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

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

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.

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

Brazil: Stock market capitalization, billion USD: The latest value from 2024 is 658.91 billion U.S. dollars, a decline from 991.2 billion U.S. dollars in 2023. In comparison, the world average is 1647.20 billion U.S. dollars, based on data from 68 countries. Historically, the average for Brazil from 2000 to 2024 is 800.44 billion U.S. dollars. The minimum value, 126.76 billion U.S. dollars, was reached in 2002 while the maximum of 1545.57 billion U.S. dollars was recorded in 2010.

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

Graph and download economic data for Stock Market Capitalization to GDP for Brazil (DDDM01BRA156NWDB) from 2000 to 2020 about market cap, Brazil, stock market, capital, and GDP.

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.

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.

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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

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

This dataset provides a comprehensive overview of the Brazilian stock market, covering various sectors and industries from 2018 to 2023. Each row in the dataset represents a specific asset, identified by its ticker on B3 (the Brazilian stock exchange). The dataset includes detailed information such as sector, industry, trading dates, opening price, closing price, trading volume, dividends, dividend yield, and P/E (price/earnings) ratio. Additionally, it contains daily historical price data for the assets over time.

Key Columns:

•  Ticker: The asset’s code on the stock exchange.
•  Sector: The sector in which the asset operates.
•  Industry: The specific industry within the sector.
•  Date: The reference date for the data.
•  Open: The asset’s opening price on the specified date.
•  Price: The asset’s closing price on the specified date.
•  Volume: The trading volume of the asset.
•  Dividend: The amount of dividends paid.
•  Dividend Yield: The dividend yield as a percentage of the price.
•  P/E Ratio: The price-to-earnings ratio.

Applications:

This dataset is ideal for stock performance analysis, sector and industry studies, investment strategy development, and machine learning models focused on market predictions. It can be used by investors, market analysts, researchers, and finance professionals interested in examining the behavior of the Brazilian stock market over five years.

Key information about Brazil Market Capitalization

• Brazil Market Capitalization accounted for 847.097 USD bn in Oct 2025, compared with a percentage of 844.883 USD bn in the previous month
• Brazil Market Capitalization is updated monthly, available from Jan 1995 to Oct 2025
• 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: Stock market value traded, percent of GDP: The latest value from 2024 is 41.74 percent, a decline from 54.73 percent in 2023. In comparison, the world average is 44.48 percent, based on data from 33 countries. Historically, the average for Brazil from 1979 to 2024 is 23.6 percent. The minimum value, 1.01 percent, was reached in 1989 while the maximum of 93.06 percent was recorded in 2020.

Actual value and historical data chart for Brazil Stock Market Capitalization To GDP Percent

Brazil: Stock market capitalization w/o top 10 firms, percent of total market cap: The latest value from 2019 is 53 percent, a decline from 54.71 percent in 2018. In comparison, the world average is 42.74 percent, based on data from 23 countries. Historically, the average for Brazil from 1998 to 2019 is 49.9 percent. The minimum value, 43 percent, was reached in 2017 while the maximum of 62.55 percent was recorded in 1998.

Actual value and historical data chart for Brazil Stock Market Total Value Traded To GDP Percent

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.

Graph and download economic data for Stock Market Turnover Ratio (Value Traded/Capitalization) for Brazil (DDEM01BRA156NWDB) from 2000 to 2020 about Brazil, ratio, and stock market.

Actual value and historical data chart for Brazil Stock Market Turnover Ratio Percent