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Brazilian Stock Exchange

FIN: 3560-02: Financial Markets and Instruments

Rishabh Desai

Rishab Mehta

Rishikesh Dhoot

Rushabh Mehta

“The authors of this paper hereby give permission to Professor Michael Goldstein to distribute this paper by hard copy, to put it on reserve at Horn Library at Babson College, or to post a PDF version

of this paper on the internet”.

“I pledge my honor that I have neither received nor provided any unauthorized assistance during the completion of this work.”

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Executive Summary:

The Brazilian Stock exchange is currently one of the fastest growing exchanges in the world. Though

most people are aware of this, not too many people know about their merger in 2008 or much about

their overall business model and services offered. Through this paper we delve further into the above

mentioned topics. In addition, over the past decade, Brazil has had three outlook changes and six

sovereign rating changes that we have used to test our hypothesis. Our hypothesis posits that a change

in the sovereign credit ratings of a country has an impact on the BM&FBOVESPA index. We expected a

positive change in outlook to create a positive effect on the market, and a negative change in outlook

to bring the market down. Movements before the announcement of a transaction take place due to

leaked information or just anticipation of the rating change. In the medium term our hypothesis would

suggest that the BM&F Bovespa would move in correspondence with the credit rating revision of its

sovereign foreign currency debt.

For our short term analysis, two out of the three results for the credit outlook change were

insignificant, while the third had significant results which supported our hypothesis. However, we did

not have enough significant results to confirm the hypothesis. For the credit rating changes, three of

the six credit rating changes had significant results that supported our hypothesis. One out of the six

results was significant yet did not support our hypothesis, while the remaining two were insignificant

results. Thus, our hypothesis could not be proved correct due to the lack of significant results obtained

from the various regressions that we ran.

For our long term analysis, we tracked the percentage growth of the BM&FBOVESPA, 6 months prior to

the event and 6 months after the event. These events are the same nine selected events of credit

ratings change/outlook revisions for the last decade that we used for short term analysis. Based on

statistical evidence, our hypotheses did not stand considering only 2 out of 9 events supported our

hypothesis. However it can be said that bullish and bearish trends in the stock market can be an

indicator (not a prediction) of similar future credit rating revisions. The results though, were not

sufficient enough to prove our hypothesis.

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Brazilian Stock Exchange: An Overview

The Brazilian Stock Exchange calculates and discloses 21 indexes the flagship of which would be the

IBOVESPA which includes about 68 of the 470 companies listed on the exchange. This represents 70%1

of the exchanges. They have a total market capitalization of US$1.22 trillion and 80% of the traded

volume is pegged at R$7.4 billion, ranking it as the 8th largest exchange in the world. The BM&F

Bovespa was formed on May 8, 2008 and was the progeny of the merger of the São Paulo Stock

Exchange (Bovespa) and the Brazilian Mercantile Futures Exchange (BM&F). The merger which was

expected to bring down combined costs by 25%, was announced just months after either company

debuted their shares through IPO’s.2

The BM&F was a marketplace for the trading of derivatives and also a risk management facility through

its derivatives, foreign exchange and asset clearing houses. The exchange had an average daily value of

1.116 million contracts and an average daily financial volume of US$4.29 billion3. With these high

volumes, the company was secured as the fourth largest commodities and futures exchange. Trading

volume on the exchange surged 61.6% in the 9 months before the IPO and attracted an increase in the

share price of the IPO from R$14.50-16.50 to 18-20 Reais4 bringing in R$ 5.98 billion.

The IPO of Bovespa Holdings too saw similar performance with the pre IPO price band range increasing

from R$15.5-18.5 to R$20-23 finally earning 6.6 billion Reais; the price of the shares went up 50% on

1 "What Is Bovespa Index." Nasdaq.com. N.p., n.d. Web. <http://community.nasdaq.com/News/2012-08/what-is-the-

bovespa-index.aspx?storyid=167129#.ULvS7eQ8CSo>. 2 "Brazil's BMF Bovespa Announce Merger Deal." Marketwatch.com. N.p., n.d. Web.

<http://www.marketwatch.com/story/brazils-bmf-bovespa-announce-merger-deal>. 3 CME Group. CME Group and the Brazilian Mercantile & Futures Exchange Agree to Cross-Equity Stakes and Exclusive Order

Routing Deal. N.p., n.d. Web. <http://cmegroup.mediaroom.com/index.php?s=43&item=642> 4 "Brazil's BM&F Exchange IPO Priced at Top of Range." Reuters, 28 Nov. 2007. Web.

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the first day of trading5. Bovespa is a subsidiary of the Chicago Mercantile Exchange (CME) which owns

and operates derivatives and futures exchanges in New York and Chicago. The company also owns the

Dow Jones stock and financial indexes. It operated one active equity exchange and one equity

derivative exchange and enjoys a monopoly in their space6. The IPO’s of both companies represented

the two largest IPO’s in Brazils history7.

The world’s fastest growing exchange in terms of trading volume (Bovespa) and the fourth largest

futures exchange in the world (BM&F) merged at a time when both the companies saw their share

prices falling and the announcement of the merger received a great response from investors. BM&F

shares saw a rise of 17.25% to R$18.49, Bovespa shares climbed 11.4% to R$26.808.

New shares were issued for the new exchange and were split by the shareholders of BM&F and

Bovespa on a 50/50 basis. In addition to the same, shareholders of Bovespa were given R$1.24 billion.

Each company also got an equal number of seats on the board and was given the discretion of

choosing their representatives. In order to ensure a smooth transition, both companies also set up a

Transition Committee, which included the chairman and chief executive officer of the two companies.9

Thanks to the merger in 2008, BM&FBOVESPA has operations in two major market segments,

derivatives (BM&F) and equities (BOVESPA). The company develops, implements and provides systems

for the trading of stocks, corporate and government bonds, financial derivatives, agricultural

commodities and spot foreign exchange, among others.

5 Rumsey, John. "Bovespa Holding: A Super-charged IPO." Weblog post. N.p., n.d. Web.

<http://johnrumsey.co.uk/article.php?cd=79>. 6 "Brazil’s Bovespa Monopoly on the Line as Government Considers Boosting Competition." Merco Press, n.d. Web.

7 "Brazil's BM&F Exchange IPO May Raise 4.9 Bln Reais." Reuters, n.d. Web.

8 "BM&F Joins Merger Mania." Futures and Options World, n.d. Web.

9 "BM&F and BOVESPA Holding to Integrate Their Activities." General Atlantic, n.d. Web.

<http://www.generalatlantic.com/en/news/article/150>.

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In the BOVESPA segment, the company offers several mechanisms for trading in both exchange

markets and over-the-counter (OTC) markets. They offer a wide range of equities and fixed-income

securities including: Brazilian depositary receipts (BDRs), stocks, stock receipts, and investment funds.

In the BM&F segment, the company manages electronic trading in derivatives contracts, spot foreign

exchange, and public debt securities and assets. They also handle registration, clearing and settlement,

which is integrated with a top quality risk management system designed to assure optimal

performance.10

In addition to providing the market with these products and services, BM&FBOVESPA acts as a central

depository for assets and securities, publishes price quotations and manages securities lending

transactions, produces.11

Besides being the only securities, commodities and futures exchange in operation in Brazil,

BM&FBOVESPA also offers various other services to their clientele. They actively promote capital

markets through financial education programs. They aim to raise awareness and spread the knowledge

and understanding of the importance of saving and long-term investment, both for the sake of national

development and as well as personal financial stability and security.12

BM&FBOVESPA develops technological solutions and maintains high-performance systems to assure

security, speed, innovation and cost-effectiveness for its customers.13 The BM&FBOVESPA trading

platforms use state-of-the-art programming language and technology as well as advanced connectivity

resources, which eases price formation and increases transparency during transactions.14The success

10

BM&FBOVESPA Annual Report 2011, pg 9 - - http://www.bmfbovespa.com.br/en-

us/bmfbovespa/download/BMFVOVESPA-Relatorio-Anual-2011.pdf 11

BM&FBOVESPA Annual Report 2011, pg 9 12



http://www.bmfbovespa.com.br/en-us/intros/intro-trading-solutions.aspx?idioma=en-us

http://www.bmfbovespa.com.br/en-us/bmfbovespa/download/BMFVOVESPA-Relatorio-Anual-2011.pdf

http://www.bmfbovespa.com.br/en-us/bmfbovespa/download/BMFVOVESPA-Relatorio-Anual-2011.pdf

http://www.bmfbovespa.com.br/en-us/intros/intro-trading-solutions.aspx?idioma=en-us

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of the Exchange’s activities depends largely on two factors; firstly, continuous improvement,

development and integration of its trading and settlement platforms. Secondly its capacity to develop

and license the cutting-edge technology required for the optimal execution of each function, making

this one of their most vital divisions for long term competency and sustainability.15

A milestone in this regard was the 2011 launch of the BM&FBOVESPA PUMA Trading System, a multi-

asset electronic platform developed jointly with CME Group to enhance processing capacity, reduce

latency to very low levels and deliver new functionality. The first phase of implementation of the

derivatives module was completed in 2011. Implementation of the equities module is scheduled for

2012.16

The information signal is a BM&FBOVESPA service that broadcasts real-time Exchange market

information including data on trading volumes, share prices, index information. They also provide

economy news and stock, futures and derivatives market news to anywhere in the world. People who

hire the signal can distribute it amongst individuals and institutional investors, as well as to brokerage

houses, who then in turn supply data such as share quotations to their clients.17

BM&FBOVESPA’s post-trade infrastructure can be divided functionally into three core units: a Central

Securities Depository (CSD), Securities Settlement Systems (SSS) and Central Counterparties (CCP).18

BM&FBOVESPA consider these units to be the “building blocks” upon which they will further develop

its post-trade infrastructure.

15



http://www.bmfbovespa.com.br/en-us/services/market-data/information-signal.aspx?idioma=en-us 18

BM&FBOVESPA Post Trade Infrastructure pg 10 -

http://www.bmf.com.br/bmfbovespa/pages/boletim2/informes/2010/marco/White_Paper.pdf

http://www.bmf.com.br/bmfbovespa/pages/boletim2/informes/2010/marco/White_Paper.pdf

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BM&FBOVESPA have also put in place sophisticated risk management systems and processes that have

mechanisms to effectively safeguard each of the CCPs against the risks associated with the default of a

participant, managing market risk, liquidity risk, credit risk, legal risk and operational risk.19

BM&FBOVESPA’s growth strategy for 2012 prioritizes projects that increase the company’s competitive

capacity and diversify its revenue streams. The Exchange is thus clearly focused on market

development and has widened its prospecting for and motivation of new issuers. It has also stepped up

BOVESPA Mais listing segment reporting, as well as the BM&FBOVESPA Institute of Education’s

Companies and Entrepreneurs training and education programs - which are not only an investment in

the financial education of individuals, but in the guidance of opinion formers and distribution

channels.20

Credit Rating Agencies:

Credit Rating Agencies primarily release reports on the credit worthiness of debts – private, public or

national debts. These credit worthiness reports outline the likelihood of default by the debtor which is

of interest to all other stakeholders involved in business operations with them. Sovereign Debt Ratings

are credit worthiness reports of national governments around the world; formed upon the request of

the government; that outline the likelihood of the government to default on its borrowings. There are

traditionally two types of sovereign debt ratings – foreign currency ratings which are based on debt in

foreign currency, and local currency which are based on debt in the national currency. Fitch, Moody’s

19

BM&FBOVESPA Post Trade Infrastructure pg 11 20

BM&FBOVESPA Annual Report 2011, pg 15

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and Standard and Poor’s (S&P) are the three largest credit rating agencies with approximately 94%

market share. While S&P and Moody’s have about 40% market shares each and Fitch about 14%, the

remaining is spread out between numerous other agencies. 21 A country’s foreign currency sovereign

debt rating is a very important factor for investors looking to invest in government bonds. Any

drop/rise in a rating reflects the corresponding risks of default associated with that government bond

for the investor.22 These can severely affect the abilities of these countries to raise money via foreign

capital markets that pay heavy emphasis on these credit ratings. 23

All three agencies – Fitch, S&P and Moody’s have their own ratings chart that reflect to what extent is a

particular debt at risk of default. While Fitch and S&P have uniformity in their ratings, Moody’s differs

slightly – however all three ratings can be equated to present a uniform chart for simplicity purposes

(Exhibit 4). The highest rating of AAA (Aaa for Moody’s) represents prime investment opportunity with

minimal chances of default. Any ratings below BBB- (Moody’s – Baa3) represent a debt that is

speculative/non-investment grade with significant chances of default. Historically, ratings agencies

have been accurate in predicting potential sovereign defaults with only 1% of investment grade

sovereigns having defaulted since 1975, compared to 30% of sovereigns in the speculative grade.24 This

accuracy has cemented investor belief over the years in the ability of these ratings to accurately reflect

the financial health of these sovereigns which in turn effects foreign investment in these countries.

21

Singh, Atul. "Credit Rating Agencies." N.p., 12 May 2012. Web. <http://www.fairobserver.com/360theme/credit-rating-agencies> 22

Armstrong, Paul. "Explainer: The Power of Credit Rating Agencies." CNN. N.p., n.d. Web. <http://edition.cnn.com/2012/06/22/business/credit-ratings-agencies-explained/index.html>. 23

How Fitch, Moody's and S&P's Rate Each Country. Guardian UK, n.d. Web. <http://www.guardian.co.uk/news/datablog/2010/apr/30/credit-ratings-country-fitch-moodys-standard> 24

"How We Rate Sovereigns." Standard & Poor's, n.d. Web. <http://img.en25.com/Web/StandardandPoors/How_We_Rate_Sovereigns.pdf>

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Two instances of information release that are important in our analysis of the Brazilian Stock

Exchange performance in relation to its credit ratings are, revisions in outlooks and revision in ratings.

An outlook (positive, stable and negative) usually reflects a trend in an economy – which if continued

will lead to a corresponding change in the country’s credit rating. Investors usually interpret a change

in outlook as a prelude to a potential change in credit rating – however it is accepted that a revised

outlook is not a symbol of an imminent rating change. The second instance of information release that

we have focused on is the rating change announcement itself.25 We have performed regression models

to analyze the stock market performance 5 days before and 5 days after the point of information

release to spot any potential trends in the BM&FBovespa due to these information releases by the

credit rating agencies for the last decade (2001-2011). In addition, we have only taken into account the

top 3 credit rating agencies in light of their dominant market share (94%). Cumulatively there have

been 40 instances (Exhibit 5) over the last decade where either one of the three agencies has revised a

sovereign debt foreign currency outlook/rating for Brazil. 26 An issue that is persistent with our analysis

would be instances when an agency’s revision of outlook/rating has followed another agency’s similar

action. Under such circumstances the release of information that was chronologically close to a similar

earlier announcement would have already been accounted by the stock exchange at the first instance

of information release. Under such circumstances, the second event of information release would have

little significance for investors who have already been alerted of a potential trend in the economic

health of Brazil. To mitigate this problem, we employed the “first-mover” principle wherein we have

only taken events of information release by an agency that moved first in terms of its public

25

Micu, Marian, Eli Remolona, and Philip Wooldridge. The Price Impact of Rating Announcements: Which Announcements Matter? Working paper no. 207. Bank for International Settlements, June 2006. Web. 26

We chose to focus on foreign currency over local currency due to government’s restricted abilities to pay foreign debt by manipulation such as issuance of more notes as in the case of local currency

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announcements. Traditionally, credit rating agencies have been assessed on how likely they are to be

the “first-mover” in terms of ratings especially in cases where their decision has been followed by

other credit rating agencies.27 Our interpretation of the “first-mover” was based on two principles –

firstly we discounted any subsequent announcements made in the following six months of a similar

announcement. Secondly, we tried to focus on announcements that we thought were significant in

terms of its potential to change investor sentiment.28 While we acknowledge that this process of

selecting events of information release on revisions of outlooks/ratings is subjective to an extent – we

have tried our best to select events that would be most likely to have a pronounced effect on investor

sentiment about the Brazilian economy. This process enabled us to reduce the forty events of

information release over the last decade to, nine events of potentially trend-setting announcements.

Short-Term Trends due to Credit Report Events (Ratings / Revisions):

We decided to test the hypothesis, that outlook changes and credit rating changes of Brazil

create a fluctuation in the BM&F BOVESPA. Based on the first mover principle we decided to take three

different occasions when the outlook was changed and six different occasions when the credit rating

was changed.

Exhibits 1A, 1B and 1C show the changes in the BM&F BOVESPA index five days before and five

days after the outlook change. A p-value of less than 0.05 was taken as a benchmark for our results to

27

"Credit-rating Agencies - Judges with Tenure." Economist.com. N.p., 13 Aug. 2011. Web. <http://www.economist.com/node/21525936> 28

The core principle behind the “first-mover” process was borrowed from another paper - Nishiotisx, George, and Panayiotis Papakyriacou. Sovereign Debt Rating Changes and the Stock Market. Rep. N.p., May 2012. Web

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be significant, as it would provide us with a 95% certainty that our results are significant. Then we

looked at the coefficients, to check whether the trend in the market supported our hypothesis. We

expected a positive change in outlook to create a positive effect on the market, and a negative change

in outlook to bring the market down. Exhibit 1A shows the effect of Fitch changing the outlook from

Stable to Negative in 2001. While we expected the stock market to fall, the p-value was 0.466, way

higher than the benchmark of 0.05. Thus our results were insignificant. Exhibit 1B shows the effect of

Fitch changing the outlook from Stable to Positive in 2003. We expect that this would cause the stock

market to rise. The p-value was extremely low 0.000, thus proving that our results were significant. The

regression equation: Index = 13108 +74.6C1 showed that as the number of days increased, so did the

stock market. This supported our hypothesis that a positive outlook change brings the stock market up.

The R-square value was 80%, also proving our results were statistically significant. However, Exhibit 1C

also had a very high p-value of 0.182. This means that the results obtained due to S&P changing Brazil’s

outlook from Stable to Positive were statistically insignificant. Thus, out of the three regressions run

two were statistically insignificant, while Exhibit 1B had significant results which supported our

hypothesis. These results were not strong enough to prove that an outlook change creates high

fluctuations in the market, and neither that a positive outlook change creates a positive impact on the

market while a negative outlook change creates a negative one.

Exhibits 2A to 2F show the changes in the BM&F BOVESPA index five days before and five days

after a rating change. Exhibit 2A shows the effect of Moody’s lowering rating from B1 to B2 in 2002.

We expect the stock market to go down due to this negative rating change. While the p-value of 0.003

was below our benchmark of 0.05, the regression equation: Index = 9069 + 86.5C1 showed a positive

correlation between the index and the number of days. This meant that despite the negative rating

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change, the coefficient for the x-value was positive; thus not supporting our theory. Exhibit 2B shows

the effect of S&P raising Brazil’s rating from B+ to BB- in 2004. Our hypothesis is that this positive

rating change will have a considerable increase in the market index. While the p-value was below 0.05,

the regression equation showed a positive correlation between the index and the number of days.

These statistically significant results supported our theory. Exhibits 2C showed the effect of S&P raising

Brazils credit rating to BB in 2006. The p-value was very high, 0.347, thus proving insignificant results.

While we expected the stock market to increase, it actually fell over this 11-day period, thus not

supporting our theory either. Exhibit 2D showed the effect of Fitch raising Brazils rating to BB+ on the

BOVESPA. We expected a positive increase in the stock market, and while the p value was below 0.05,

the number of days did have a positive correlation with the index. The equation was: Index = 49815 +

122C1, and the index increased from 49,471 to 51,737 through these 11 days. Thus, these results did

support our hypothesis. Exhibit 2E shows the effect of S&P increasing the rating from BB+ to BBB- in

2008 on the stock market. The p-value is 0.001, well below 0.05. The r-square is relatively high as well,

showing that the results are quite significant. The regression equation is: Index = 63440 + 647C1, which

proves the positive correlation between the number of days and the index. The index increased from

64,947 to 69,722, giving significant results to support our theory. Exhibit 2F showed the Effect of Fitch

raising the credit rating to BBB on the stock market. While the regression equation did show a positive

correlation between the increasing number of days and the stock market index, the p-value of 0.101

was well above the benchmark of 0.05. Thus, these results were deemed insignificant. Exhibit 3 is a

table showing which exhibits had insignificant results and which results supported our theory and

which did not.

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Two out of the three results for the credit outlook change were insignificant, while the third

had significant results which supported our hypothesis. However, we did not have enough significant

results to confirm the hypothesis. For the credit rating changes, 50% of the credit rating changes had

significant results that supported our hypothesis. One out of the six results was significant yet did not

support our hypothesis, while the remaining two were insignificant results. Thus, neither of our

hypotheses were able to be proved correct due to the lack of significant results obtained from the

various regressions that we ran.

Medium-Term Trends due to Credit Report Events (Ratings /Revisions):

Stock Markets are directly influenced by the individual companies that form its index. A bullish forecast

for these components will lead the stock market such as BM&F Bovespa to increase while a bearish

forecast will cause such an index to move on a downward trend. One would expect that a sovereign

rating cut would make borrowing for the government more expensive due to higher interest rates. This

would consequently affect its budgeting where it would have to equate the higher borrowing costs by

increasing corporate taxes – something that would decrease profitability of the components of a stock

exchange. This in turn would cause a long term negative factor in the stock exchange. In addition – a

credit rating is often perceived as an indicator of the financial health of the economy as well – and one

would expect any shift in the credit rating to have a corresponding shift in the stock market – which is

also an indicator of the economy.

To investigate this relationship between stock markets and sovereign credit rating revisions – we have

tracked the percentage growth of the BM&F Bovespa 6 months prior to the event and 6 months after

the event. These events are the same 9 selected events of credit ratings change/outlook revisions

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based on our first-mover principle, that we used for the short term effects of credit ratings in the last

decade.

Upon analyzing the 9 events, we realized that markets react strongly in the corresponding trend of the

credit rating changes (by either reversing an earlier downward/upward trend or strengthening an

existing upward/downward trend) in only 2 cases. For instance, for Fitch’s outlook revision on June 3rd

2003 from stable to positive, the BM&F Bovespa rises 54% after the announcement compared to 15%

in the 6 months prior to the announcement (Exhibit 1B). Similarly the upgrade in credit rating by S&P

on September 17 2004 is followed by 22% rise in the BM&F Bovespa as compared to a meager 5% rise

in the 6 months prior to the announcement (Exhibit 2B). It must be stressed that various other external

factors play a vital role in the downward/upward trend of the BM&F Bovespa and 2 out of 9 events

supporting the trend is not enough evidence to prove a link.

On the contrary, the markets react in a contradictory, rather than corresponding manner to credit

rating changes in 3 out of the 9 events after discounting the 2008 event considering the global financial

meltdown late in 2008. The BM&F Bovespa rose 11% in the 6 months after Moody’s lowered its ratings

on August 20, 2002 (Exhibit 2A). This was despite the downward trend of the BM&F Bovespa reflected

by the 30% drop in the 6 months leading up to the rating cut. The BM&F Bovespa dropped 6% in the

medium term after S&P raised its rating on February 28, 2006 despite a 43% rise in the 6 months prior

to the event (Exhibit 2C). The third event also highlights a 27% drop in the medium term despite an

increase in credit rating by Fitch on April 4 2011 (Exhibit 2F). However one must take into account the

Eurozone debt problems and its spillover effects on the world economy to see a potential cause in the

BM&F Bovespa’s drop. Hence it cannot be statistically proven that the BM&F Bovespa in the medium

term acts correspondingly after a significant credit rating revision/outlook revision. It can be safe to

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suggest that a credit rating revision/outlook revision is not a strong predictor of the BM&F Bovespa in

the medium term, which is more likely to be affected by a greater extent by other macroeconomic

factors.

Interestingly, the BM&F Bovespa index accurately “predicts” a credit rating (considering both are

indicators of financial health of the economy) on 4 events where the stock market performance in the

6 months prior to the selected event is in line with the credit rating revision/outlook revision. In the

first instance, the BM&F Bovespa drops 18% before Fitch changed its outlook from stable to negative

on July 17, 2001(Exhibit 1A). The BM&F Bovespa also dropped 30% in the 6 months leading up to the

August 20 credit rating cut from B1 to B2 the following year (Exhibit 2A). In the 6 months leading up to

the increase in credit rating on February 28, 2006 the BM&F Bovespa rose 43% (exhibit 2C) and

another 25% in the 6 months before Fitch’s increase in Brazils credit rating from BB to BB+ on May 9th

2007 (Exhibit 2D). While it would be incorrect to state that stock market performance can accurately

predict an imminent credit ratings revision – it is helpful to understand that both are partly indicators

of the financial health of the same economy. It can be categorically said that from the statistical

evidence we have – there isn’t a strong relationship between the performances of the stock market

based on credit ratings changes – the BM&F Bovespa is more likely to be affected by other

macroeconomic factors such as global uncertainty. However, bullish and bearish trends in the stock

market can be an indicator (and not a prediction) of similar future credit rating revisions. However

even this relationship is not strong enough based on statistical evidence considering only 4 out of 9

events have suggested the same.

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Hence while we recognize that credit rating revisions/outlook revisions by the big three credit rating

agencies are significant events that may lead to short term fluctuations in the BM&F Bovespa – in the

medium term (6 month period) its effects are not apparent based on the stock market trends.

17

Works Cited

"What Is Bovespa Index." Nasdaq.com. N.p., n.d. Web.

<http://community.nasdaq.com/News/2012-08/what-is-the-bovespa-

index.aspx?storyid=167129#.ULvS7eQ8CSo>.

"Brazil's BMF Bovespa Announce Merger Deal." Marketwatch.com. N.p., n.d. Web.

<http://www.marketwatch.com/story/brazils-bmf-bovespa-announce-merger-deal>.

CME Group. CME Group and the Brazilian Mercantile & Futures Exchange Agree to Cross-Equity

Stakes and Exclusive Order Routing Deal. N.p., n.d. Web.

<http://cmegroup.mediaroom.com/index.php?s=43&item=642>.

"Brazil's BM&F Exchange IPO Priced at Top of Range." Reuters, 28 Nov. 2007. Web.

Rumsey, John. "Bovespa Holding: A Super-charged IPO." Weblog post. N.p., n.d. Web.

<http://johnrumsey.co.uk/article.php?cd=79>.

"Brazil’s Bovespa Monopoly on the Line as Government Considers Boosting Competition."

Merco Press, n.d. Web.

"Brazil's BM&F Exchange IPO May Raise 4.9 Bln Reais." Reuters, n.d. Web.

"BM&F Joins Merger Mania." Futures and Options World, n.d. Web.

"BM&F and BOVESPA Holding to Integrate Their Activities." General Atlantic, n.d. Web.

<http://www.generalatlantic.com/en/news/article/150>.

Singh, Atul. "Credit Rating Agencies." N.p., 12 May 2012. Web.

<http://www.fairobserver.com/360theme/credit-rating-agencies>.

Armstrong, Paul. "Explainer: The Power of Credit Rating Agencies." CNN. N.p., n.d. Web.

<http://edition.cnn.com/2012/06/22/business/credit-ratings-agencies-explained/index.html>.

How Fitch, Moody's and S&P's Rate Each Country. Guardian UK, n.d. Web.

<http://www.guardian.co.uk/news/datablog/2010/apr/30/credit-ratings-country-fitch-moodys-

standard>.

"How We Rate Sovereigns." Standard & Poor's, n.d. Web.

<http://img.en25.com/Web/StandardandPoors/How_We_Rate_Sovereigns.pdf>.

18

Micu, Marian, Eli Remolona, and Philip Wooldridge. The Price Impact of Rating Announcements:

Which Announcements Matter? Working paper no. 207. Bank for International Settlements,

June 2006. Web.

Nishiotisx, George, and Panayiotis Papakyriacou. Sovereign Debt Rating Changes and the Stock

Market. Rep. N.p., May 2012. Web.

"Credit-rating Agencies - Judges with Tenure." Economist.com. N.p., 13 Aug. 2011. Web.

<http://www.economist.com/node/21525936>.

19

Exhibit 1A – Effect of Fitch Changing Outlook from Stable to Negative on the 17th of July, 2001 on the BOVESPA

The regression equation is C3 = 13800 + 13.1 C1 Predictor Coef SE Coef T P Constant 13800.1 116.8 118.14 0.000 C1 13.12 17.22 0.76 0.466 S = 180.640 R-Sq = 6.1% R-Sq(adj) = 0.0% Analysis of Variance Source DF SS MS F P Regression 1 18942 18942 0.58 0.466 Residual Error 9 293676 32631 Total 10 312618

07/25/200107/22/200107/19/200107/16/200107/13/200107/10/2001

14200

14100

14000

13900

13800

13700

13600

13500

Date

Ind

ex

Market Change from 10th July 2001 to 25th July 2001

20

BOVESPA Index corresponding to date

Date Index Difference Regression Results

1 07/10/2001 13569.79 -243.38455 13813.17455

2 07/11/2001 13811.84 -14.456909 13826.29691

3 07/12/2001 13912.93 73.5107273 13839.41927

4 07/13/2001 14078.46 225.918364 13852.54164

5 07/16/2001 13811.39 -54.274 13865.664

6 07/17/2001 14168.65 289.863636 13878.78636

7 07/18/2001 13790.88 -101.02873 13891.90873

8 07/19/2001 13761.51 -143.52109 13905.03109

9 07/23/2001 14067.72 149.566545 13918.15345

10 07/24/2001 13737.59 -193.68582 13931.27582

11 07/25/2001 13955.89 11.4918182 13944.39818

IBOVESPA Index Change:

6 Months Prior To Event to Date of Announcement

6 Months After Announcement

-18% -6%

21

Exhibit 1B – Effect of Fitch Changing Outlook from Stable to Positive on the 3rd of June, 2003 on the BOVESPA

The regression equation is Index = 13108 + 74.6 C1 Predictor Coef SE Coef T P Constant 13107.7 84.1 155.87 0.000 C1 74.57 12.40 6.01 0.000 S = 130.040 R-Sq = 80.1% R-Sq(adj) = 77.9% Analysis of Variance Source DF SS MS F P Regression 1 611646 611646 36.17 0.000 Residual Error 9 152193 16910 Total 10 763839

06/10/200306/7/200306/4/200306/1/200305/28/2003

14000

13900

13800

13700

13600

13500

13400

13300

13200

Date

Ind

ex

Market Change from 27th May 2003 to 10th June 2003

22



1 05/27/2003 13246.2 63.913636 13182.28636

2 05/28/2003 13294.3 37.445455 13256.85455

3 05/29/2003 13405.2 73.777273 13331.42273

4 05/30/2003 13421.6 15.609091 13405.99091

5 06/2/2003 13228.7 -251.85909 13480.55909

6 06/3/2003 13350.1 -205.02727 13555.12727

7 06/4/2003 13718 88.304545 13629.69545

8 06/5/2003 13779.8 75.536364 13704.26364

9 06/6/2003 13923.1 144.26818 13778.83182

10 06/9/2003 13845.7 -7.7 13853.4

11 06/10/2003 13893.7 -34.268182 13927.96818




15.09% 53.85%

23

Exhibit 1C – Effect of S&P Changing Outlook from Stable to Positive on the 22nd of November, 2006 on the BOVESPA

The regression equation is Index = 41009 + 64.0 C1 Predictor Coef SE Coef T P Constant 41009.0 300.4 136.53 0.000 C1 64.05 44.29 1.45 0.182 S = 464.474 R-Sq = 18.9% R-Sq(adj) = 9.8% Analysis of Variance Source DF SS MS F P Regression 1 451225 451225 2.09 0.182 Residual Error 9 1941624 215736 Total 10 2392849

11/28/200611/25/200611/22/200611/19/200611/16/200611/13/2006

42250

42000

41750

41500

41250

41000

40750

40500

Date

Ind

ex

Market Change from 13th November 2006 to 29th November 2006

24



1 11/13/2006 40605.79 -467.2877 41073.07773

2 11/14/2006 41290.7 153.57509 41137.12491

3 11/16/2006 41161.87 -39.30209 41201.17209

4 11/17/2006 41029.43 -235.7893 41265.21927

5 11/21/2006 41570.4 241.13355 41329.26645

6 11/22/2006 41912.92 519.60636 41393.31364

7 11/23/2006 42069.83 612.46918 41457.36082

8 11/24/2006 41757.72 236.312 41521.408

9 11/27/2006 40914.63 -670.8252 41585.45518

10 11/28/2006 41043.15 -606.3524 41649.50236

11 11/29/2006 41970.01 256.46045 41713.54955


6 Months Prior To Event to Date of

Announcement 6 Months After Announcement

15.00% 25.00%

25

Exhibit 2A – Effect of Moodys Lowering Rating from B1 to B2 on the 20th of

August, 2002 on the BOVESPA The regression equation is Index = 9069 + 86.5 C1 Predictor Coef SE Coef T P Constant 9068.7 149.2 60.80 0.000 C1 86.45 21.99 3.93 0.003 S = 230.663 R-Sq = 63.2% R-Sq(adj) = 59.1% Analysis of Variance Source DF SS MS F P Regression 1 822148 822148 15.45 0.003 Residual Error 9 478849 53205 Total 10 1300997

08/28/200208/25/200208/22/200208/19/200208/16/200208/13/2002

10400

10200

10000

9800

9600

9400

9200

Date

Ind

ex

Market Change from 13th August 2002 to 27th August 2002

26



1 08/13/2002 9444.1 288.90909 9155.190909

2 08/14/2002 9343 101.35636 9241.643636

3 08/15/2002 9183.2 -144.8964 9328.096364

4 08/16/2002 9526.2 111.65091 9414.549091

5 08/19/2002 9416.7 -84.30182 9501.001818

6 08/20/2002 9263 -324.4545 9587.454545

7 08/21/2002 9437.6 -236.3073 9673.907273

8 08/22/2002 9702.5 -57.86 9760.36

9 08/23/2002 9676.3 -170.5127 9846.812727

10 08/26/2002 10097.5 164.23455 9933.265455

11 08/27/2002 10371.9 352.18182 10019.71818




-30.36% 10.67%

27

Exhibit 2B – Effect of S&P Raising Rating from B+ to BB- on the 17th of September, 2004 on the BOVESPA

The regression equation is Index = 21970 + 115 C1 Predictor Coef SE Coef T P Constant 21969.6 187.7 117.02 0.000 C1 114.57 27.68 4.14 0.003 S = 290.310 R-Sq = 65.6% R-Sq(adj) = 61.7% Analysis of Variance Source DF SS MS F P Regression 1 1443868 1443868 17.13 0.003 Residual Error 9 758521 84280 Total 10 2202390

09/25/200409/22/200409/19/200409/16/200409/13/200409/10/2004

23200

23000

22800

22600

22400

22200

22000

21800

Date

Ind

ex

Market Change from 10th September 2004 to 24th September 2004

28



1 09/10/2004 21968 -116.2091 22084.20909

2 09/13/2004 21809.2 -389.5782 22198.77818

3 09/14/2004 22309.4 -3.947273 22313.34727

4 09/15/2004 22343.5 -84.41636 22427.91636

5 09/16/2004 22875.7 333.21455 22542.48545

6 09/17/2004 23073.5 416.44545 22657.05455

7 09/20/2004 23078.2 306.57636 22771.62364

8 09/21/2004 23105.7 219.50727 22886.19273

9 09/22/2004 22748.9 -251.8618 23000.76182

10 09/23/2004 22943.5 -171.8309 23115.33091

11 09/24/2004 22972 -257.9 23229.9




5.00% 22.00%

29

Exhibit 2C – Effect of S&P Raising Rating from BB- to BB on the 28th of February, 2006 on the BOVESPA

The regression equation is Index = 38782 - 61.1 C1 Predictor Coef SE Coef T P Constant 38782.4 417.9 92.81 0.000 C1 -61.07 61.61 -0.99 0.347 S = 646.160 R-Sq = 9.8% R-Sq(adj) = 0.0% Analysis of Variance Source DF SS MS F P Regression 1 410205 410205 0.98 0.347 Residual Error 9 3757707 417523 Total 10 4167912

03/7/200603/4/200603/1/200602/25/200602/22/2006

39500

39000

38500

38000

37500

37000

Date

Ind

ex

Market Change from 20th February 2006 to 8th March 2006

30



1 02/20/2006 38539.18 -182.20045 38721.38045

2 02/21/2006 38165.97 -494.34382 38660.31382

3 02/22/2006 38246.4 -352.84718 38599.24718

4 02/23/2006 38405.48 -132.70055 38538.18055

5 02/24/2006 38610.39 133.27609 38477.11391

6 03/1/2006 39177.87 761.82273 38416.04727

7 03/2/2006 39125.84 770.85936 38354.98064

8 03/3/2006 39239.75 945.836 38293.914

9 03/6/2006 38353.98 121.13264 38232.84736

10 03/7/2006 37422.58 -749.20073 38171.78073

11 03/8/2006 37289.08 -821.63409 38110.71409




42.50% -5.79%

31

Exhibit 2D – Effect of Fitch Raising Rating from BB to BB+ on the 9th of May,

2007 on the BOVESPA The regression equation is Index = 49815 + 122 C1 Predictor Coef SE Coef T P Constant 49815.5 302.7 164.57 0.000 C1 122.43 44.63 2.74 0.023 S = 468.082 R-Sq = 45.5% R-Sq(adj) = 39.5% Analysis of Variance Source DF SS MS F P Regression 1 1648792 1648792 7.53 0.023 Residual Error 9 1971910 219101 Total 10 3620702

05/16/200705/13/200705/10/200705/07/200705/04/2007

52000

51500

51000

50500

50000

49500

Date

Ind

ex

Market Change from 2nd May 2007 to 16th May 2007

32



1 05/02/2007 49471.54 -466.37455 49937.91455

2 05/03/2007 50218.22 157.875818 50060.34418

3 05/04/2007 50597.79 415.016182 50182.77382

4 05/07/2007 50281.73 -23.473455 50305.20345

5 05/08/2007 50277.69 -149.94309 50427.63309

6 05/09/2007 51300.13 750.067273 50550.06273

7 05/10/2007 50234.68 -437.81236 50672.49236

8 05/11/2007 50902.38 107.458 50794.922

9 05/14/2007 50510.76 -406.59164 50917.35164

10 05/15/2007 50518.21 -521.57127 51039.78127

11 05/16/2007 51737.56 575.349091 51162.21091




25.00% 25.00%

33

Exhibit 2E – Effect of S&P Raising Rating from BB+ to BBB- on the 30th of April, 2008 on the BOVESPA The regression equation is Index = 63440 + 647 C1 Predictor Coef SE Coef T P Constant 63440.1 864.6 73.38 0.000 C1 647.3 127.5 5.08 0.001 S = 1336.97 R-Sq = 74.1% R-Sq(adj) = 71.2% Analysis of Variance Source DF SS MS F P Regression 1 46083061 46083061 25.78 0.001 Residual Error 9 16087475 1787497 Total 10 62170535

05/7/200705/4/200705/1/200704/28/200704/25/2007

71000

70000

69000

68000

67000

66000

65000

64000

63000

Date

Ind

ex

Market Change from 23rd April 2008 to 8th May 2008

34



1 04/23/2007 64947.54 860.21318 64087.32682

2 04/24/2007 64576.26 -158.32018 64734.58018

3 04/25/2007 65187.34 -194.49355 65381.83355

4 04/28/2007 65677.74 -351.34691 66029.08691

5 04/29/2007 63825.74 -2850.6003 66676.34027

6 04/30/2007 67868.46 544.86636 67323.59364

7 05/2/2007 69366.39 1395.543 67970.847

8 05/5/2007 70174.88 1556.7796 68618.10036

9 05/6/2007 70195.27 929.91627 69265.35373

10 05/7/2007 69017.66 -894.94709 69912.60709

11 05/8/2007 69722.25 -837.61045 70559.86045




5.00% -44.00%

35

Exhibit 2F – Effect of Fitch Raising Rating from BBB- to BBB on the 4th of April,

2011 on the BOVESPA The regression equation is Index = 67824 + 137 C1 Predictor Coef SE Coef T P Constant 67823.9 509.1 133.23 0.000 C1 136.92 75.06 1.82 0.101 S = 787.198 R-Sq = 27.0% R-Sq(adj) = 18.9% Analysis of Variance Source DF SS MS F P Regression 1 2062270 2062270 3.33 0.101 Residual Error 9 5577123 619680 Total 10 7639393

04/10/201104/7/201104/4/201104/1/201103/28/2011

70000

69500

69000

68500

68000

67500

67000

Date

Ind

ex

Market Change from 28th March 2011 to 11th April 2011

36



1 03/28/2011 67192.82 -768.05136 67960.87136

2 03/29/2011 67418.76 -679.03436 68097.79436

3 03/30/2011 67997.06 -237.65736 68234.71736

4 03/31/2011 68586.7 215.059636 68371.64036

5 04/1/2011 69268.29 759.726636 68508.56336

6 04/4/2011 69703.8 1058.31364 68645.48636

7 04/5/2011 69837.52 1055.11064 68782.40936

8 04/6/2011 69036.91 117.577636 68919.33236

9 04/7/2011 69176.12 119.864636 69056.25536

10 04/8/2011 68718.01 -475.16836 69193.17836

11 04/11/2011 68164.36 -1165.7414 69330.10136




-1.00% -27.00%

37

Exhibit 3

Exhibit Credit Rating Change/Outlook Change Raised/Lowered Company Regression Dates

1A Outlook Lowered - Stable to Negative Fitch Not significant 2001

1B Outlook Raised - Stable to Postive Fitch Supports 2003

1C Outlook Raised - Stable to Postive S&P Not significant 2006

2A Rating Change Lowered - B1 to B2 Moodys Does not support 2002

2B Rating Change Raised - B+ to BB- S&P Supports 2004

2C Rating Change Raised - BB- to BB S&P Not significant 2006

2D Rating Change Raised - BB to BB+ Fitch Supports 2007

2E Rating Change Raised - BB+ to BBB- S&P Supports 2008

2F Rating Change Raised - BBB- to BBB Fitch Not significant 2011

Supported 44%

Not Supported 11%

Insignificant Results 44%

38

Exhibit 4

39

Exhibit 5

S&P Fitch Moodys

Date Company Long Term Outlook

Long Term Outlook

Long Term Outlook

Tuesday, July 17, 2001 Fitch - Outlook Changed BB- Negative

Thursday, August 09, 2001 S&P - Outlook Changed BB- Negative

Wednesday, February 27, 2002 Moodys - Outlook Changed B1 Positive

Tuesday, June 04, 2002 Moodys - Outlook Changed B1 Stable

Thursday, June 20, 2002 Moodys - Outlook Changed B1 Negative

Thursday, June 20, 2002 Fitch - Rating Lowered B+ Negative

Tuesday, July 02, 2002 S&P - Rating Lowered B+ Negative

Tuesday, August 20, 2002 Moodys - Rating Lowered B2 Stable

Monday, October 21, 2002 Fitch - Rating Lowered B Negative

Monday, March 10, 2003 Fitch - Outlook Changed B Stable

Tuesday, April 29, 2003 S&P - Outlook Changed B+ Stable

Tuesday, June 03, 2003 Fitch - Outlook Changed B Positive

Thursday, November 06, 2003 Fitch - Rating Raised B+ Stable

Thursday, December 11, 2003 S&P - Outlook Changed B+ Positive

Thursday, September 09, 2004 Moodys - Rating Raised B1 -

Friday, September 17, 2004 S&P - Rating Raised BB- Stable

Tuesday, September 28, 2004 Fitch - Rating Raised BB- Stable

Wednesday, January 12, 2005 Moodys - Outlook Changed B1 Positive

Tuesday, October 11, 2005 Fitch - Outlook Changed BB- Positive

Wednesday, October 12, 2005 Moodys - Rating Raised Ba3 Positive

Tuesday, November 08, 2005 S&P - Outlook Changed BB- Positive

Tuesday, February 28, 2006 S&P - Rating Raised BB Stable

Wednesday, June 28, 2006 Fitch - Rating Raised BB Stable

Tuesday, August 01, 2006 Moodys - Review for upgrade Ba3 RUR+

Thursday, August 31, 2006 Moodys - Rating Raised Ba2 Stable

Wednesday, November 22, 2006 S&P - Outlook Changed BB Positive

Wednesday, May 09, 2007 Fitch - Rating Raised BB+ Stable

Wednesday, May 16, 2007 S&P - Rating Raised BB+ Positive

Thursday, May 24, 2007 Moodys - Review for upgrade Ba2 RUR+

Thursday, August 23, 2007 Moodys - Rating Raised Ba1 Stable

Wednesday, April 30, 2008 S&P - Rating Raised BBB- Stable

Thursday, May 29, 2008 Fitch - Rating Raised BBB- Stable

Monday, July 06, 2009 Moodys - Review for upgrade Ba1 RUR+

Tuesday, September 22, 2009 Moodys - Rating Raised Baa3 -

Tuesday, September 22, 2009 Moodys - Outlook Changed Baa3 Positive

Monday, June 28, 2010 Fitch - Outlook Changed BBB- Positive

Monday, April 04, 2011 Fitch - Rating Raised BBB Stable

40

Monday, May 23, 2011 S&P - Outlook Changed BBB- Positive

Friday, June 24, 2011 Moodys - Rating Raised Baa2 Positive

Thursday, November 17, 2011 S&P - Rating Raised BBB Stable

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