Do Rating Announcements convey new Information?
An Event Study an Credit Default Swap Spreads
©2010
Diplomarbeit
57 Seiten
Zusammenfassung
Inhaltsangabe:Introduction:
Since the beginning of the last century, investors in capital markets have strongly relied on rating agencies assessments of credit quality to decide on investments. Due to their important role in debt markets, they are supposed to provide accurate ratings without delay. However, cases like the defaults of WorldCom or Enron have damaged their reputation. In particular, credit rating agencies have been heavily criticized for their role during the financial crisis of 2007-2009. Many economists blame the rating agencies for having played a major part in the securitization process of mortgage loans by providing too high rating grades; and thus sowing the seeds of the crisis. Having rated credit derivatives like collateralized debt obligations with best grades, the rating agencies encouraged banks and other financial institutions to keep these assets in their portfolios.
As a result, it caused severe problems for the banking sector when these products heavily lost in value. Along with imprecise assessments of creditworthiness, the slow reaction of rating agencies has been critizised over the last few years. Therefore, the question of how well the agencies assess credit quality arises. This question is of great importance because of their dominant role on capital markets and the fact that decisions are made upon their ratings. To put it more precisely, this study asks whether the agencies process and convey new information to the market. On the other hand, it might be the case that market participants anticipate any change in the credit quality of a company before these institutions publish their assessments. Answering this question is of particular importance: if the rating announcements convey unknown information and the market reacts, then rating agencies are a systemic part of capital markets and policy should consider stricter regulation to prevent manipulation and failures like those described above. Conversely, if their announcements do not contain any new information or to put it differently, if markets react faster then we could think about using market based indicators instead in order to assess credit risk. In this case, the economic task of signaling creditworthiness could be handed over, among others, to Credit Default Swaps (see Chapter 2), which is also suggested by Hart & Zingales. This thesis contributes to the field of rating agencies performance measurement.
Evaluating their announcements with the […]
Since the beginning of the last century, investors in capital markets have strongly relied on rating agencies assessments of credit quality to decide on investments. Due to their important role in debt markets, they are supposed to provide accurate ratings without delay. However, cases like the defaults of WorldCom or Enron have damaged their reputation. In particular, credit rating agencies have been heavily criticized for their role during the financial crisis of 2007-2009. Many economists blame the rating agencies for having played a major part in the securitization process of mortgage loans by providing too high rating grades; and thus sowing the seeds of the crisis. Having rated credit derivatives like collateralized debt obligations with best grades, the rating agencies encouraged banks and other financial institutions to keep these assets in their portfolios.
As a result, it caused severe problems for the banking sector when these products heavily lost in value. Along with imprecise assessments of creditworthiness, the slow reaction of rating agencies has been critizised over the last few years. Therefore, the question of how well the agencies assess credit quality arises. This question is of great importance because of their dominant role on capital markets and the fact that decisions are made upon their ratings. To put it more precisely, this study asks whether the agencies process and convey new information to the market. On the other hand, it might be the case that market participants anticipate any change in the credit quality of a company before these institutions publish their assessments. Answering this question is of particular importance: if the rating announcements convey unknown information and the market reacts, then rating agencies are a systemic part of capital markets and policy should consider stricter regulation to prevent manipulation and failures like those described above. Conversely, if their announcements do not contain any new information or to put it differently, if markets react faster then we could think about using market based indicators instead in order to assess credit risk. In this case, the economic task of signaling creditworthiness could be handed over, among others, to Credit Default Swaps (see Chapter 2), which is also suggested by Hart & Zingales. This thesis contributes to the field of rating agencies performance measurement.
Evaluating their announcements with the […]
Leseprobe
Inhaltsverzeichnis
Jan Klobucnik
Do Rating Announcements convey new Information?
An Event Study an Credit Default Swap Spreads
ISBN: 978-3-8366-4928-5
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Do Rating Announcements convey new Information?
An Event Study on Credit Default Swap Spreads
Jan Klobucnik
22 March 2010
Abstract
Rating agencies play an important role on the capital markets; however,
during the financial crisis 2007-2009 people began to question how good
their assessments of credit quality really are. In my study, I empirically
examine the effect of rating announcements from Standard & Poor's on the
Credit Default Swap (CDS) Market. It contributes to the field of rating
agencies' performance measurement. Based on Event Study Methodology
and recent CDS data, I detect virtually no significant abnormal spread
change at the announcement date neither for downgrades nor upgrades.
However, the CDS show some anticipation prior to the event especially for
downgradings. Considering the rating date, I find evidence for an asym-
metric reaction where downgrades cause stronger movement in the spreads.
As a result, it seems as if rating changes do not convey a great part of new
information to the markets. At the same time, the significant anticipation
indicates that the CDS market processes information more efficiently.
Table of Contents
I
Table of Contents
List of Tables
II
List of Figures
III
1
Introduction
1
2
Rating Agencies and the Market for Credit Risk
3
3
Previous Literature and Hypotheses
12
4
Data
16
4.1
Ratings
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
16
4.2
Credit Default Swap Spreads . . . . . . . . . . . . . . . . . . . . .
17
5
Methodology
20
5.1
Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
20
5.2
Hypothesis Testing . . . . . . . . . . . . . . . . . . . . . . . . . .
23
6
Empirical Results
30
6.1
Event Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
30
6.2
Regressions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
37
6.3
Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
39
7
Conclusion
43
8
References
45
9
Appendix: Robustness Test
48
List of Tables
II
List of Tables
1
Classification of rating classes from Standard & Poor's . . . . . .
5
2
Default frequencies from S&P . . . . . . . . . . . . . . . . . . . .
14
3
Distribution of ratings . . . . . . . . . . . . . . . . . . . . . . . .
17
4
Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . .
19
5
Boehmer test statistic for downgrades . . . . . . . . . . . . . . . .
31
6
Sign test for downgrades . . . . . . . . . . . . . . . . . . . . . . .
32
7
Boehmer test statistic for upgrades . . . . . . . . . . . . . . . . .
34
8
Sign test for upgrades . . . . . . . . . . . . . . . . . . . . . . . . .
35
9
T-test for asymmetric reaction . . . . . . . . . . . . . . . . . . . .
37
10
Regression results for downgrades and upgrades . . . . . . . . . .
38
11
Regression results for absolute spread changes . . . . . . . . . . .
39
12
Results for downgrades with interpolated data . . . . . . . . . . .
48
13
Results for upgrades with interpolated data
. . . . . . . . . . . .
49
14
Regression results with interpolated data . . . . . . . . . . . . . .
50
List of Figures
III
List of Figures
1
Volume outstanding in the global CDS market . . . . . . . . . . .
7
2
Variation in CDS spreads . . . . . . . . . . . . . . . . . . . . . . .
10
3
CDS Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21
4
CASC downgrades . . . . . . . . . . . . . . . . . . . . . . . . . .
33
5
CASC upgrades . . . . . . . . . . . . . . . . . . . . . . . . . . . .
36
1
Introduction
1
1
Introduction
Since the beginning of the last century, investors in capital markets have strongly
relied on rating agencies' assessments of credit quality to decide on investments.
Due to their important role in debt markets, they are supposed to provide ac-
curate ratings without delay. However, cases like the defaults of WorldCom or
Enron have damaged their reputation. In particular, credit rating agencies have
been heavily criticized for their role during the financial crisis of 2007-2009. Many
economists blame the rating agencies for having played a major part in the se-
curitization process of mortgage loans by providing too high rating grades; and
thus sowing the seeds of the crisis. Having rated credit derivatives like collateral-
ized debt obligations with best grades, the rating agencies encouraged banks and
other financial institutions to keep these assets in their portfolios. As a result, it
caused severe problems for the banking sector when these products heavily lost
in value. Along with imprecise assessments of creditworthiness, the slow reaction
of rating agencies has been critizised over the last few years.
Therefore, the question of how well the agencies assess credit quality arises.
This question is of great importance because of their dominant role on capital
markets and the fact that decisions are made upon their ratings.
To put it
more precisely, this study asks whether the agencies process and convey new
information to the market. On the other hand, it might be the case that market
participants anticipate any change in the credit quality of a company before these
institutions publish their assessments. Answering this question is of particular
importance: if the rating announcements convey unknown information and the
market reacts, then rating agencies are a systemic part of capital markets and
policy should consider stricter regulation to prevent manipulation and failures
like those described above. Conversely, if their announcements do not contain
any new information or to put it differently, if markets react faster then
we could think about using market based indicators instead in order to assess
credit risk. In this case, the economic task of signaling creditworthiness could be
handed over, among others, to Credit Default Swaps (see Chapter 2), which is
also suggested by Hart & Zingales (2009).
This thesis contributes to the field of rating agencies' performance measure-
1
Introduction
2
ment. Evaluating their announcements with the help of the Credit Default Swap
(CDS) market, I examine the information content of their ratings. At the same
time, this study can be seen as part of the market efficiency research on the CDS
market.
This empirical analysis shows that there are only weak effects of rating an-
nouncements, which might indicate that rating changes is no news to the markets.
By observing the CDS market, the empirical evidence displays some anticipation
of rating changes, especially for downgrades, such that markets seem to react
faster. Moreover, there seems to be some counter-movement to the prior adjust-
ment after the rating was announced. Finally, I can detect both an asymmetric
reaction between upgrades and downgrades, which means that latter ones have a
stronger impact on the market, and a higher sensitivity in poorer rating classes.
In order to give an answer to the question in the title, the thesis proceeds in
the following way: The next section provides background information on rating
agencies and CDS to build up the theoretical foundation of this study. The
previous research and the working hypotheses are presented thereafter in section
3. The subsequent section introduces the data and its transformations. In order
to perform the analyses, section 5 addresses the methodology of the event study.
The empirical results are then stated in section 6 and finally, section 7 concludes.
2
Rating Agencies and the Market for Credit Risk
3
2
Rating Agencies and the Market for Credit
Risk
The U.S. Securities and Exchange Commission (SEC) defines a credit rating
agency as "a firm that provides its opinion on the creditworthiness of an entity
and the financial obligations (such as, bonds, preferred stock, and commercial
paper) issued by an entity."
1
These agencies play an important economic role for
capital markets as they assess the credit risk of companies or states such that
private and institutional investors can use these assessments as basis for their in-
vestment decisions. In this context, credit risk is regarded as an exposure to the
losses arising from the borrower's default. Collecting data about these entities,
the agencies publish ratings which help to reduce the information asymmetry be-
tween potential borrowers and potential lenders. This is for the benefit of both
parties: Potential borrowers, for instance, gain additional information about the
creditworthiness of the lender which allows better decision making with respect to
credit risk and avoid monitoring costs. At the same time, lenders profit from the
positive signaling effect of a rating which can reduce financing costs. As a result,
the majority of institutions that borrow from the capital markets are willing to
pay for this service.
Credit ratings also play an important role in financial regulation. For ex-
ample, money market funds in the United States are restricted to invest in high
quality short term instruments only. The criteria set by the Investment Com-
pany Act to decide on the quality are rating agencies' assessments of credit risk.
In banking regulation, which was designed by the Basel Committee on Banking
Supervision, the ratings are used for the calculation of regulatory capital.
2
The credit rating industry arose in the early 1900's in the U.S. and by the year
2000, the Bank for International Settlements (BIS) counted around 150 agencies
worldwide (BIS 2000, p.14). Currently, there are three big global rating agencies,
which are situated in the U.S.: Standard & Poor's Credit Market Services (S&P),
1
United States Securities and Exchange Commission (SEC), 2005: Credit Rating Agencies
- NRSROs.
Modified 09/25/2008.
Accessed at http://www.sec.gov/answers/nrsro.htm in
January, 2010.
2
Basel Committee on Banking Supervision, 1999: A New Capital Adequacy Framework.
2
Rating Agencies and the Market for Credit Risk
4
Moody's Investors Service and Fitch, Inc. According to the SEC, they control 98
percent of the market for debt ratings in the U.S. and dominate the global credit
risk assessment.
3
Looking at the revenues or the number of employees in the
year 2008, S&P is the largest one.
4
The agencies' role in global capital markets
has expanded in the last couple of years due to the growing number of companies
issuing securities. In order to successfully raise funds they are required to be rated
by one of the major rating agencies. The reason is that institutional investors, for
instance, are restricted to hold highly rated assets. Usually, the issuing company
itself pays for this rating service.
In general, credit ratings are considered as "forward-looking opinions about
the creditworthiness of issuers and obligations".
5
They represent a relative rank-
ing of creditworthiness rather than the issuer's absolute probability of default.
Nevertheless, as Standard & Poor's claims, the "likelihood of default encom-
passing both capacity and willingness to pay is the single most important factor
in our assessment of the creditworthiness of an issuer or an obligation". Other
such factors that might enter the rating are, for example, payment priority of
the debt instrument, recovery in case of default, and credit stability. Generally,
there are two ways to determine the rating: First, there are qualitative methods,
in which experienced analysts assess the creditworthiness of an entity. Alterna-
tively, there is the quantitative approach with the help of statistical models. The
three principal rating agencies include a combination of qualitative and quanti-
tative judgements.
Normally, rating agencies do not fully publish key bases and assumptions
underlying their ratings as the models they use are confidential. Furthermore,
on the basis of the SEC's Regulation Fair Disclosure (Reg FD), which prohibits
selective disclosure of non-public information, they exclusively gain access to con-
fidential information from the issuer. On the basis of this unique access they have
a better insight of the company which they rate. This might give clues related
to the information content of ratings from rating agencies depending on whether
3
Statement at SEC Open Meeting by Commissioner Kathleen L. Casey. U.S. Securities and
Exchange Commission Washington, D.C. September 17, 2009.
4
revenues 2008: S&P $2654 million, Moody's $1205 million, Fitch $727 million; employees 2008:
S&P 8500, Moody's 3000, Fitch 2300.
5
Standard & Poor's, 2009: Understanding Standard & Poor's Rating Definitions. Accessed at
http://www.sec.gov/answers/nrsro.htm in January, 2010.
2
Rating Agencies and the Market for Credit Risk
5
S&P Rating
Rating class
Description
Grade
AAA
1
Prime
Investment
AA+
2
High grade
Investment
AA
2
High grade
Investment
AA-
2
High grade
Investment
A+
3
Upper medium grade
Investment
A
3
Upper medium grade
Investment
A-
3
Upper medium grade
Investment
BBB+
4
Lower medium grade
Investment
BBB
4
Lower medium grade
Investment
BBB-
4
Lower medium grade
Investment
BB+
5
Non-investment grade speculative
Non-investment
BB
5
Non-investment grade speculative
Non-investment
BB-
5
Non-investment grade speculative
Non-investment
B+
6
Highly speculative
Non-investment
B
6
Highly speculative
Non-investment
B-
6
Highly speculative
Non-investment
CCC+
7
Substantial risks
Non-investment
CCC
7
Extremely speculative
Non-investment
CCC-
7
In default with little prospect for recovery
Non-investment
D
8
In default
Non-investment
Table 1: Classification of rating classes from Standard & Poor's
they use this private information efficiently.
The three principal rating agencies use an alphabetical scale to rank the en-
tities, which reaches from "AAA" to "D" for S&P (see Table 1). The intention is
to stress the ordinality and avoid the connotations of cardinality that might be
immediately associated with a numerical rating scale (BIS 2000, p.15). Addition-
ally, they use "+" and "-" signs to show relative standing within the major rating
categories from "AA" to "CCC". As such, the distance for example between "AA"
and "AA-" is called one "notch".
Once an initial rating is attached to an entity, the rating agencies normally
continue monitoring the issuer and might announce a rating change, i.e.
an
upgrade or a downgrade, if a change in credit quality has occurred. The rating
itself consists of the actual grade on the alphabetical scale, which is frequently
accompanied by an outlook that is either positive, negative or stable. These
outlooks represent the potential for a rating change and its direction over the
intermediate term (typically six months to two years). In addition, Standard
& Poor's place ratings on the watch list, which they call "Credit Watch", as
2
Rating Agencies and the Market for Credit Risk
6
reaction to events that affect the credit risk of the rated entity but whose extent
cannot be assessed yet. Thereby, they gain additional time to collect information
and evaluate the effect on the credit quality. However, Standard & Poor's state
that they complete their analysis of the magnitude of the rating impact normally
within 90 days. Thus, within this period of time, the Credit Watch listing might
lead to an actual upgrade or downgrade.
Efficient Markets Hypothesis
For the following analyses, the concept of efficient markets is fundamental. Al-
though the theoretical foundations of information-efficient markets can be traced
back to the beginning of the twentieth century, the Efficient Markets Hypothesis
(EMH) was developed by Eugene Fama in the early 1960s. In his study concern-
ing efficient capital markets from 1970 he states: "A market in which prices always
`fully reflect' available information is called `efficient'." Thus, the simple definition
of an information-efficient market is that all known information is contained in
the prices. This implies that prices in efficient markets should instantaneously
react to the release of previously unknown and relevant information. For this
relation to be valid, there have to be rational agents and a frictionless market
without disturbing transaction costs.
In an efficient market the release of former publicly unknown information
should lead to an immediate abnormal reaction in the prices. Consequently, the
announcements of ratings, among others, should yield an abnormal reaction on
an efficient market dealing with credit risk if they convey new information. This
implies that if no reaction can be observed on the particular market, credit rating
announcements cannot contain significant information that is new to the market.
Therefore, this relation can be used to investigate the information content of
ratings, i.e. whether there is an unexpected part which is new to the public.
As such, this requires that there is no significant insider trading, for example
from rating agencies that anticipate the announcements. In the next step, an
appropriate market has to be determined, which trades credit risks and can be
assumed to be information-efficient. As we will see in the following section, the
Credit Default Swap market suits both conditions and is dominated by credit
risk.
2
Rating Agencies and the Market for Credit Risk
7
Figure 1: Volume outstanding in the global CDS market
Credit Default Swaps
Aside from the bond market, credit risk is traded with credit derivatives,
especially with Credit Default Swaps (CDS). This is a type of insurance contract
that is traded over-the-counter, which means that there is no formal exchange
up until now.
6
They were developed in the mid nineties, and turned into the
most popular credit derivative with markedly growing volumes (see Figure 1).
There are two parties who enter this contract. On the one hand, there is the
protection buyer who wishes to buy insurance against the possible default of a
reference entity. This entity might be a corporation or a sovereign which the
protection buyer has financial claims against. The underlying that the buyer
intends to insure with a CDS contract is called reference obligation (for example
a bond). However, the contract is based on the reference entity itself. The
protection seller represents the counterparty that acts as the insurer. Usually,
these are financial institutions, such as banks and insurances or hedge funds,
which take the risk that the underlying entity can default. If there is no default,
then the contract lasts until maturity as the parties previously agreed upon.
6
However, as reaction to the financial distress of AIG, a clearing house was established in the
U.S. and in Europe during 2009.
Details
- Seiten
- Erscheinungsform
- Originalausgabe
- Jahr
- 2010
- ISBN (eBook)
- 9783836649285
- DOI
- 10.3239/9783836649285
- Dateigröße
- 451 KB
- Sprache
- Deutsch
- Institution / Hochschule
- Eberhard-Karls-Universität Tübingen – Ökonometrie, Volkswirtschaftslehre
- Erscheinungsdatum
- 2010 (Juli)
- Note
- 1,3
- Schlagworte
- ratings rating agency credit risk capital market
