Brazilian Stock Exchange - Babson Collegefaculty.babson.edu/goldstein/Teaching/FIN3560Fall2012/2012...
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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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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]
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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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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 ]
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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:
December 31st, 1991 through December 31st, 2001
Exhibit 1.3:
December 31st, 2001 through December 31st, 2011
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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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.
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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Exhibit: 2.4 Regression Analysis: IBOV versus BRL/USD, S&P500 USD, ... The regression equation is
IBOV = 37564 - 8748 BRL/USD - 15.8 S&P500 USD + 192 WTI Oil + 1016 MSCI China
+ 802 MSCI India + 59.6 Iron Ore - 12396 Brazil Reference Interest Rate
Predictor Coef SE Coef T P VIF
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
Brazil Reference Interest Rate -12396 3471 -3.57 0.001 2.380
S = 2688.27 R-Sq = 98.3% R-Sq(adj) = 98.2%
Analysis of Variance
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
Brazil Reference Interest Rate 1 92179802
Unusual Observations
Obs BRL/USD IBOV Fit SE Fit Residual St Resid
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
R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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Exhibit: 2.5
Regression Analysis: IBOV versus BRL/USD, S&P500 USD, ... The regression equation is
IBOV = 33724 - 9294 BRL/USD - 8.93 S&P500 USD + 191 WTI Oil + 2148 MSCI China
+ 74.3 Iron Ore - 13421 Brazil Reference Interest Rate
Predictor Coef SE Coef T P VIF
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
Brazil Reference Interest Rate -13421 3964 -3.39 0.001 2.375
S = 3074.00 R-Sq = 97.8% R-Sq(adj) = 97.7%
Analysis of Variance
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
Brazil Reference Interest Rate 1 108321737
Unusual Observations
Obs BRL/USD IBOV Fit SE Fit Residual St Resid
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
R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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
- 23897 Brazil Reference Interest Rate
Predictor Coef SE Coef T P VIF
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
Brazil Reference Interest Rate -23897 4580 -5.22 0.000 2.096
S = 3780.81 R-Sq = 96.7% R-Sq(adj) = 96.5%
Analysis of Variance
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
Brazil Reference Interest Rate 1 389129789
Unusual Observations
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
R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
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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
- 23546 Brazil Reference Interest Rate
Predictor Coef SE Coef T P VIF
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
Brazil Reference Interest Rate -23546 4585 -5.14 0.000 2.088
S = 3791.27 R-Sq = 96.6% R-Sq(adj) = 96.5%
Analysis of Variance
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
Brazil Reference Interest Rate 1 379142597
Unusual Observations
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
R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
-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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
-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
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
-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
118 cases used, 2 cases contain missing values
Predictor Coef SE Coef T P VIF
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%
Analysis of Variance
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
Unusual Observations
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
R denotes an observation with a large standardized residual.
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
-31-
Exhibit 3.3
Regression Analysis: PetroBras versus Vale, Itau, BP PLC, Exxon
The regression equation is
PetroBras = - 8.64 + 1.18 Vale - 0.027 Itau + 0.142 BP PLC + 0.108 Exxon
118 cases used, 2 cases contain missing values
Predictor Coef SE Coef T P VIF
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%
Analysis of Variance
Source DF SS MS F P
Regression 4 28525.0 7131.2 168.97 0.000
Residual Error 113 4769.1 42.2
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
Unusual Observations
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
R denotes an observation with a large standardized residual.
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
-32-
Exhibit 3.4
Regression Analysis: PetroBras versus Itau, BP PLC, Exxon
The regression equation is
PetroBras = - 15.0 + 1.49 Itau + 0.134 BP PLC + 0.238 Exxon
Predictor Coef SE Coef T P VIF
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%
Analysis of Variance
Source DF SS MS F P
Regression 3 27824.2 9274.7 173.32 0.000
Residual Error 116 6207.3 53.5
Total 119 34031.5
Source DF Seq SS
Itau 1 26404.9
BP PLC 1 994.4
Exxon 1 424.9
Unusual Observations
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
R denotes an observation with a large standardized residual.
Brazilian Stock Exchange Almajali, Bastos-Moreira, Benavides, & Parikh
-33-
Exhibit 3.5
Regression Analysis: PetroBras versus Itau, Exxon The regression equation is
PetroBras = - 11.7 + 1.34 Itau + 0.329 Exxon
Predictor Coef SE Coef T P VIF
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%
Analysis of Variance
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
Unusual Observations
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
R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.