦、芬兰、法国、德国、中国香港、马恩岛、列支敦士登、荷兰、新西兰、挪威、新加坡、瑞典、瑞士和英国。 穆迪评级 穆迪长期评级（一年期以上债务）共分9个级别：Aaa、Aa、A、Baa、Ba、B、Caa、Ca 和C。其中Aaa级债务的信用质量最高；C级债务为最低等级，收回本金及利息的机会微乎其微。 在Aa到Caa的6个级别中，还可以添加数字1、2或3进一步显示各类债务在同类评级中的排位，1为最高，3则最低。通常认为，从Aaa级到Ba A3级属于投资级，从B A1级以下则为投机级。 穆迪的短期评级（一年期以下债务）依据发债方的短期债务偿付能力从高到低分为P-1、P-2、P-3和NP四个等级。 目前，穆迪的业务范围主要涉及国家主权信用、美国公共金融信用、银行业信用、公司金融信用、保险业信用、基金以及结构性金融工具信用评级等几方面。穆迪在全球26个国家和地区设有分支机构。 惠誉评级 惠誉的规模较小，是唯一的欧洲控股的评级机构。其长期评级用以衡量一个主体偿付外币或本币债务的能力。

标普和穆迪资产证券化评级方法比较

资产证券化在国外，尤其在美国，经过多年的运作已相对成熟。资产证券化资信评级，从其评级指标、评级程序、评级内容看，都在实践中趋于完善。标准普尔（S&P ）、穆迪（Moody ）在债券信用评级方面积累了近百年的历史，在资信评估市场上占据绝对优势地位。本文主要通过对标准普尔和穆迪对资产证券化评级方法的研究，比较二者评级过程方法运用的异同。 一、S&P 和Moody 的资产证券化评级框架 标准普尔金融资产证券化评级框架主要包括：证券化资产的信用质量分析、法律和监管体系风险分析、支付结构和现金流机制分析、业务运营行政风险分析和交易对手分析五个关键领域的分析，总体上与惠誉的资产证券化的评级体系较为相似。而穆迪金融资产证券化评级框架主要包括四个方面：资产质量分析、法律和监管体系分析、结构分析、运营和管理分析，对抵押债务凭证（CDO ）的风险分析也包括交易对手的风险分析。 图表1. 标准普尔和穆迪对资产证券化的评级框架 标准普尔和穆迪对金融资产证券化的评级框架均涵盖了资产证券化评级的关键要素，尤其在资产证券化评级标的资产多元化的背景下，针对各个标的资产的特色，又做了相关改进和完善，形成了一整套评级方法，如CDO 、设备融资担保证券、汽车贷款、交易应收款、信用卡贷款、标普和穆迪资产证券化评级方法比较 周美玲/文

出口应收帐款担保证券、不动产担保证券等。 二、S&P和Moody的资产证券化评级方法比较 （一）对证券化资产的信用质量分析 标准普尔对证券化资产信用质量的分析侧重于确定在情景压力测试下的评级： ●证券存续期间资产池中的基础资产出现违约或损失的比例； ●如果有资产出现违约或损失，可以通过抵押、担保以及其他方式覆盖的比例； ●最大债务人违约压力测试； ●最大行业违约压力测试。 前两项决定了债务问题最终潜在的损失比例，而后两项决定了交易中的事件风险和模型风险。在此基础上标准普尔采用各种分析方法和定量工具对来自内部和外部的信息进行评价，包括使用违约和现金流模型。最终，标准普尔选择适当的增信水平，对通过压力情景测试的，投资者基本能够在发行条款规定的最终到期日前及时收到利息和本金的资产给予相应的信用增级。 一般情况下，CDO的每层均需通过各自对应级别的压力测试，包括适用性测试以及对合成式CDO估值结果的违约率情景压力测试和损失率情景压力测试、对现金流量型CDO的相关现金流压力测试。 最大债务人违约压力测试和最大行业违约压力测试，是标准普尔在2011年更新的现金流量型CDO和合成式CDO评估方法新标准中，对交易中可能发生的事件风险和模型风险而改进和新增的压力测试。最大债务人违约测试是评估在制定的相关资产发生违约且挽回率仅为5%的情况下，CDO的标的资产的信用级别是否具有足够的信用增级（不包括超额利差）来支撑。最大行业违约测试由两部分组成，即最大主要行业的违约测试和最大替代性行业的违约测试。此二者均需要评估信用级别在AA-级（含）以上的CDO，在交易所处最大主要行业或最大替代性行业的所有债务人发生违约且挽回率为17%的情况下，其标的资产在相应级别下是否具有足够的信用增级（不包括超额利差）来支撑。这两项测试结果均会影响到CDO的信用级别。 标准普尔认为在分析中加入定量和定性因素的分析，要比单纯使用数值模型模拟违约提供更加可靠的分析。经过重新校准的CDO评估程序，以及特别提供“目标投资组合违约率”，使得评级和分析过程更透明。 相对而言，穆迪对资产质量的分析则侧重于精算统计和组合分析。穆迪在评估CDO时，

信用评级方法框架

信用评级方法概览 目录 一、总论 (2) （一）什么是信用评级 (2) （二）信用评级内涵及外延 (2) 1 预期损失率vs 违约率 (2) 2评级对应的预期损失率/违约率不是恒定不变的 (2) 3 短期信用评级与中长期信用评级 (3) 4主体信用评级与债项信用评级 (3) 二、信用评级方法概览 (3) （一）传统信用分析方法 (4) 1 要素分析法 (4) 2 综合分析方法的比较 (4) 3 比率分析法 (6) （二）新兴信用评级方法 (7) CM模型（信用计量模型） (7) KMV模型 (7) 三、评级公司采用评级方法介绍 (8) （一）穆迪 (8) （二）标准普尔 (11) （三）大公国际 (12) （四）中诚信 (14) 四、总结 (15)

一、总论 （一）什么是信用评级 狭义的信用评级指独立的第三方信用评级中介机构对债权人如期足额偿还债务本息的能力和意愿进行评价，并用简单的评级符号表示其违约风险和损失的严重程度。按评级对象的不同，信用评级主要分为两种类型：主体信用评级与债项信用评级。 因此，信用评级涉及到两个方面的评估： 违约概率（Probability of Default,PD）：评级对象违约的可能性。因此，违约概率更加倾向于对主体信用的评价。 违约损失率（LGD）：违约损失严重程度。其大小不仅受到评级对象信用水平的影响，还受到具体债项的特定信用保障措施设计，如合同的具体条款（抵押、担保等等）的影响，同时，还与债权人（如商业银行）的管理水平有关。违约损失率是对主体信用评价与债项信用评价的综合评估。 （二）信用评级内涵及外延 1 预期损失率vs 违约率 前面提到，信用评级使用简单的评级符号表示损失的概率和损失严重程度。 不同的评级公司和不同类型债项，其评级系统对PD和LGD的关注侧重程度有所不同。Moody’s 和S&P对评级的定义有所不同，关键在于度量的目标并不完全相同，前者更强调预期损失率，而后者更强调违约率。但以上区别并不是完全绝对的，根据产品和投资者偏好的不同，评级公司的评级目标也会有所侧重。例如，Moody’s 和标普都指出因为公司债券尤其是高等级公司债券的投资者都不喜欢违约风险，而且违约后损失率比违约更难预测，因此其在对公司债券评级时，对投资级债券的评估更侧重对违约率风险的评估，而因为投机级债券违约风险已经比较高，在评级时会考虑到违约后损失率。 图表 1 评级机构对PD或LGD侧重情况 2评级对应的预期损失率/违约率不是恒定不变的 第一，评级对应的预期损失率/违约率是一个时间序列。随着时间的增加，所有级别的平均累积违约率都在增加，如下表穆迪给出的违约概率所示。因此对同一个发行人而言，如果发行其他条件相同但期限不同的债券，如5 年和10 年，那么从直观上来看10 年的债券比5 年债券的信用风险更高。

Moodys采矿业评级方法2006

评级方法
2005 年 9 月
联系人
多伦多
电话号码
Terry Marshall Fadwa Sahly
泽西市
1.416.214.1635
Mark Gray Steve Oman
纽约
1.201.915.8750
Carol Cowan James O’Shaughnessy
悉尼
1.212.553.1653
Terry Fanous Ileria Chan
伦敦
61.2.9270.8100
Francois Lauras Ruchi Gupta
香港
44.20.7772.5397
Anna Ho
852.2916.1110
全球采矿业
穆 迪 报 告 “Global Mining Industry” 的 中 文 翻 译 本 （中文为翻译稿，如有出入，以英文为准）
评论摘要
本评级方法报告针对穆迪向全球矿业公司授予信用评级的分析方法提供详细的说明。就本方法而言， 我们将矿业发行人 定义为从事基础金属与贵金属、其他工业金属及煤炭的采矿、熔炼和精炼业务的公司。大型铝业公司亦积极从事包装与 制造业务，这是唯一与上游和下游业务全面融合的矿业企业。 本评级方法报告的主要目的是帮助发行人、投资者和其他矿业参与者了解穆迪如何评估矿业公司的风险，并使我们 的委托人能够大概估测一家公司的评级。 本方法并非穆迪在授予矿业公司评级的过程中所考虑的全部因素， 但可以帮助 读者理解穆迪在评级过程中考虑的主要考虑因素、采用的财务比率及其权重。 穆迪评级的 40 家矿业发行人覆盖了矿业的多个界别（例如铜、铝、黄金、煤炭等） ，并展示出相近的业务基本及许 多共同的信用考虑因素。整体而言，我们采用 5 大评级因素来衡量全球矿业公司的信用风险并授予评级。我们将在本报 告中详细讨论各个评级因素，包括了多项具体要素与指标（或“次级因素”，5 个评级因素如下： ） 1. 2. 3. 4. 5. 储量 成本效率与盈利能力 财务政策 财务实力 业务多样性与规模
此外，我们加入了“其他考虑因素”一节，讨论难以有意义地量化或预测，但对于矿业发行人的评级有显著影响的 因素（例如政治风险） 。

三大评级公司评级符号体系

一、主体评级符号及其定义 标普、穆迪和惠誉三大国际评级机构的主体评级符号及其定义均采用各自的中长期信用等级符号体系。 在等级划分方面，标普采用四等十一级制，且对于‘AA’至‘CCC’级别，可通过增加‘+’或‘-’符号来表示评级在各主要评级分类中的相对强弱；穆迪采用三等九级制，对于‘Aa’至‘Caa’级别，通过增加修正数字1、2、3来表示同类评级中的相对排位，其中数字1表示级别在所属同类评级中排位较高，数字3则表示级别在所属同类评级中排位较低；惠誉也采用四等十一级制，但与标普和穆迪不同的是，修正符号‘+’和‘-’可用于‘AA’至‘B’级别（见附件一）。 二、债项评级符号及其定义 债项评级分为中长期债项评级和短期债项评级。 中长期债项评级 标普、穆迪和惠誉的中长期债项评级与主体评级一样，也均采用各自的中长期信用等级符号体系。但是，由于评级历史和评级理念不同，上述三家评级机构对各类级别的定义幵不完全相同。标普和惠誉认为长期信用评级主要衡量的应是被评对象的违约风险，因而其符号定义侧重于强调偿债能力；穆迪则认为不同的长期信用评级表示被评对象可能给投资者带来信用损失的相对大小，因而其符号定义更侧重于反映被评对象的预期损失（见附件二）。同时，为了更好的满足投

资者需求，三家机构在评级实践中对债券级别的划分和含义方面赋予了更多内容。 在债券级别划分方面，为使市场具有统一认知，同时满足投资者的不同偏好，三家机构均设定‘BBB-’或‘Baa3’及以上级别属于投资级别，这些级别以下则属于投机级别。从标普和惠誉的级别定义可以看出，区分投资和投机级别的关键因素是发行人偿债能力对经济周期以及不利环境变化的承受能力，此定义可通过美国近20年的违约率统计数据得以印证，即投机级债券违约率随经济的波动而剧烈变动，而投资级债券违约率则基本保持稳定。投资级别和投机级别的划分与定义可为投资者提供初步的投资建议，即具有长期持有、配置型偏 好的投资者可关注级别为‘BBB-’或‘Baa3’及以上的债券，而具有高风险、高收益偏好的投资者则可关注级别为‘BB+’或‘Ba1’及以下的债券。 此外，为了使评级结果更准确地反映被评对象的实际信用水平，各机构在评级实践中会视被评对象和投资者需求做出调整。如穆迪指出，由于高等级债券的投资者以觃避违约风险为主要目的之一，加之违约后损失率比违约率更难预测，因而其在对投资级债券评估时侧重于债券的违约率，而投机级债券则更侧重于预期损失率。同时标普也指出，虽然其评级主要关注违约风险，但由于投机级债券的违约风险本就比较高，其在评级时也会考虑违约后损失率。由此可见，国际评级公司的评级理念和方法实际上在逐渐趋同，即投资级债券评级应注重违约率评估，而投机级债券评级应注重预期损失率的评估。

穆迪评级[最新]

穆迪评级[最新] 什么是评级? 评级是穆迪对一个发债机构能否於债券等发行债务工具到期日前按时偿还的能力和意愿作出的意见 评级并不是。。。 评级并不是为买卖作出的推荐，也不是对不会发生违约的保证。 资本市场如何使用评级? 投资者使用评级协助为其可能购买或出售的固定收入证券信贷风险定价。不少投资者使用评级作为其投资规范的限制,和作为扩大投资范围到其分析没有覆盖的市场和证券种类的工具。由於全球主要投资者都倚赖穆迪的评级，因此评级为债务投资者提供了稳定和灵活的资本来源。 穆迪为那种证券提供评级, 任何机构投资者有兴趣的债券或有关的债务(如债券，公司债券，资产抵押和按揭抵押证券，可转换债券，中期票据，衍生证券等)。不过穆迪不为股票作评级。 信用评级衡量什么? 评级是对发行人无法偿还款项，延迟还款，或只能偿还部分款项时投资者有可能蒙受的信用损失的预测及指示。信用损失是发行人答应偿付和真正偿付的款项之间的差异。穆的评级量度总信用损失 - 包括发行人违约的可能性和违约后预计损失的严重性。 穆迪的评级过程? 评级过程包括: , 收集足以为可能拥有或购买特定证券的投资者评估风险的资料,

, 讨论达致适当的评级， , 持续监控证券，厘定是否需要更改评级，及 , 向市场公布穆迪的行动。 穆迪如何进行评级委员会, 穆迪评级的最初决定和最后更改都是透过评级委员会进行。某一个公司，行业，国家或资产种类的主分析师负责制定讨论内容，包括提供评级推荐及其基础原理。 评级委员会最少有一个常务董事或其他指定人员，和主分析师。评级委员会可以扩大到包括任何方面或范围的人员，以覆盖其他所有有关受评发债机构和证券分析事项的讨论。 可影响评级委员会人数的决定因素，包括发债机构的规模，证券的复杂性，地理环境或在过去有没有进行同类交易等。评级委员会的讨论事项内容是绝对保密的，而且只有穆迪分析师才可担任委员会的委员。分析师使用那些种类的资料, , 公开取得的数据，如公司年报 , 说明书，销售通告，销售协议书，信托契约，或某特定证券的契约。 , 市场数据，如股票价格趋势，交易量，债券价格差价幅度数据。 , 行业团体，组织或机构等的经济数据，如世界银行。 , 事务处的数据，如中央银行，政府部门或监管机构。 , 学术团体，金融杂志，新闻报导等书籍或记事。 , 与行业，政府或学界专业人士的讨论。 , 与债券发行机构的会议或谈话中取得的数据。如果这些是机密数据，穆迪会绝对保密。 评级系统已使用了多久,

穆迪-全球化工业评级方法(中文)

穆迪报告 2006年2月 全球化工业评级方法 目录 一、评级概要 (2) 二、全球评级概况 (2) 三、行业概况 (3) 1、行业风险因素 (3) 2、未来10 年的信用问题 (3) 四、主要评级因素 (3) 1、业务运营 (3) 2、经营规模和稳定性 (3) 3、成本状况 (4) 4、财务政策 (4) 5、财务实力 (4) 五、其他评级考虑因素 (5)

一、评级概要 整体而言，采用五大评级因素来衡量全球化工业公司的信用风险。其中各个评级因素，包括了多项具体要素与指标，五大评级因素如下： 业务运营 经营规模和稳定性 成本状况 财务政策 财务实力 另外，其他考虑因素（讨论难以有意义地量化或预测，但对于化工业发行人的评级有显著影响的因素，例如公司治理、管理效率等。） 二、全球评级概况 穆迪对全球111家化工企业进行了评级，被评企业涉及基本化学原料、特殊化学原料和工业煤气等子行业，主要分布于美国、欧洲和日本等地，总收入规模介于1.5亿美元至400亿美元间，级别分布见下图： 家数 25

Huntsman B1 发展美国 Lyondell Chemical B1 正面美国 PolyOne Corp B2 正面美国 三、行业概况 1、行业风险因素 原油价格波动导致原材料进口量和成本的差异； 全球与区域经济周期差异给企业经营带来的影响； 业务组合及多元化程度； 扩充产能及环保项目导致的周期性资本支出需求； 企业性质和发展战略不同带来的资本结构差异。 2、未来10 年的信用问题 原油和天然气价格波动将给经营成本带来较大影响，并传导至下游客户； 供需不平衡的状况将时有出现，并影响市场价格； 政府政策的影响，包括：大量原油、天然气的引进；政府对行业的扶持政策；环保制度增加企业成本压力； 行业内的整合将改善供需不平衡的状况。 四、主要评级因素 1、业务运营 （1）衡量方法 经营差异性 通过对具有国际竞争规模的营运厂数量来衡量，一般拥有厂家越多，打分越高 产品差异性 一般产品线和产品品种越多，打分越高 地理位置差异性 跨多个区域经营的企业打分较高 产品附加值 附加值越高打分越高，EBITDA也可作为另一量化指标 市场占有率 市场占有率越大、竞争者越少打分越高 原材料成本率 若原材料成本占总成本比率设定为10%-33%，该比率越低，则打分越高 政府制度或政策的影响 根据政府政策对企业的长期发展是正面还是负面影响来确定分数高低 （2）级别对应 级别Aa A Baa Ba B Caa 市场地位>4.5 3.5和4.0 2.5和3.0 1.5和2.0 0.5和1.0 <0.5 2、经营规模和稳定性 （1）衡量方法 收入规模

三大评级机构评级标准

三大评级机构评级标准 一、穆迪评级等级含义 (一)长期评级 Aaa级债务的信用质量最高，信用风险最低。 Aa级债务的信用质量很高，只有极低的信用风险。 A级债务为中上等级，有低信用风险。 Baa级债务有中等信用风险。这些债务属于中等评级，因此有某些投机特征。 Ba级债务有投机成分，信用风险较高。 B级债务为投机性债务，信用风险高。 Caa级债务信用状况很差，信用风险极高。 Ca级债务投机性很高，可能或极有可能违约，只有些许收回本金及利息的希望。 C级债务为最低债券等级，通常都是违约，收回本金及利息的机会微乎其微。 附注:修正数字1、2及3可用于Aa至Caa各级评级。修正数字1表示该债务在所属同类评级中排位较高;修正数字2表示排位在中间;修正数字3则表示该债务在所属同类评级中排位较低。 二、标准普尔评级 (一)长期信用评级 AAA 偿还债务能力极强，为标准普尔给予的最高评级。 AA 偿还债务能力很强，与最高评级差别很小。 A 偿还债务能力较强，但相对于较高评级的债务/发债人，其偿债能力较易受外在环境及经济状况变动的不利因素的影响。

BBB 目前有足够偿债能力，但若在恶劣的经济条件或外在环境下其偿债能力可能较脆弱。获得'BB'级、'B'级' CCC'级或' CC'级的债务或发债人一般被认为具有投机成份。其中'BB'级的投机程度最低，'CC'级的投机程度最高。这类债务也可能有一定的投资保障，但重大的不明朗因素或恶劣情况可能削弱这些保障作用。 BB 相对于其它投机级评级，违约的可能性最低。但持续的重大不稳定情况或恶劣的商业、金融、经济条件可能令发债人没有足够能力偿还债务。 违约可能性较'BB'级高，发债人目前仍有能力偿还债务，但恶劣的商业、金融或经济B 情况可能削弱发债人偿还债务的能力和意愿。 CCC 目前有可能违约，发债人须依赖良好的商业、金融或经济条件才有能力偿还债务。如果商业、金融、经济条件恶化，发债人可能会违约。 CC目前违约的可能性较高。 SD/D 当债务到期而发债人未能按期偿还债务时，纵使宽限期未满，标准普尔亦会给予'D'评级，除非标准普尔相信债款可于宽限期内清还。此外，如正在申请破产或已做出类似行动以致债务的偿付受阻时，标准普尔亦会给予'D'评级。当发债人有选择地对某些或某类债务违约时，标准普尔会给予"SD"评级(选择性违约)。 加号(+)或减号(-):'AA'级至'CCC'级可加上加号和减号，表示评级在各主要评级分类中的相对强度。 NR 发债人未获得评级。 三、惠誉评级 (一)国际长期评级(International Long-Term Credit Ratings ----LTCR) 对发行人的长期评级也就是发行人违约评级(IDR)，是衡量发行人违约可能性的基准。对发行证券的长期评级可能高于或低于发行人的评级(IDR)，反映了证券回收可能性的不同。

国内外评级公司简介及排名

中国五大信用评级机构，国际信用评级机构排名 信用评级机构是金融市场上一个重要的服务性中介机构，它是由专门的经济、法律、财务专家组成的、对证券发行人和证券信用进行等级评定的组织。证券信用评级的主要对象为各类公司债券和地方债券，有时也包括国际债券和优先股票，普通股股票一般不作评级 信用评级机构是依法设立的从事信用评级业务的社会中介机构，即金融市场上一个重要的服务性中介机构，它是由专门的经济、法律、财务专家组成的对证券发行人和证券信用进行等级评定的组织。国际上公认的最具权威性的专业信用评级机构只有三家，分别是美国标准·普尔公司和穆迪投资服务公司和惠誉国际信用评级有限公司。面对巨大的机遇和生存的压力，信用评级机构应加强与外部各界的合作与交流，同时不断提高自身的业务质量和管理水平。最根本的作用是就证券的信用状况独立发表意见，信用状况表述出来就是投资者按时获取利息和收回本金的可能性。 一般情况下，信用评级主要包括以下程序： （一）接受委托。包括评估预约、正式接受委托、交纳评级费用等。 （二）前期准备。包括移送资料、资料整理、组成评估项目组、确定评级方案等。 （三）现场调研。评估项目组根据实地调查制度要求深入现场了解、核实被评对象情况。（四）分析论证。评估项目组对收集的信息资料进行汇集、整理和分析，形成资信等级初评报告书，经审核后提交信用评级评审委员会评审。 （五）专家评审。包括评审准备、专家评审、确定资信等级、发出《信用等级通知书》。（六）信息发布。向被评对象出具《信用等级证书》，告知评级结果。

（七）跟踪监测。在信用等级有效期内，评估项目组定期或不定期地收集被评对象的财务信息，关注与被评对象相关的变动事项，并建立经常性的联系、沟通和回访工作制度。 中国五大信用评级机构： 1.东方金诚国际信用评估有限公司： 东方金诚国际信用评估有限公司是经财政部批准由中国东方资产管理公司以资本金投资控股的全国性、专业化信用评级机构。公司先后获批中国证监会、中国人民银行和国家发改委三个国家政府部门认定的证券市场及银行间债券市场两大债券市场国内全部债务工具类信用评级资质，以及各地人民银行批准的信贷市场评级资质。公司注册资本1.25亿元人民币，在全国各地设立了26家分公司，并全资控股一家专业数据公司－北京东方金诚数据咨询有限公司，是中国境内经营资本实力最雄厚的信用评级机构之一，是五家机构中唯一的国有控股评级公司，实际控制人为财政部。 2.中诚信： 分为中诚信国际信用评级有限公司和中诚信证券评估有限公司，共同具有国家发改委、证监会和人民银行的资质。作为中国本土评级事业的开拓者，中国诚信（中诚信国际前身）自1992年成立以来，一直引领着我国信用评级行业的发展，创新开发了数十项信用评级业务，包括企业债券评级、短期融资券评级、中期票据评级、可转换债券评级、信贷企业评级、保险公司评级、信托产品评级、货币市场基金评级、资产证券化评级、公司治理评级等。近年

标准普尔、穆迪主权评级标准

Table 3a: S&P’s sovereign rating methodology profile, 2002Stability and legitimacy of political institutions Popular participation in political processes Orderliness of leadership succession Transparency in economic policy decisions and objectives Public Security Political risk Geopolitical Risk Prosperity, diversity and degree to which economy is market-oriented Income disparities Effectiveness of financial sector in intermediating funds Competitiveness and profitability of non financial private sector Efficiency of public sector Protectionism and other non market influences Income and economic structure Labor flexibility Size and composition of savings and investment Economic growth prospects Rate and pattern of economic growth General government revenue, expenditure and surplus/deficit trends Revenue-raising flexibility and efficiency Expenditure effectiveness and pressures Timeliness, coverage and transparency in reporting Fiscal flexibility Pension obligations General government gross and net debt as a percentage of GDP Share of revenue devoted to interest Currency composition and maturity profile General government debt burden Depth and breadth of local capital markets Size and health of non financial public-sector enterprises Offshore & contingent liabilities Robustness of financial sector Price behavior in economic cycles Money and credit expansion Compatibility of exchange-rate regime and monetary goals Institutional factors such as central bank independence Monetary stability Range and efficiency of monetary policy tools Impact of fiscal and monetary policies on external accounts Structure of the current account Composition of capital flows External liquidity Reserve adequacy Gross and net public-sector external debt Maturity profile, currency composition and sensitivity to interest rates Access to concessional funding Public-sector external debt burden Debt service burden Gross and net financial sector external debt Gross and net non financial private-sector external debt Maturity profile, currency composition and sensitivity to interest rates Access to concessional funding Private-sector external debt burden Debt service burden Source: S&P’s (2002b).

穆迪全球航空企业信用评级方法

CORPORATES MAY 24, 2012

Each of the factors (except the Financial Policy factor) also encompass a number of sub-factors that we explain in detail. Since an issuer’s scoring on a particular grid factor often will not match its overall rating, in the Appendix we include a discussion of “outliers” – companies whose grid-indicated rating for a specific sub-factor differs significantly from the actual rating. This rating methodology is not intended to be an exhaustive discussion of all factors that Moody’s analysts consider to be pertinent for ratings in the passenger airline sector. We note that our analysis for ratings in this sector covers factors that are common across all industries (such as ownership, management, liquidity, legal structure in the corporate organization, corporate governance) as well as factors that can be meaningful on a company-specific basis. Our ratings consider qualitative considerations and factors that do not lend themselves to a transparent presentation in a grid format. The grid represents a compromise between greater complexity that would result in grid-indicated ratings that map more closely to actual ratings, and simplicity that enhances a transparent presentation of the factors that are most important for ratings in this sector most of the time. Highlights of this report include: ?An overview of the rated universe ? A summary of the rating methodology ? A description of the key factors that drive rating quality ?Comments on the grid assumptions and limitations, including a discussion of rating considerations that are not included in the grid. The Appendices show the full grid (Appendix A), tables that illustrate the application of the methodology grid to the covered issuers with explanatory comments on some of the more significant differences between the grid-implied rating for each sub-factor and our actual rating (Appendix B)1. About the Rated Universe We presently rate fourteen passenger airlines using this methodology, covering approximately $30 billion of rated debt. These companies represent a diverse group of issuers with ratings (senior unsecured rating or Corporate Family Rating) ranging from Baa3 to Caa1. Seven of the rated airlines are based in the US; three are from Europe and the remainder come from either Australia, Brazil, Canada or New Zealand. Of the rated airlines, only three are investment grade being; Qantas, Air New Zealand and Southwest Airlines. The median rating for the industry is situated at B1.2 The relatively low ratings for the sector reflect the effect of high fuel prices on these companies ability to generate earnings and free cash flow at levels that would lead to more supportive financial leverage measures. Additionally, sustained pressure on non-fuel costs, particularly labor as the work force becomes more tenured and the need to replace older, less fuel-efficient aircraft should limit the extent of any improvement in credit profiles in upcoming years. 1In general, the actual rating utilized for comparison to the grid-implied rating is the Corporate Family Rating (CFR) for speculative-grade issuers and senior unsecured rating for investment-grade issuers. 2For the purposes of comparability in this methodology, Moody’s compares individual corporate family ratings (CFR) and senior unsecured ratings. As both Air New Zealand (ANZ) and Scandinavian Airlines System (SAS) are partially owned by their respective governments, their corporate family ratings reflect implied government support. However for the purpose of grid outliers, we will refer to the Baseline Credit Assessment (BCA) of these airlines, which represents an assessment of their credit standing excluding government support. ANZ’s BCA is 11, equivalent to Ba1, and SAS’ BCA is 18, equivalent to Caa2.