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Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh

12/3/2012

FIN3560 BRAZILIAN STOCK EXCHANGE

Omar Almajali

Mauricio Bastos-Moreira

Frederico Benavides

Anshul Parikh


“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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Table of Contents:

Executive Summary………………………………………………………………...1

Overview………………..………………………………………………………….2

Technology Impacts Exchanges……………………………………………..2

Demutualization Trend………………………………………………………3

Functions...…………………………………………………………………………4

Roles...………………………………………………………………………4

Subsidiaries………………………………………………………………….4

Corporate Governance………………………………………………………5

Investing……………………………………………………………………………7

Big Players…………………………………………………………………..7

Foreign Investment……………...…………………………………………..7

Trading Hours……………………………………………………………….9

Index………………...………………………………………………………9

Analysis…………………………………………………………………………...11

Novo Mercado……………………………………………………………...11

IBOV……………………………………………………………………….11

Petrobras……………………………………………………………………15

Conclusion………………………………………………………………….17

References………………………………………………………………………...18

Exhibits……………………………………………………………………………20

1.0 – 1.3…………………………………………………………………….20

2.0 – 2.8…………………………………………………………………….21

3.0 – 3.6…………………………………………………………………….29


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Executive Summary:

We begin our paper by disclosing some of the most important historical aspects and transitional

phases that the BM&FBOVESPA went through since its establishment. BM&FBOVESPA, the largest

securities market in Latin America, would not be in its superior position today if it was not for the

milestones it has accomplished along the way. Some of these milestones include: the merging of BM&F

and the Bovespa, altering the combined group’s business model, undergoing demutualization, and

creating a new market segment, Novo Mercado. Our paper also covers the several subsidiary groups that

BM&FBOVESPA possesses in order to support its functionality such as: the BM&F bank, BM&F USA

Inc. and the BSM. We further explore Bovespa by analyzing the exchange’s big players, the requirements

it imposes on foreign investors, and its trading hours. The Bovespa Index (Ibovespa or IBOV) is the main

indicator of the stock market’s weighted-average performance. Though the indicator is available to

investor’s world-over, only few understand its composition; in this book report we include a detailed

section on how this index is calculated.

Political and financial deregulation have attributed to Brazil’s fast growing economy for the past

two decades; however, there has been one specific implementation in the exchange that has drawn in

foreign capital ranging from Europe to Australia. In this paper we prove that the initiation and

implementation of the Novo Mercado, is a significant reason behind BM&F’s enhanced performance.

This conclusion was supported by performing a return analysis on the exchange before and after the

establishment of the Novo Mercado.

BM&F’s exponential growth and success, though home grown, have international exposure due

to the country’s large export of commodities. Therefore, we felt it would be worthwhile to explore

ibovespa’s sensitivity relative to several international and national factors. In our analysis, we attempted

to understand, explain, and predict the index’s movements.


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Overview:

BM&FBOVESPA S.A is a Brazilian company that “operates as a securities, commodities, and

futures exchange in Brazil.” 1 It was formed in 2008 by the merger of Bovespa Holding S.A (Sao Paulo

Stock Exchange) and the Brazilian Mercantile & Futures Exchange (BM&F).2 The rationale behind this

merger was to combine “the region’s largest stock and derivatives exchange” and take advantage of

growth opportunities at a global scale while reducing costs. 3 “The rise of global competition and

technological advances” during the 1990s cornered stock exchanges into rethinking their business models.

It did so because it negatively affected the ways they generated revenue threatening their profitability.

Prior to this period, an exchange’s “main sources of revenue” were “transaction fees, listing fees,

membership fees, and sales of information services such as market data.” However, with the major

technological improvements investors were able to easily invest in foreign exchanges and obtain market

data at considerably lower prices; thus, stock exchanges were forced to lower their fees in hopes to

maintain business while branching out towards alternative sources of income. In order to best cope with

the situation they shifted their focus towards trading commissions, which were not so negatively affected ,

and expanded “their offering of products and services[,]” such as: “derivatives trading, and clearance and

settlement services.” Quickly it became clear that “the key to an exchange’s success” in a globalized

market place would be its “ability to generate trading volume.” This was the case because their revenue

became much more dependent on trading commissions – the more volume the greater the overall

commission – and the demand for the new products/services that are also positively related to the volume

of trades. Therefore, it is not surprising that many exchanges sought out “strategic alliances or joint

ventures” in attempts to be ahead of the competition. Moreover, this merging strategy was “particularly”

important “for exchanges in emerging markets,” like Brazil, because it served “as a means of ensuring

survival” since the “ability of Brazil’s own blue chip companies to list on the New York and London

1 Bloomberg Business Week [# 1 on references page]

2 BM&FBovespa Sobre a Bolsa [# 2 on references page]

3 Bloomberg [# 3 on references page]


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Stock Exchanges resulted in sharp declines in their” overall “trading volumes.” The fierce competition

truly pushed exchanges to adapt and as a result brought forth a “trend of demutualization.” 4

Demutualization is “when a mutual company owned by its users/members converts into a

company owned by shareholders.”5 Besides focusing on increasing volume, stock exchanges had another

critical challenge: efficiency. In the past, when there was limited competition, exchanges acted similar to

monopolies where its members held all the power. Therefore, with the intensification of rivalry it was

evident that this model became obsolete and unproductive. By demutualizing, an exchange generated

capital to invest in technology and on the long-run was able to transfer the “decision-making power to

outside investors. And this mean[t] that the old consensus decision-making of the exchange members …

eventually” would “be supplanted by a professional management team presumably motivated by

significant share ownership to increase efficiency and profits.” 6 Consequently this process gave

exchanges a much better chance of thriving in the new international trading scene. Following this trend

Bovespa went through the demutualization, in May of 2007, just preceding its merger with BM&F. An

interesting aspect of this demutualization is that the exchange not only went straight from a non-for-profit

organization to a “public held company”, but also listed its stocks on Bovespa itself.7 Looking back we

can confirm this was a very beneficial strategy for Bovespa. Today the exchange is Latin America’s

“largest public security-trading market,” the second in the overall Americas, the 9th worldwide equity by

volume market, and the 6th “derivative exchange by contract volume.”

8 +

9 Although these results are

very impressive, it has not stopped BM&FBovespa’s management to constantly push for

improvements/innovations in efforts to add more value to the company.

4 Reena Aggarwal – Demutualization and Corporate Governance of Stock Exchanges [# 4 on references page]

5 Investopedia Definition [# 5 on references page]

6 Reena Aggarwal – Demutualization and Corporate Governance of Stock Exchanges [# 4 on references page]

7 Bovespa Holding Communication on Progress [# 6 on references page]

8 Markets Wiki [# 7 on references page]

9 World Federation of Exchanges PDF pg.6 [# 8 on references page]


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Functions:

BM&FBOVESPA is the primary institution in Brazil that oversees and supports capital markets

operations. “The company develops, implements, and provides systems for … trading” as well as it offers

“recording, clearing, settlement, and risk management systems; custodian systems for agribusiness

securities, gold, and other assets; and WebTrading, an environment of electronic trading.” Furthermore it

“operates as a central securities depository, and licenses software and stock indices. Additionally, it

provides securities and annuities listing, and market data vending.” 10

In order to provide all of these

services the Bovespa group manages a cluster of subsidiary companies where each company has been

specifically designed to aid in an important aspect of the daily operations. For instance, the

BM&FBOVESPA Bank performs “custody and bookkeeping support for investment funds (including

calculation of unit value); risk mitigation and operational support for market participants; and access to

the Central Bank of Brazil for immediate settlement of transactions involving government bonds pledged

as collateral to BM&FBOVESPA.” Besides these services, it is directly involved in providing service to

non-Brazilian residents’ investors (individuals). These services range from “legal and tax representation,

and foreign exchange” to providing information to the investors. Another important subsidiary is BM&F

USA Inc., which has its office representing the group in New York City. They offer infra-structure and

support to foreign investors, but more on a corporate level rather than an individual one. Also, the office

in New York is in charge of building relationships with foreign regulatory, governmental agencies, and

exchanges with the goal of analyzing potential attractive opportunities. 11

Last but not least, there is

BM&FBOVESPA Supervisao de Mercado (BSM) which is a “not-for-profit association” in charge of

supervision and regulation of all activities and agents in the market. 12

” “Given the nature of its activities,

BSM is a functionally autonomous” and “financially independent entity.” This truly helps promote its

transparency and affirm the unbiased of its due diligence while monitoring the market. One of the, if not

10

Bloomberg Business Week [# 1 on references page] 11

BM&FBovespa Sobre a Bolsa [# 2 on references page] 12

BSM webpage [ # 10 on references page]


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the most, important function of BSM is its supervision of corporate governance requirements through its

surveillance board. 13

Corporate governance is “a system by which companies are directed and monitored, concerning

Shareholders, the Board, Directors, Independent Audit and Fiscal Council.” 14

This system is very

important because it is the main way companies guarantee a certain level of security to investors. A

company following good corporate governance practices transmits a message of “integrity and fairness,”

of “being transparent with regard to all transactions;” thus, demonstrating a sense of “responsibility

towards the stakeholders” by clearly showing a “commitment to conducting business in an ethical

manner.” 15

In Brazil, the implementation of good corporate governance principles has always been a

challenge. “The prevalence of family owned companies, limited capital pulverization, and low percentage

of shareholders with voting rights are characteristics that lead to an adverse environment for governance

practices.” 16

Bovespa’s management understood that governance was an issue that needed to be fixed in

order to make the exchange a safer and more attractive option to investors.

In life, and in financial markets, every single action one takes is subject to risks. In markets there

are two main types of risks: systematic and unsystematic risks. Systematic risks are the overall market

risks that cannot be avoided (significantly reduced) but only hedged. Whereas, unsystematic are specific

risks that can be avoided through diversification. To better explain their difference lets imagine a

scenario: Joe takes the bus from Boston to New York to visit his family during thanksgiving break.

However, before he purchased his ticket he checked if the vehicle had passed the state’s inspection.

During this trip Joe is exposed to all the systematic risks any person would be while on board of a motor

vehicle. For instance, he runs the risk of a collision or a tire blow-out, yet because the bus passed the

state’s inspection the odds of it suffering a system malfunction are slim to none. Hence, similar to this

oversimplified example, Bovespa acts as the government setting safety requirements for vehicles

13

BM&FBovespa Corporate Governance Paper [# 11 on references page] 14

BM&FBovespa website [# 12 on references page] 15

The Economic Times [# 13 on references page] 16

Azevedo Sette Advogados [# 14 on references page]


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(companies) so that passengers (investors) can be safe while travelling (investing). In other words

Bovespa only wants investors to have the regular unavoidable risks of investing in a capital market. The

way the group decided to do that is very clever and interesting. Since Bovespa is not the Brazilian

government it has no authority to obligate companies to comply with governance laws. Therefore there is

a high risk for Bovespa to lose its listed companies if it decided to impose sudden strict regulations on

them. Moreover, knowing that volume is crucial for the exchange’s financial health, this was certainly not

an option. To bypass this obstacle, BM&F created a different listing segment with requirements for

admission and continued membership. This is when the Novo Mercado was born (December 2000).

“Novo Mercado is a listing segment designed for shares issued by companies that voluntarily

undertake to abide by corporate governance practices and transparency requirements in additional to those

already requested by the Brazilian Law and CVM (Brazilian Securities and Exchange Commission).” It

was designed to further the rights of the investors and their ability to make educated decisions by

requiring companies to regularly disclose accurate, trustworthy, and relevant information. To be admitted

and maintain its membership in the Novo Mercado a company must: maintain a minimum free float (≤

25%) of capital; provide tag along conditions to all investors; “establish two-year unified mandate for

entire Board of Directors, which must have at least 5 members” (20% shall be Independent); “disclose an

annual balance sheet according to US GAAP or IFRS standards”; Improve quarterly reports with

“consolidated financial statements and special audit revision”; “Comply with disclosure rules” of the

exchange; “Obligated to hold a tender offer by the economic value criteria” if delisted from Novo

Mercado. 17

Moreover, other segments were created besides the Novo Mercado: level 1, level 2, and

Bovespa Mais. These new segments have different requirements in order to offer investors and companies

more options. Level 1 and Level 2 require lower levels of corporate governance and hence is tailored to

companies that do not want to comply with Novo Mercado’s strict requirements. Bovespa Mais, on the

other hand, is a segment that mostly mimics the Novo Mercado, but is designed to facilitate the access of

17

BM&FBovespa webpage [# 15 on references page]


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small and medium companies into the capital markets. The idea behind this new segment is to eventually

drive the companies listed in Bovespa Mais to transfer to Novo Mercado once they are more established

and thriving.

Investing in Bovespa:

Brazil is the largest economy in Latin America and with it comes some of the most thriving

companies in the entire southern hemisphere. One of the largest companies in the Bovespa is Petrobras, a

semipublic energy company headquartered in Rio de Jainero. It was created in 1953 as a legal monopoly

in the oil industry and in 1997 became a semipublic company. Petrobras gives a significant output of 2

million oil barrels a day and it is a world leader in the development of advanced technology for deep-

water water oil production.18

In Brazil there is also the largest financial conglomerate in Latin America:

Banco Itaú. This holding company is headquartered in São Paulo where it focuses mainly on financial

services, such as commercial and corporate banking. Banco Itaú also offers insurance, assets

management, and capitalization plans.19

They have 456 billion Brazilian Reais of assets as of 2011 and

14.5 million clients. Not only does Brazil have the largest oil company and bank in Latin America, but

also the largest mining company: Companhia Vale do Rio Doce. Vale S.A. is the world’s second largest

mining company, leader in iron-ore production and second biggest nickel producer. It was founded in

1942 by the Brazilian government; however Vale was privatized right around the same time Petrobras

was (1997).20

These big companies, along with the Brazilian economy, thrived even further when foreign

investments started to flourish in Brazil.

“Brazil has one of the most liberal investment climates for outside investors. Non-resident

investors, both individuals and legal entities, can invest in most of the financial and capital

market instruments available to resident investors, without any restrictions. International investors have

two options for foreign investors to invest in the Brazilian stocks. The first option is to go straight to the

place of action by investing in stocks listed on the Brazilian stock exchange. The second option is to try

18

Petrobras [# 16 on references page] 19

The Brazil Business [# 17 on references page] 20

Brazil [#18 on references page]


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the offshore investment route available in the form of American depository receipts (ADRs), Global

depository receipt (GDRs), exchange-traded funds (ETFs) and mutual funds focused on Brazil or Latin

America. Furthermore, Investors desiring a shorter route can use the option of operating as participants

("passengers") in collective accounts registered in the name of some other investor."21

Regardless of any scenario, non-resident investors have to abide by specific admission rules in

order to start initiating investments in the Bovespa. “According to the CMN (Brazilian Monetary Council)

Resolution 2689, since international investors are not established or resident in the country, it is necessary

to hire an institution to act as Legal Representative which would be responsible to present all the

registration information of the investor to the Brazilian Authorities. The role of a legal representative can

be done by any financial institution authorized by the Central Bank22

.” In addition, a Fiscal

Representative must be appointed who would be responsible for taxes and fiscal issues on behalf of the

investor before the Brazilian Authorities (usually their legal representative). Next, a Custodian must be

hired to be responsible for keeping physical records of all investor documents and must present them to

the Brazilian authorities whenever required. 23

These sets of documents include Statues of the investor,

minutes of meetings that nominated the responsible for trading, registry documents of the company and

others according to the Custodian compliance rules. Several financial institutions are authorized by the

CVM and Central Bank to perform the custodian activities while act as investor's legal and fiscal

representatives too.

After these contracts with the legal representative, the tax representative and the custodian bank

have been established; they must be signed and submitted to the Brazilian Securities Commission. This

process could be also handled by the legal representative. “The registration with the CVM is usually made

electronically and it will then provide the legal representative with a tax code (CNPJ) within 24 hours

21

Investopedia [#19 on references page] 22

BM&FBOVESPA – How to invest [#20 on references page] 23

BM&FBOVESPA –Getting started [#21 on references page]


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after the request. Finally, the foreign investor must register with a local brokerage house in Brazil for

execution services.” 24

The trading hours for equity markets in the Bovespa starts with the pre-opening at 9:45 till 10:00

am. This pre-opening is dedicated for brokers to insert orders (no order is executed before the pre-

opening). Moreover, it is used for “the calculation of the theoretical opening price.”25

The market

officially opens at 10:00am and it closes at 5:00pm, during this time there is a continuous trading session

for all listed securities. There is also a closing call that extends from 4:55 to 5:00 for shares included in

the exchange’s index portfolio, ETF’s and other stocks. This closing call also applies to the options on the

IBrX-100 portfolio (top 100 stocks traded on the Bovespa). In addition, the closing call period for ETFs is

extended by 2 minutes after the end of the last stock closing call. There is an after-market period where

trades can occur after the regular market has closed, and that is from 5:30pm to 7:00pm. During the after-

marker hours only shares included in the IBOVESPA and the IBrX-100 portfolios can be traded.26

The Bovespa Index, IBOV for short, “is the main indicator of the Brazilian stock market’s

average performance.” Its function is to accurately reflect the variation of the most traded and relevant

stocks listed in the exchange. Its value is “the current value in Brazilian currency, of a theoretical stock

portfolio.” Moreover, this portfolio was constituted in 1968 – when the IBOV was first implemented –

and “no additional investment has been made since this date, apart from the reinvestment of the

distributed benefits (such as dividends, subscription rights and stocks bonuses).” 27

Another very

interesting aspect of the IBOV is how this portfolio is build.

In order for a listed company to be part of the portfolio it must, in the past 12 months, have met

all of these three criteria: 1. Be traded on at least 80% of trading sessions; 2. Have an average daily

participation volume ≥ 0.1% of Bovespa’s overall daily average volume; 3. Be in the 80% IN group. The

24

BM&FBOVESPA – Opening an account [#22 on references page] 25

BM&FBOVESPA – Operational manual procedure [#23 on references page] 26

BM&FBOVESPA – Operational manual procedure [#23 on references page] 27

Bovespa Index: [# 27 on references page]


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first two criteria take care that the stock is liquid and actively contributing to the exchange. The third

criterion ensures the portfolio is constituted of relevant stocks (≥ 80%) of the index. To select these

companies Bovespa uses a geometric average to define each company’s Index of Negotiability (IN). To

calculate the IN one must multiply the ratios of the company to overall market # of trades and company to

overall market volume (gross transaction value); then take the square root of the result. Once this is

calculated Bovespa lists each company by decreasing (largest to smallest) order and selects the top 80%

IN to be part of the portfolio. After that it adjusts the base to figure out how many shares of each company

the portfolio will have. For instance, Company A has an IN of 10% of the overall market but it composes

12.5% of the portfolio (10/100 = 10% and 10/80 = 12.5%). Moreover, Bovespa reevaluates the portfolio

three times per year (every 4 months) and makes sure that the index value is not subjected to

discontinuity. It does so by allowing flexibility in calculating the quantity/portion each company makes

up in the portfolio. It also has rules for adjustments set up for specific cases such as mergers, IPOs, spin-

offs, and other relevant situations. 28

Bellow you can see a visual representation of the IN and base

Adjustment formulas:

AND:

Source: http://www.monitorinvestimentos.com.br/ver_artigo.php?id_artigo=397

28

Monitor Investimentos [# 28 on references page]

http://www.monitorinvestimentos.com.br/ver_artigo.php?id_artigo=397


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Statistical Analysis:

Novo Mercado (New Market):

The investor friendly rules of the Novo Mercado were set in full function at the start of 2002,

which has had a positive impact on the Brazilian financial markets in its ability to draw in foreign

investment. Exhibit 1.1 displays returns for the most recent decade of returns; the Bovespa is compared to

the S&P 500 (US) which shows the mighty growth in the emerging economy versus the mature North

American one. The Bovespa’s total return at the close of 2011 was up over 300.0% for the decade as

opposed to its American rival, which was only up 9.5%. Additionally, the five largest companies by

weight on the ibovespa had a range of returns from 11.2% to 1060.4%.

Brazil’s Petroleo Brasilerio SA, better known as Petrobras, is one of the strongest performing

stocks and is considered to be a national blue chip for investors. In comparison to its multinational rivals,

the company is tracked across two decades divided by the implementation of the new market rules in the

beginning of 2002. For the 10 years prior there was an astronomical return of above 4000.0% (see Exhibit

1.2); however, the currency gain went from 0.19 Reals to 6.39 Reals. Its competitors performed well

during this time period too, specifically Shell and BP which had returns of 339% and 293%, respectively.

The explosive growth, however, was during the past decade in which (see Exhibit 1.3) Petrobras grew its

share price by 236% from 6.39 Reals to 21.49 Reals. The only other company to see higher numbers was

CNOOC, another BRIC nation with strong backing from the Chinese state.

IBOV:

We decided to explore what factors would cause the Bovespa Index, ibovespa, to appreciate or

depreciate. After researching Brazil’s economy we found out that South America’s largest country and

economy was influenced by several factors. In the early part of the 2000’s, Brazil had one of the fastest

growing GDP supported by local industries that in turn have drawn attention from foreign investors world


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round.29

There are approximately 11 ETFs that track the Bovespa on the New York Stock Exchange;

additionally several of Brazil’s largest companies have co-listings in the form of ADRs on the New York

Stock Exchange30

.

With heightened international importance, we wanted to test out if the ibovespa appreciated or

depreciated more in line with national factors versus international factors. We chose a set of 17 factors

that included both national and international factors and ran several regressions. The national factors

included the Brazilian Real vs. US Dollar exchange rate(BRL-USD <Currency>), Iron Ore &

Concentrates priced in Reals, Soy Beans priced in Reals, Sugar Cane priced in Reals, the Brazil

Reference Rate (BZTRTRD) and the Brazil CPI Inflation Index (BZPIIPCY)31

. The International factors

include the S&P 500 (SPX), Dow Jones Industrial Average (DJIA), West Texas Intermediate sweet crude

(WTI), MSCI India Index (MXIN), MSCI China Index (MXCN), MSCI Russia Index (MXRU), and the

Gold Spot Price (XAU-USD).32

Starting with the national factors, we will now present why each factor was included in the

regression. The foreign exchange rate between the BRL-USD is an important factor because Brazil is rich

in natural resources and we wanted to see the impact of large exports to the rest of the world and the

fluctuation of the home currency upon the national index. Iron Ore & Concentrates account for

approximately 15% of the Brazilian economy as of Q1 2012 and therefore is a significant factor in our

regression.33

Brazil is one of the world’s top producers of soy beans and related soy products, and for the

local economy are accounts for 5.4% of exports as of Q1 2012.34

Another commodity in which Brazil

ranks number one in the world is for producing raw sugar cane; it accounts for 6.4% of the country’s

exports.35

Moving towards financial indicators, the country’s reference rate is another important factor

because it serves as the prime rate in which Brazil’s Central Bank lends to 20 of the country’s largest

29

Seeking Alpha – [#25 on reference page] 30

Seeking Alpha – [# 25 on references page] 31

Index Mundi – [#26 on references page] 32

The quotes in brackets are the Bloomberg standard ticker symbols for the respective security/index/commodity


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banks. Finally, the CPI inflation rate is another factor that will be included in the regression because it

helps to track price levels in the country, which had suffered record levels of hyper-inflation in the 1980s.

Morgan Stanley Capital International (MSCI) helps to track many of the world’s indices and

tracking Brazil is no exception. The country has had one of the best returning indices in the world and is

part of the BRIC nations (Brazil, Russia, India and China). The US has two major benchmark indices that

are followed world over by investors, the S&P 500 and the DJIA. The first tracks approximately 500 of

the largest companies in the US markets, while the latter tracks the top 30 “blue chip” companies of the

US, which historically has been paying high dividends (with the exception of technology companies). Oil

and gas play a large part in international trade, and with Brazil being one of the world’s largest consumers

and producers of natural gas and oil, it is important to see how the West Texas Intermediate sweet crude

fares as a factor. The WTI is lighter and contains less sulfur than other rival oil types such as the BRENT,

and is used by more industries. The MSCI indices of China, India, and Russia are vital in the regression

because they are also members of the “BRIC” emerging economies which have experienced high growth

over the last decade; therefore it is a natural fit for inclusion in the regression. Since the 2007 global

financial crisis, global investors have flocked to gold as a safe heaven, making it more valuable per ounce

than platinum; with Brazil facing hyper-inflation in the past, gold is an important component to this

regression.

After selecting the variables we obtained the historical data to run our statistical analysis. It is

important to point out that our model is based on monthly data (beginning of 2002 to the end of 2011).

We decided to do this in order to have the ability to use our model to forecast IBOV’s values for year to

date 2012 and compare it to the actual market values. Firstly, we started by running a best subset

regression analysis of the IBOV versus all 17 variables. As seen in exhibit 2.2, by performing this

analysis we were able to identify a set of eight variables that best correlate with the index. We feel

confident that these eight variables are the best options for our model because they combined have a very

strong R-squared adjusted of 98.3, the smallest Mallows Cp value of 7.6, and are aligned with the


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parsimony principle. Then, once we were able to identify these variables we ran a second multiple linear

regression paying particular attention to variance inflation factors (VIF). The reasoning behind this is that

VIF accounts for the co-linearity between variables and this negatively influences our model. Using the

common statistical rule of thumb, VIF < 5, we continued with our analysis; meaning we eliminated the

highest variable falling in the category of “VIF<5” and ran another multi-linear regression. This process

took place continuously until we got all of these invalid variables out of the way. So as seen in exhibit 2.3

we eliminate Gold due to its incredibly high VIF of 17.845. Then we ran a third regression shown in

exhibit 2.4 and eliminated MSCI India with a VIF of 16.348. In the fourth regression displayed by exhibit

2.5 we took out the foreign exchange rate between US and Brazil because of its VIF of 5.840. Then we

ran a fifth regression where finally all of our variables had a VIF < 5. Nevertheless, we were not done yet

because in this latest regression we examined that the S&P500 variable possessed a p-value > .05.

Therefore, it proved to be statistically insignificant to our model and we eliminated it and ran a sixth and

final regression with the remaining four variables.

This final regression presented in exhibit 2.6 provided us with an equation for forecasting the

index’s value: IBOV = - 2461 + 257 WTI Oil + 2168 MSCI China + 106 Iron Ore - 23546 Brazil

Reference Interest Rate. After obtaining it we analyzed each variable and the weights set to them to make

sense of our model. It is very understandable why WTI Oil has a correlation with the IBOV. Petrobras is

one of the biggest companies listed in Bovespa and a change in the world prices of oil definitely affects

its price and subsequently the index value. Moreover, China is a big importer of Brazilian commodities so

it makes sense that whenever China is doing well it will import more from Brazil hence appreciating the

IBOV. Due to its size and importance the large weight set to China by our model is quite logical.

Actually this is supported through the fact that as China has been slowing down recently we have seen

depreciation in IBOV’s value. Also, as we mentioned earlier Iron Ore accounts for about 15% of Brazil’s

economy and a change in its value should have an impact in the index. The last variable in our model is

Brazil’s Reference Interest Rate. It is very consistent and interesting to see that an increase in interest


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rates would lower the index’s value. This should be true because as interest rates rise the overall cost of

capital rises which in turn make investing riskier and lower the index. Finally, after we were satisfied with

our model we ran it forecasting IBOV and comparing it to the actual 2012 values.

Referring to Exhibit 2.8 we can see a table of values with our forecasts and the graphical

representation of them. The first thing to notice in our forecast is that although it is often correlated it over

predicts IBOV’s value. This is very relevant because although the general movement is similar our

predictions were always at least 1% up to 12% higher than the actual values. We feel that the main

explanation behind this is that Interest Rates are not behaving normally. Our model is based on historical

data and the current extremely low levels of interests rate could not have been predicted based on past

events. As a result our model has the tendency of taking this as a sign of positive market conditions that

should propel the IBOV. Nevertheless, it fails to acknowledge the insecurity capital markets are facing

globally. Investors are not sure of what is going to happen and because of that are not acting like they

normally would. The perfect example of this would be how US 10 year treasury notes have an YTM of

only1.76%. This is extremely low and astonishing that people are willing to lose money (rates lower than

inflation) in order to obtain security.

Petrobras:

Petrobras is easily one of the most identifiable companies in Brazil as it had one of the largest

share offerings in the early part of this decade; the semi-public company managed to raise over $70B

Dollars in 2010.36

Although there is government ownership in the company, it is the second largest

member on the ibovespa by weight, second only to Vale SA.

In this regression, we wanted to explore Petrobras’ movement in relation to other large national

companies and other multinational oil companies; we also wanted to find a regression model that would

aid in predicting the share price of Petrobras and understanding whether it moves more accordingly to

other Brazilian or international oil powerhouses. In order to keep a common denominator, all companies

36

PetroBras [#27 on references page ]


-16-

used in this regression were priced in US dollar; the companies were either US listed companies or

American Depository Receipts (ADR) – which allows foreign companies to attract international money

using the greenback as a common currency. Ultimately taking data from 2002 (the implementation of the

Novo Mercado) to 2011 on a monthly basis, we wanted to test the regression model to see how well it fits

against the actual results of 2012 up to October 31st last price of Petrobras. The companies used in this

regression were Vale SA, OGX, Banco Bradesco, BP PLC (British Petroleum), Exxon Mobil, CNOOC

(China National Offshore Oil Corporation), Royal Dutch Shell and Chevron Corporation.

The initial regression run was a best subset which helped to identify stronger factors from weaker

ones. As per Exhibit 3.1, there were several companies removed after an Adjusted R-Sq of 83.7%, a

Mallows Cp of 3.2 and a low standard deviation of 2.7288 resulted in Vale SA, Itaú, BP PLC, Exxon

Mobil and Chevron as better representations of Petrobras ADR price movements. The next step was to

run a regression checking for VIF factors above five so as to avoid co-linearity. Exhibit 3.2 shows the

improved regression with a higher R-Sq(adj) of 89.1%; however, Chevron had a high VIF of 17.119 and

was subsequently removed. Exhibit 3.3, showed a dip in the R-Sq(adj) value and additionally the co-

linearity of Vale required it to be removed. Exhibit 3.4 shows a high p-value of BP PLC which was

greater than 0.05 was subsequently removed to see if the model would strengthen. Exhibit 3.5, results in

the equation: Petrobras = -11.7+1.34(ITAU)+0.329(Exxon) Taking the regression equation from above,

we next went to see how well this equation was able to serve as a predictor of future end-month values of

Petrobras. Exhibit 3.6 depicts the regression’s attempt to predict the future values of the Petrobras.

Ultimately, our regression model was weak as it only had an R-Sq(adj) value of 80.1%. Additionally, the

model over predicted the price on every occasion and is thus not a good fit for predicting the price of

Petrobras in international markets. It is clear that there are more factors that affect the oil companies’

stock price that we do not have a way to factor in such as investor sentiment and outlook. These

unidentifiable factors are likely to be due to the slowing of the Brazilian economy and the effects of the

post financial market meltdown that began in 2007. The model, however, is not all bad because there is a


-17-

relationship that is not accountable quantitatively. Even though the model over-predicts the value of

Petrobras, it moves in line with Itaú, the country’s largest bank by assets, and additional research shows

that Petrobras is a big client of Itaú.37

Therefore, the larger weight placed on Itaú is not a definitive factor

but a good indication of the performance of Petrobras as its stock price moves with the performance of the

regression equation noted above.

Conclusion:

The Brazilian Stock exchange has underwent major structural and regulatory changes in the past

20 years. These changes have positioned the exchange as a strong and attractive option to investors

around the world. The Novo Mercado, supported by great returns after its introduction, has definitely

been a big contributor to the exchange’s success thus far. Nevertheless, as shown by our quantitative

analysis it does not completely ensure future results. This holds true because Brazil’s performance is

directly correlated to international factors such as other partners performances (ex: China & US) and

commodities values (Iron Ore and Oil). Moreover, it currently faces – as any other exchange in the world

– the challenges of global financial instability. Therefore, we believe that in order to maintain or even

improve its current position Bovespa will need to continue pushing transparency in its markets and hope

for a strong country’s performance. Our reasoning is that investors are very skeptical and reluctant to take

risks; which explains – to certain extend – why our current models tend to over predict values.

37

Bloomberg Terminal: <ITUB4 BS <Equity>> -> Supply Chain Analysis -> Petrobras


-18-

REFERENCES:

1. Bloomberg Business Week:

http://investing.businessweek.com/research/stocks/private/snapshot.asp?privcapId=21953226

2. BM&FBovespa Sobre a Bolsa:

http://www.bmfbovespa.com.br/pt-br/intros/intro-sobre-a-bolsa.aspx?idioma=pt-br

3. Bloomberg:

http://www.bloomberg.com/apps/news?pid=newsarchive&sid=aNzQELxR42ms&refer=latin_am

erica

4. Reena Aggarwal – Demutualization and Corporate Governance of Stock Exchanges:

http://www.set.or.th/setresearch/files/demutualization/ResearchPaper_2002_Reena.pdf

5. Investopedia Definition:

http://www.investopedia.com/terms/d/demutualization.asp#axzz2DJEHqzk7

Bovespa Holding Communication on Progress:

http://www.unglobalcompact.org/system/attachments/3061/original/COP.pdf?1262614370

6. Markets Wiki:

http://www.marketswiki.com/mwiki/BM%26FBOVESPA

World Federation of Exchanges PDF pg.6:

http://www.worldexchanges.org/files/file/stats%20and%20charts/2011%20WFE%20Market%20

Highlights.pdf

7. BM&FBOVESPA Bank website:

http://www.bmfbovespa.com.br/BancoBmfbovespa/Nonresident/en-us/about-us.asp

8. BSM webpage:

http://www.bovespasupervisaomercado.com.br/QuemSomos.asp

9. BM&FBovespa Corporate Governance Paper

http://ri.bmfbovespa.com.br/upload/portal_investidores/pt/governanca_corporativa/estatutos_polit

icas/CA-28-Annex1_CG_Guidelines.pdf

10. BM&FBovespa Website:

http://www.bmfbovespa.com.br/en-us/markets/equities/companies/corporate-

governance.aspx?idioma=en-us

11. The Economic Times:

http://articles.economictimes.indiatimes.com/2009-01-18/news/28462497_1_corporate-

governance-satyam-books-fraud-by-satyam-founder

12. BM&FBovespa website:

http://www.bmfbovespa.com.br/cias-listadas/Empresas-

Listadas/BuscaEmpresaListada.aspx?indiceAba=2&seg=NM&Idioma=en-us

http://investing.businessweek.com/research/stocks/private/snapshot.asp?privcapId=21953226

http://www.bmfbovespa.com.br/pt-br/intros/intro-sobre-a-bolsa.aspx?idioma=pt-br

http://www.bloomberg.com/apps/news?pid=newsarchive&sid=aNzQELxR42ms&refer=latin_america

http://www.bloomberg.com/apps/news?pid=newsarchive&sid=aNzQELxR42ms&refer=latin_america

http://www.set.or.th/setresearch/files/demutualization/ResearchPaper_2002_Reena.pdf

http://www.investopedia.com/terms/d/demutualization.asp#axzz2DJEHqzk7

http://www.unglobalcompact.org/system/attachments/3061/original/COP.pdf?1262614370

http://www.marketswiki.com/mwiki/BM%26FBOVESPA

http://www.worldexchanges.org/files/file/stats%20and%20charts/2011%20WFE%20Market%20Highlights.pdf

http://www.worldexchanges.org/files/file/stats%20and%20charts/2011%20WFE%20Market%20Highlights.pdf

http://www.bmfbovespa.com.br/BancoBmfbovespa/Nonresident/en-us/about-us.asp

http://www.bovespasupervisaomercado.com.br/QuemSomos.asp

http://ri.bmfbovespa.com.br/upload/portal_investidores/pt/governanca_corporativa/estatutos_politicas/CA-28-Annex1_CG_Guidelines.pdf

http://ri.bmfbovespa.com.br/upload/portal_investidores/pt/governanca_corporativa/estatutos_politicas/CA-28-Annex1_CG_Guidelines.pdf

http://www.bmfbovespa.com.br/en-us/markets/equities/companies/corporate-governance.aspx?idioma=en-us

http://www.bmfbovespa.com.br/en-us/markets/equities/companies/corporate-governance.aspx?idioma=en-us

http://articles.economictimes.indiatimes.com/2009-01-18/news/28462497_1_corporate-governance-satyam-books-fraud-by-satyam-founder

http://articles.economictimes.indiatimes.com/2009-01-18/news/28462497_1_corporate-governance-satyam-books-fraud-by-satyam-founder

http://www.bmfbovespa.com.br/cias-listadas/Empresas-Listadas/BuscaEmpresaListada.aspx?indiceAba=2&seg=NM&Idioma=en-us

http://www.bmfbovespa.com.br/cias-listadas/Empresas-Listadas/BuscaEmpresaListada.aspx?indiceAba=2&seg=NM&Idioma=en-us


-19-

13. Azevedo Sette Advogados:

http://www.azevedosette.com.br/en/noticias/corporate_governance_in_brazil_and_the_bovespa_n

ew_market/338

14. Petrobras: http://www.petrobras.com/en/about-us/

15. The Brazil Business:

http://thebrazilbusiness.com/article/the-10-major-brazilian-banks

16. Brazil: http://www.brazzil.com/pages/p18jun97.htm

Investopedia: http://www.investopedia.com/articles/stocks/10/investing-in-brazil.asp#axzz2DgUMZobv

17. BM&FBOVESPA –How to invest: http://www.bmfbovespa.com.br/en-us/intros/intro-how-to-invest.aspx?idioma=en-us

18. BM&FBOVESPA – Getting started: http://www.bmfbovespa.com.br/en-us/international-investors/getting-started-with-bvmf/getting-started-with-bvmf.aspx?Idioma=en-us

19. BM&FBOVESPA – Opening an account: http://www.bmfbovespa.com.br/en-us/international-investors/opening-an-account/opening-an-account.aspx?Idioma=en-us

20. BM&FBOVESPA Operational manual procedures: http://www.bmfbovespa.com.br/en-us/download/Operational-Procedure-Manual-Bovespa-Segment.pdf

21. Seeking Alpha – A Forecasting Analysis on the BOVESPA http://seekingalpha.com/article/265224-a-forecasting-analysis-of-the-bovespa-part-1

22. Index Mundi – World Commodity Prices www.indexmundi.com

23. Bloomberg Standard ticker symbols via the Terminal

24. PetroBras: http://www.petrobras.com.br/pt/

25. Supply Chain Analysis – Bloomberg Terminal

26. Bloomberg Terminal: <ITUB4 BS <Equity>> -> Supply Chain Analysis -> PetroBras

27. Bovespa Index: http://www.bmfbovespa.com.br/indices/ResumoIndice.aspx?Indice=Ibovespa&Idioma=en-us

28. Monitor Investimentos: http://www.monitorinvestimentos.com.br/ver_artigo.php?id_artigo=397

http://www.azevedosette.com.br/en/noticias/corporate_governance_in_brazil_and_the_bovespa_new_market/338

http://www.azevedosette.com.br/en/noticias/corporate_governance_in_brazil_and_the_bovespa_new_market/338

http://www.petrobras.com/en/about-us/

http://thebrazilbusiness.com/article/the-10-major-brazilian-banks

http://www.brazzil.com/pages/p18jun97.htm

http://www.investopedia.com/articles/stocks/10/investing-in-brazil.asp#axzz2DgUMZobv

http://www.bmfbovespa.com.br/en-us/intros/intro-how-to-invest.aspx?idioma=en-us

http://www.bmfbovespa.com.br/en-us/international-investors/getting-started-with-bvmf/getting-started-with-bvmf.aspx?Idioma=en-us

http://www.bmfbovespa.com.br/en-us/international-investors/getting-started-with-bvmf/getting-started-with-bvmf.aspx?Idioma=en-us

http://www.bmfbovespa.com.br/en-us/international-investors/opening-an-account/opening-an-account.aspx?Idioma=en-us

http://www.bmfbovespa.com.br/en-us/international-investors/opening-an-account/opening-an-account.aspx?Idioma=en-us

http://www.bmfbovespa.com.br/en-us/download/Operational-Procedure-Manual-Bovespa-Segment.pdf

http://seekingalpha.com/article/265224-a-forecasting-analysis-of-the-bovespa-part-1

http://www.indexmundi.com/

http://www.petrobras.com.br/pt/

http://www.bmfbovespa.com.br/indices/ResumoIndice.aspx?Indice=Ibovespa&Idioma=en-us

http://www.monitorinvestimentos.com.br/ver_artigo.php?id_artigo=397


-20-

Exhibit 1.0: Total Returns of the Novo Mercado (The New Market)

Exhibit 1.1:

December 31st, 2001 through December 31st, 2011

Exhibit 1.2:


Exhibit 1.3:


Name Price App Tot Ret Entry Price Exit Price Entry Mkt Val Exit Mkt Val Capital Gain Tot Gain

Bovespa Brasil Sao Paulo Stock Exchange Index 317.9988% 317.9988% 13,577.57 56,754.08 135,775,700.00 567,540,800.00 431,765,100.00 431,765,100.00

S&P 500 Index 9.5394% 33.3427% 1,148.08 1,257.60 11,480,800.00 15,308,807.44 1,095,200.00 3,828,007.44

Petroleo Brasileiro SA 236.0963% 408.3370% 6.39 21.49 6,394.00 32,503.07 15,096.00 26,109.07

Vale SA 745.1397% 1060.3629% 4.48 37.82 4,475.00 51,926.24 33,345.00 47,451.24

Itau Unibanco Holding SA 431.0938% 602.8001% 6.40 33.99 6,400.00 44,979.21 27,590.00 38,579.21

OGX Petroleo e Gas Participacoes SA 11.1837% 11.1837% 12.25 13.62 12,250.00 13,620.00 1,370.00 1,370.00

Banco Bradesco SA 459.0909% 672.5872% 5.50 30.75 2,750.00 21,246.15 12,625.00 18,496.15

Name Price App Tot Ret Tot DPS Entry Price Exit Price Entry Mkt Val Exit Mkt Val Capital Gain Tot Gain

Petroleo Brasileiro SA 3195.8763% 4107.4097% 0.78 0.19 6.39 1,940.00 81,623.75 62,000.00 79,683.75

BP PLC 182.9506% 293.5309% 9.67 16.44 46.51 164,375.00 646,866.34 300,725.00 482,491.34

Exxon Mobil Corp 158.2332% 261.3222% 7.94 15.22 39.30 15,218.80 54,988.90 24,081.20 39,770.10

CNOOC Ltd 22.2962% 23.7876% 0.02 1.20 1.47 1,202.00 1,487.93 268.00 285.93

Royal Dutch Shell PLC 253.2143% 339.8703% 4.80 8.05 28.45 8,054.60 35,429.79 20,395.40 27,375.19

Chevron Corp 159.7391% 270.3607% 10.85 17.25 44.81 17,250.00 63,887.22 27,555.00 46,637.22

Name Price App Tot Ret Tot DPS Entry Price Exit Price Entry Mkt Val Exit Mkt Val Capital Gain Tot Gain

Petroleo Brasileiro SA 236.0963% 408.3370% 7.14 6.39 21.49 63,940.00 325,030.65 150,960.00 261,090.65

BP PLC -8.1058% 34.4044% 20.72 46.51 42.74 465,100.00 625,114.68 -37,700.00 160,014.68

Exxon Mobil Corp 115.6743% 170.0621% 13.55 39.30 84.76 39,300.00 106,134.41 45,460.00 66,834.41

CNOOC Ltd 823.8095% 1205.2630% 2.54 1.47 13.58 1,470.00 19,187.37 12,110.00 17,717.37

Royal Dutch Shell PLC -1.0545% 56.3747% 10.54 28.45 28.15 28,450.00 44,488.61 -300.00 16,038.61

Chevron Corp 137.4735% 232.4097% 21.50 44.81 106.40 44,805.00 148,936.16 61,595.00 104,131.16


-21-

Exhibit 2.0: IBOV’s Analysis

Exhibit 2.1:

Source: Economic Complexity Observatory, MIT Media Lab and the Center for International Development at Harvard

University. http://atlas.media.mit.edu/ Author: R Haussman, Cesar Hidalgo, et. al. Creative Commons Attribution-Share alike 3.0 Unported license. See

permission to share at: http://atlas.media.mit.edu/about/permissions/ Taken from: http://en.wikipedia.org/wiki/File:Brazil_Export_Treemap.jpg

http://atlas.media.mit.edu/

http://atlas.media.mit.edu/about/permissions/

http://en.wikipedia.org/wiki/File:Brazil_Export_Treemap.jpg


-22-

Exhibit: 2.2 Best Subsets Regression: IBOV versus BRL/USD, S&P500 USD, ... Response is IBOV

B

r

a

z

i

l

R

e

f

e

r

e

n

c

e

I

n

M t

S M M S S e

& S S C S u r I

P C C I G I o g e n

B 5 W I I o r y a s f

R 0 T R l o r t l

L 0 I C I u d n B a

/ D h n s e C R t

U U J O i d s U O a a a i

S S I i n i i S r n n t o

Vars R-Sq R-Sq(adj) Mallows Cp S D D A l a a a D e s e e n

1 83.3 83.2 1043.3 8303.8 X

1 83.2 83.0 1053.5 8340.3 X

2 93.2 93.1 356.4 5311.9 X X

2 92.6 92.5 398.7 5545.7 X X

3 96.4 96.3 140.0 3904.4 X X X

3 95.9 95.8 173.4 4155.3 X X X

4 97.3 97.2 80.2 3406.6 X X X X

4 97.1 97.0 94.5 3533.1 X X X X

5 97.7 97.6 49.9 3118.0 X X X X X

5 97.7 97.6 54.4 3161.6 X X X X X

6 98.2 98.1 22.5 2824.6 X X X X X X

6 98.1 98.0 24.7 2848.7 X X X X X X

7 98.3 98.2 11.3 2688.3 X X X X X X X

7 98.3 98.2 13.6 2714.8 X X X X X X X

8 98.4 98.3 7.6 2632.3 X X X X X X X X

8 98.4 98.2 11.9 2683.1 X X X X X X X X

9 98.4 98.3 7.8 2622.8 X X X X X X X X X

9 98.4 98.3 8.4 2630.4 X X X X X X X X X

10 98.5 98.3 9.0 2624.7 X X X X X X X X X X

10 98.5 98.3 9.3 2628.5 X X X X X X X X X X

11 98.5 98.3 10.1 2626.2 X X X X X X X X X X X

11 98.5 98.3 10.9 2635.4 X X X X X X X X X X X

12 98.5 98.3 12.0 2636.8 X X X X X X X X X X X X

12 98.5 98.3 12.1 2638.3 X X X X X X X X X X X X

13 98.5 98.3 14.0 2649.2 X X X X X X X X X X X X X


-23-

Exhibit: 2.3 Regression Analysis: IBOV versus BRL/USD, S&P500 USD, ... The regression equation is

IBOV = 40198 - 9094 BRL/USD - 16.5 S&P500 USD + 207 WTI Oil + 1136 MSCI China

+ 766 MSCI India - 6.11 Gold USD + 94.1 Iron Ore

- 12653 Brazil Reference Interest Rate

Predictor Coef SE Coef T P VIF

Constant 40198 4441 9.05 0.000

BRL/USD -9094 1046 -8.69 0.000 5.997

S&P500 USD -16.493 2.274 -7.25 0.000 3.020

WTI Oil 207.24 20.66 10.03 0.000 5.223

MSCI China 1136.2 226.1 5.03 0.000 12.175

MSCI India 766.2 132.1 5.80 0.000 16.552

Gold USD -6.115 2.536 -2.41 0.018 17.845

Iron Ore 94.12 16.31 5.77 0.000 13.275

Brazil Reference Interest Rate -12653 3400 -3.72 0.000 2.383

S = 2632.29 R-Sq = 98.4% R-Sq(adj) = 98.3%

Analysis of Variance

Source DF SS MS F P

Regression 8 48049590619 6006198827 866.82 0.000

Residual Error 111 769115160 6928965

Total 119 48818705778

Source DF Seq SS

BRL/USD 1 40610580318

S&P500 USD 1 85761653

WTI Oil 1 2550845178

MSCI China 1 3625690582

MSCI India 1 599639253

Gold USD 1 245545588

Iron Ore 1 235578816

Brazil Reference Interest Rate 1 95949230

Unusual Observations

Obs BRL/USD IBOV Fit SE Fit Residual St Resid

65 1.92 52268 45928 700 6341 2.50R

70 1.74 65318 69565 1259 -4247 -1.84 X

77 1.63 72593 64188 931 8405 3.41R

78 1.60 65018 61449 1302 3568 1.56 X

95 1.76 67044 60361 538 6684 2.59R

96 1.74 68588 62463 499 6126 2.37R

117 1.88 52324 58791 810 -6466 -2.58R

119 1.81 56875 55095 1306 1780 0.78 X

R denotes an observation with a large standardized residual.

X denotes an observation whose X value gives it large leverage.


-24-

Exhibit: 2.4 Regression Analysis: IBOV versus BRL/USD, S&P500 USD, ... The regression equation is


+ 802 MSCI India + 59.6 Iron Ore - 12396 Brazil Reference Interest Rate


Constant 37564 4396 8.54 0.000

BRL/USD -8748 1058 -8.27 0.000 5.884

S&P500 USD -15.773 2.303 -6.85 0.000 2.967

WTI Oil 192.30 20.13 9.55 0.000 4.754

MSCI China 1015.9 225.2 4.51 0.000 11.581

MSCI India 801.5 134.0 5.98 0.000 16.348

Iron Ore 59.573 7.959 7.48 0.000 3.030


S = 2688.27 R-Sq = 98.3% R-Sq(adj) = 98.2%


Source DF SS MS F P

Regression 7 48009305790 6858472256 949.03 0.000

Residual Error 112 809399989 7226786

Total 119 48818705778

Source DF Seq SS

BRL/USD 1 40610580318

S&P500 USD 1 85761653

WTI Oil 1 2550845178

MSCI China 1 3625690582

MSCI India 1 599639253

Iron Ore 1 444609003




65 1.92 52268 46221 704 6047 2.33R

70 1.74 65318 69315 1282 -3998 -1.69 X

72 1.78 63886 68913 975 -5027 -2.01R

77 1.63 72593 63689 927 8903 3.53R

78 1.60 65018 60968 1314 4049 1.73 X

95 1.76 67044 60875 504 6170 2.34R

96 1.74 68588 62311 506 6278 2.38R

117 1.88 52324 59720 728 -7395 -2.86R




-25-

Exhibit: 2.5

Regression Analysis: IBOV versus BRL/USD, S&P500 USD, ... The regression equation is


+ 74.3 Iron Ore - 13421 Brazil Reference Interest Rate


Constant 33724 4973 6.78 0.000

BRL/USD -9294 1205 -7.71 0.000 5.840

S&P500 USD -8.926 2.284 -3.91 0.000 2.234

WTI Oil 191.18 23.02 8.31 0.000 4.753

MSCI China 2148.4 139.2 15.43 0.000 3.387

Iron Ore 74.318 8.654 8.59 0.000 2.740


S = 3074.00 R-Sq = 97.8% R-Sq(adj) = 97.7%


Source DF SS MS F P

Regression 6 47750914314 7958485719 842.21 0.000

Residual Error 113 1067791464 9449482

Total 119 48818705778

Source DF Seq SS

BRL/USD 1 40610580318

S&P500 USD 1 85761653

WTI Oil 1 2550845178

MSCI China 1 3625690582

Iron Ore 1 769714846




65 1.92 52268 45386 789 6883 2.32R

70 1.74 65318 72958 1289 -7640 -2.74RX

77 1.63 72593 65329 1013 7263 2.50R

78 1.60 65018 63810 1401 1208 0.44 X

95 1.76 67044 60854 577 6191 2.05R

96 1.74 68588 61912 574 6676 2.21R

99 1.78 70372 64272 557 6099 2.02R

117 1.88 52324 58776 813 -6452 -2.18R




-26-

Exhibit: 2.6

Regression Analysis: IBOV versus S&P500 USD, WTI Oil, ... The regression equation is

IBOV = 398 - 3.41 S&P500 USD + 272 WTI Oil + 2215 MSCI China + 100 Iron Ore



Constant 398 3025 0.13 0.896

S&P500 USD -3.415 2.669 -1.28 0.203 2.015

WTI Oil 272.40 25.17 10.82 0.000 3.758

MSCI China 2214.9 170.9 12.96 0.000 3.374

Iron Ore 100.101 9.817 10.20 0.000 2.330


S = 3780.81 R-Sq = 96.7% R-Sq(adj) = 96.5%


Source DF SS MS F P

Regression 5 47189125798 9437825160 660.24 0.000

Residual Error 114 1629579980 14294561

Total 119 48818705778

Source DF Seq SS

S&P500 USD 1 11786040814

WTI Oil 1 26578933487

MSCI China 1 6319216569

Iron Ore 1 2115805139



S&P500

Obs USD IBOV Fit SE Fit Residual St Resid

9 815 8623 16050 792 -7427 -2.01R

65 1531 52268 44077 947 8192 2.24R

70 1549 65318 73579 1583 -8261 -2.41RX

78 1280 65018 64365 1721 653 0.19 X

93 1057 61518 53870 767 7648 2.07R

95 1096 67044 59471 674 7573 2.04R

96 1115 68588 61087 693 7502 2.02R

117 1131 52324 60260 971 -7936 -2.17R




-27-

Exhibit: 2.7

Regression Analysis: IBOV versus WTI Oil, MSCI China, ... The regression equation is

IBOV = - 2461 + 257 WTI Oil + 2168 MSCI China + 106 Iron Ore



Constant -2461 2045 -1.20 0.231

WTI Oil 256.90 22.13 11.61 0.000 2.888

MSCI China 2168.0 167.4 12.95 0.000 3.220

Iron Ore 105.592 8.853 11.93 0.000 1.885


S = 3791.27 R-Sq = 96.6% R-Sq(adj) = 96.5%


Source DF SS MS F P

Regression 4 47165723308 11791430827 820.34 0.000

Residual Error 115 1652982470 14373761

Total 119 48818705778

Source DF Seq SS

WTI Oil 1 38278926565

MSCI China 1 5700810236

Iron Ore 1 2806843910



Obs WTI Oil IBOV Fit SE Fit Residual St Resid

70 94 65318 73698 1584 -8380 -2.43RX

78 140 65018 63501 1588 1516 0.44 X

93 70 61518 53343 649 8175 2.19R

95 77 67044 59026 579 8018 2.14R

96 80 68588 60698 625 7891 2.11R

112 114 66133 73746 957 -7614 -2.08R

117 79 52324 60490 957 -8165 -2.23R




-28-

Exhibit: 2.8

IBOV

Date Actual Prediction Difference WTI MSCI China Iron Ore

Interest Rate

1/31/2012 63072.31 64679.419 -1607.1093 96.83 13.23 140.35 0.055

2/29/2012 65811.73 67325.396 -1513.6663 104.82 13.81 140.4 0.084

3/30/2012 64510.97 66881.618 -2370.6475 96.92 13.67 144.66 0.023

4/30/2012 61820.26 70280.536 -8460.2756 98.87 14.71 147.65 0.009

5/31/2012 54490.41 62825.527 -8335.1168 82.93 13.87 136.27 0.023

6/29/2012 54354.63 63348.492 -8993.8618 83.21 13.91 134.62 0.000

7/31/2012 56097.05 64277.903 -8180.8531 87.21 14.35 127.94 0.014

8/31/2012 57061.45 63246.525 -6185.0751 95.07 13.77 107.8 0.000

9/28/2012 59175.86 62995.69 -3819.8304 90.69 14.58 99.47 0.000

10/31/2012 57068.18 63721.892 -6653.7119 80.24 15.44 113.95 0.000

IBOV = - 2461 + 257 WTI Oil + 2168 MSCI China + 106 Iron Ore - 23546 Brazil Reference Interest Rate

50000

55000

60000

65000

70000

75000

IBOV Index

Actual Prediction


-29-

Exhibit 3.0: Petrobras Analysis

Exhibit 3.1

Best Subsets Regression: PetroBras versus Vale, Itau, ... Response is PetroBras

32 cases used, 88 cases contain missing values

B

a

n

c

o

B

r C

a B h

d P E C S e

V I e x N h v

a t O s P x O e r

Mallows l a G c L o O l o

Vars R-Sq R-Sq(adj) Cp S e u X o C n C l n

1 57.6 56.2 44.0 4.4784 X

1 28.8 26.5 92.8 5.8023 X

2 71.7 69.7 22.1 3.7227 X X

2 68.5 66.3 27.5 3.9285 X X

3 83.3 81.6 4.3 2.9056 X X X

3 80.4 78.3 9.2 3.1499 X X X

4 85.1 82.9 3.2 2.7947 X X X X

4 85.1 82.9 3.2 2.7949 X X X X

5 86.4 83.7 3.2 2.7288 X X X X X

5 86.1 83.4 3.6 2.7548 X X X X X

6 86.9 83.8 4.2 2.7273 X X X X X X

6 86.6 83.4 4.7 2.7543 X X X X X X

7 87.0 83.2 6.1 2.7763 X X X X X X X

7 87.0 83.1 6.1 2.7778 X X X X X X X

8 87.0 82.5 8.0 2.8294 X X X X X X X X

8 87.0 82.4 8.1 2.8354 X X X X X X X X

9 87.0 81.7 10.0 2.8917 X X X X X X X X X


-30-

Exhibit 3.2

Regression Analysis: PetroBras versus Vale, Itau, BP PLC, Exxon, Chevron

The regression equation is

PetroBras = 1.48 + 1.32 Vale + 0.382 Itau - 0.0253 BP PLC + 0.667 Exxon

- 0.651 Chevron



Constant 1.476 3.221 0.46 0.648

Vale 1.3187 0.1744 7.56 0.000 15.621

Itau 0.3825 0.2701 1.42 0.160 15.353

BP PLC -0.02527 0.06052 -0.42 0.677 1.875

Exxon 0.6672 0.1089 6.12 0.000 13.981

Chevron -0.65057 0.09987 -6.51 0.000 17.119

S = 5.55705 R-Sq = 89.6% R-Sq(adj) = 89.1%


Source DF SS MS F P

Regression 5 29835.5 5967.1 193.23 0.000

Residual Error 112 3458.6 30.9

Total 117 33294.1

Source DF Seq SS

Vale 1 27884.6

Itau 1 4.2

BP PLC 1 556.4

Exxon 1 79.8

Chevron 1 1310.5


Obs Vale PetroBras Fit SE Fit Residual St Resid

65 22.7 27.040 38.357 0.964 -11.317 -2.07R

69 33.9 37.750 52.382 1.529 -14.632 -2.74R

70 37.7 47.815 58.976 1.766 -11.161 -2.12R

77 39.8 70.500 55.360 1.724 15.140 2.87R

78 35.8 70.830 48.324 1.843 22.506 4.29R

80 26.5 52.740 38.862 0.755 13.878 2.52R

81 19.1 43.950 29.701 1.123 14.249 2.62R

107 31.7 32.440 44.898 1.405 -12.458 -2.32R



-31-

Exhibit 3.3

Regression Analysis: PetroBras versus Vale, Itau, BP PLC, Exxon


PetroBras = - 8.64 + 1.18 Vale - 0.027 Itau + 0.142 BP PLC + 0.108 Exxon



Constant -8.642 3.299 -2.62 0.010

Vale 1.1813 0.2024 5.84 0.000 15.392

Itau -0.0275 0.3071 -0.09 0.929 14.520

BP PLC 0.14232 0.06404 2.22 0.028 1.536

Exxon 0.10771 0.07834 1.37 0.172 5.291

S = 6.49651 R-Sq = 85.7% R-Sq(adj) = 85.2%


Source DF SS MS F P

Regression 4 28525.0 7131.2 168.97 0.000


Total 117 33294.1

Source DF Seq SS

Vale 1 27884.6

Itau 1 4.2

BP PLC 1 556.4

Exxon 1 79.8


Obs Vale PetroBras Fit SE Fit Residual St Resid

69 33.9 37.750 50.772 1.763 -13.022 -2.08R

77 39.8 70.500 57.615 1.974 12.885 2.08R

78 35.8 70.830 52.557 2.016 18.273 2.96R

80 26.5 52.740 39.066 0.882 13.674 2.12R

81 19.1 43.950 29.047 1.308 14.903 2.34R

89 19.1 44.030 28.093 0.809 15.937 2.47R

90 17.6 40.980 26.104 1.022 14.876 2.32R

93 23.1 45.900 33.093 1.483 12.807 2.02R



-32-

Exhibit 3.4

Regression Analysis: PetroBras versus Itau, BP PLC, Exxon


PetroBras = - 15.0 + 1.49 Itau + 0.134 BP PLC + 0.238 Exxon


Constant -14.978 3.475 -4.31 0.000

Itau 1.4942 0.1825 8.19 0.000 4.145

BP PLC 0.13383 0.07209 1.86 0.066 1.542

Exxon 0.23797 0.08445 2.82 0.006 4.986

S = 7.31514 R-Sq = 81.8% R-Sq(adj) = 81.3%


Source DF SS MS F P

Regression 3 27824.2 9274.7 173.32 0.000


Total 119 34031.5

Source DF Seq SS

Itau 1 26404.9

BP PLC 1 994.4

Exxon 1 424.9


Obs Itau PetroBras Fit SE Fit Residual St Resid

73 16.9 55.480 39.439 1.231 16.041 2.22R

74 18.4 58.670 41.946 1.185 16.724 2.32R

77 22.3 70.500 49.220 1.522 21.280 2.97R

78 18.5 70.830 42.893 1.296 27.937 3.88R

79 19.4 55.910 41.318 1.014 14.592 2.01R

80 17.3 52.740 37.584 0.952 15.156 2.09R



-33-

Exhibit 3.5

Regression Analysis: PetroBras versus Itau, Exxon The regression equation is

PetroBras = - 11.7 + 1.34 Itau + 0.329 Exxon


Constant -11.657 3.010 -3.87 0.000

Itau 1.3401 0.1643 8.16 0.000 3.289

Exxon 0.32945 0.06929 4.75 0.000 3.289

S = 7.39124 R-Sq = 81.2% R-Sq(adj) = 80.9%


Source DF SS MS F P

Regression 2 27640 13820 252.97 0.000

Residual Error 117 6392 55

Total 119 34031

Source DF Seq SS

Itau 1 26405

Exxon 1 1235


Obs Itau PetroBras Fit SE Fit Residual St Resid

73 16.9 55.480 39.497 1.244 15.983 2.19R

74 18.4 58.670 41.706 1.190 16.964 2.33R

77 22.3 70.500 47.516 1.226 22.984 3.15R

78 18.5 70.830 42.121 1.240 28.709 3.94R

79 19.4 55.910 40.790 0.983 15.120 2.06R

80 17.3 52.740 37.850 0.950 14.890 2.03R

103 22.4 36.400 38.010 2.041 -1.610 -0.23 X

105 24.2 36.270 41.104 2.201 -4.834 -0.69 X

120 18.6 24.850 41.140 1.092 -16.290 -2.23R




-34-

Exhibit 3.6

0.00

10.00

20.00

30.00

40.00

50.00

60.00

PetroBras ADR price for 2012

Actual Predicted

brazilian stock exchange - babson collegefaculty.babson.edu/goldstein/teaching/fin3560fall2012/2012...

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