100+ datasets found
  1. United States US: No of Listed Domestic Companies: Total

    • ceicdata.com
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    CEICdata.com, United States US: No of Listed Domestic Companies: Total [Dataset]. https://www.ceicdata.com/en/united-states/financial-sector/us-no-of-listed-domestic-companies-total
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    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    United States
    Variables measured
    Turnover
    Description

    United States US: Number of Listed Domestic Companies: Total data was reported at 4,336.000 Unit in 2017. This records an increase from the previous number of 4,331.000 Unit for 2016. United States US: Number of Listed Domestic Companies: Total data is updated yearly, averaging 5,930.000 Unit from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 8,090.000 Unit in 1996 and a record low of 4,102.000 Unit in 2012. United States US: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  2. w

    Dataset of public companies in the United States

    • workwithdata.com
    Updated Nov 27, 2024
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    Work With Data (2024). Dataset of public companies in the United States [Dataset]. https://www.workwithdata.com/datasets/public-companies?f=1&fcol0=country&fop0=%3D&fval0=United+States
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    Dataset updated
    Nov 27, 2024
    Dataset authored and provided by
    Work With Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    This dataset is about companies in the United States. It has 4,752 rows. It features 17 columns including sector, industry, website, and city.

  3. F

    Stocks, Value of Shares Sold on the New York Stock Exchange for United...

    • fred.stlouisfed.org
    json
    Updated Aug 15, 2012
    + more versions
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    (2012). Stocks, Value of Shares Sold on the New York Stock Exchange for United States [Dataset]. https://fred.stlouisfed.org/series/M11003USM144NNBR
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 15, 2012
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Stocks, Value of Shares Sold on the New York Stock Exchange for United States (M11003USM144NNBR) from Jan 1885 to Dec 1920 about stock market and USA.

  4. Stock Portfolio Data with Prices and Indices

    • kaggle.com
    Updated Mar 23, 2025
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    Nikita Manaenkov (2025). Stock Portfolio Data with Prices and Indices [Dataset]. http://doi.org/10.34740/kaggle/dsv/11140976
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 23, 2025
    Dataset provided by
    Kaggle
    Authors
    Nikita Manaenkov
    License

    https://www.gnu.org/licenses/gpl-3.0.htmlhttps://www.gnu.org/licenses/gpl-3.0.html

    Description

    This dataset consists of five CSV files that provide detailed data on a stock portfolio and related market performance over the last 5 years. It includes portfolio positions, stock prices, and major U.S. market indices (NASDAQ, S&P 500, and Dow Jones). The data is essential for conducting portfolio analysis, financial modeling, and performance tracking.

    1. Portfolio

    This file contains the portfolio composition with details about individual stock positions, including the quantity of shares, sector, and their respective weights in the portfolio. The data also includes the stock's closing price.

    • Columns:
      • Ticker: The stock symbol (e.g., AAPL, TSLA)
      • Quantity: The number of shares in the portfolio
      • Sector: The sector the stock belongs to (e.g., Technology, Healthcare)
      • Close: The closing price of the stock
      • Weight: The weight of the stock in the portfolio (as a percentage of total portfolio)

    2. Portfolio Prices

    This file contains historical pricing data for the stocks in the portfolio. It includes daily open, high, low, close prices, adjusted close prices, returns, and volume of traded stocks.

    • Columns:
      • Date: The date of the data point
      • Ticker: The stock symbol
      • Open: The opening price of the stock on that day
      • High: The highest price reached on that day
      • Low: The lowest price reached on that day
      • Close: The closing price of the stock
      • Adjusted: The adjusted closing price after stock splits and dividends
      • Returns: Daily percentage return based on close prices
      • Volume: The volume of shares traded that day

    3. NASDAQ

    This file contains historical pricing data for the NASDAQ Composite index, providing similar data as in the Portfolio Prices file, but for the NASDAQ market index.

    • Columns:
      • Date: The date of the data point
      • Ticker: The stock symbol (for NASDAQ index, this will be "IXIC")
      • Open: The opening price of the index
      • High: The highest value reached on that day
      • Low: The lowest value reached on that day
      • Close: The closing value of the index
      • Adjusted: The adjusted closing value after any corporate actions
      • Returns: Daily percentage return based on close values
      • Volume: The volume of shares traded

    4. S&P 500

    This file contains similar historical pricing data, but for the S&P 500 index, providing insights into the performance of the top 500 U.S. companies.

    • Columns:
      • Date: The date of the data point
      • Ticker: The stock symbol (for S&P 500 index, this will be "SPX")
      • Open: The opening price of the index
      • High: The highest value reached on that day
      • Low: The lowest value reached on that day
      • Close: The closing value of the index
      • Adjusted: The adjusted closing value after any corporate actions
      • Returns: Daily percentage return based on close values
      • Volume: The volume of shares traded

    5. Dow Jones

    This file contains similar historical pricing data for the Dow Jones Industrial Average, providing insights into one of the most widely followed stock market indices in the world.

    • Columns:
      • Date: The date of the data point
      • Ticker: The stock symbol (for Dow Jones index, this will be "DJI")
      • Open: The opening price of the index
      • High: The highest value reached on that day
      • Low: The lowest value reached on that day
      • Close: The closing value of the index
      • Adjusted: The adjusted closing value after any corporate actions
      • Returns: Daily percentage return based on close values
      • Volume: The volume of shares traded

    Personal Portfolio Data

    This data is received using a custom framework that fetches real-time and historical stock data from Yahoo Finance. It provides the portfolio’s data based on user-specific stock holdings and performance, allowing for personalized analysis. The personal framework ensures the portfolio data is automatically retrieved and updated with the latest stock prices, returns, and performance metrics.

    This part of the dataset would typically involve data specific to a particular user’s stock positions, weights, and performance, which can be integrated with the other files for portfolio performance analysis.

  5. United States US: Market Capitalization: Listed Domestic Companies

    • ceicdata.com
    Updated Apr 30, 2021
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    CEICdata.com (2021). United States US: Market Capitalization: Listed Domestic Companies [Dataset]. https://www.ceicdata.com/en/united-states/financial-sector/us-market-capitalization-listed-domestic-companies
    Explore at:
    Dataset updated
    Apr 30, 2021
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    United States
    Variables measured
    Turnover
    Description

    United States US: Market Capitalization: Listed Domestic Companies data was reported at 32,120.703 USD bn in 2017. This records an increase from the previous number of 27,352.201 USD bn for 2016. United States US: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 11,322.354 USD bn from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 32,120.703 USD bn in 2017 and a record low of 1,263.561 USD bn in 1981. United States US: Market Capitalization: Listed Domestic Companies data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  6. United States US: Stocks Traded: Total Value

    • ceicdata.com
    Updated Mar 15, 2023
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    CEICdata.com (2023). United States US: Stocks Traded: Total Value [Dataset]. https://www.ceicdata.com/en/united-states/financial-sector/us-stocks-traded-total-value
    Explore at:
    Dataset updated
    Mar 15, 2023
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    United States
    Variables measured
    Turnover
    Description

    United States US: Stocks Traded: Total Value data was reported at 39,785.881 USD bn in 2017. This records a decrease from the previous number of 42,071.330 USD bn for 2016. United States US: Stocks Traded: Total Value data is updated yearly, averaging 17,934.293 USD bn from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 47,245.496 USD bn in 2008 and a record low of 1,108.421 USD bn in 1984. United States US: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  7. d

    BrightQuery (BQ) Public Companies Dataset (4000 US companies covered)

    • datarade.ai
    Updated Apr 22, 2021
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    Bright Query (2021). BrightQuery (BQ) Public Companies Dataset (4000 US companies covered) [Dataset]. https://datarade.ai/data-products/brightquery-bq-public-companies-dataset-bright-query
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    Dataset updated
    Apr 22, 2021
    Dataset authored and provided by
    Bright Query
    Area covered
    United States
    Description

    Dataset containing over 5000 data metrics (including raw data and BQ calculated scores & metrics) for over 4000 public companies (~95% of the Russell 3000). Includes financials (from SEC filings) as well as data that is not reported to the SEC, including monthly headcount, detailed employee benefits data, credit events related to contributions to benefits plans. Also includes BQ scores, industry and macro statistics that provide a comprehensive view of the sector & industry.

    BQ's Public Companies dataset is applicable to both quantitative investment managers as well as fundamentals public equity investors, who wish to use alternative (non-financial) data to enhance their investment analysis and investment decisions.

  8. Biggest companies in the world by market value 2024

    • statista.com
    • ai-chatbox.pro
    Updated May 30, 2025
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    Statista (2025). Biggest companies in the world by market value 2024 [Dataset]. https://www.statista.com/statistics/263264/top-companies-in-the-world-by-market-capitalization/
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    Dataset updated
    May 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 17, 2024
    Area covered
    World
    Description

    With a market capitalization of 3.12 trillion U.S. dollars as of May 2024, Microsoft was the world’s largest company that year. Rounding out the top five were some of the world’s most recognizable brands: Apple, NVIDIA, Google’s parent company Alphabet, and Amazon. Saudi Aramco led the ranking of the world's most profitable companies in 2023, with a pre-tax income of nearly 250 billion U.S. dollars. How are market value and market capitalization determined? Market value and market capitalization are two terms frequently used – and confused - when discussing the profitability and viability of companies. Strictly speaking, market capitalization (or market cap) is the worth of a company based on the total value of all their shares; an important metric when determining the comparative value of companies for trading opportunities. Accordingly, many stock exchanges such as the New York or London Stock Exchange release market capitalization data on their listed companies. On the other hand, market value technically refers to what a company is worth in a much broader context. It is determined by multiple factors, including profitability, corporate debt, and the market environment as a whole. In this sense it aims to estimate the overall value of a company, with share price only being one element. Market value is therefore useful for determining whether a company’s shares are over- or undervalued, and in arriving at a price if the company is to be sold. Such valuations are generally made on a case-by-case basis though, and not regularly reported. For this reason, market capitalization is often reported as market value. What are the top companies in the world? The answer to this question depends on the metric used. Although the largest company by market capitalization, Microsoft's global revenue did not manage to crack the top 20 companies. Rather, American multinational retailer Walmart was ranked as the largest company in the world by revenue. Walmart also had the highest number of employees in the world.

  9. T

    United States - Stocks Traded, Total Value

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 21, 2013
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    TRADING ECONOMICS (2013). United States - Stocks Traded, Total Value [Dataset]. https://tradingeconomics.com/united-states/stocks-traded-total-value-us-dollar-wb-data.html
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Jul 21, 2013
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    Stocks traded, total value (current US$) in United States was reported at 44315891180000 USD in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Stocks traded, total value - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

  10. United States US: Market Capitalization: Listed Domestic Companies: % of GDP...

    • ceicdata.com
    Updated Mar 29, 2018
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    CEICdata.com (2018). United States US: Market Capitalization: Listed Domestic Companies: % of GDP [Dataset]. https://www.ceicdata.com/en/united-states/financial-sector
    Explore at:
    Dataset updated
    Mar 29, 2018
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    United States
    Variables measured
    Turnover
    Description

    US: Market Capitalization: Listed Domestic Companies: % of GDP data was reported at 165.651 % in 2017. This records an increase from the previous number of 146.862 % for 2016. US: Market Capitalization: Listed Domestic Companies: % of GDP data is updated yearly, averaging 102.679 % from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 165.651 % in 2017 and a record low of 39.352 % in 1981. US: Market Capitalization: Listed Domestic Companies: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  11. d

    PREDIK Data-Driven I Private Company Data I Enhanced Custom Dataset to...

    • datarade.ai
    .json, .csv
    Updated Feb 16, 2021
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    Predik Data-driven (2021). PREDIK Data-Driven I Private Company Data I Enhanced Custom Dataset to Understand Private & Public Business Relations between US Companies [Dataset]. https://datarade.ai/data-products/company-to-company-relations-data-predik-data-driven
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Feb 16, 2021
    Dataset authored and provided by
    Predik Data-driven
    Area covered
    United States
    Description

    This private company dataset provides an in-depth view of any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental US.

    Also, using robust supply chain data you will be able to map US facilities (including factories, warehouses, and retail outlets).

    With this private company dataset, it is possible to track the movement of trucks and devices between locations to identify supply chain connections and company data insights.

    Our Machine learning algorithms ingest 7-15bn daily events to estimate the volume of goods transported between locations. Consequently, we can map supply chain connections between:

    •Different companies (expressed as a percentage of volume transported).

    •Locations owned by the same company (e.g. warehouse to shop).

    With this novel geolocation approach, it is possible to "draw" a knowledge graph of any private or public company´s relations with other companies within the country.

    This solution, in the form of a dataset, provides an in-depth view of any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental United States.

    Use cases:

    • Identification and understanding of relations company-to-company: It helps to identify and infer relationships and connections between specific companies or facilities and between sectors/industries.

    • Identification and understanding of relations place-to-place: A logistics and domestic distribution supply chain can be mapped, both nationwide and state-wide in the US, and across countries in Europe.

    • Visualization and mapping of an entire supply chain network.

    • Tracking of products in any distribution or supply chain.

    • Risk assessment

    • Correlation analysis.

    • Disruption analysis.

    • Analysis of illicit networks and tracking of illegal use of corporate assets.

    • Improvement of casualty risk management.

    • Optimization of supply chain risk management.

    • Security and compliance.

    • Identification of not only the first tier of suppliers in the value chain, but also 2nd and 3rd tier suppliers, and more.

    Current largest use case: global corporation using it to model risk at a facility level (+100,000 locations).

    Why should you trust PREDIK Data-Driven? In 2023, we were listed as Datarade's top providers. Why? Our solutions for private company data, supply chain data, and B2B data adapt according to the specific needs of companies. Also, PREDIK methodology focuses on the client and the necessary elements for the success of their projects.

  12. United States US: Stocks Traded: Turnover Ratio of Domestic Shares

    • ceicdata.com
    Updated Mar 15, 2023
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    CEICdata.com (2023). United States US: Stocks Traded: Turnover Ratio of Domestic Shares [Dataset]. https://www.ceicdata.com/en/united-states/financial-sector/us-stocks-traded-turnover-ratio-of-domestic-shares
    Explore at:
    Dataset updated
    Mar 15, 2023
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    United States
    Variables measured
    Turnover
    Description

    United States US: Stocks Traded: Turnover Ratio of Domestic Shares data was reported at 116.078 % in 2017. This records an increase from the previous number of 94.719 % for 2016. United States US: Stocks Traded: Turnover Ratio of Domestic Shares data is updated yearly, averaging 114.857 % from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 407.630 % in 2008 and a record low of 51.444 % in 1991. United States US: Stocks Traded: Turnover Ratio of Domestic Shares data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. Turnover ratio is the value of domestic shares traded divided by their market capitalization. The value is annualized by multiplying the monthly average by 12.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  13. T

    United States - Listed Domestic Companies, Total

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 21, 2013
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    TRADING ECONOMICS (2013). United States - Listed Domestic Companies, Total [Dataset]. https://tradingeconomics.com/united-states/listed-domestic-companies-total-wb-data.html
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jul 21, 2013
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    Listed domestic companies, total in United States was reported at 4642 in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Listed domestic companies, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

  14. F

    S&P 500

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
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    (2025). S&P 500 [Dataset]. https://fred.stlouisfed.org/series/SP500
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-pre-approvalhttps://fred.stlouisfed.org/legal/#copyright-pre-approval

    Description

    View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

  15. Japan JP: Market Capitalization: Listed Domestic Companies

    • ceicdata.com
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    CEICdata.com, Japan JP: Market Capitalization: Listed Domestic Companies [Dataset]. https://www.ceicdata.com/en/japan/financial-sector/jp-market-capitalization-listed-domestic-companies
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    Japan
    Variables measured
    Turnover
    Description

    Japan JP: Market Capitalization: Listed Domestic Companies data was reported at 6,222.825 USD bn in 2017. This records an increase from the previous number of 4,955.300 USD bn for 2016. Japan JP: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 3,005.697 USD bn from Dec 1975 (Median) to 2017, with 43 observations. The data reached an all-time high of 6,222.825 USD bn in 2017 and a record low of 21.530 USD bn in 1977. Japan JP: Market Capitalization: Listed Domestic Companies data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

  16. d

    Hiring Activity dataset on 5,400 US public companies

    • datarade.ai
    .json, .sql
    Updated Jan 10, 2022
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    Contora Inc. (2022). Hiring Activity dataset on 5,400 US public companies [Dataset]. https://datarade.ai/data-products/contora-s-hiring-activity-dataset-on-5-400-us-public-companies-contora-inc
    Explore at:
    .json, .sqlAvailable download formats
    Dataset updated
    Jan 10, 2022
    Dataset authored and provided by
    Contora Inc.
    Area covered
    United States
    Description

    We track hiring activity and employees growth for all US public companies. For each company, we have a link to its Indeed, Glassdoor, and Linkedin profiles, which allows us to understand growth trends in real-time.

    The main fields are the number of open job positions, headcount, and various employee ratings (diversity, salary satisfaction, etc.). The dataset has 1 year of history, and the data is updated daily.

    This data gives answers to such questions as: - Which companies are most actively hiring right now? - Which companies had the most significant growth of employees over the past week/month/year? - Which companies have the highest rates from employees in terms of ESG, and which ones cannot retain an employee for more than a month?

    Such data helps estimate the risks of long-term investing in shares and is valuable for Hedge Funds, M&A firms, and consulting companies.

  17. US Stock Market Giants: Top Companies Stocks Data

    • kaggle.com
    Updated Nov 8, 2024
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    Azhar Saleem (2024). US Stock Market Giants: Top Companies Stocks Data [Dataset]. https://www.kaggle.com/datasets/azharsaleem/us-stock-market-giants-top-companies-stocks-data/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 8, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Azhar Saleem
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    United States
    Description

    Stock Data of Top USA Companies: Apple, Tesla, Amazon

    👨‍💻 Author: Azhar Saleem

    "https://github.com/azharsaleem18" target="_blank"> https://img.shields.io/badge/GitHub-Profile-blue?style=for-the-badge&logo=github" alt="GitHub Profile"> "https://www.kaggle.com/azharsaleem" target="_blank"> https://img.shields.io/badge/Kaggle-Profile-blue?style=for-the-badge&logo=kaggle" alt="Kaggle Profile"> "https://www.linkedin.com/in/azhar-saleem/" target="_blank"> https://img.shields.io/badge/LinkedIn-Profile-blue?style=for-the-badge&logo=linkedin" alt="LinkedIn Profile">
    "https://www.youtube.com/@AzharSaleem19" target="_blank"> https://img.shields.io/badge/YouTube-Profile-red?style=for-the-badge&logo=youtube" alt="YouTube Profile"> "https://www.facebook.com/azhar.saleem1472/" target="_blank"> https://img.shields.io/badge/Facebook-Profile-blue?style=for-the-badge&logo=facebook" alt="Facebook Profile"> "https://www.tiktok.com/@azhar_saleem18" target="_blank"> https://img.shields.io/badge/TikTok-Profile-blue?style=for-the-badge&logo=tiktok" alt="TikTok Profile">
    "https://twitter.com/azhar_saleem18" target="_blank"> https://img.shields.io/badge/Twitter-Profile-blue?style=for-the-badge&logo=twitter" alt="Twitter Profile"> "https://www.instagram.com/azhar_saleem18/" target="_blank"> https://img.shields.io/badge/Instagram-Profile-blue?style=for-the-badge&logo=instagram" alt="Instagram Profile"> "mailto:azharsaleem6@gmail.com"> https://img.shields.io/badge/Email-Contact%20Me-red?style=for-the-badge&logo=gmail" alt="Email Contact">

    Dataset Description

    This dataset provides daily stock data for some of the top companies in the USA stock market, including major players like Apple, Microsoft, Amazon, Tesla, and others. The data is collected from Yahoo Finance, covering each company’s historical data from its starting date until today. This comprehensive dataset enables in-depth analysis of key financial indicators and stock trends for each company, making it valuable for multiple applications.

    Column Descriptions

    The dataset contains the following columns, consistent across all companies:

    • Date: The date of the stock data entry.
    • Open: The stock's opening price for the day.
    • High: The highest price reached during the trading day.
    • Low: The lowest price during the trading day.
    • Close: The stock’s closing price for the day.
    • Volume: The total number of shares traded on that day.
    • Dividends: Any dividends paid out on that day.
    • Stock Splits: Records stock split events, if any, on that day.

    Potential Use Cases

    1. Machine Learning & Deep Learning:

      • Stock Price Prediction: Use historical prices to train models for forecasting future stock prices.
      • Sentiment Analysis and Price Correlation: Combine with external sentiment data to predict price movements based on market sentiment.
      • Anomaly Detection: Detect unusual price patterns or volume spikes using classification algorithms.
    2. Data Science:

      • Trend Analysis: Identify long-term trends for each company or compare trends between companies.
      • Volatility Analysis: Calculate volatility to assess risk and return patterns over time.
      • Correlation Analysis: Compare stock performance across companies to study market relationships.
    3. Data Analysis:

      • Historical Performance: Review historical data to understand growth trends, market impact of stock splits, and dividends.
      • Seasonal Patterns: Analyze data for seasonal trends or recurring patterns across years.
      • Investment Strategy Backtesting: Test various investment strategies based on historical data to assess potential profitability.
    4. Financial Research:

      • Economic Impact Studies: Investigate how major events affected stock prices across top companies.
      • Sector-Specific Analysis: Identify performance differences across sectors, such as tech, healthcare, and retail.

    This dataset is a powerful tool for analysts, researchers, and financial enthusiasts, offering versatility across multiple domains from stock analysis to algorithmic trading models.

  18. h

    stock-market-tweets-data

    • huggingface.co
    Updated Dec 16, 2023
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    Stephan Akkerman (2023). stock-market-tweets-data [Dataset]. https://huggingface.co/datasets/StephanAkkerman/stock-market-tweets-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 16, 2023
    Authors
    Stephan Akkerman
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Stock Market Tweets Data

      Overview
    

    This dataset is the same as the Stock Market Tweets Data on IEEE by Bruno Taborda.

      Data Description
    

    This dataset contains 943,672 tweets collected between April 9 and July 16, 2020, using the S&P 500 tag (#SPX500), the references to the top 25 companies in the S&P 500 index, and the Bloomberg tag (#stocks).

      Dataset Structure
    

    created_at: The exact time this tweet was posted. text: The text of the tweet, providing… See the full description on the dataset page: https://huggingface.co/datasets/StephanAkkerman/stock-market-tweets-data.

  19. d

    Stock Market Data North America ( End of Day Pricing dataset )

    • datarade.ai
    Updated Aug 24, 2023
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    Techsalerator (2023). Stock Market Data North America ( End of Day Pricing dataset ) [Dataset]. https://datarade.ai/data-products/stock-market-data-north-america-end-of-day-pricing-dataset-techsalerator
    Explore at:
    .json, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Aug 24, 2023
    Dataset authored and provided by
    Techsalerator
    Area covered
    Greenland, United States of America, El Salvador, Belize, Guatemala, Mexico, Bermuda, Panama, Honduras, Saint Pierre and Miquelon, North America
    Description

    End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

  20. Colombia CO: Market Capitalization: Listed Domestic Companies

    • ceicdata.com
    Updated Dec 15, 2022
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    CEICdata.com (2022). Colombia CO: Market Capitalization: Listed Domestic Companies [Dataset]. https://www.ceicdata.com/en/colombia/financial-sector/co-market-capitalization-listed-domestic-companies
    Explore at:
    Dataset updated
    Dec 15, 2022
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    Colombia
    Variables measured
    Turnover
    Description

    Colombia CO: Market Capitalization: Listed Domestic Companies data was reported at 68.412 USD bn in 2022. This records a decrease from the previous number of 90.541 USD bn for 2021. Colombia CO: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 105.082 USD bn from Dec 2005 (Median) to 2022, with 18 observations. The data reached an all-time high of 262.101 USD bn in 2012 and a record low of 50.501 USD bn in 2005. Colombia CO: Market Capitalization: Listed Domestic Companies data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.;World Federation of Exchanges database.;Sum;Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Share
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CEICdata.com, United States US: No of Listed Domestic Companies: Total [Dataset]. https://www.ceicdata.com/en/united-states/financial-sector/us-no-of-listed-domestic-companies-total
Organization logo

United States US: No of Listed Domestic Companies: Total

Explore at:
Dataset provided by
CEIC Data
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Dec 1, 2006 - Dec 1, 2017
Area covered
United States
Variables measured
Turnover
Description

United States US: Number of Listed Domestic Companies: Total data was reported at 4,336.000 Unit in 2017. This records an increase from the previous number of 4,331.000 Unit for 2016. United States US: Number of Listed Domestic Companies: Total data is updated yearly, averaging 5,930.000 Unit from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 8,090.000 Unit in 1996 and a record low of 4,102.000 Unit in 2012. United States US: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

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