Brazil's main stock market index, the IBOVESPA, rose to 159976 points on December 2, 2025, gaining 0.86% from the previous session. Over the past month, the index has climbed 6.33% and is up 26.83% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Brazil. Brazil Stock Market (BOVESPA) - values, historical data, forecasts and news - updated on December of 2025.

Key information about Brazil Month End

• Brazil Month End closed at 149,540.4 points in Oct 2025, compared with 146,237.0 points at the previous month end
• Brazil Index: B3: IBOV: Month End data is updated monthly, available from Jan 1983 to Oct 2025, with an average number of 19,544.7 points
• The data reached an all-time high of 149,540.4 points in Oct 2025 and a record low of 0.0 points in Jan 1983

The main stock market in Brazil is located in the city of São Paulo, which was also the Brazilian region with the majority of coronavirus infections. Right after the COVID-19 pandemic reached Brazil with the first confirmed case on *****************, the IBOVESPA stock market index sank to ******* Brazilian reals on ***********. On **************, this index reached the lowest value since the beginning of the year, at ****** Brazilian reals. In ***********, the stock market was starting to stabilize, at an average value of ****** Brazilian reals. By the beginning of 2021, the index achieved values comparable to those observed before the outbreak.

Photo by Maxim Hopman on Unsplash.

Introduction

According to Economatica, a company specializing in the Latin American stock market, the Brazilian stock exchange market, governed by Brasil, Bolsa, Balcão (B3), exchanged BRL ~25.9 billion per day in the first half of 2020, during the coronavirus epidemic. Furthermore, it is estimated that in this same period there was an 18% growth in the number of Brazilian investors, totaling ~2.6 million active investors. Therefore, the financial market moves a large amount of values and, consequently, produces a vast amount of information and data daily; These data represent the movements of shares, their respective prices, dollar exchange values, and so on. This dataset contains daily stock values and information about their companies.

Inspiration

• Data Analysis - Spark
• Price Prediction - Regression task
• Best Group of Stocks - Association Rules task

This dataset provides an environment (Data Warehouse-like) for analysis and visualization of financial business for users of decision support systems. Specifically, the data allow compare different assets (i.e. stocks) listed on B3, according to the sectors of the economy in which these assets operate. For example, with this Data Warehouse, the user will be able to answer questions similar to this one: What are the most profitable sectors for investment in a given period of time? In this way, the user can identify which are the sectors that are standing out, as well as which are the most profitable companies in the sector.

Dataset

https://i.imgur.com/28Mf0sN.png" alt="Data Warehouse">

This dataset is split into five files: - dimCoin.csv - Dimension table with information about the coins. - dimCompany.csv - Dimension table with information about the companies. - dimTime.csv - Dimension table with information about the datetime. - factCoins.csv - Fact table with coin value over time. - factStocks.csv - Fact table with stock prices over time.

Source

The data were available by B3. You can access in https://www.b3.com.br/en_us/market-data-and-indices/ .I just structure and model the data as Data Warehouse tables. You can access my code in https://github.com/leomaurodesenv/b3-stock-indexes

Graph and download economic data for Financial Market: Share Prices for Brazil (SPASTT01BRM661N) from Jan 1980 to Oct 2025 about Brazil and stock market.

Content

Merging the contents of all files from 1995 onwards. COTAHIST_AAAATXT from B3 site

Data source

http://www.b3.com.br/en_us/market-data-and-indices/data-services/market-data/historical-data/equities/historical-quotes/

Basic Concepts

The COTAHIST.AAAA.TXT file contains the historical quotation data relative to the negotiation of all financial market papers during a one-year period, classified by the fields: Type of Register, Date of Exchange, BDI (Daily Information Bulletin) Code, Company Name and Negotiation Code. This subdivision can be modified according to the user’s preferences / requirements, according to the equipment and software available. The name of the file identifies the corresponding year. Ex.: COTAHIST.1990.TXT, COTAHIST.1991.TXT, Etc.

Attached Tables

CODBDI Table

02 - Round Lot
05 - Bmfbovespa Regulations Sanction
06 - Stocks Of Cos. Under Reorganization
07 - Extrajudicial Recovery
08 - Judicial Recovery
09 - Temporary Especial Management
10 - Rights And Receipts
11 - Intervention
12 - Real Estate Funds
14 - Investment Certificates / Debentures / Public Debt Securities
18 - Bonds
22 - Bonuses (Private)
26 - Policies / Bonuses / Public Securities
32 - Exercise Of Index Call Options
33 - Exercise Of Index Put Options
38 - Exercise Of Call Options
42 - Exercise Of Put Options
46 - Auction Of Non-Quoted Securities
48 - Privatization Auction
49 - Auction Of Economical Recovery Fund Of Espirito Santo State
50 - Auction
51 - Finor Auction
52 - Finam Auction
53 - Fiset Auction
54 - Auction Of Shares In Arrears
56 - Sales By Court Order
58 - Others
60 - Share Swap
61 - Goal
62 - Term
66 - Debentures With Maturity Dates Of Up To 3 Years
68 - Debentures With Maturity Dates Greater Than 3 Years
70 - Forward With Continuous Movement
71 - Forward With Gain Retention
74 - Index Call Options
75 - Index Put Options
78 - Call Options
82 - Put Options
83 - Debentures And Promissory Notes Bovespafix
84 - Debentures And Promissory Notes Somafix
90 - Registered Term View
96 - Factionary
99 - Grand Tota

Actual value and historical data chart for Brazil Stock Market Return Percent Year On Year

Brazil Market Capitalization: Sao Paulo Stock Exchange: USD data was reported at 908.108 USD bn in Nov 2025. This records an increase from the previous number of 847.097 USD bn for Oct 2025. Brazil Market Capitalization: Sao Paulo Stock Exchange: USD data is updated monthly, averaging 1,153.445 USD bn from Jan 1995 (Median) to Nov 2025, with 371 observations. The data reached an all-time high of 1,593.579 USD bn in Apr 2011 and a record low of 109.250 USD bn in Oct 2002. Brazil Market Capitalization: Sao Paulo Stock Exchange: USD data remains active status in CEIC and is reported by B3 S.A. - Brasil, Bolsa, Balcão. The data is categorized under Global Database’s Brazil – Table BR.ZA: B3 S.A. – Brasil, Bolsa, Balcao: Market Capitalization: USD.

Techsalerator's Corporate Actions Dataset in Brazil offers a comprehensive collection of data fields related to corporate actions, providing valuable insights for investors, traders, and financial institutions. This dataset includes crucial information about the various financial instruments of all 475 companies traded on the B3 S.A. - Securities, Commodities and Futures Exchange (BVMF).

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Top 5 used data fields in the Corporate Actions Dataset for Brazil:

• Dividend Declaration Date: The date on which a company's board of directors announces the dividend payout to its shareholders. This information is crucial for investors who rely on dividends as a source of income.

• Stock Split Ratio: The ratio by which a company's shares are split to increase liquidity and affordability. This field is essential for understanding changes in share structure.

• Merger Announcement Date: The date on which a company officially announces its intention to merge with another entity. This field is crucial for investors assessing the impact of potential mergers on their investments.

• Rights Issue Record Date: The date on which shareholders must be on the company's books to be eligible for participating in a rights issue. This data helps investors plan their participation in fundraising events.

• Bonus Issue Ex-Date: The date on which a company's shares start trading without the value of the bonus issue. This information is vital for investors to adjust their portfolios accordingly.

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Top 5 corporate actions in Brazil:

Mergers and Acquisitions (M&A): Brazil's large and diverse economy often witnesses M&A activities across various industries, including banking, consumer goods, energy, and technology. Notable transactions include mergers, acquisitions, and strategic partnerships that reshape industry landscapes and enhance market competitiveness.

Initial Public Offerings (IPOs): IPOs of Brazilian companies on domestic and international stock exchanges are significant corporate actions. IPOs offer companies access to capital markets and enable investors to participate in the growth potential of newly listed companies.

Infrastructure Projects: Brazil frequently undertakes infrastructure projects, such as transportation, energy, and telecommunications. Corporate actions in this sector involve public-private partnerships, concessions, and investments to enhance national infrastructure.

Energy Sector Investments: Given Brazil's reliance on renewable energy sources like hydropower, wind, and solar, corporate actions in the energy sector include investments in energy generation and distribution, renewable energy projects, and regulatory changes affecting the industry.

Financial Sector Reforms: Reforms and regulatory changes within Brazil's financial sector can lead to significant corporate actions. These may include changes in banking regulations, fintech innovation, and adjustments to monetary and fiscal policies.

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Top 5 financial instruments with corporate action Data in Brazil

B3 Stock Exchange Domestic Index (IBOVESPA): The main index that tracks the performance of domestic companies listed on B3, the main stock exchange in Brazil. This index reflects the performance of the largest publicly traded companies in Brazil.

B3 Stock Exchange Foreign Company Index: An index that tracks the performance of foreign companies listed on B3, showcasing the international diversity of Brazil's stock market.

SuperMercado Brasil: A Brazil-based supermarket chain with operations across various regions. SuperMercado Brasil focuses on providing essential products to local communities and contributing to the retail sector's growth.

FinanceBrasil Group: A financial services provider in Brazil with a focus on inclusive finance, digital banking, and innovative financial solutions to meet the diverse needs of customers.

AgriTech Brasil: A leading producer and distributor of certified crop seeds, agricultural technology, and solutions, supporting sustainable farming practices and food security in Brazil and beyond.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Brazil, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Dividend Declaration Date Stock Split Ratio Merger Announcement Date Rights Issue Record Date Bonus Issue Ex-Date Stock Buyback Date Spin-Off Announcement Date Dividend Record Date Merger Effective Date Rights Issue Subscription Price ‍

Q&A:

How much does the Corporate Actions Dataset cost in Brazil?

The cost of the Corporate Actions Dataset may vary depending on factors such as the number of data fields, the frequenc...

Ibovespa Stocks

Context

Here you will find information about all the stocks negotiated in the B3 stock exchange from 1994 to 2020. All the stocks that compose the Ibovespa Index are present in this dataset.

Acknowledgements

All data presented here was constructed by the information provided by B3 in this site.

Graph and download economic data for Financial Market: Share Prices for Brazil (SPASTT01BRQ661N) from Q1 1980 to Q3 2025 about Brazil and stock market.

As of October 2024, *********, a state-owned corporation in the ********* industry, was the largest public company in Brazil, with a market capitalization of nearly ** billion U.S. dollars. ***********, a Brazil-based *************** platform, was second in the ranking, with a market cap of ***** billion U.S. dollars. Brazilian financial services company ************* followed closely and came in third, amounting to almost ** billion U.S. dollars in market cap.

Historical dataset of the Brazil Stock Market PE Ratio, covering values from 1996-04-01 to 2025-12-02, with the latest releases and long-term trends. Available for free download in CSV format.

Brazil B3 Index: Special Corporate Governance Stock Index (IGC) data was reported at 15,923.080 25Jun2001=1000 in 11 Jul 2019. This records a decrease from the previous number of 16,023.810 25Jun2001=1000 for 10 Jul 2019. Brazil B3 Index: Special Corporate Governance Stock Index (IGC) data is updated daily, averaging 6,746.940 25Jun2001=1000 from Jun 2001 (Median) to 11 Jul 2019, with 4465 observations. The data reached an all-time high of 16,023.810 25Jun2001=1000 in 10 Jul 2019 and a record low of 758.540 25Jun2001=1000 in 14 Sep 2001. Brazil B3 Index: Special Corporate Governance Stock Index (IGC) data remains active status in CEIC and is reported by B3 S.A.. The data is categorized under Daily Database’s Financial and Futures Market – Table BR.ZA001: B3: Index: Daily.

Brazil's B3 Stock Exchange is the one and only public financial market of the 13th largest economy in the world with a 2021 market cap of R$ 5.2 trillion BRL.

With the goal of improving financial literacy, this dataset contains more than 400 stock listings that are updated daily for the purposes of providing data for quantitative analysis.

How to use this dataset

• Create a time series regression model to predict ^IBOV value and/or stock prices.
• Explore the yield and volatility of the stocks listed.
• Identify high and low performance stocks among the list.

Highlighted Notebooks

• Your kernel can be featured here!
• More datasets

Acknowledgements

License

CC0: Public Domain

Splash banner

Stonks by unknown memer.

Description

The "B3 Stock Market Dataset: Brazilian Stock Exchange Data" is a comprehensive collection of stock trading data from the B3 (Bolsa de Valores, Mercadorias e Futuros de São Paulo) exchange in Brazil. This dataset provides a detailed record of trading activities for various assets, offering insights into stock market trends and behaviors.

###

The Python algorithm provided is essential for transforming the raw data into an organized DataFrame for analysis. Please make sure to follow the provided algorithm instructions to process and analyze the B3 stock market data effectively.

The algorithm is at the end of the description

Features

• TIPREG: Type of record.
• DATPRE: Trading date.
• CODNEG: Asset's trading code.
• NOMRES: Abbreviated name of the issuing company.
• ESPECI: Specification of the type of share or asset.
• PREABE: Opening price.
• PREMAX: Highest price during the trading session.
• PREMIN: Lowest price during the trading session.
• PREMED: Average price during the trading session.
• PREULT: Closing price.
• PREOFC: Best bid price.
• PREOFV: Best ask price.
• QUATOT: Total quantity of traded securities.
• VOLTOT: Total trading volume in currency units.
• CODISI: ISIN code of the asset.
• DISMES: Number of working days in the month.

Usage of Algorithm

The provided algorithm is mandatory for data processing and analysis in tabular format. It ensures that the data is properly organized and processed according to the specified attributes. ``` def tratamento(caminho_arquivo): # File Path ( TXT ) # Lista para armazenar os dados organizados ordem = []

# Leitura do arquivo de dados brutos
with open(caminho_arquivo, 'r') as arquivo:
  linhas = arquivo.readlines()

# Configuração da barra de carregamento
with tqdm(total=len(linhas), desc='Processando', bar_format='{l_bar}{bar}| {n_fmt}/{total_fmt}') as pbar:
  # Iteração pelas linhas do arquivo
  for linha in linhas:

    if linhas == '':
      continue

    # Extrai as informações de cada campo
    tipreg = int(linha[0:2])
    datpre = pd.to_datetime(linha[2:10], format='%Y%m%d', errors='coerce')
    if pd.isnull(datpre):
      continue
    codneg = linha[12:24].strip()
    nomres = linha[27:39].strip()
    especi = linha[39:49].strip()
    preabe = float(linha[56:69]) / 100
    premax = float(linha[69:82]) / 100
    premin = float(linha[82:95]) / 100
    premed = float(linha[95:108]) / 100
    preult = float(linha[108:121]) / 100
    preofc = float(linha[121:134]) / 100
    preofv = float(linha[134:147]) / 100
    quatot = int(linha[152:170])
    voltot = float(linha[170:188]) / 100
    codisi = linha[245:257].strip()
    dismes = int(linha[257:260]) if linha[257:260].strip() else 0

    # Adiciona os dados à lista
    ordem.append([tipreg, datpre, codneg, nomres, especi, preabe, premax, premin,
                 premed, preult, preofc, preofv, quatot, voltot, codisi, dismes])

    # Atualiza a barra de carregamento
    pbar.update(1)

# Criação do DataFrame com os dados organizados
df = pd.DataFrame(ordem, columns=['TIPREG', 'DATPRE', 'CODNEG', 'NOMRES', 'ESPECI',
                        'PREABE', 'PREMAX', 'PREMIN', 'PREMED', 'PREULT',
                        'PREOFC', 'PREOFV', 'QUATOT', 'VOLTOT', 'CODISI', 'DISMES'])

df_dict = {
  'TIPREG': 'Tipo de registro',
  'DATPRE': 'Data de pregão',
  'CODNEG': 'Código de negociação do ativo',
  'NOMRES': 'Nome resumido da empresa emissora do ativo',
  'ESPECI': 'Especificação do tipo de ação ou ativo',
  'PREABE': 'Preço de abertura',
  'PREMAX': 'Preço máximo',
  'PREMIN': 'Preço mínimo',
  'PREMED': 'Preço médio',
  'PREULT': 'Preço de fechamento',
  'PREOFC': 'Preço da melhor oferta de compra',
  'PREOFV': 'Preço da melhor oferta de venda',
  'QUATOT': 'Quantidade total de títulos negociados',
  'VOLTOT': 'Volume total de títulos negociados',
  'CODISI': 'Código ISIN do ativo',
  'DISMES': 'Número de dias úteis do mês'
}

df.rename(columns=df_dict)

# Exibe o DataFrame
return df

Graph and download economic data for Share Prices: All Shares/Broad: Total for Brazil (SPASTT01BRA657N) from 1989 to 2024 about Brazil and stock market.

Folks, this data was scraped from CVM's Open Data API, which is equivalent to SEC.

The data refer to the quarterly balance sheets of companies listed on the Brazilian stock exchange. This dataset is updated monthly!

https://media.giphy.com/media/ZCyYT0bdwZECPpxHDk/giphy.gif">

Look how i've used this data: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F8082416%2F39ae1be51491feedea317e566c28beef%2FCapturar3.PNG?generation=1677470019840711&alt=media" alt=""> https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F8082416%2F1f38d2554cf326babb9ef0b03aaf5c4b%2FCapturar4.PNG?generation=1677470028625106&alt=media" alt="">

Tableau Link: https://public.tableau.com/app/profile/marcus.vinicius3800/viz/Fashioncompaniesfundamentalsstockanalysis/Capa

CVM Open data: https://dados.cvm.gov.br/dataset/?q=cia

Email: marcus.rodrigues4003@gmail.com Whatsapp: (11)94937-0306

Context

My objective sharing this data is to make studies about stock quotes using real data from the Brazilian stock market.

Content

This is the daily stock quotes from B3 for the period from 2009 to 2019. B3 is the unique stock exchange in Brazil, here we don't have competition in this sector as in USA.

Acknowledgements

This data is directly extracted from B3 site, without changes.

💥This dataset contains historical information about stocks (PETR4.SA, MGLU3.SA, ABEV3.SA, BBDC4.SA, ITUB4.SA, RAIZ4.SA, VALE3.SA) traded on the Brazilian stock exchange. The dataset was collected from Yahoo Finance and has records updated until 01/17/2023.

It includes variables such as the opening price, high and low change, closing price, trading volume and stock name for each stock.

It can be used by financial analysts, investors, and students to study and understand how stocks work and how stock prices are affected by different economic and political events. This dataset can also be used to train forecasting models and develop stock trading strategies.

✨**Dataset Variables**:

• Date: Day the share was traded
• Open: Open price of the share
• High: maximum variation in the day
• Low: Minimum variation in the day
• Close: Closing price of the stock
• Volume: Trading volume
• Stock Name: Traded stock name

👀The data was taken from the Yahoo Finance website: https://br.financas.yahoo.com/