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8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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Chapter 1: Introduction1.1 Introduction
Credit rating agencies have compete a very important role for many
years in monetary markets. The foremost responsibility of rating agencies
is to convey their opinions concerning the default risks of sure issuers or
market instruments by assignment credit ratings. The ratings they supply
square measure wide employed by numerous market participants.
Additional specically, lenders will place condence in ratings in decision-
making while not having to have interaction themselves within the pricey
and long operation method. or borrowers, ratings will widen their access
to funding through dissemination of their credit quality info to investors.
!ortfolio managers con"ointly use credit ratings in portfolio management.
#atings from sure reliable agencies are employed by regulator. As an
e$ample, the %&C pro"ected that public rms inform investors what
square measure the ratings of their securities as given by the agencies.
The city Committee on banking direction '(C(%) establishes capital
adequacy needs supported ratings provided by e$ternal credit rating
agencies. The performance of rating agencies has been the topic of intense
dialogue within the past few years. #ating agencies are defendant of
failing to supply reliable and timely ratings. *t can be a con+ict of interest
owing to a relationship with the corporate management. Accusations of
lagged reaction to info have intense particularly when many rising
market monetary crises. #ating agencies square measure criticied for
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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passively reacting to the crisis rather than having the ability to predict
the crisis. The disputation over rating agencies leads to a copious
quantity of analysis being carried out on the data worth of ratings.
(eneath the economical markets hypothesis, there would be market
reaction related to rating revision announcement if the event
incorporates valuable and price-relevant info.A large variety of studies have e$amined the impact of rating changes
on stock costs. The bulk agitate learning the orth American nation
market, whereas few analysis studies are done on work the Asian
markets. The dearth of analysis arises from the embedded characteristics
of Asian economies. *n distinction to the orth American nation market,
the Asian markets square measure comparatively tiny and fewer well-
regulated. %pecially, the weaker is that the market regulation and the
larger the market segmentation, the additional seemingly it is to look at
info leak and trading before any natural event.owever, owing to the continuing development and increasing
importance of the Asian markets, additional analysis ought to be
conducted to ascertain if the results obtained from mature markets like
orth American nation square measure similar. #ising markets square
measure characteried by info spatiality and low transparency. There
square measure restricted channels for rms to broadcast info to the
investment public. Credit rating therefore is one among the few out there
signals to convey relevant info in smaller Asian markets. Consequently,
the data discharged by rating agencies may be additional news-worthy in
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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these markets. Also, in lightweight of the vital restrictive role of rating in
some mature markets, this study may be additional substantive for
smaller Asian markets wherever the regulation could also be weaker
compared with orth American nation market. This study con"ointly seeks to look at the in+uence of world credit
rating agencies relative to native agencies. Against the background of an
apace growing rising economy, the demand for domestic ratings has
been gaining larger importance over time. The worldwide rating agencies
like /oody0s, normal and !oor0s usually charge abundant higher fees for
rating services than native ones given their larger specialied skills and
knowledge in rendering rating service. Therefore, from the monetary
perspective, the native rater is in a very stronger position to service the
rising market by allocating its resources to rate tiny issuers that will be of
less interest to the worldwide raters. Additionally, the domestic rater is
looked as if it would have a large and straightforward access to native
info, therefore facilitating a much better understanding and insights of
native issuers0 credit goodness. *n contrast, the orth American nation
headquartered international rating agencies might react additional slowly
owing to the inherent geographic disadvantages. *f that1s the case, the
rating announcement by domestic raters may be additional informative
relative to their international counterparts.owever, given the short history of rating record, lack of transparency,
the native agencies might receive very little recognition from investors.
This argument is according to Associate in ursing Asian development
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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bank paper that surveys a pool of investors on their opinions of native
raters. *t0s reportable that forty fth of investors surveyed aforesaid the
native raters were completely not timely the least bit. *f this market
perception dominates, the market may be insensitive to the native rating
announcement. Another criticism of native agencies is that the native
rating agencies square measure additional seemingly to use weaker
standards to domestic corporations, that is mentioned a home bias. To
induce an additional comprehensive understanding of however info is
mirrored in rising market, e$ploring the distinction between native and
international news announcement is of important importance.
1.2 Objectives of the study The ob"ect of this study is to e$amine the impact of credit rating
changes on common stock returns.2. 3o rating agencies have superior information and analytical skills
and hence can their rating revisions in+uence e$cess equity returns4
5. 3o the response patterns to rating events vary across di6erentmarkets4
7. 3oes the placement to credit watch list have information value4
8. 3o the unanticipated events carry more information than theanticipated ones4
9. 3oes the Asian crisis have an influence on the market reaction to
news announcement4
:. *s there any di6erence between the market reactions to rating events
announced by international agencies relative to those announced by
local agencies4;.
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1.3 Organization of the study This paper proceeds as follows=
Chapter Two reviews the e$isting literature and provides the
theoretical background of this study.
Chapter Three describes the data used and e$plain how we select the
sample in detail. *n addition, the methodology employed in empirical
analysis is discussed.Chapter our presents the empirical results with corresponding
e$planations and related discussions.Chapter ive outlines the main ndings of this empirical work and
points out the limitations and suggests additional avenues for future
research.
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Chapter 2: Literature Revie
A large body of literature has investigated the informativeness of
credit ratings by operating with the rating-related events. Those events
cowl varied views relating to credit rating. or e$ample, (arron, Clare and
Thomas '2>>;) analye the impact of assignment of latest rating on ?@
capital market and realie no important abnormal come related to it.
Associate degree empirical work by @liger and %arig '5) suggests that
rating data is price-relevant and valuable, citing proof that bond worth
ad"usts to data following /oody0s renement of its rating system.
Additional recently, Aintablian and /ora '59) realie no market
response around /oody0s announcement of eliminating the sovereign
ceiling on company rating. These studies square measure comparatively
rare since the events coated happen less oftentimes. Consequently,
additional and additional works specialie in the upgrade and downgrade
events.2.1 I!pact of rating changes on security price
The argument that there1s a linkage between rating revision and
security value has its principle embedded within the belief that rating
agencies area unit capable of gathering, process and so transfer vital
personal data to the market. At intervals the theoretical framework of
market potency, the knowledge content of rating will be tested by means
that of e$amining the abnormal returns close the announcement of rating
revision. The initial focus of the literature during this space is that the result of
rating changes on bond costs. Those works report con+icting noticing=
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;8), Brierand
@at '2>;:), *ngram, (rooks and Copeland '2>7), >5) do notice vital bond
value reaction. These variations in results will be attributed mostly to the
problems of methodology, sample periods and also the knowledge
frequency 'monthly, weekly or daily). #esearches began to think about
the stock value reaction to bond ratings further.umerous studies have investigated the knowledge worth of credit
rating changes by measure the abnormal stock returns round the
announcement.'BriEn and %anvicente 2>5, Boh and &derington 2>>7,
2>>, 3ichev and !iotroski, 52) though there1s some variation in results
across studies, there1s proof that associate degree imbalance e$ists
available value reactions to credit rating downgrades and upgrades.
%pecically, a downgrade announcement is followed by a ma"or negative
accumulative abnormal stock come back, whereas associate degree
upgrade associate degree announcement is followed by an insignicant
positive accumulative abnormal stock come back. This puling empirical regularity is e$plained from the side of the
incentives of the businesses and also the rating agencies 'Boh and
&derington '2>>)). *t1s argued that rm0s area unit additional probably to
unharness the favorable data rather than the unfavorable data. Fn the
opposite hand, the rating agencies have the sturdy incentive to pay
additional resources in police work deterioration in credit quality instead
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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of enhancements as a result of the upper reputational price of failing to
discover credit issues. Those biases create the downgrade data additional
interesting within the market and so the market reaction to the
downgrade is stronger.
There are studies viewing the worth activity before and following the
rating changes.
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whether or not new and valuable data is sent to the market. The rating
revision has detail content as long as the announcement communicates
new and value-relevant information to plug. *f the data is already
anticipated by investors, the market might not answer the news. They use
equity possession dispersion and charge per unit volatility as live of the
number of data o6ered to regulate for the market anticipation of a rating
amendment announcement. They notice no market response to rating
changes for larger companies and vital worth movements for smaller
companies with less data o6ered within the market. Creighton, Bower and
*. A. #ichards '58) additionally o6er proof for di6erential market
response associated with rm sie. Gorion and Hhang '59) recommend that initial worth of the rating is a
vital however neglected consider the reason of cross-sectional distinction.
They notice a way stronger stock worth movement for rating changes
ranging from a lower initial rating. %upporting proof for this argument will
be found within the study by Boh and &derington '2>>>). The magnitude of market response additionally depends on whether or
not the rating amendment crosses the investment to speculative-grade
border. *nstitutional investor are prohibited from holding the problems of
investment grade, resulting in a bigger worth movement once the border
is crossed. This Iinvestment-gradeJ result is mentioned in Gorion and
Hhang '59).2.3 $he in for!ativeness of credit atch procedure
Aside from enormous empirical evidence concerning the upgrades and
downgrades, the credit watch procedure, an issue little studied, has
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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stirred interest in this related stream of research. Fn the theoretical side,
(oot, /illbourn and %chmeits '5:) analye the economic role played by
credit rating agencies through the credit watch procedures in the
nancial markets. *n their proposed model, the credit watch procedure
helps to establish an implicit contractual relationship between the
agencies and the rated rms. The mechanism works as follows. %uppose
the agency observes potential deterioration in the firm0s credit quality, it
will ask the firm to deal with the unfavorable situation and place the rm
on the watch list. The rated rm can choose whether or not to undertake
recovery e6ort 'observable to the rating agency but not by the market)
after being put on negative credit watch list. *f the rm succeeds in
restoring the credit quality, the rating may get reconfirmed. Ftherwise, it
will be downgraded ultimately. The subsequent downgrade enables the
market to realie that the downgraded rm did not undertake
recovery e6ort or failed in improving the credit quality. *n contrast, for the
downgrade in absence of a prior credit watch, the market only learns
about the failure of the recovery e6ort over time, thus the price impact
takes more time to materialie. Biven that, they draw an empirical
prediction= a rating change after a credit watch procedure is more
likely to be informative than a rating change without an early warning. *n
addition, they propose that this mechanism only works in the case of
downgrade because the rating agency has less incentive to put a
company on the positive credit watch list. /ore importantly, their model
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is based on the conditionality of investment decisions on the credit
rating, an institutional feature prevailing in the ?% market.*n related empirical work, and, #ichard and Deftwich '2>>5) e$amine
the security price reactions associated with the announcement of
additions to credit watch list, more specifically to the negative watch list
and positive watch list. >8 and 2>>: by (hattacharya, 3aouk, Gorgenson
and @ehr '5) shows no abnormal "ump in stock returns around the
announcement date. The authors then provide 9 possible candidates for
the e$planation of such an interesting nding. They are small sample
sie, ineEcient market, eEcient market but no information value inherent
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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in those events, full anticipation by the market and unrestricted insider
trading. urther, they provide evidence favoring the last one. They
conclude that the insider trading causes the prices to fully incorporate
the information before its public release, thus turning an event into a
non-event.As regards the information content of credit rating in developing and
small economies, there appears to be little research addressing this
issue. 3i6erent from many ?% studies that concentrate on company
rating, most emerging market studies are primarily concerned with the
e6ect of sovereign rating. The only study investigating the
informativeness of rating at rm level in emerging markets is by #ichards
and 3eddouche '2>>>). %urprisingly, the market is either insensitive to
rating changes or responsive in an opposite direction from what is
e$pected. owever, the surprising results in this paper may arise from a
non-robust empirical methodology. /ore broadly, the combination of 29
markets with di6ering level of sophistication could lead to misleading
results. ?sing weekly data instead of daily data is not ideal since
using a shorter observation interval is more e6ective in e$ploring daily
trends or security price reactions on specic event days. *n addition,
further investigation on all industries is preferable to the concentration
on only the banking industry. Therefore, there is scope for a more
comprehensive analysis on this issue.
2.& Co!parison of the in'uence of rating agenciesA very limited number of studies have previously e$amined the
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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di6erential impact of rating agencies. @ish, @aren and Flson document
no evidence that market values one agency over the other by
comparing the ratings from /oody0s and %K!. urther, %hin and /oore
'57) compare credit ratings assigned to Gapanese rms by two leading
?.%. rating agencies and two leading Gapanese agencies. Their ndings
suggest that the ratings by the ?.%. agencies are systematically lower
than those assigned by Gapanese raters. A follow-up study by Di, %hin and
/oore '5:) conclude that global agencies are more in+uential than
local raters for downgrades in Gapanese conte$t. Also, they nd the
ratings by the two prominent rating agencies are homogenous.
Chapter 3: (ata and )ethodo*ogy3.1 +vent de,nition
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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possible di6erent impact. An anticipated event refers to a change where
the rated company was put on the credit watch list prior to the
announcement date, with a direction consistent with the actual
subsequent changes. Credit watch is a valuable predictor of issuer0s
creditworthiness. (y placing rms on the credit watch list, the rating
agencies disseminate the information that an improvement or
deterioration is likely to take place in the short term to market
participants. %uppose the rm is ultimately downgraded or upgraded as
the credit watch list indicates, the market reaction to the rating revision
announcement might be muted since the news has already been
anticipated by the public through the credit watch procedures. Therefore,
we e$pect that the unanticipated events carry more information than the
anticipated ones.Aside from the actual rating changes, we also consider the credit watch
events. The credit watch event deals with the announcement of
additions to the credit watch list. %pecically, Inegative watch eventsJ
and Ipositive watch eventsJ are dened based on the direction of the
likely change indicated by the agency. The e$act definitions and specific e$amples of various rating events
to be employed in the conte$t of this study are outlined in table 7.2.
Table 7.2 about here
3.2
(ata3.2.1 (ata
source
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The data required for the analysis include the credit revision
events and time series stock price data of several ma"or Asian markets.
The credit rating change data are collected from the (loomberg
database. The information provided by (loomberg consist of the
announcement date, rating type, rating agency, current rating, last rating
and industry type of the rated issuers. The ratings selected for analysis
are from /oody0s, %tandard and !oor0s and itch, the three most
recognied rating agencies in the world. The raw sample collected
covers changes in credit ratings between Ganuary 2>>; and 3ecember
59. %i$ Asian ma"or markets e$cluding Gapan are selected= *ndonesia,
ong@ong, %outh @orea, /alaysia, Taiwan and Thailand. *n addition to t he
rating information from the international raters, we also e$amine the
rating revision announcement by local raters to obtain a more
comprehensive analysis. Those data are obtained from (loomberg. Aside
from the actual rating changes information, (loomberg also provides the
credit watch indicators, which forms a part of our analysis. As for the
stock return of the rated companies, we use the daily closing price from
the data stream. These are supplemented with information from
(loomberg as well as from the local stock e$change. To measure the
abnormal return, we also collect the daily local stock indices data
denominated in local currencies of the : markets from data stream. The
sample of credit events is reduced substantially because of the data
problems.
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3.2.3 -a!p*e
se*ection To avoid a loss of power in our tests resulting from other events with
potentially confounding e6ect on stock prices, we eliminate the
observation if another news announcement concerning earnings and
mergers occurred during the event window of 82 days. There are also
some cases where the rating is changed consecutively by multiple
agencies. The temporal clustering of rating revisions for the same
company might be potentially problematic for empirical analysis since it
may induce a biased estimate of stock price movement around a
particular event. or the two consecutive events within a2 day window, we include the event if both are upgrades or both are
downgrades. *n this case, the earlier not the later event is included. The
resulting sample used for analysis is summaried in table 7.5.
Table 7.5 about here
3.3 +vent study !ethodo*ogy The information content of rating is e$amined by means of an event
study. The length of the event window and the estimation window are
illustrated below=
tL-25 tL-5 tL tL5&stimation window &vent window
The choice of the event window is based on an attempt to obtain a
comprehensive picture of how the market responds to rating-related
events.
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5 days on both sides of this day are chosen. The event window is split
into three sub-windows. To capture the likely information leakage, we
dene the period '-5,-2) as the pre-announcement period. Although the
information from (loomberg includes the announcement day of each
event, we cannot identify the e$act time of announcement and thus
cannot determine whether the announcement occurs during the
trading hours. Therefore, we choose a two-day period ', 2) as the
announcement window to account for this uncertainty. *n addition, we
also e$amine another period '5, 5) following the announcement window
to take the possible lagged reaction into consideration. This paper uses daily stock price data to compute two di6erent
measures of returns for the rated companies. The rst measure is based
on the market model as follows= Rit = α I + β iRmt + ε it (1)
Where
Rit = return on firm i for day t Rmt = return on market index for day t
ε it = error for day t
The coefficients are estimated for a given firm over a 100day estimation !indo! starting 1"0 days
#rior to the announced event and ending "0 days $efore the event day% The a$norma& return is defined
as the difference $et!een actua& returns and the returns #redicted $y the a$ove mode&%
'nother measure com#utes the excess return version of the market mode&
Rit = R ft + β i ( Rmt R ft ) + ε it (")
Where the risk free rate R ft is co&&ected from data stream% The resu&ts of this mode& are not
materia&&y different from the other mode&* and hence !e on&y re#ort the resu&ts of euation 1%
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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,ext* the average a$norma& return* ''-* is ca&cu&ated $y averaging the n events for a s#ecific event day
t
1
,
AAR t = . A R it
(/ )
N i= 1
Then* the ''-s are aggregated in order to dra! overa&& inferences for a certain #eriod
t "
CAARt 1* t " =
. AARt
t =t 1
The test statistic for the significance of ''- eua&s to the ratio of ''- to its standard
deviation% The standard deviation is estimated $y the data o$tained !ithin the estimation !indo!%
urther* the standard deviation of cumu&ative average a$norma& return is given $y standard
deviation of ''- mu&ti#&ied $y the suare root of the num$er of days in the #eriod%
t =
AARt
s( AARt )
1
)"0
()
s( AARt ) = . ( AARt AAR)"
100 1"0
(2
)
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Chapter %: +!pirica* Resu*ts This chapter discusses the empirical analysis by e$amining the
information value of credit rating in four di6erent aspects. *n each
case, the results for average abnormal returns on ve specic event
days are presented. (esides, cumulative average abnormal returns over
the pre-announcement, announcement and post-announcement windows
are reported respectively. The discussion in this chapter centers on the
price movement over the 7 windows in order to give a more
comprehensive picture of the price ad"ustment.%.1 Is there any !ar#et reaction to actua* rating changes and
credit atch re*ated events The rst section e$amines whether stock returns are signicantly
in+uenced by actual rating changes announcement and by credit watch
placement announcement. The inclusion of credit watch event is based
on an e$pectation that the placement of a rm on the credit watch list
may convey some new price-relevant information to the market because
the credit watch list serves as an early warning system for likely rating
changes in the short run. The results are reported by market in table 8.2.
Table 8.2 about here
ong @ong and %outh @orea display a uniform response pattern to the
events investigated. /ore specically, price ad"ustment surrounding
downgrades are signicantly negative, reinforcing the evidence of
information value of downgrades observed in other markets. or
upgrades, there is little evidence of signicant price movement. *t is
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apparent that the two markets do not treat upgrades as an informational
event. These ndings suggest that %outh @orea and ong @ong appear to
behave in a manner consistent with other mature markets. or the credit
watch events, only the negative watch placement has an impact on
market and the magnitude of reaction is smaller than that of downgrades
for both markets, indicating that a possibility of being downgraded is
less informative than an actual downgrade. This evidence is consistent
with prior research 'and, #ichard and Deftwich '2>>5)). As regards the
di6erence between the two markets, the price ad"ustment observed in
%outh @orea is more drastic than that in ong @ong in terms of
magnitude and signicance level.*n the case of *ndonesia, there is no market reaction associated with
upgrades and credit watch events. As regards downgrades, there appears
to be a full information leakage which translates into a strong negative
cumulative average abnormal return of -29.> over the pre-
announcement window. The information is found to be incorporated into
prices prior to downgrade announcements, suggesting a degree of
ineEciency in the *ndonesia market.As shown in table 8.2, the /alaysia market reacts to both negative
watch placement and downgrades announcements. An interesting nding
is that a signicant lagged price ad"ustment appears for upgrades over
the post-announcement window, indicating that upgrade constitutes an
informational event in the conte$t of /alaysia. This detected response is
contrary to the usual result found in previous literature that upgrades do
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not have an impact on market.or the Thailand market, it appears that the good news
announcements contain new information that surprises investors. /ore
specifically, positive watch placement contributes to a highly signicant
cumulative average abnormal return of 5.:: over the two-day
announcement window. *n addition, positive price ad"ustment is observed
for upgrades announcement. *n terms of bad news, the market
apparently does not treat downgrades and negative watch placement as
informational events, thus no evident market reaction being detected. *t
is obvious that the Thailand market behaves in a totally di6erent way
from its more developed counterparties. The informative upgrades
may arise from the limited access to information in developing
economies, an e$planation can be provided to account for the similar
market reaction to upgrades observed in /alaysia. or the lack of
reaction to bad news, it is diEcult to identify the e$act reason. As
discussed by (hattacharya, 3aouk, Gorgenson and @ehr '5), five
possibilities are suggested. *t is possible that the market is too ineEcient
to re+ect new information. Alternatively, there might be no price-relevant
information in downgrades. Fr the market has fully anticipated the event,
thus no abnormal "umps in stock return are being detected around
announcement period. Also, unrestricted insider trading, which can
cause prices to fully incorporate the information prior to public
announcement, may contribute to the observed insensitivity. Aside from
those possibilities, another likely reason is that this result is only unique
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in this specic period which includes the Asian crisis. *n our case, the
rst reason mentioned above is unlikely because there is evidence of
response to upgrades in Thailand. *n terms of other possibilities, it is
too premature to conclude which one is the most relevant candidate and
further discussion will follow.As regards Taiwan, the results are to a great e$tent surprising. either
upgrades nor downgrades have an e6ect on security prices. The
discussions regarding Thailand can be applied to the case of Taiwan. o
sign of information leakage is observed, indicating that insider trading
seems unlikely in this case. *n the subsequent sections, we0ll seek to
e$plore why Taiwan behaves in such an interesting way.(ased on findings in this section, it is apparent that a variety of
di6erent reactions e$ist across the Asian markets. The di6erent market
behaviors observed are in accord with prior e$pectation that markets
with di6ering level of sophistication may e$hibit unique patterns.
%.2 (o the unanticipated events carry !ore infor!ation than
the anticipated onesaving determined that the si$ Asian markets di6er in reaction to
rating related events, we now attempt to reveal more about the nature
of rating changes. This section hence e$tends the main results by
segmenting the rating changes into anticipated and unanticipated ones
according to whether the rerated rm was placed on credit watch list
with the same direction as the announced rating change before the
announcement. Table 8.5 provides the results from the si$ investigated
markets.
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Table 8.5 about here
our markets present a similar pattern that the unanticipated
events have a more drastic market impact. /ore specically, in the case
of ong @ong, %outh @orea and /alaysia, the information value of
downgrades observed in section 8.2 almost entirely comes from the
unanticipated downgrades. or the anticipated downgrades, no
informational content is found, as shown by the insignicant market
reaction over the event window. Also, the di6erential impact of
anticipated and unanticipated downgrades holds true for the upgrades in
/alaysia.
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e6ect over the announcement window. ?nlike other markets, the
di6erence between anticipated and unanticipated events lies in the
response time instead of the magnitude. This di6erence appears to be
driven by the differing incentives to possible leakage of information. *n
particular, for the unanticipated downgrades, insiders tend to trade on
relevant information because it is more likely to be a shock to market,
leading to a negative CA# of -2.857 preceding the announcement. or
anticipated downgrades, however, the same incentives may not e$ist
because the information regarding the downgrades was already
conveyed to market when the rms in question were added to the
negative credit watch list. *n addition, the signicant announcement
e6ect of anticipated downgrades contrasts with what was observed in
other markets, suggesting that although investors may receive prior
warning of downgrades in the form of credit watch placement, there is
still uncertainty regarding the timing and magnitude of the possible
downgrades. This uncertainty is reflected in the negatively significant
market reaction, which is suggestive of a component of surprise in the
news.
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As with Taiwan, the market is still insensitive to any kind of rating
revisions when the market anticipation is taken into consideration.
Therefore, it is tempting to conclude that the market anticipation may not
e$plain the curious ndings of Taiwan in section 8.2.%.3 (oes the /sian
crisis have an i!pact on the !ar#et reaction to nes
announce!ents*n addition to the di6erences in the response induced by market
anticipation, the market reaction may di6er in other ways. The selected
period in previous discussion incorporates the Asian nancial crisis which
leads to a spike in downgrades. As discussed in #eisen '55), the rating
agencies were accused for reacting to events rather than anticipating
them in the /e$ican crisis of 2>>8-2>>9. This opinion is in line with the
argument of #eisen and von /altan '2>>>) that the performance of
rating agencies is poor during the Asian crisis. The discussion with regard
to agency performance in emerging markets is mainly concerned with
the sovereign rating. >; to 3ecember, 2>>. %ince almost all the
upgrades cluster in the non-crisis period, this analysis is only carried out
for downgrades. %ample sie and empirical results are presented in table
8.7 and 8.8 respectively.
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Table 8.7 about here
Table 8.8 about here
!anel A in table 8.8 looks at Thailand, ong @ong and *ndonesia.
Among the three markets, the rst two markets share some common
features. *n particular, no e6ect is encountered for downgrades in crisis
period, whereas strong impact e$ists for those during the non-crisis
period. This phenomenon can be attributed to the likely e$cess
pessimism due to the financial crisis in which investors tend to have a
negative anticipation towards the financial status of firms in the market.
This psychological factor may turn a piece of negative news into a non-
surprise. *n this way, downgrades in a bad time would not have any
impact on market. ow we can safely conclude that the interesting
nding for downgrades in Thailand detected in section 8.2 can be
attributed to the time period chosen. The result of overall sample is
neutralied by the lack of response in the crisis period. The *ndonesia market appears to behave in a slightly di6erent way.
The negative e6ect of downgrades during non-crisis period is much
stronger than that of the other two markets.
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insider trading causes the market to fully incorporate relevant
information into prices before publicly announced. Taken together, the
results in panel A suggest that the rating changes during non-crisis
period e$ert a much stronger announcement e6ect on market.urther evidence from %outh @orea and Taiwan can be found in panel
(. The result of %outh @orea contrasts with that of markets in panel A.
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for the lack of market reaction in Taiwan.*n a practical sense, there is something to get e$cited about. #eferring
to the third column in panel (, while the CA#s over the announcement
and post-announcement window are not statistically signicant, the
di6erence between the two gures is economically signicant. An
opportunity for prot might arise supposing the investors buy stocks of
downgraded rms during the announcement period and then hold them
for one month 'about 5 trading days).
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55-59 'T#*%). *n order to make the results more comparable and
meaningful, the sample periods for global raters are confined to be
consistent with their respective local counterparts. *n addition, caution
and prudence will be e$ercised in comparing the di6erent markets due to
the di6ering sample period across markets.
Table 8.9 about here
To get a sense of the distinct rating activities across agencies, table
8.9 outlines the coverage frequency of global and local raters using the
raw sample. or all the markets, local agencies rate the largest number
of rms, >7, 5; and 57; for T#C, T#*% and @*% respectively. owever,
among the rated rms, only a small number of firms are covered by both
local and global agencies. This common feature can be attributed to the
di6erent client groups they have been serving. Benerally, firms with large
capitaliation are more willing to request rating service from international
agencies since their ob"ective is to step into the global market and attract
more international investors. The financially disadvantaged small issuers,
in contrast, tend to choose local agencies who charge less prohibitive
fees. Dooking at the number of events announced by local and global
raters, %outh @orea and Thailand share a resemblance that the ma"ority
of the upgrades and downgrades are by global raters and local raters
respectively. This can be e$plained by the fact that large firms rated by
global raters are more likely to be upgraded due to their relatively sound
nancial status, whereas there is a higher possibility for small and
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medium enterprises '%/&) to be downgraded because they are in more
volatile and vulnerable nancial position. Among the three markets,
%outh @orea has the largest number of rating revision events and the
largest coverage of rms rated. This is possibly due to its relatively well-
established and sophisticated nancial market. This pattern still remains
after its longer sample period has been taken into consideration.
The remaining sample after dropping events with insu6icient data and
those contaminated by other price-relevant news is summaried in table
8.:. e$t, table 8.; provides the event study results for the selected
period.
Table 8.: about here
Table 8.; about here
or %outh @orea in panel A, there is no big di6erence in the global
upgrades and local upgrades. As with downgrades by global raters, a
statistically significant negative abnormal return of -5.28;7 is detected.
Compared to the price behavior of rated rms by global raters over the
event period, the results for local downgrades show di6erent
characteristics. There is some indication that most downgrades are
foreseen by the market. A signicant negative CA# is observed over the
'-5, -2) window.
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surprise in the news announcement. *n addition, a prolonged market
reaction is observed over the subsequent period '5, 5). Therefore, the
%outh @orea market, on average, reacts strongly to local downgrades, a
supporting evidence for the higher influence of local agency.*n the case of Taiwan, upgrades, regardless of being rated by global
agencies or by local ones, are statistically insignicant during the event
window. The downgrades, however, e$hibit di6erent characteristics.
There is no evidence that the market is responsive to downgrades by
global raters, consistent with the earlier nding using an alternative
period from 2>>;-59. '%ee panel ( in table 8.2). %urprisingly, stock
price responds signicantly to downgrades by local agency in the
e$pected direction. This result contrasts greatly with that of global
agencies, providing evidence that local agency provides better quality
information than its international counterparts at least in the Taiwan
conte$t.As noted in the previous discussion regarding the non-response of
Taiwan market to both upgrades and downgrades by global raters, si$
possibilities are potentially relevant= full market anticipation, insider
trading, sample period chosen, small sample, ine6icient market and
value-irrelevant rating information. The fourth e$planation fails to hold
because the sample sie of informative local downgrades is only slightly
larger than that of global downgrades. %imilarly, if Taiwan market is
informational ine6icient, we should not observe any signicant price
impact for the local downgrades. Biven that the first three alternative
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possibilities have been ruled out in the earlier section, we, therefore, can
conclude that the investors in Taiwan do not value the information as
much from global rating agencies. *n other words, there is little
information value inherent in global rating changes.#esults in panel C of table 8.; are for rated firms in Thailand. As
can be seen, the news by global raters has a CA# signicant at 2M for
the two-day announcement window, a result consistent with the nding
in section 8.2 where a longer sample period is involved. *t appears that
the upgrades by global agencies contain new information that surprises
investors and the market interprets it as good news. onetheless, this
fails to hold true for upgrades by local agency and no signicant e6ect is
produced during the event period. There appears to be a greater
average price impact of global rating relative to local rating. *n the case
of downgrades, comparison is not available because all the downgrades
by local raters happened before 55. The result of local news shows no
market reaction associated with downgrade announcements.aving investigated the above three markets individually, we now
seek to e$plore the reason why the relative importance of local raters
vary across markets. To gain further insight into the three local rating
agencies, we present their characteristics in table 8..
Table 8. about here
*n terms of available services provided by local raters, T#*% has been
o6ering the most e$tensive services to its clients, followed by @*%. *n
contrast, T#C do not e$pand its services as its peers do. *nstead, it
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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chooses to concentrate e$clusively on the rating services. Dooking at the
various shareholding structures outlined in panel (, the I*nternational
C#A-3omestic C#AJ link-ups seem to be a common practice. or instance,
/oody has a 9M stake in @*% and %K! holds a 9M equity stake in T#C.
evertheless, T#*% is an e$ception with no "oint partnership with
international C#As. The di6erent background shown above may contribute to e$plaining
the fairly divergent market reaction patterns observed. Among the
analyed local agencies, only T#*% has no impact on security price. *t may
be true that the possible political dependence, as shown by a
government ownership of 2>M, may deplete the credibility of T#*%. The
stock price, therefore, is not responsive due to the market
perception of political intervention. Aside from that, a more likely
candidate might be the lack of "oint partnership with global raters. The
market may anticipate that the local raters are able to receive technical
support and skill transfer from their partner and thus enhance their
credibility. This raises the possibility that the responsiveness observed in
the case of T#C and @*% may be partly the result of international rating
agencies0 participation in ownership.Another interesting nding in this section is the strong di6erential
e6ects of downgrades detected for global versus local agencies 'T#C). *t
is possible that the di6erence arises from T#C0s concentration on rating
service, as indicated by panel A in table 8..
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Chapter &: -u!!ary and Conc*usion
&.1 -u!!ary of the resu*tsCredit ratings are quite prevalent in nancial markets and a large
body of literature has documented that the security price will be
significantly a6ected when rating agencies revise the ratings they issued.
owever, there has been a lack of studies on Asian markets. Credit rating
has been regarded as an e6ective channel to reduce the degree of
information asymmetry. ence the role played by rating agencies is more
meaningful to smaller markets where transparency is weaker. Biven that,
this study aims to discuss the information value of credit ratings in
smaller Asian markets e$cluding Gapan. This issue is investigated by
measuring the pre-announcement and post-announcement as well as the
contemporaneous responses of si$ Asian nancial markets to rating
related events.
This study begins with an e$amination of market response to rating
related events announced by /oody0s, %K! and itch. The evidences
from the si$ Asian markets are mi$ed, suggesting the manner in which
markets react to credit rating di6ers across markets and relates to the
distinct characteristics of specic markets. *n particular, ong @ong and
%outh @orea, more advanced markets are found to behave in a similar
way to their developed counterparties= immediate reaction to bad news
but no response to good news. %trong evidence of information leakage is
observed for *ndonesia, indicating a degree of ineEciency. The results
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from the other three markets= /alaysia, Thailand and Taiwan are quite
interesting. /alaysia and Thailand markets respond to upgrades. This
nding can be attributed to the lesser availability of opportunities by
rms to communicate good news in the two markets. Thailand,
however, shows non-response to downgrades. /ore surprisingly and
interestingly, there is no impact associated with any kind of rating
events announced by the international rating agencies in Taiwan.e$t, the main results from above are further investigated by the
partition of rating changes. The segmentation is based on the di6ering
market anticipation incorporated in rating revisions. The results suggest
that, on average, the unanticipated events carry more information value
than the anticipated ones. *n the case of Taiwan, no di6erence is
detected because the market remains unresponsive after the partition of
the overall sample.
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analysis, three markets are investigated. %outh @orea and Taiwan seem
to be more sensitive to local raters. The di6erential impact of local and
global rater is e$tremely apparent in Taiwan, indicating that the local
rater is much more credible in the domestic market. or the Thailand
market, the global rater is more influential in terms of both market
coverage and market impact. To sum up, all the ndings in this study show that generally the credit
ratings in emerging markets do contain new information. owever,
the market reaction to the information di6ers in term of market
characteristics, rating agencies, markets conditions and investors
anticipation.
&.2 Li!itation of the study There are some limitations with respect to the analysis and data that
may a6ect the accuracy of the results.2. The sample sie for the covered markets is small due to the
di6iculty in the availability of data going farther back in time. This may
bring bias into research. ?sing small sample sie may increase the
possibility that the nal sample "ust happen to behave in the observed
manner. The small number of events in this study might be a caveat, we
therefore e$ercise prudence and caution when interpreting the empirical
results to ensure a more reliable conclusion.
5. The sample of credit events is reduced substantially because of the
data problems. /any rated companies do not issue stocks and the data
of some listed companies is not available due to inactive trading.
&.3 (irection for future research There are several additional avenues that could be e$plored, all of
8/16/2019 Impact of Credit Rating Announcements: An evidence from Major Asian Markets
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which would help in understanding this issue better.An e$tension to this study would be to consider the cases of listing
abroad. The globaliation of nancial market has catalyed the growing
migration of nancing activities abroad and the number of companies
seeking a foreign listing has increased over the last few decades. This
is particularly the case in emerging markets where the minority
shareholder protection is weaker and hence the rms have incentives
to signal the willingness to protect minority shareholder right through
cross listing.
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implications from the policy perspective. The regulators in emerging
markets can rely on ratings to monitor the banking industry, "ustifying
the incorporation of e$ternal credit ratings into the capital adequacy
requirements proposed by (asel Committee.
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(arren, /. G., Clare, A. 3., K Thomas, %. . '2>>;). The e6ect of bond rating
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(erk, G., K 3e/aro, !. '5;). Corporate Finance. !earson &ducation.
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ama, &. . '2>>2). &Ecient Capital /arkets= **. The Journal of Finance, 4+ '9), 29;9-
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Boh, G. C., K &derington, D. . '2>>>). Cross-sectional variation in the stock market
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Finance, 3 '2), 22-225.
Boh, G. C., K &derington, D. . '2>>7). *s a (ond #ating 3owngrade (ad ews, Bood
ews, or o ews for %tockholders4 The Journal of Finance, 4*-, 52-
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Bonale, ., aas, ., Gohannes, #., !ersson, /., Toledo, D, Nioli, #., et al. '58).
/arket dynamics associated with credit ratings= A literature review. /CB
ccasional aper '2:), 2-8.
BriEn, !. A., K %anvicente, A. H. '2>5). Common %tock #eturns and #ating
Changes= A /ethodological Comparison. The Journal of Finance, 7;'2), 27-
22>.
Bropp, #., K #ichards, A. G. '52). #ating Agency Actions and the !ricing of 3ebt
and &quity of &uropean (anks=
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and, G. #., olthausen, #. .
sueh, D. !., K Diu, O. A. '2>>5). /arket anticipation and the e6ect of bond rating
changes on common stock prices. Journal of Business Research, 24 '7), 559-
57>.
Gorion, !., K Hhang, B. '5;). *nformation &6ects of (ond #ating Changes= The
#ole of the #ating !rior to the Announcement. The Journal of Fi6e" $ncoe,
2:'8), 89-9>.
@liger, 3., K %arig, F. '5). The *nformation Nalue of (ond #atings. The Journal of
Finance, ** ':), 5;>-5>5.
Dinciano, . '58). The #eaction of %tock !rices to #ating Changes. 7oring
paper.
/ac@inlay, A. C. '2>>;). &vent studies in economics and nance. Journal of
/conoic 8iterature, 3* '2), 27-7>.
/atolcsy, H. !., K Dianto, T. '2>>9). The incremental information content of bond
rating revisions= The Australian evidence. Journal of Baning & Finance, )
'9), >2->5.
/oody1s *nvestors %ervices. '55). Role of the Cre"it Rating Agencies in Securities
!arets. /oody1s *nvestors %ervice.
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orden, D, K -88.
!oon, -
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%chweiter, #., %ewcyk, %. ., K Narma, #. '2>>5). (ond rating agencies and their
role in bank market discipline. Journal of Financial Ser%ices Research, + '7),
58>-5:7.
%teiner, /., K einke, N. B. '52). &vent study concerning international bond price
e6ects of credit rating actions. $nternational Journal of Finance & /conoics,
+ '5), 27>-29;.
%tickel, %. &. '2>:). The e6ect of preferred stock rating changes on preferred and
common sloc. Journal of Accounting an" /conoics, 3-, 2>;-52:.
%ylla, #. '52). A istorical !rimer on the (usiness of Credit #atings. The Role of
Cre"it Reporting Systes in the $nternational /conoy 'pp. 2-7).
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The ;). (ond rating agencies and the capital markets.
7oring aper.
-79.
, pp. 82-:7).
ew Oork= %pringer ?%.
Haima, G. @., K /cCarthy, G. '2>). The impact of bond rating changes on common
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Re%ie1, 23 '8), 87-8>.
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$ab*e 3.1: +vents de,nition
+vent type (e,nition +1a!p*es
?pgrade The announcement of a positive change in rating ((( 3 AAAPAAA
((( QR 3 AAAPAAAQRPAAAQ-
3owngrade The announcement of a negative change in rating AAA3 (((P (((QRP
AAAQ- 3(((P (((QRP(((Q-
Anticipated The announcement of an upgrade preceded by a positive ((( QR 3 AAAPAAAQRPAAAQ-?pgrade
?nanticipate The announcement of an upgrade not preceded by a prior ((( 3 AAAPAAAQRPAAAQ-?pgrade
Anticipated The announcement of an downgrade preceded by a negative AAAQ- 3 (((P (((QRP(((Q-downgrade
?nanticipate The announcement of a downgrade not preceded by a prior AAA 3 (((P (((QRP(((Q-downgrade
!ositivewatch
The announcement of additions to the positive watch list AAA3 AAA QR
egativewatch
The announcement of additions to the negative watch list AAA3 AAA Q-
ote= 2. QR = positive credit watch indicatorS Q- = negative credit watch
indicatorS Cases involving developing credit watch 'e.g. (((Q) are
e$cluded5. There are only a few cases in which the change direction is inconsistent
with the credit watch indicators. These are omitted. 'e.g. (((Q-
AAAPAAAQRPAAAQ-, AAAQR (((P (((QRP (((Q-)7. There are only a few cases where rms are removed from the credit
watch list without subsequent rating change. 'e.g. AAAQR AAA ,
AAAQ- AAA) These are omitted.
8. There are only a few cases involving changes in the status on credit
watch list, but without changes in rating classification 'e.g. AAAQR
AAAQ- , AAAQ- AAAQR). These are not considered.
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$ab*e 3.2: -u!!ary -tatistics of ,na* rating sa!p*e 14"255&6
7pgrades (ongrades Credit atch
Anticipated ?nanticipated
Anticipated?nanticipated
egative !ositive Total Total
ong@ong
22 58 79 25 29 5; 58 25
*ndonesia 2 7 8 5 78 98 25
/alaysia 2> 5; 8: 2 5 5> ; 55
Taiwan 2 5 52 9 59 59 8
Thailand 2> 9> :> 9> :; ; 58
%outh@orea
7 7 77 29 8 99 22 5>
ote= umber of negativePpositive watch e$ceeds number of
anticipated downgradePupgrade in some markets because some
negativePpositive watch rms subsequently became e$cluded from
the sample. %ome also remained as negativePpositive watch at end of
sample period.
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42
$ab*e %.1 )ar#et reaction to actua* rating changes and credit
atch events 14"255&6
8ane* /: 9ood nes
3ays Average abnormal returns
relativeto
event
ong @ong %outh @orea *ndonesia /alaysia Thailand Taiwan
!ositive .99 Q .582 .:9> .:> .;2: .292
.58: .222 .:88 .8:9 -.52 .:2 -.292 .5:: 5.5> .;52 QQ -2. -.859
2 .:> .; .7:> .:>; .> -.2; .875 .9: .7;2 .57:2 -.;5> .5;7
5 .972 -.85 -.7> .58 -2.; -.>2 -.22: -.2 -.9> .2:; -.5 -.52;
Cumulative average abnormal returns
-5 to -5.5;: .798 -.5 -.975 2.; -7.255 2.25 .;> 8.5 -2.78 9.>78 .82
to 2 .729 .2>> 2.27 2.2:7 .;> .828 .52 .755 5.:: .>9; QQ -2.2; -.295
5 to 5 -.7 .9: -2.;9; -5.5 -9.>99 -5.:88 .75 5.97 QQ -2.8>:; -.:77 -:.:72 -7.28
8ane* : ad nes
3ays Average abnormal returns
relativetoevent
ong @ong %outh @orea *ndonesia /alaysia Thailand Taiwan
egative8 .758
-.> .2:7 -5.87; QQ-.::5 2.27 .7;7 -.;88 -.>2 Q 5.2: -.857 -.52 -.2>;
2 -2.5>5 QQ-2.:>7 QQQ -.2: -2.8: QQQ -2.28 .2>; -.;7 -.8>2 -.> -.2:> -2.2>5 .298
5 -2.2>: QQ.:5 -2.87 Q -.7:5 -2.;2 -.97 -.;:; -.; -.>2: -.58: .9 -.9;
Cumulative average abnormal returns
-5 to -7.79; 8.5;: -5.:5 .8: -;.55 -29.>QQQ .;: 2.>> 7.89 5.58 -2.7:7 -5.599
to 2 -2.7> Q -2.97 QQ -5.9>;Q -5.28;QQQ -.25 .9; -2.95; Q -2.82 Q 2.2;> -.9>5 -2.7>5 -.85
5 to 5 -.;7: 5.92> 9.52 5.: 2.98> 2.; -2.75>9 5.5: 9.9>: .295 5.72 2.:>>
otes=
1. %ince the e$cess return results are almost identical to the market
model results, only thelatter model is reported.5. The sample sie is listed in table 7.5.
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7. Q indicates signicance at the 2M level, QQ at the 9M level and QQQ at the
2M level$ab*e %.2 )ar#et reaction to anticipated and unanticipated
rating change
8ane* /: /nticipated events
3ays Average abnormal returns
relativetoevent
ong @ong %outh @orea /alaysia Thailand *ndonesia Taiwan
?pgrade3owngrade
?pgrade3owngrade
?pgrade3owngrade
?pgrade3owngrade
?pgrade3owngrade
?pgrade3owngrade
-5 .78 .88 -.9: .:: -.92 .>9 .9>7 .82 .5;2 2.:7 .52 .82;
-2 .92 .59: -.58 2.:5 .527 .52 .85 -.2:8 -2.2; 2.598 2.8 -2.972
-.22 .>: .97> 2.98 .7>9 .22 2.2>5 Q .:> 7.285 -7.7 QQQ -.7; .89:
2 -.5 -2.>8 QQ .;: -.>58 .7: .77 .> .9 -2.;; -7.89 QQQ -.2:: -5.5:
5 -.5: -.559 .5> .>; -.77: -.;> .> -.5; -.887 -2.799 .:; -.72
Cumulative average abnormal returns
-5 to .:99 2.779 -2.8;> -.>22 2.;87 -2.;72 -.:>9 7.582 -:.>9 -5.; -.:7> -8.2 to 2 -.5:7 -.>:5 2.589 .:2: .872 .728 2.2>7 2.2> 2.7;59 -:.9:; QQQ -.55 -2.;9
5 to 5 2.75 -5.8 -7.;7 9.8; 2.7:: 8.8> .85; -8.992 -9.292 2.9;2 7.58 .5;8
8ane* : 7nanticipated events
3ays Average abnormal returns
relativetoevent
ong @ong %outh @orea /alaysia Thailand *ndonesia Taiwan
?pgrade3owngrade
?pgrade3owngrade
?pgrade3owngrade
?pgrade3owngrade
?pgrade3owngrade
?pgrade3owngrade
-5 .852 -.98> -.:8 .:9 -.55 -.5;; .2: -.8:8 -.5; -5.925 QQQ .;;2 -.5>7
-2 .22; .:27 -.2;8 -2.: QQ .5:2 -.98 -.9 .2 -.89 -5.::8 QQQ .28 .;
-.2>7 -.8>: -.5; -2.8:9QQ .2;8 -.>87 Q .985 Q -.9:7 -.: .9:: -.889 -.7:
2 -.>; -2.8>QQ .: -5.>;9 QQQ .; -.:2; .759 -.5;2 .57 .78 .5>9 .;88
5 -.88 .5>2 2.>99 -2.9:; QQ -.; -.89 .555 -.585 .2 .785 -.5:5 -.;9
Cumulative average abnormal returns
-5 to 2.55 8.5> .>8 -.8>9 .22> 5.272 -2.9>: 5.:7 -5.25> -2.857 .8:7 -2.2:
to 2 -.5> -2.>9QQ .77 -8.889 .588 -2.9: QQ .:; QQ -.78 .2:5 .>9 -.29 .78
5 to 5 2.825 8.;;; .855 2.889 5.97; QQ 2.5;> -2.79 .;> -2.>8 -2.899 -7.75; 5.9:
otes=2. %ince the e$cess return results are almost identical to the market model results,
only the latter model is reported.5. The sample sie is listed in table 7.57. The sample period is 2>>;-598. Q indicates signicance at the 2M level, QQ at the 9M level and QQQ at the 2M
level
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45
$ab*e %.3: -a!p*e size of dongrades in crisis versus non"crisis period
$hai*and
;ong>; to 3ecember 72, 2>>.5. The rating changes are by /oody0s, %K! and itch.7. All the downgrades in /alaysia are announced in the crisis period,
thus this market is not included in this section8. %ince almost all the upgrades were announced in the non-crisis period,
only downgrades are investigated.
$ab*e %.%: $he i!pact of dongrades in crisis period and non"crisis
period
8ane* /: ;ong Q
-2 .>7>9 .52 -.2::9 .982:; -2.7>;2 -.:2:8
A .5922 .7>7 .78; -2.789 .8;7 -.89QQ
2 -2.8;:2: -2.>5: -.5>2 -2.5728Q .:98; -9.;7>QQQ
5 -.8>27 .2> -.7>5 .;:9; -.:22 -2.2>:9
Cumulative average abnormal returns
-5 to -2 9.;:7 5.:;;8 5.7:;7 5.77>> -27.>8QQQ -:.;;8
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46
to 2 -2.2>29 -2.>9 .9;; -5.5:9> QQ .>95 -27.>2>QQQ
5 to 5 8.:29> .59>>> -5.:98 .858: -2.5>5>> 8.:8:2
8ane* : -outh 89: 5.25:;8 -.28;55> -.2959;
-2 -2.9;85; QQQ .>2;99> 2.98225 -.79>>9
-2.288> QQQ 2.92; .92>9857 -.9>>5>
2 -2.29982 QQQ -5.>;2 Q 2.:2>555 -.:;;
5 -.>5:;: Q 5.;55 -2.:5>9> .5:9
Cumulative average abnormal returns
-5 to -2 .>;:5: -5.29>22 .:72>8> -7.:7 to 2 -5.5>>>7 QQQ -2.8:>2 5.27;:87 -2.5:>7;
5 to 5 5.59>>;2: 9.:9;:; .59;2;; 5.:8;2;
otes= 2.The crisis period refers to Guly 5, 2>>; to 3ecember 72, 2>>.5. The rating changes are by /oody0s, %K! and itch.
7. All the downgrades in /alaysia are announced in the crisis period,
thus this market is not included in this section.8. Q indicates signicance at the 2M level, QQ at the 9M level and QQQ at the
2M level.
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$ab*e %.& Coverage fre>uency of g*oba* and *oca* rater ra sa!p*e6
$aian $hai*and -outh .8>M 8; 79.78M 5> 8;.M Total 2;; 2.M 277 2.M :78 2.M
umber of downgrades announced by global82 92.>M 7 5.M 58 85.98M
#ater
umber of downgrades announced by local 7 8.2M 25 .M 779 9;.8:M
Total >9 2.M 29 2.M 97 2.M
umber of rms covered by global rater 92 79.85M 57 8:.M ; 55.M
umber of rms covered by local rater >7 :8.9M 5; 98.M 57; ;;.5M
Total 288 2.M 9 2.M 7; 2.M
umber of rms covered by both global and
9 .A 5 .A 2 .A#ater
ote= The sample periods for comparison are= 2>>;-59 '%outh @orea), 5-
59 'Taiwan)and 55-59 'Thailand).
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$ab*e %.?: -u!!ary -tatistics of ,na* rating sa!p*e
7pgrades (ongrades
/arkets Blobal raters Docal Blobal raters Docal
Taiwan 2: 98 59 5;
Thailand 9 58 ;%outh 77 295 99 2;
otes= 2.The sample periods for comparison are= 2>>;-59 '%outh @orea),
5-59 'Taiwan) and 55-59 'Thailand).5. The global raters refer to /oody0s, %K! and itch for all markets. The
respective local raters are= @*% '%outh @orea), T#C 'Taiwan) and T#*% 'Thailand).7. *n the case of Thailand, no downgrade is announced in the clean sample
by global raters for the period 55-59.
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$ab*e %.4 / co!parison of !ar#et reaction to rating changes
announced by *oca* raters and g*oba* raters
8ane* /: -outh 29278 QQQ
-2 -.529 .9522 -2.::95 QQ -.2>::;
.8:979 .;8:: -.::292 -.7885:
2 .:>;8: .885 -2.89; QQQ -2.58289 QQQ
5 .57; -.9:7> -.7:52: .7>>77
Cumulative average abnormal returns
-5 to -2 -.972 .:7872 .8:2>> -8.888;:95 QQQ
to 2 2.2:52 .279>8 -5.28;7 QQQ -2.95955; QQQ
5 to 5 -5.5;; -2.;>88 5.:5> -8.89:2:; QQQ
8ane* : $aianAverage abnormal returns
3ays relative to ?pgrades 3owngrades
&vent Blobal ratersDocalraters
Blobal raters Docal raters
-5 -.2959; -.58>>: -.29:9 .>:72
-2 -.79>>9 .78;>22 .75887; .5957
-.9>>5> -.89 -.2>:92 -.9852>
2 -.:;; -.7958 .298;7 -.;2>>2 Q
5 .5:9 .5228 -.9:>;; .7;:2
Cumulative average abnormal returns
-5 to -2 -7.:7 -2.5>78 -5.5992; -5.2;:
to 2 -2.5:>7; -.79:> -.8588 -2.5:52 QQ
5 to 5 5.:8;2; 2.25 2.:>>72 -2.:29
8ane* C: $hai*and
Average abnormal returns
3ays relative to ?pgrades 3owngrades
&vent Blobal ratersDocalraters
Blobal raters Docal raters
-5 .59:8 -.7; .A -.8;>7>
-2 .:595 .2>;2; .A -2.7:29
.579: QQQ .95:>8> .A -2.5>59>;
2 .52:>;; .88;; .A .2>8;:
5 .8852 .5227;7 .A .;>;;>:
Cumulative average abnormal returns
-5 to -2 -.8788 -2.7>9 .A -7.:8::7
to 2 2.897; QQQ .>72:9: .A -2.2598>8
5 to 5 .87282 -2.8:2 .A 7.729998
otes= 2.The sample periods for comparison are= 2>>;-59 '%outh @orea),
5-59 'Taiwan) and 55-59 'Thailand).5. The global raters refer to /oody0s, %K! and itch for all markets. The
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respective local raters are= @*% '%outh @orea), T#C 'Taiwan) and T#*% 'Thailand).7. *n the case of Thailand, no downgrade is announced in the nal sample
by global raters for the period 55-59.8. Q indicates signicance at the 2M level, QQ at the 9M level and QQQ at
the 2M level
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$ab*e %.@ -u!!ary of do!estic rating agencies
8ane* /: range of services
Oear
/arket Agency&stablishe
d
/a"or services Additional services
-#ating services -!ro"ect nancing
%outh @*% 2>9 -Advisory services rating
@orea -Training
Taiwan T#C 2>>; -#ating services o additional services
-#ating services -Buarantor rating
-Bovernance rating services -Bovernment rating
Thailand T#*% 2>>7-!erformance evaluationservices
8ane* : shareho*ding structures
Current share holding
/arket Agency !ublic listedDocal
rmsPbanksBovt *ntl C#A Fther
%outh @orea @*% 9M M M 9M M
Taiwan T#C .A .A .A 9M .A
Thailand T#*% M ;:M 2>M M 9M
otes= 2. 3ata source= U3evelopment of #egional %tandards for Asian Credit
#atingAgencies V !rogress K Changes0 prepared for A3( '59)5. .A denotes data is not available
7. %K! initially took a 9M ownership stake in T#C and announced that it
had signed an agreement to raise its stake in T#C from 9M to 92M on 5;
%eptember 59.